Skip to main content
Frontiers in Molecular Neuroscience logoLink to Frontiers in Molecular Neuroscience
. 2018 Mar 22;11:71. doi: 10.3389/fnmol.2018.00071

A Comparison of Pathophysiology in Humans and Rodent Models of Subarachnoid Hemorrhage

Jenna L Leclerc 1,2,, Joshua M Garcia 1,, Matthew A Diller 1, Anne-Marie Carpenter 1, Pradip K Kamat 1, Brian L Hoh 2,3, Sylvain Doré 1,2,4,*
PMCID: PMC5875105  PMID: 29623028

Abstract

Non-traumatic subarachnoid hemorrhage (SAH) affects an estimated 30,000 people each year in the United States, with an overall mortality of ~30%. Most cases of SAH result from a ruptured intracranial aneurysm, require long hospital stays, and result in significant disability and high fatality. Early brain injury (EBI) and delayed cerebral vasospasm (CV) have been implicated as leading causes of morbidity and mortality in these patients, necessitating intense focus on developing preclinical animal models that replicate clinical SAH complete with delayed CV. Despite the variety of animal models currently available, translation of findings from rodent models to clinical trials has proven especially difficult. While the explanation for this lack of translation is unclear, possibilities include the lack of standardized practices and poor replication of human pathophysiology, such as delayed cerebral vasospasm and ischemia, in rodent models of SAH. In this review, we summarize the different approaches to simulating SAH in rodents, in particular elucidating the key pathophysiology of the various methods and models. Ultimately, we suggest the development of standardized model of rodent SAH that better replicates human pathophysiology for moving forward with translational research.

Keywords: aneurysm, heme, hemoglobin, ischemia, iron, stroke, vasospasm

Introduction

Although a variety of rodent models for subarachnoid hemorrhage (SAH) are in use, there is no standardized method of simulating the human equivalent, making translation to clinical observations challenging. Development of a rodent model began with Barry et al., who induced SAH by puncturing the basilar artery with a tungsten electrode (Barry et al., 1979). Additional models have been developed, predominantly involving intravascular perforation of a vessel in the Circle of Willis or direct injection of blood into the cisterna magna or prechiasmatic cistern. While each of these models has their advantages and disadvantages, none involve the spontaneous rupture of an intracranial aneurysm, as is observed in the majority of clinical cases. Thus, the purpose of this review is to address the current data surrounding SAH models and subsequently propose a bridge between these models and those that would more replicate the human equivalent to direct future preclinical model development and clinical studies.

Clinical SAH

Non-traumatic SAH affects ~30,000 people per year in the United States (Rincon et al., 2013), with ~15% of patients dying before they ever reach the hospital (Connolly et al., 2012) and in-hospital mortality estimated at 20% (Rincon et al., 2013). Around 10% of SAH cases are due to non-aneurysmal bleeding in idiopathic perimesencephalic hemorrhage, while another 5% are due to anomalies such as intracranial arterial dissections and vascular malformations, among other rare causes (Marder et al., 2014). The remaining 85% of clinical SAH results from the spontaneous rupture of a cerebral aneurysm (Van Gijn and Rinkel, 2001). Intracranial aneurysms form at sites of high shear wall stress such as the arterial bifurcations in the Circle of Willis (Wong et al., 2008). The most common sites include the anterior cerebral artery (ACA), internal carotid artery (ICA), or the middle cerebral artery (MCA); whereas, aneurysms in vessels of the posterior circulation are less frequent but routinely observed (Wong et al., 2008). Symptom onset is characteristically marked by a sudden headache, often described as “the worst headache of my life (Gorelick et al., 1986).” As the majority of cases are due to aneurysmal subarachnoid hemorrhage (aSAH) and because non-aneurysmal SAH patients tend to experience fewer complications and better outcomes than aSAH patients (Cánovas et al., 2012; Boswell et al., 2013), the majority of this review will focus on aSAH.

Most patients surviving the initial bleed are critically ill and require prolonged intensive care unit stay (Diringer, 2009), resulting in significant public health costs. Additionally, aSAH has an earlier mean age of onset and is associated with higher disability and morbidity rates when compared to other types of stroke (Kolias et al., 2009). It has been shown that early treatment of aSAH increases the likelihood of having no to minimal disability following discharge from the hospital (Siddiq et al., 2012). Thus, it is important to understand the pathophysiology of aSAH in order to ensure its early treatment and direct preclinical studies to expound on existing standards of care.

Cerebral vasospasm and delayed cerebral ischemia in clinical SAH

Following aSAH, patients often develop complications from the bleed that contribute to the high mortality rate of this disease. Hydrocephalus, seizures, cerebral ischemia, tissue shifts and herniations, hyponatremia, cardiac anomalies, and respiratory depression are formidable consequences that can result (Diringer et al., 2011). However, the leading cause of morbidity and mortality after aSAH is delayed cerebral ischemia (DCI).

DCI occurs in nearly 33% of aSAH cases and is defined as new focal neurological signs, acute mental status decline, or appearance of new infarction on computed tomography or magnetic resonance imaging (MRI) (MacDonald et al., 2014). Clinical identification of DCI is often difficult since fever, infection, hypoxia, sedatives, and electrolyte imbalances produce a similar clinical picture (Vergouwen et al., 2010). Additionally, acute mental status decline is undetectable in the subset of SAH patients that remain comatose throughout hospitalization; thus, the incidence of DCI may be higher than documented. Further work to elucidate the underlying mechanism of DCI will allow for development of additional treatments that may prove more effective.

The most supported theory regarding the pathogenesis of DCI points to a phenomenon known as cerebral vasospasm (CV), which is a narrowing of cerebral arteries leading to a transiently sustained interruption of blood flow to the brain parenchyma (Velat et al., 2011). Approximately 30–70% of aSAH patients, will experience CV between days 4 and 14 after aneurysm rupture, with peak vessel constriction occurring on days 7 and 8 (Izzy and Muehlschlegel, 2014), making the identification, treatment, and prevention of CV paramount to achieving favorable outcomes following aSAH. Because CV is a causative mechanism of DCI, treatment of diagnosed DCI focuses on attempting to reverse CV by inducing hypertension, hypervolumia, and hemodilution (HHH therapy)(Siasios et al., 2013). Although such measures can be helpful after symptom onset, it nevertheless remains an enigma why certain patients develop CV and symptomatic ischemia following aSAH, while others remain asymptomatic with minimal CV. Currently, the only documented and verified risk factor for the development of CV is a larger hemorrhage volume assessed by CT scan and quantitated using the Fisher scoring system (Fisher et al., 1980; Ko et al., 2016).

Pathophysiology of clinical SAH

After aneurysm rupture, blood enters the subarachnoid space at arterial pressure and produces immediate pathophysiological effects and early brain injury (EBI) (MacDonald et al., 2014). Intracranial pressure (ICP) rises above 20 mmHg, mean arterial blood pressure (MABP) falls reflexively, and cerebral perfusion pressure (CPP) is reduced; this can lead to severe headache or syncope due to decreased cerebral blood flow (CBF) (Voldby and Enevoldsen, 1982). Following acute conditions, vessel constriction due to delayed CV contributes to further reductions in CPP (Dhar et al., 2012). In practice, detecting impairment in CPP early in the management of SAH is essential in monitoring for DCI (Diringer et al., 2011). Ischemia, infarction, hydrocephalus, and impaired cerebral autoregulation further contribute to increased ICP and exacerbate the reductions in CPP and CBF (Zoerle et al., 2015). A delicate balance must be maintained with managing MABP following SAH, as increases can lead to elevation of ICP, while decreases may result in further worsening of CPP and exacerbation of DCI. Current recommendations for MABP focus on hemodynamic stability, encouraging a stepwise titration of MABP with assessment of neurological status at each level to determine if the target value is appropriate (Diringer et al., 2011). Overall, vigilant management of physiological outcomes is critical in the SAH patient, as extremes in ICP, CPP, CBF, and MABP can ultimately lead to poor functional outcomes (Zoerle et al., 2015).

Mortality and functional outcomes of clinical SAH

After aSAH, up to 15% of patients will die immediately following the ictus, and the total case fatality rate approaches 50% (MacDonald et al., 2014). Long-term survival is correlated with increased consciousness and neurological grade on admission, less blood volume on initial CT scan, and age at ictus (Rosengart et al., 2007). Clinically, stratifying SAH based on the acute presentation can be accomplished with several widely used rating systems, such as the Glasgow Coma Scale, World Federation of Neurological Surgeon's scale, Fisher grade, and Hunt and Hess scale. These scales each have their own utility and are aimed at predicting the risk for CV or clinical outcome based on groupings of symptoms such as amount of subarachnoid blood, degree of mentation, focal deficits, and motor dysfunction. These scales integrate information regarding risk factors and symptoms in an effort to guide management and predict prognosis. In addition to stratification of SAH presentations, functional assessment tools are widely used for survivors of the initial hemorrhage. These instruments assign a quantitative value to deficits following SAH, analyzing factors such as language and speech, motor function and sensory loss, consciousness, coordination, and independence in activities of daily living (McGeoch et al., 2002; Rademaker et al., 2002a,c,d). Measures include the National Institutes of Health Stroke Scale (NIHSS), Barthel Index, modified Rankin scale (mRS), and Glasgow Outcome Scale (GOS).

Those who survive aSAH experience long-term complications such as memory impairment, epilepsy, neurocognitive dysfunction, neuropsychiatric disturbances, and focal neurological deficits (Al-Khindi et al., 2010). Hütter et al. (1995) published that SAH patients report deficits in verbal short-term memory, concentration, language, motivation, interests, mental capacity, free-time activities, social relationships, and fine motor coordination (Hütter et al., 1995). Longitudinally, 40–50% of patients require help in common household activities, and almost 50% exhibit disability in leisure and vocational activities (Lindberg et al., 1992). Approximately 40% will be cognitively impaired (Dombovy et al., 1998), which is influenced by the incidence of CV, DCI, and infarction, but unrelated to the initial location of the ruptured aneurysm (MacDonald et al., 2012). Cognitive domain deficits commonly affected in aSAH patients with DCI are verbal memory, language, and visuospatial memory and skills (Caeiro et al., 2011; Chu et al., 2015a). DCI has been associated with poor outcomes after SAH, but even with good outcomes, persistent cognitive deficits can still manifest, limiting psychosocial functioning. The correlation between neuropsychological and neurophysiological measures indicate frontal lobe damage, which in some patients persisted for years after the initial insult (Ravnik et al., 2006). Additionally, cognitive deficits also occurs in patients with CV and no DCI (Larsson et al., 1989; Richardson, 1991; Pluta et al., 2009; Miller et al., 2014). Neuropsychiatric disturbances including depression, anxiety, apathy, and sleep disorders are common following aSAH (Hackett and Anderson, 2000). Patients that do not undergo neuropsychological testing and subsequent treatment following SAH have worse outcomes than those that do (Kreiter et al., 2002), indicating a pressing need to evaluate all SAH patients for potential cognitive disability. It has also been shown that the Glascow Coma Scale score is able to predict self-reported quality of life in patients, but is otherwise unable to predict neurocognitive impairment (Cedzich and Roth, 2005). Little is known about the molecular pathways involved in mediating these long-term neurocognitive and neuropsychiatric outcomes after SAH. These findings indicate a need for additional mechanistic research and more efficient tools to predict functional outcomes, especially neurocognitive and neuropsychiatric impairments in SAH patients.

SAH is a devastating clinical disease with numerous debilitating outcomes. Understanding EBI, the pathophysiological changes that occur, and identifying predictors of CV and DCI will improve functional outcomes and reduce mortality following SAH. In order to further improve the outcomes of SAH patients, a standardized rodent model that better replicates human pathophysiology must be developed for use in preclinical studies.

Preclinical models of non-aneurysmal SAH

While most cases of SAH in humans are due to rupture of an intracranial aneurysm, the majority of rodent studies have used models that more mimic non-aneurysmal SAH. This disparity is most likely due to the difficulty in producing a cerebral aneurysm in rodents (Hashimoto et al., 1984). Two main approaches to modeling non-aneurysmal SAH have been used: (1) direct injection of blood into the subarachnoid space, or (2) endovascular perforation of a cerebral vessel. While each of these models allows for the study of how extravascular blood within the subarachnoid space affects various outcomes after SAH, none addresses the specific consequences related to the formation and spontaneous rupture of an intracranial aneurysm, which may have its own independent additive or blood-dependent synergistic effect on SAH outcome.

Direct injection of blood

Direct injection of autologous or heterologous whole blood into the subarachnoid space is the most commonly used method of inducing non-aneurysmal SAH in rodents. During the procedure, stereotactic frames are used to produce precise coordinates for injection in an effort to control the location and distribution of blood in the subarachnoid space. Blood is either injected into the cisterna magna or prechiasmatic cistern, with each location producing a characteristic pattern of blood distribution. The former results in a blood clot primarily localized around vessels of the posterior circulation and the latter around vessels of the anterior circulation (Prunell et al., 2002; Raslan et al., 2012). Figure 1 provides a representative visualization of the blood distribution in the cisterna magna and prechiasmatic cistern injection models.

Figure 1.

Figure 1

Representative illustrations of blood clot distribution in the cisterna magna and prechiasmatic cistern models. Images correspond to (a) cisterna magna control, (b) prechiasmatic cistern control, (c) cisterna magna experimental, and (d) prechiasmatic cistern experimental mouse brains. Cisterna magna and prechiasmatic cistern injections primarily result in blood clots surrounding the posterior and anterior circulations, respectively. The scale bar represents 2cm. Photo was obtained from Cai J. et al. (2012).

Direct injection models may involve a single or double injection of blood (Vatter et al., 2006; Weidauer et al., 2006; Lee et al., 2008, 2009; Güresir et al., 2010, 2012; Cai J. et al., 2012; Raslan et al., 2012; Boyko et al., 2013). In double injection models, the second infusion is typically performed 24 h after the first and injection occurs in the cisterna magna. Double injection of blood into the prechiasmatic cistern has not been performed, presumably because the hemorrhagic insult is more severe and the rodents may not be able to sustain two infusions. In general, less blood is required to produce the same deficits in the prechiasmatic cistern location compared to the cisterna magna site. The various blood volumes that have been introduced into both locations and the injection characteristics are summarized in Table 1.

Table 1.

Summary of single- and double-injection cisterna magna models and single-injection prechiasmatic cistern models in published studies that used various strains of mice or rats.

Rodent Injection 1 (μL) Injection length (s) Injection rate (μL/s) References Comments
CISTERNA MAGNA—SINGLE INJECTION
C57BL/6 mice 60 60 1.0 Lin et al., 2003 Replaced 60 μL saline
SD rats 70 or 300 5 or 30 14 or 10 Delgado et al., 1985
SD rats 70 Rasmussen et al., 1992
SD rats 300 15 20.0 Boyko et al., 2013
SD rats 300 15 20.0 Glenn et al., 2002 Replaced 300 μL saline
SD rats 300 Solomon et al., 1985 Replaced 300 μL donor blood
SD rats 300 15 20.0 Prunell et al., 2003 Attempted to keep ICP at the level of MABP
SD rats 300 30 10.0 Schwartz et al., 2000
SD rats 300 120 2.5 Gules et al., 2002 Removed 300 μL CSF
SD rats 370 Solomon et al., 1987 Replaced 370 μL saline
SD rats 600 60 10.0 Swift and Solomon, 1988
SD rats 500 1200 0.4 Ram et al., 1991 Removed 200 μL CSF
SD rats 300 180–240 Jackowski et al., 1990 Injections were made in 50 μL sequential steps, each over 3–4 min
Wistar rats 100 30 3.3 Munoz-Sanchez et al., 2012a Removed 100 μL CSF
Wistar rats 200 Turowski et al., 2007
C57BL/6 mice 60 Chaichana et al., 2007 Replaced 60 μL saline
Rodent Injection 1 (μL) Injection 2 (μL) Injection length (s) Injection rate (μL/s) References Comments
CISTERNA MAGNA—DOUBLE INJECTION
SD rats 200 or 300 100 or 200 600 or 180 0.33/0.17 and 1.67/1.11 Lee et al., 2008
SD rats 200 100 60 and 30 3.3 Lee et al., 2009
SD rats 200 200 180 1.1 Cai J. et al., 2012 Remove 100 μL CSF each time
SD rats 200 200 Vatter et al., 2006 Remove 100 μL CSF first time
SD rats 200 200 Weidauer et al., 2006
SD rats 250 250 Güresir et al., 2010 Remove 100 μL CSF each time
SD rats 250 250 Güresir et al., 2012 Remove 100 μL CSF each time
SD rats 200 100 180 1.1 and 0.56 Raslan et al., 2012 Remove 100 μL CSF first time
SD rats 300 300 15 20.0 Boyko et al., 2013
SD rats 300 300 120 2.5 Gules et al., 2002 48 h apart, remove 300 μL CSF each time
SD rats 300 300 120 2.5 Meguro et al., 2001 48 h apart, remove 100 μL CSF first time
Wistar rats 500 300 600 0.8 and 0.5 Takata et al., 2008 48 h apart, remove 200 μL CSF first time
SD rats 300 300 120 2.5 Wang et al., 2010
SD rats 300 300 180 1.7 Qin et al., 2015 48 h apart, remove 300 μL CSF each time
SD rats 300 300 600 0.5 Zhang Z. Y. et al., 2015 48 h apart
SD rats 200 200 120 1.7 Zhao et al., 2016 48 h apart
SD rats 340–440 340–440 Chang et al., 2015a 48 h apart
SD rats 300 300 Chang et al., 2015b 48 h apart, removed 100 μL CSF each time
SD rats 200 100 80 and 40 2.5 He et al., 2015 48 h apart, removed 100 μL CSF each time
Rodent Injection 1 (μL) Injection length (s) Injection rate (μL/s) References Comments
PRECHIASMATIC CISTERN—SINGLE INJECTION
CD1 mice 100 15 6.7 Sabri et al., 2009
SD rats 200, 250, or 300 Prunell et al., 2002 Attempted to keep ICP at the level of MABP
SD rats 200 12 16.7 Prunell et al., 2003 Attempted to keep ICP at the level of MABP
SD rats 200 120 1.7 Cai J. et al., 2012
SD rats 300 20 15.0 Jeon et al., 2010
Wistar rats 300 60 5.0 Piepgras et al., 1995
SD rats 300 180 1.7 Zhang D. et al., 2015
SD rats 250 Ansar and Edvinsson, 2008 Injected at a pressure equal to that of MABP (80–100 mmHg)
SD rats 300 20 15.0 Zhang X. S. et al., 2015

Information presented includes rodent strain, injection volumes (μL), duration of injection (s), and injection rate (μL/s). Specific notes on the replacement volume of blood or saline, in addition to details regarding minor alterations to the model, are provided if mentioned in the referenced text. SD, Sprague Dawley.

The direct injection model allows for a predictable distribution of blood, but can introduce variations in physiologic parameters. Given the large volume of blood and location of injection into the cisterna magna, pressure rises may cause blood to enter the spinal canal, potentially confounding results due to the functional impairments produced (Leonardo et al., 2012). In order to avoid this complication, many authors choose to remove CSF prior to injection to create more potential space for blood (Ram et al., 1991; Takanashi et al., 2001; Gules et al., 2002; Vatter et al., 2006; Takata et al., 2008; Güresir et al., 2010, 2012; Cai C. Y. et al., 2012; Muñoz-Sanchez et al., 2012b; Raslan et al., 2012). Unfortunately, this can alter the ICP, potentially affecting all observed outcomes. Another source of error is often seen in autologous blood injection models, as some have attempted to maintain normovolemia after blood withdrawal and SAH induction by replacing equivalent volumes of saline (Solomon et al., 1987; Glenn et al., 2002; Lin et al., 2003) or donor blood (Solomon et al., 1985) into the systemic circulation. However, because total blood volume decreases following SAH, this step may alter results by keeping MABP artificially high. Additionally, cisterna magna models commonly keep the animal tilted from 20 to 40° angle after injection to facilitate blood distribution into the anterior circulation (Gules et al., 2002; Lee et al., 2008). This manipulation likely disrupts intracranial pressure (ICP) and other important physiological parameters.

As noted in Table 1, the amount of time over which blood is injected also varies widely among different researchers. Ideally, blood injection would occur at a rate that maintains a pressure similar to MABP in order to mimic the true pressure seen in a spontaneous arterial bleed. In an effort to adhere to these conditions, Prunell et al. (2002) attempted to keep ICP at the same level as MABP during manual injection of blood, rather than choosing constant injection rates (Prunell et al., 2002, 2003). Additionally, Ram et al. (1991) did not allow ICP to rise to over 25 mmHg at any point during the injection (Ram et al., 1991). While these elegant procedures eliminate possible confounding variables, they are nevertheless technically strenuous and difficult to reproduce.

Endovascular perforation

In addition to the direct injection of whole blood, SAH can be simulated by endovascular perforation (Table 2). This model involves advancing a suture into the ICA until it perforates a vessel within the Circle of Willis. Briefly, the method involves surgically exposing the bifurcation of the common carotid artery (CCA) into the ICA and external carotid artery (ECA). The suture is then threaded through the ECA into the ICA and advanced into the Circle of Willis at the branch point of the ICA into the ACA and MCA (Bederson et al., 1995).

Table 2.

Summary of endovascular perforation models in published studies that used various strains of mice or rats.

Rodent Suture size References Comment
ENDOVASCULAR PERFORATION
C57BL/6 mice 5–0 Feiler et al., 2010
C57BL/6 mice 5–0 Parra et al., 2002 ECA ligated, blunted suture tip
SD Rats 3–0 and 4–0 Schwartz et al., 2000
SD Rats 3–0 Gules et al., 2002
SD rats 3–0 Prunell et al., 2003
SD rats 3–0, 4–0, or 5–0 Westermaier et al., 2009a Suture left in ECA for 20–30 min before advancing through ICA
SD rats 3–0 Westermaier et al., 2009b CCA clamped before placing suture in ECA, suture left in ECA for 20–30 min before advancing through ICA
SD rats 3–0 Bederson et al., 1998 ECA ligated
SD rats 3–0 Bederson et al., 1995 ECA ligated
SD rats 4–0 Sugawara et al., 2008 ECA ligated
SD rats 0.076 mm tungsten filament Park et al., 2008 ECA ligated, hollow tubing
SD rats 3–0 Silasi and Colbourne, 2009 ECA ligated
Wistar rats 3–0 Van Den Bergh et al., 2005 ECA ligated, ICA and carotid communicis clamped before suture threaded into ECA
Wistar rats 3–0 Veelken et al., 1995 Blunted suture tip
Wistar rats 4–0 Tiebosch et al., 2013
C57BL/6 mice 5–0 Egashira et al., 2015a Blunted suture tip
C57BL/6 mice 5–0 Siler et al., 2015
C57BL/6 mice 5–0 Vellimana et al., 2011 ECA ligated
SD Rats 4–0 Suzuki et al., 2010
SD Rats 4–0 Topkoru et al., 2013
C57BL/6 mice 5-0 Bühler et al., 2015 ECA ligated
C57BL/6 mice 5–0 Sheng et al., 2011
SD Rats 3–0 Hockel et al., 2012
SD Rats 4–0 He et al., 2012
SD Rats 4–0 Li et al., 2012
C57BL/6 mice 5–0 Egashira et al., 2015b Blunted suture tip
SD Rats 4–0 Britz et al., 2007
SD Rats 4–0 Hasegawa et al., 2011
SD Rats 4–0 Duris et al., 2011
SD Rats 3–0 Shishido et al., 2015
SD Rats 4–0 Li et al., 2016
SD Rats 3–0 Huang et al., 2015
SD Rats 3–0, 0.08 mm tunsgten filament Hollig et al., 2015 Hollow tubing
SD Rats 0.075 mm tungsten filament Xu et al., 2015 Hollow tubing

Information presented includes rodent strain and the size of the suture. Details regarding alterations to the model, such as the use of a blunted suture tip or ligation of the ECA, are also included if mentioned in the referenced text. SD, Sprague Dawley; ECA, external carotid artery; CCA, common carotid artery; ICA, internal carotid artery.

Unlike most direct injection models, the bleed produced via endovascular perforation occurs at MABP. Furthermore, no needle is inserted through brain structures, greatly reducing the risk of intracerebral hemorrhage or confounding alterations in ICP. However, the volume of blood produced by this model depends on the size of suture used to perforate the artery, and even with the same size suture, the amount of blood is variable from rodent to rodent (Schwartz et al., 2000). Researchers have used a number of suture sizes to control the hemorrhage severity. While the sutures are usually sharpened, some have chosen a blunted tip in order to prevent endothelial damage when passing the suture through the ICA (Veelken et al., 1995; Parra et al., 2002; Lee et al., 2009). For further protection, Park et al. (2008) used hollow tubing and a tungsten filament rather than a suture to avoid injury to the vasculature before puncture (Park et al., 2008). With this model, it is not possible to control whether the suture perforates either the ACA or MCA specifically (Bederson et al., 1995). In some cases, the ICA can even be perforated (Bederson et al., 1995). Thus, in addition to the variation in hemorrhage volume, differences in puncture location between rodents in a given study may result in a non-uniform blood distribution.

Another complicating factor of the endovascular perforation model is the common practice of ligating the ECA into a stump to facilitate advancing the suture through the CCA and into the ICA (Bederson et al., 1995, 1998; Schwartz et al., 2000; Gules et al., 2002; Parra et al., 2002; Prunell et al., 2003; Van Den Bergh et al., 2005; Park et al., 2008; Sugawara et al., 2008; Lee et al., 2009; Silasi and Colbourne, 2009). As a result of this ligation, CBF is increased on the ipsilateral side, potentially exacerbating the severity of hemorrhage for a given filament size. In attempts to reduce extracranial blood loss as a result of ECA ligation, the CCA (Westermaier et al., 2009b) or ICA and carotid communicis (Van Den Bergh et al., 2005) have been clamped before placing the suture in the ECA. Finally, some researchers have left the suture in the ECA for 20–30 min before advancing it through the ICA, in order to obtain baseline measurements for data analysis (Schwartz et al., 2000; Westermaier et al., 2009a,b).

Preclinical models of aneurysmal SAH

Thus far, the rodent models discussed do not involve aneurysm formation and rupture, even though non-aneurysmal SAH only represents ~10% of human SAH cases (Marder et al., 2014). The endothelial changes and local pro-inflammatory state associated with development of an aneurysm and its subsequent rupture may contribute to SAH outcomes. However, the incidence of spontaneous cerebral aneurysms in rodents is extremely low (Handa et al., 1983; Kim and Cervos-Navarro, 1991), making true aSAH difficult to study in rodents. Without such an understanding of these potential aneurysm effects, challenges arise in evaluating putative preventative and therapeutic paradigms in experimental models.

In an attempt to address the discrepancy between experimental models and clinical reality, extensive effort has been extended to the study of intracranial aneurysm induction in rodents. Methods involving hypertension and hemodynamic stress can result in aneurysm formation, although the aneurysms are relatively small and can take as long as 3 months to develop (Handa et al., 1983; Hashimoto et al., 1984; Li et al., 2014). Elastase can also be injected to degrade the internal and external elastic lamina of cerebral vessels, causing aneurysm formation in ~3 weeks (Nuki et al., 2009; Hoh et al., 2010; Tada et al., 2011, 2014; Ruzevick et al., 2013; Wada et al., 2013; Hosaka and Hoh, 2014; Starke et al., 2014a,b; Shimada et al., 2015). Using this hypertension, hemodynamic stress, and elastase triad, others have characterized the first mouse model that featured intracranial aneurysm formation (Nuki et al., 2009; Wada et al., 2013). In the method, C57BL/6J mice were injected with elastase at the right basal cistern and continuously infused with angiotensin-II to produce the desired hypertension and hemodynamic stress (Nuki et al., 2009). Accordingly, intracranial aneurysms of 500 μm size were produced, exhibiting a dose-dependent relationship between aneurysm incidence and concentrations of both elastase and angiotensin-II.

The choice of hypertensive agent is a key factor to consider in an aSAH model. Angiotensin-II can be used as the hypertensive agent (Nuki et al., 2009; Kanematsu et al., 2011; Pena Silva et al., 2014; Chu et al., 2015b), supported by data demonstrating that angiotensin-converting enzyme inhibitors can attenuate aneurysm rupture (Li et al., 2014). However, administering angiotensin II to promote aneurysm rupture may have confounding effects through its involvement in systemic inflammation and reactive oxygen species generation in the vessel wall (Tada et al., 2011, 2014). As an alternative, deoxycorticosterone acetate (DOCA) and saline can also induce intracranial aneurysm formation and rupture in a dose-dependent manner (Tada et al., 2014). Using a model involving unilateral nephrectomy, subcutaneous DOCA pellet implantation, 1% NaCl drinking water supplementation, and elastase injection, aSAH can successfully be induced in mice (Makino et al., 2012; Wada et al., 2013; Peña-Silva et al., 2015; Shimada et al., 2015). With this methodology, intracranial aneurysms form in the Circle of Willis and spontaneously rupture between days 7 and 16 after aneurysm induction, and rupture is reliably indicated by a simple assessment of neurological symptoms in the mice (Wada et al., 2014). While this novel approach offers promising results in developing an improved aSAH model in mice with features that are reflective of human parameters, limitations exist that can pose problems in experimental settings. First, the practice of unilateral nephrectomy can alter systemic levels of renin and other hormones affecting systemic blood pressure (Tada et al., 2014). In light of this, it is possible to achieve similar levels of systemic hypertension with the subcutaneous DOCA implants supplemented with 1% NaCl drinking water alone without altering the physiology of the anatomical organs in charge of the renin-angiotensin system (Klanke et al., 2008; Amann et al., 2009; Hartner et al., 2009; Rinne et al., 2013), although this has not been investigated in the setting of cerebral aneurysms. Furthermore, mice are typically euthanized to confirm aneurysm rupture after the onset of neurological symptoms, precluding further measurements of longitudinal aSAH outcomes unless in vivo imaging studies are performed. Additionally, while reflective of the unpredictable clinical course of aSAH, the spontaneous nature of aneurysm rupture in this model prevents synchronization of experimental rodent groups.

Comparison of preclinical SAH models and clinical SAH

Direct injection models are widely employed because they allow investigators to control the initiation, volume, and rate of hemorrhage; although, the volumes used, and injection rates vary widely across studies. Additionally, the inability to simulate vessel rupture limits the translatability to clinical SAH. Alternatives such as the endovascular perforation model do incorporate vessel rupture, and this model is also advantageous in simulating several important physiologic parameters of clinical SAH, including direct entry of blood from the vasculature that occurs at MABP. However, there are several potential variables that can affect hemostasis and outcome in this model. Unfortunately, the amount and location of blood is not as controllable as with the direct injection methods and there is significant chance of artificial injury to the vasculature when advancing the suture. Finally, neither the injection nor endovascular perforation models include the formation and rupture of an aneurysm (Table 3). Further optimization of a spontaneous aneurysm formation and rupture model of aSAH is needed. If such a standardized and translational model can be developed, it would be optimal for studying the pathophysiology of aSAH and evaluating putative therapeutic avenues to improve outcomes.

Table 3.

Presents a summary of the advantages and disadvantages of the two blood injection and endovascular perforation preclinical SAH models.

Model Advantages Disadvantages
Endovascular perforation Bleed is at physiologic MABP Inability to control the hemorrhage volume
No needle insertion through brain structures Artificial injury of vasculature
Reduced risk of ICH ECA ligation
Cisterna magna Controlled hemorrhage volume Lacks vessel rupture
High variability in physiological parameters
Head rotation artificially elevates ICP
Prechiasmatic cistern Controlled hemorrhage volume Lacks vessel rupture
Reproducibility
Most translational with respect to outcomes

Cerebral vasospasm and delayed cerebral ischemia in rodent models of SAH

Following SAH, in addition to EBI, the most dreaded complication is cerebral vasospasm (CV), a prolonged narrowing of cerebral arteries resulting in diminished perfusion in the tissue distal to the narrowing (Greenberg et al., 2000). The consequences of CV include DCI, infarction, and diffuse edema, leading to poor outcomes for patients experiencing this unpredictable vascular event (Biller et al., 1988). In light of the delayed nature of CV and severe consequences, it is necessary to develop preventative measures and treatments for CV that can attenuate its ominous effects. In order to accomplish this task, efforts should be placed on developing a rodent model of aSAH that reproducibly yields delayed CV in a way that reflects the timing, location, and severity of clinical SAH.

Identification of cerebral vasospasm in rodent models of SAH

Various methods have been developed and used to assess the occurrence and severity of CV following experimental SAH, each with their advantages and disadvantages. The most straightforward method of identifying CV is via histological analysis using fixed coronal brain slices and measuring the intraluminal or adventitial diameter of photomicrographs (Bederson et al., 1998; Meguro et al., 2001; Alkan et al., 2002; Gules et al., 2002; Lee et al., 2008, 2009; Park et al., 2008; Sugawara et al., 2008; Sabri et al., 2009; Güresir et al., 2010, 2012; Jeon et al., 2010; Cai J. et al., 2012; Raslan et al., 2012). Ideally, perfusion is performed with reagents at 37°C to avoid thermoregulatory vasoconstriction; although, most protocols either do not specify perfusion temperatures or document using ice-cold solvents (Lord et al., 2012). While this method proves experimentally convenient, varying degrees of dehydration among brain samples can result in significant differences in measured vessel diameters (Cai J. et al., 2012). Indeed, Cai and colleagues showed that the intraluminal diameter was much smaller in post-mortem histological analysis compared to synchrotron radiation angiography, an in vivo method (Cai J. et al., 2012). Furthermore, histological analysis is a terminal measurement, precluding the ability to repeat measurements of CV in the same animal at different time points.

In addition to histological analysis, some researchers identify CV via gel casting of the cerebral vasculature (Parra et al., 2002; Lin et al., 2003; Takata et al., 2008; Altay et al., 2009). Briefly, animals are perfused with 10% formalin, followed by perfusion with a combination of gelatin and India ink. Cerebral vessels are imaged using a video-linked dissecting microscope, and diameters are measured from the digitized images. While this method avoids desiccation seen in traditional histological analysis, limitations still exist. Parra and colleagues showed that the perfusion pressure of the gelatin cast expands the vessels, removing measurable CV when rats are perfused at pressures greater than MABP (Parra et al., 2002). Additionally, the group found that particulate and air emboli within the gelatin fixative could induce artifact that resembled CV histologically (Parra et al., 2002). In light of these findings, it is recommended that perfusion pressure remain at MABP to avoid increasing luminal diameter of vessels. While some studies document perfusing animals at pressures close to physiological values (Gules et al., 2002; Sugawara et al., 2008), many studies either do not report perfusion pressures or document values that tend to be higher than the MABP (Parra et al., 2002; Takata et al., 2008).

Many researchers have addressed the aforementioned issues by using angiography to study the rodent cerebral vessels (Delgado et al., 1985; Verlooy et al., 1991; Piepgras et al., 1995). Since rodent vessels are too small for accurate measurement with typical angiographic techniques, synchrotron radiation angiography and digital subtraction angiography are used to visualize vessel diameter in vivo (Vatter et al., 2006; Weidauer et al., 2006; Turowski et al., 2007; Cai J. et al., 2012). These methods employ radiologic techniques resulting in images with higher resolution. However, their use in assessing CV is limited due to the toxicity of the contrasts used. Indeed, angiography appears to remain a terminal measure that cannot be used to obtain serial in vivo measurements of CV.

A possible solution for measuring CV serially in vivo may be found in MRI. In 2005, Van Den Bergh and colleagues used MRA to determine the degree of CV in the rat, employing 3D time of flight images to measure vessel diameter (Van Den Bergh et al., 2005). The results produced were similar to those obtained in histological or angiographic methods (Bederson et al., 1998; Gules et al., 2002; Parra et al., 2002; Sugawara et al., 2008; Lee et al., 2009). Furthermore, the resolution achieved via MRI can be greater than angiographic methods, especially when 4.7T magnets are used. However, the method is disadvantageous in that MRI can be both time-consuming and expensive, and the rodent must be anesthetized for the procedure which itself could affect CV pathophysiology and the neuroinflammatory milieu following SAH.

Arteries affected by cerebral vasospasm in rodent models of SAH

In the current rodent models of SAH, the location of CV appears to be dependent on the site of hemorrhage and the model used (Table 4). For example, in rat models employing a single injection of blood within the cisterna magna, CV predominantly occurs in the basilar artery (BA) (Delgado et al., 1985; Ram et al., 1991; Gules et al., 2002), and less frequently in the posterior communicating artery (Pcom) (Gules et al., 2002). In rat cisterna magna models employing double injection, CV also primarily occurred in the BA (Meguro et al., 2001; Vatter et al., 2006; Lee et al., 2008, 2009; Takata et al., 2008; Güresir et al., 2012; Raslan et al., 2012), and the Pcom (Meguro et al., 2001); however, CV was additionally observed in both the ACA (Lee et al., 2009; Cai J. et al., 2012) and MCA (Takata et al., 2008). This difference is likely due to the greater volumes of blood introduced into the subarachnoid space with repeated hemorrhage in the double injection models that allows for greater overall dispersal. Furthermore, when single injections were made in the rat prechiasmatic cistern rather than the cisterna magna, CV was predominantly found in the ACA (Jeon et al., 2010; Cai J. et al., 2012) and MCA (Piepgras et al., 1995; Sabri et al., 2009; Cai J. et al., 2012). In contrast to these rat studies, mouse single injection cisterna magna models elicited CV not only in the BA, but also in the ACA and MCA (Lin et al., 2003). This discrepancy is perhaps due to the smaller size of the mouse cranial vault compared to the rat and thus a larger clot distribution.

Table 4.

Summary of cerebral vasospasm itemized by the model used for SAH induction in published studies that used various strains of mice or rats.

Rodent Location Severity (% Reduction) Time References Comments
CISTERNA MAGNA-SINGLE INJECTION
SD rats BA 50 3 d Ram et al., 1991 CV measured using photographs of the BA
SD rats BA 34 or 40* and 23 or 27* 10 min, 2 d Delgado et al., 1985 Blood volumes of 70 or 300*μL
C57Bl/6 mice BA 24, 11, 12, 13 6 h, 12 h, 24 h, 36 h Lin et al., 2003 No CV at 1 h, 2 d, 3 d, 4 d, or 7 d
ACA 27, 38, 24, 19, 16, 21 6 h, 12 h, 24 h, 36 h, 48 h, 72 h No CV at 1 h, 4 d, or 7 d
MCA 21, 16, 15, 12 6 h, 12 h, 24 h, 36 h No CV at 1 h, 2 d, 3 d, 4 d, or 7 d
SD rats BA 20 2 d Gules et al., 2002 No CV at 7 d
Pcom 20 2 d No CV at 7 d
Wistar rats ICA, ACA, MCA, and PCA No significant difference 5 d Turowski et al., 2007
C57Bl/6 mice BA 9 24 h Chaichana et al., 2007
C57Bl/6 mice MCA 18 6 h Luo et al., 2016 CV measured via two-photon imaging
SD rats BA 20 5 d Raslan et al., 2012
CISTERNA MAGNA-DOUBLE INJECTION
SD rats BA 47 5 d Vatter et al., 2006 No CV at 2 d, 3 d, 7 d, 9 d
SD rats BA 9 and 46 3 d, 5 d Güresir et al., 2012
SD rats BA 7 and 45 3 d, 5 d Güresir et al., 2010
SD rats BA 40 5 d Raslan et al., 2012
SD rats BA 36 5 d Lee et al., 2008 No CV immediately after SAH
Wistar rats BA 20 3 d Takata et al., 2008 No CV at 7 d
MCA 23 3 d No CV at 7 d
SD rats BA 32 5 d Weidauer et al., 2006 No CV at 11 d
SD rats BA 37 and 32 5 d, 7 d Meguro et al., 2001
Pcom 39 and 46 5 d, 7 d
SD rats BA 4 and 10 90 min, 24 h Lee et al., 2009
ACA 23 and 26 90 min, 24 h
SD rats ACA 51, 50, 44, 30 1 d, 3 d, 5 d, 7 d Cai J. et al., 2012
MCA 59, 57, 52, 42 1 d, 3 d, 5 d, 7 d
SD rats BA 33 7 d Gules et al., 2002
Pcom 35 7 d
SD rats BA 38 5 d Wang et al., 2010
SD rats BA 40, 36, 22 3 d, 5 d, 7 d Zhao et al., 2016
SD rats BA 50 and 46 3 d Chang et al., 2015a
SD rats BA 47 3 d Chang et al., 2015b
SD rats BA 67 3 d He et al., 2015
PRECHIASMATIC CISTERN-SINGLE INJECTION
SD rats ACA 55, 60, 32, 31 1 d, 3 d, 5 d, 7 d Cai J. et al., 2012
MCA 56, 64, 50, 44 1 d, 3 d, 5 d, 7 d
SD rats ACA 50 8 d Jeon et al., 2010
CD1 mice MCA 51 7 d Sabri et al., 2009
ACA No significant difference 7 d
Wistar rats MCA 16 2 d Piepgras et al., 1995
ENDOVASCULAR PERFORATION
SD rats ICA 17 1 d Sugawara et al., 2008
Wistar rats ICA 12 2 d Van Den Bergh et al., 2005
C57Bl/6 mice MCA 57 3 d Parra et al., 2002
SD rats ICA 51 60 min Bederson et al., 1998
ACA 43 60 min
SD rats ACA 45 and 48 90 min, 24 h Lee et al., 2009
BA 33 and 44 90 min, 24 h
SD rats BA 17 2 d Gules et al., 2002 No CV at 7 d
Pcom 25 2 d No CV at 7 d
C57Bl/6 mice MCA 27 2 d Vellimana et al., 2011
C57Bl/6 mice ACA 33 3 d Sheng et al., 2011
MCA 29 3 d
ICA 31 3 d
SD rats BA 43 5 d Qin et al., 2015
MCA 23 5 d
ACA 42 5 d
SD rats BA 33 3 d Huang et al., 2015

Information presented includes rodent strain, severity, and location of cerebral vasospasm, and the timing of vasospasm post-SAH induction. Severity of cerebral vasospasm is measured as the percent reduction in vessel diameter. CV, cerebral vasospasm, SD, Sprague Dawley; BA, basilar artery; ACA, anterior cerebral artery; MCA, middle cerebral artery; Pcom, posterior communicating artery; PCA, posterior cerebral artery; ICA, internal carotid artery.

In the endovascular perforation model, CV is observed in the ICA (Bederson et al., 1998; Parra et al., 2002; Van Den Bergh et al., 2005; Sugawara et al., 2008), ACA (Bederson et al., 1998; Lee et al., 2009), MCA (Parra et al., 2002), Pcom (Gules et al., 2002), and even the BA (Gules et al., 2002; Lee et al., 2009). This variability in the CV location is likely due to an inability to directly control both the specific hemorrhage location and the amount of blood in this model. In contrast, when Altay and colleagues specifically transected a vein in the cisterna magna of mice simulating non-aneurysmal SAH, they noted CV only in the MCA (Altay et al., 2009).

Timing of cerebral vasospasm in rodent models of SAH

The need for a reliable tool to measure the rodent vasculature in vivo is necessary to properly quantify the temporal nature of CV in these preclinical models. Initiation of CV is difficult to determine, as rodents are typically sacrificed to measure vessel diameter directly, preventing temporal observation of vessel narrowing. However, using the methodologies herein described, several studies have recorded chronological findings of CV occurrence in both the direct injection and endovascular perforation models of SAH.

In rodent single injection cisterna magna models, CV is most common at 2 d (Delgado et al., 1985; Gules et al., 2002), but has also been shown at 10 min (Delgado et al., 1985), 6 h (Lin et al., 2003), 12 h (Lin et al., 2003), 36 h (Lin et al., 2003), and 3 d (Ram et al., 1991). In double injection cisterna magna models, CV is most reproducibly found at 3 d (Takata et al., 2008; Güresir et al., 2010, 2012) and 5 d (Meguro et al., 2001; Vatter et al., 2006; Weidauer et al., 2006; Lee et al., 2008; Güresir et al., 2010; Raslan et al., 2012). Moreover, maximal narrowing of vessels in this model has been reported at 7 d (Dombovy et al., 1998; Lee et al., 2009). Injection into the prechiasmatic cistern resulted in CV at 2 d (Piepgras et al., 1995), 3 d (Cai J. et al., 2012), 5 d (Cai J. et al., 2012), 7 d (Sabri et al., 2009; Cai J. et al., 2012), and 8 d (Jeon et al., 2010). Finally, in endovascular perforation models, CV is seen at 1 h (Bederson et al., 1998), 90 min (Lee et al., 2009), 1 d (Sugawara et al., 2008; Lee et al., 2009), 2 d (Gules et al., 2002; Van Den Bergh et al., 2005), and 3 d (Parra et al., 2002).

Of these models, in regards to the development of CV, the double injection model into the cisterna magna has classically been cited as the most similar to humans, due to the paralleled maximal narrowing of cerebral vessels at 7 d (Dombovy et al., 1998; Lee et al., 2009). However, some researchers have studied CV in this model on 7 and 9 d after SAH and were not able to reproduce the findings (Vatter et al., 2006; Takata et al., 2008). Similarly, injection in the prechiasmatic cistern produces CV at 7 and 9 d (Sabri et al., 2009; Jeon et al., 2010; Cai J. et al., 2012). It remains unclear what model most reproducibly replicates clinical SAH pathophysiology in regard to the development of CV.

Severity of cerebral vasospasm in rodent models of SAH

In addition to the temporospatial nature of CV in rodent SAH models, the severity of CV can be assessed and is an important consideration. It is generally regarded as the degree of vessel constriction, either as a decrease in the luminal diameter or cross sectional area (Sobey and Faraci, 1998), although some studies have reported a decrease in vessel perimeter (Meguro et al., 2001). Notably, there is no standardized method for quantifying the severity of CV; however, it can be expressed as the percent reduction in vessel size regardless of the methodology employed, as reflected in Table 4. Due to the lack of standardization, the severity of rodent CV ranges widely, from as low as 10% in some studies to 64% in others depending on location of CV and on the method used to measure vessel size. In single injection cisterna magna models, the degree of constriction ranges from 20 to 40% (Delgado et al., 1985; Gules et al., 2002; Lin et al., 2003). In double injection cisterna magna models, CV tends to be more severe, with a constriction ranging from 20 to 64% (Meguro et al., 2001; Gules et al., 2002; Vatter et al., 2006; Weidauer et al., 2006; Lee et al., 2008, 2009; Takata et al., 2008; Güresir et al., 2010, 2012; Cai J. et al., 2012; Raslan et al., 2012). In prechiasmatic cistern single injection models, the degree of CV is reported as 17–62% (Piepgras et al., 1995; Sabri et al., 2009; Jeon et al., 2010; Cai J. et al., 2012). Finally, endovascular perforation models show a vessel reduction of 10–57% (Bederson et al., 1998; Gules et al., 2002; Parra et al., 2002; Van Den Bergh et al., 2005; Sugawara et al., 2008; Lee et al., 2009). The vast ranges recorded in these studies once again exemplify the need for both a standardized model of SAH induction and method for quantifying CV.

Cerebral vasospasm-induced neuronal death in rodent models of SAH

Among histopathological outcomes observed and reported, neuronal cell loss is an important parameter for consideration in rodent SAH models. The causal mechanism of neuronal death after SAH can in part be attributed to EBI and to CV and subsequent ischemia. At 24 h, 5, 7 d, and as far as 8 d post-SAH, CV and neuronal death were observed simultaneously in rodent specimens (Lee et al., 2009; Sabri et al., 2009; Güresir et al., 2010; Jeon et al., 2010).

Several methods are available to evaluate neuronal death. Conventional techniques such as H&E staining (Prunell et al., 2003; Feiler et al., 2010; Güresir et al., 2010) can depict global necrosis of brain tissue and slightly more neuron-specific stains like cresyl violet can offer added specificity (Westermaier et al., 2009b). However, these stains detect features such as vacuolation and hyperchromatism that are not specific to neuronal degeneration, and are thus prone to false positives (Cammermeyer, 1961). Silver stains are more specific for degenerating neurons, but are more time-consuming and intensive (de Olmos et al., 1994). Addressing these issues, TUNEL and Fluoro-Jade have been used to assess tissues for degenerating neuronal cells (Takata et al., 2008; Lee et al., 2009; Sabri et al., 2009; Silasi and Colbourne, 2009; Jeon et al., 2010). TUNEL reveals DNA breaks in cells undergoing programmed cell death via an immunohistochemical staining procedure (Gavrieli et al., 1992), while Fluro-Jade detects the cell bodies, dendrites, axons, and axon terminals of degenerating neurons via an acidic fluorophore that binds specifically to dying neurons (Schmued et al., 1997). Fluoro-Jade can identify both apoptotic and necrotic cells, as opposed to the apoptosis-specific TUNEL method; as such, the neuronal damage assessed with TUNEL is often less pronounced than that identified with Fluoro-Jade (Lee et al., 2009). For example, apoptotic cells were not observed in the mouse hippocampus subjected to TUNEL in a 2009 study although neuronal injury was visualized in that region using Fluoro-Jade imaging (Sabri et al., 2009).

Regardless of the staining method used, neuronal damage is commonly observed in the hippocampus and cortex in all the rodent SAH models assessing this outcome (Prunell et al., 2003; Takata et al., 2008; Lee et al., 2009; Westermaier et al., 2009b; Feiler et al., 2010; Güresir et al., 2010; Jeon et al., 2010). Neuron death can also occur in regions such as the cerebellum (Jeon et al., 2010) and basal ganglia (Lee et al., 2009). Interestingly, the study identifying necrotic cells in the cerebellum utilized a prechiasmatic cistern injection model of SAH, thus observing neuronal damage in a location relatively distant from the injection site (Jeon et al., 2010). In contrast, cisterna magna injection models produce neuronal death in the hippocampus and cerebellum, locations in close proximity to the clot site (Takata et al., 2008; Lee et al., 2009; Güresir et al., 2010; Jeon et al., 2010). In a 2003 study comparing the incidence of neuronal cell loss between SAH models, only 11% of rats in the perforation model exhibited neuronal loss compared to 28 and 44% of rats in the cisterna magna and prechiasmatic cistern models, respectively (Prunell et al., 2003). Additionally, Lee et al. (2009) showed that neuronal degeneration has a tendency for sidedness in the endovascular perforation model, where cell death occurs more frequently ipsilateral to the puncture (Lee et al., 2009).

Molecular pathways of cerebral vasospasm

Multiple molecular pathways of CV have been proposed, including nitric oxide scavenging, disruption of endothelin-1 (ET1), toxicity of blood breakdown products, and inflammation. It is likely that not one pathway is responsible for the development of CV, but rather that each of these pathways is acting concurrently and influencing each other throughout the course of CV pathophysiology.

ET1 is a soluble factor primarily produced by the vascular endothelium and is a canonical potent vasoconstrictor (Sumner et al., 1992; Schneider et al., 2007). ET1 binds the ETA and ETB receptors expressed by the vascular smooth muscle cells resulting in vasoconstriction via phospholipase C activation, inositol trisphosphate (IP3) production, and calcium mobilization (Schneider et al., 2007). Following SAH, ET1 is produced by activated mononuclear leukocytes in the CSF and is elevated acutely in patients that develop CV and neurological deterioration (Fassbender et al., 2000; Thampatty et al., 2011). Given the potent and prolonged effects of ET1, it remains a top contender in mediating the development of CV, and, therefore, also remains a therapeutic target (Penn et al., 2015). Although, a recent meta-analysis of the four clinical trials investigating the use of clazosentan, an endothelin receptor antagonist, showed that the drug does reduce the incidence of CV and DCI, but does not significantly improve neurologic outcomes (Shen et al., 2013).

A second main theory for the molecular pathways involved in the development of CV is regarding the presence of red blood cells, and their main cellular component, hemoglobin, in close proximity to the major cerebral vessels traversing through the CSF (MacDonald and Weir, 1991; Zhang et al., 2001; Asleh et al., 2003; Buehler et al., 2009). This correlation is further strengthened by the known association between the volume of blood in the subarachnoid space and the severity of angiographic vasospasm (Kolias et al., 2009) and a study involving monkeys where removal of the blood clot was shown to reverse angiographic vasospasm (Zhang et al., 2001). More specifically, CV has its onset around day 3 after aSAH, peaks on days 6–8, and usually lasts 2–3 weeks (Kolias et al., 2009). Phagocytosis and lysis of RBCs occurs by 16–32 h, peaks around day 7, and continues for days, with clumps of intact RBCs still enmeshed in the arachnoid for up to 35 days (MacDonald and Weir, 1991). Furthermore, it has been documented that changes in hemoglobin concentrations within the CSF tend to mirror the evolution of CV, though the mechanisms by which extracorpuscular hemoglobin causes delayed arterial narrowing are multiple and poorly understood (Dreier et al., 2002; Nishizawa and Laher, 2005; Pluta et al., 2009). Possibilities include neuronal apoptosis, scavenging or decreased production of the vasodilator nitric oxide, increased ET1 levels, direct oxidative stress on smooth muscle cells, ROS production and lipid peroxidation of cell membranes, modification of potassium and calcium channels, and differential up-regulation of genes (Pluta et al., 2009). In addition to hemoglobin itself, its breakdown products heme, iron, bilirubin, and bilirubin oxidation products have been implicated in initiating oxidative stress and a toxic neuroinflammatory cascade that contributes to the development of CV (MacDonald and Weir, 1991; Clark and Sharp, 2006). Improving the clearance of blood products from the brain remains a viable therapeutic target following SAH, as it would also inhibit nitric oxide scavenging and thereby shift the balance toward a more vasodilatory environment.

Comparison of cerebral vasospasm and delayed cerebral ischemia in preclinical models and clinical SAH

It is difficult to assess whether similar arteries are affected in preclinical models and clinical SAH due to the limited and varied number of arteries assessed in preclinical studies when compared to clinical counterparts. In addition, whereas in clinical SAH the timing of CV usually occurs 6–8 days post-stroke, in preclinical models the timing varies dramatically both within and between models. This discrepancy is particularly noteworthy given the implications of CV in poor functional outcomes following clinical SAH. Moreover, barriers to the reproducibility of CV in preclinical models hinder efforts to studying the mechanisms that underlie its pathophysiological sequelae, as well as its severity. One other barrier to studying severity of CV is the histopathological methods used to measure vessel narrowing, which often tend to warp the shape or size of the vessels prior to analysis. Finally, despite the severe clinical consequences of DCI in clinical SAH, it is frequently not observed in preclinical models.

Pathophysiology of rodent models of SAH

In addition to the anatomic changes that occur in cerebral vessels following SAH, several physiological parameters are substantially affected. CBF, ICP, MABP, CPP change throughout the course of SAH pathophysiology, and these variables are related by the following equation:

CPP=MABP-ICP

Following the bleed, there is an acute rise in ICP, which is mirrored by a compensatory rise in MABP in an attempt to maintain CPP. This results in a decrease in both CPP and CBF if the magnitude and rate of change in ICP is greater than that of MABP (Young and Bowling, 2012). With time, CBF typically recovers due to the reflex rise in the MABP, unless CPP has decreased dramatically, in which case autoregulation is impaired and global ischemia ensues (McMullan et al., 2010).

These physiological parameters can be measured in preclinical SAH models. In non-aneurysmal SAH, all of these parameters follow the patterns seen in humans and return to near-baseline levels within 1 h post-induction of SAH. Figure 2 diagrams the interrelatedness between CBF, ICP, MABP, and CPP at baseline and within 1 h following experimental SAH in rodents. Additionally, Table 5 provides specific values for ICP, MABP, CPP, and CBF obtained from the various non-aneurysmal SAH models immediately following SAH and after 1 h (or as otherwise stated). These values have not been measured in aSAH mouse models due to the inability to predict the timing of spontaneous aneurysm rupture. As aSAH models are further developed and standardized, the quantification of physiological variables may be facilitated and improve our understanding of the differences in pathophysiology between the various SAH preclinical models and relevance to clinical SAH.

Figure 2.

Figure 2

Temporal changes in CBF, ICP, MABP, and CPP over 1 h after induction of SAH with the x-axis representing the progression of time and the y-axis as relative change in each parameter. Due to the variation in the absolute values of these parameters after SAH (refer to Table 5), the relative changes in the variables are shown because these trends are preserved in nearly all preclinical studies and in humans. CBF and CPP sharply decrease shortly after SAH, followed by a return to near-baseline values within 1 h. Similarly, there is an acute increase in both ICP and MABP, followed by a return to baseline or near-baseline values within 1 h. Values for CBF were taken from studies that measured CBF using laser Doppler flowmetry.

Table 5.

Summary of pathophysiological outcomes itemized by the model used for SAH induction in published studies that used various strains of mice or rats.

CISTERNA MAGNA-SINGLE INJECTION
CBF MABP ICP CPP
Rodent Acute (%Change) Recovery (%Baseline) Time Acute (%Change) Recovery (%Baseline) Time Acute (%Change) Recovery (%Baseline) Time Acute (%Change) Recovery (%Baseline) Time References Comments
SD rats −42 Baseline 60 min −10 Baseline 60 min +463 234 60 min −47 Baseline 60 min Lee et al., 2009
SD rats −94/−94 55/50 60 min +27 117 60 min +1,625 18 60 min Schwartz et al., 2000 Right hemisphere CBF/Left hemisphere CBF
SD rats −63 Baseline 90 min +5 Baseline 90 min +1,300 243 90 min −71 Baseline 90 min Prunell et al., 2003
SD rats −43 57 60 min Baseline Baseline 60 min +200 Baseline 60 min Solomon et al., 1985
SD rats −50 57 3 h +25 Baseline 3 h +1,150 400 3 h −20 85 3 h Jackowski et al., 1990
SD rats −18 82 3 h Swift and Solomon, 1988
SD rats −80 2 h Raslan et al., 2012
SD rats +8 Baseline 1 d Delgado et al., 1985 Preseted values pertain to animals injected with 300 μL of blood
SD rats +1,212 400 60 min Cai C. Y. et al., 2012
C57Bl/6 mice NS Baseline 60 min +270 292 30 min Luo et al., 2016
CISTERNA MAGNA-DOUBLE INJECTION
SD rats −48 75 60 min −10 Baseline 60 min +532 277 60 min −75 87 60 min Lee et al., 2009
SD rats −50 70 7 d +1,212 400 60 min Cai C. Y. et al., 2012
SD rats −32.5 110.5 1 d Lee et al., 2008
SD rats −70 2 h Raslan et al., 2012
Wistar rats 73 14 d Takata et al., 2008
SD rats NS Baseline Zhao et al., 2016
PRECHIASMATIC CISTERN-SINGLE INJECTION
Wistar rats −47 80 30 min −13* Baseline 30 min +662 190 30 min −57 30 min Piepgras et al., 1995
SD rats −69 89 90 min +9 Baseline 90 min +1,357 271 90 min −77 Baseline 90 min Prunell et al., 2003
SD rats −50 Baseline 7 d +1,090 380 60 min Cai J. et al., 2012
SD rats −94 Baseline 45 min +27 Baseline 45 min Jeon et al., 2010
CD1 mice −89 70 40 min Sabri et al., 2009
SD rats +20 Baseline 60 min +1,429 243 60 min Prunell et al., 2002
SD rats −82 Baseline 1 h +1,233 Baseline 60 min Ansar and Edvinsson, 2008
SD rats NS Baseline He et al., 2015
ENDOVASCULAR PERFORATION
SD rats −60 60 60 min +40 89* 60 min +1,175 339 60 min −93 68 60 min Lee et al., 2009
C57Bl/6 mice −81 80 30 min +5 77 30 min +1,439 588 30 min −75 60 30 min Feiler et al., 2010
SD rats −94* and −94/−88 and −94 67* and 75/70* and 58 60 min +29* and Baseline Baseline (both groups) 60 min +1,522* or +9,23 32* or 20 60 min Schwartz et al., 2000 Used filament sizes3–0* and 4–0, respectively; Right hemisphere CBF/Left hemisphere CBF
SD rats 50 min −67 75 50 min Bederson et al., 1995
SD rats −83 44 60 min +957 293 60 min −66 83 60 min Bederson et al., 1998
SD rats −29 Baseline 30 min −20 Baseline 30 min +332 30 min Park et al., 2008
SD rats −78* and −88 60* and 45 6 h +30 117 6 h +817 367 6 h −70 89 6 h Westermaier et al., 2009b Ipsilateral CBF* and contralateral CBF, respectively
SD rats −93, −81, and −68/−93, −81, and −74 47, 58, and 62/51, 57, and 78 120 min +38, +38, and NS Baseline, Baseline, and NS 120 min +783, +433, and +233 467, Baseline, and Baseline 120 min −46, NS, and NS Baseline, NS, and NS 120 min Westermaier et al., 2009a Used filament sizes3–0, 4–0, and 5–0, respectively; Ipsi CBF/contra CBF
SD rats −70 69 90 min +25 Baseline 90 min +1,243 414 90 min −57 Baseline 90 min Prunell et al., 2003
C57Bl/6 mice −45 81 30 min 15 Baseline 30 min 254 194 30 min Siler et al., 2015
C57Bl/6 mice −88 75 45 min 1,060 340 45 min Bühler et al., 2015
SD rats −75 74 60 min 1,400 400 60 min −55 82 60 min Hockel et al., 2012
SD rats NS Baseline 10 min 948 377 10 min Britz et al., 2007
SD rats −81 70 60 min Ostrowski et al., 2006
SD rats 755 and 580 90 min Hollig et al., 2015 Classic technique and modified technique, respectively
SD rats 14 57 20 min −26 Baseline <5 min Xu et al., 2015
SD rats −90 37 30 min +16 Baseline 30 min +564 231 30 min 55 Baseline 30 min Huang et al., 2015

Particular focus is placed on key physiologic parameters that change after SAH, including CBF, CPP, ICP, and MABP. Information presented includes rodent strain, values for both the acute and recovery phases, and the post-SAH time at which the values were measured. Acute phase values are presented as the overall percent change, while the recovery phase values are presented as the percent of baseline. Missing values indicate that the study either did not measure that particular variable or that no value was mentioned in the paper. CBF, cerebral blood flow; MABP, mean arterial blood pressure; ICP, intracranial pressure; CPP, cerebral perfusion pressure; SD, Sprague Dawley.

Cerebral blood flow in rodent models of SAH

CBF is the most studied physiological variable in rodent models due to its importance in evaluating ischemia following SAH. Clinically, CBF exhibits a biphasic pattern: blood flow drops to a nadir near zero flow immediately after the bleed, followed by a return to levels slightly below baseline, decreasing once again if delayed CV occurs (Luft et al., 2004).

In order to evaluate CBF fluctuations following SAH in rodents, laser Doppler flowmetry (LDF) is most commonly used, although other methods such as MRI and autoradiography are also employed (Van Den Bergh et al., 2005; Tiebosch et al., 2013). LDF involves advancing a laser-emitting fiber optic probe into the epidural space of an anesthetized rodent and measuring changes in the wavelength of backscattered light detected by the probe as erythrocytes pass through vessels beneath it (Sutherland et al., 2014). This method obtains instantaneous measurements of relative changes in CBF and can be used at any time during SAH induction experiments. However, LDF is disadvantageous in that it measures cortical blood flow rather than total CBF. Additionally, it only provides temporal measurements, as any spatial information is limited by the location in which the probe is placed. Despite these limitations, LDF is the current method of choice in conducting rodent CBF measurements.

In the cisterna magna single injection models employing LDF, CBF drops acutely to 6–82% of baseline values, recovering to 58–100% of baseline values within 1 h (Schwartz et al., 2000; Prunell et al., 2003; Lee et al., 2009; Raslan et al., 2012). In the cisterna magna double injection model, there is an acute decrease to 30–52% of baseline after the first injection (Lee et al., 2009; Cai J. et al., 2012; Raslan et al., 2012); however, CBF tends to remain below baseline in these models, sometimes for as long as 2–3 d following injection (Lee et al., 2009; Cai J. et al., 2012). The return of CBF to original values following SAH thus depends on the number of injections and amount of blood injected into the cisterna magna. The notion that the double hemorrhage model imparts a greater physiologic insult than the single injection model is further evidenced by a study performed by Raslan and colleagues in which CBF fell to 20% below baseline initially and 30% below baseline at 5 d concurrent with CV in the BA (Raslan et al., 2012). In the prechiasmatic cistern injection model, the CBF nadir ranged from 6 to 31% of baseline with a return to ~80–100% of baseline values 1 h after SAH (Piepgras et al., 1995; Prunell et al., 2003; Sabri et al., 2009; Jeon et al., 2010; Cai J. et al., 2012). Finally, in the endovascular perforation model, the CBF nadir was between 6 and 71%, with regression to 44–81% of baseline values (Bederson et al., 1995, 1998; Schwartz et al., 2000; Prunell et al., 2003; Park et al., 2008; Lee et al., 2009; Westermaier et al., 2009a,b; Feiler et al., 2010). Based off of these values, the perforation model appears to be the most debilitating in terms of CBF, where the severity of the CBF reduction after perforation is likely due to the extent of insult, which is difficult to control with this method.

In addition to LDF, radiolabeled tracer molecules have also been used to measure CBF. This method involves injecting a chemically inert diffusible tracer such as [14C]N-isopropyl-p-iodoamphetamine into the circulation. Arterial blood is then withdrawn at a continuous rate, the animal is sacrificed, and brain tissue is extracted. A scintillation counter is used to measure the concentration of the tracer in both the arterial blood and brain sections, and CBF is calculated from these concentrations and the rate of blood withdrawal (Sakurada et al., 1978). Microspheres have been employed in a similar manner, but to date, both of these methods have been used only in single (Kim and Cervos-Navarro, 1991; Klanke et al., 2008) and double cisterna magna injection models (Delgado et al., 1985; Solomon et al., 1985; Swift and Solomon, 1988; Jackowski et al., 1990; Ram et al., 1991; Lee et al., 2008; Takata et al., 2008). Single injection models employing this technique show an acute decrease in CBF from 50 to 82% of baseline, with return to baseline values within a few days thereafter (Solomon et al., 1985; Swift and Solomon, 1988; Jackowski et al., 1990). One double injection model showed a 62% decrease in CBF, followed by a regression to initial values over 24 h; however, CBF then decreased once again to 70% of baseline at 5 d, again exhibiting a biphasic pattern (Lee et al., 2008). Overall, the recovery of CBF to near original values is highly variable, even when investigators inject similar volumes of blood in the cisterna magna: recovery was noted at 24 h (Swift and Solomon, 1988), 2 d (Jackowski et al., 1990), 7 d (Lee et al., 2008; Cai J. et al., 2012), and 35 d (Takata et al., 2008). The variations in observations, in conjunction with the terminal nature of experiments, make radiolabel tracer molecules less attractive than LDF or more recently developed radiographic techniques.

In light of the limitations of both LDF and radiolabeling methods, recent advances have been made in measuring rodent CBF using MRI (Van Den Bergh et al., 2005; Vatter et al., 2006; Güresir et al., 2010, 2012; Tiebosch et al., 2013). The method involves acquiring T1-weighted images that are ultimately constructed into perfusion maps used to calculate global CBF. Additional benefit is added in that these measurements of CBF can be conducted serially in vivo. In contrast to other studies up to that point, Van Den Bergh and colleagues found that there was no significant difference in CBF following SAH induced by endovascular perforation compared with injection models. Another endovascular perforation study demonstrated a baseline increase of 200% of CBF at 2 d and 150% at 7 d in both the ipsilateral and contralateral somatosensory cortex, contradictory to the findings of prior studies which document decreases in CBF (Tiebosch et al., 2013). Although justification is unclear for the discrepancy between MRI and LDF findings in perforation models, a possible explanation may be due to the fact that MRI measures global blood flow, while standard LDF only measures cortical flow in specific locations dependent upon probe placement. Furthermore, some areas of the brain may be hyperperfused in relation to others as a protective measure following SAH induction, which would not be identified using LDF alone. In addition to investigations with the perforation models, other studies have employed MRI to investigate the subacute stages of CBF following SAH in the cisterna magna injection models. In double hemorrhage models, CBF showed a 33–50% decrease at 3 d and 27–44% at 5 d (Vatter et al., 2006; Güresir et al., 2010, 2012). Not surprisingly, there was also marked CV at 5 d in each of these experiments, which was responsible for the delayed reduction in CBF (Vatter et al., 2006; Güresir et al., 2010, 2012). Unlike the recorded discrepancy in data for endovascular perforation models, the biphasic nature of CBF identified by MRI is in line with studies using LDF for the double injection models.

In conclusion, CBF can be measured in rodent models using LDF, radiolabeling methods, and MRI. Radiolabeling methods tend to have some variability and require euthanizing the animal to obtain the data output, making them less attractive. While LDF is easy to perform and is currently the mainstay of CBF measurements, its use is mainly limited to during SAH induction and immediately thereafter. On the other hand MRI is more time consuming, difficult to perform, and it is not plausible to measure CBF during the acute phase after SAH induction, as is commonly done with LDF. Although, MRI offers the benefit of serial measurements in vivo and the ability to measure global CBF and CBF in specific regions of interest such that correlations can possibly be made to the location of CV at that time.

Intracranial pressure in rodent models of SAH

In addition to CBF, ICP is a commonly assessed physiological parameter following SAH. In the neurointensive care setting, increases in ICP are observed in over 50% of SAH patients (Badjatia et al., 2005). Typically, an ICP greater than 20 mmHg results in increased mortality and disability (MacDonald and Weir, 1991). In order to maintain an ICP within an appropriate range, the pressure is monitored continuously by insertion of a catheter through the parenchyma into the ventricles. The catheter is coupled to a pressure gauge that provides ICP values on a continuous basis (MacDonald and Weir, 1991).

Experimentally, a rise in ICP is often used as an indicator that SAH has occurred. As reflected in Figure 2, there is an acute rise in ICP after experimental SAH induction from the average rodent baseline of 5–7 mmHg, followed by a fall to either baseline or near baseline levels. While general trends in ICP can be outlined, measurements in rodent SAH models vary widely, perhaps due to the limitations of the method used to record ICP. At present, ICP is typically measured continuously via a catheter that is inserted into the rodent cranium through burr holes created in the calvarium, similar to the procedure done in humans.

More complications arise in injection models, as the added blood volume can alter ICP. Some studies attempt to correct for this confounding variable by not allowing ICP to increase above an arbitrarily-defined threshold while making the injection (Ram et al., 1991). Others have made multiple injections over a defined time period (Lacy and Earle, 1983), or attempted to keep the increase in ICP parallel to that of MABP during injection (Prunell et al., 2002, 2003). However, this is far from the ideal injection, which would occur at physiologic MABP. Furthermore, researchers often hold the rodent upside down following injection into the cisterna magna to facilitate blood distribution (Ram et al., 1991; Lin et al., 2003; Lee et al., 2008; Takata et al., 2008; Güresir et al., 2010, 2012; Cai J. et al., 2012; Munoz-Sanchez et al., 2012a). This step will falsely elevate the measured ICP. While injection models may elevate ICP erroneously due to the punctures created in the rodent cranium and subsequent maneuvers to distribute blood, these complications are not observed in the endovascular perforation model.

Despite the limitations in measuring ICP, important trends can be identified in the values obtained for this outcome following SAH. In cisterna magna single injection models, an acute rise from 18 mmHg to as much as 120 mmHg is observed following blood injection, with a subsequent decrease ranging from baseline values to 18 mmHg (Lacy and Earle, 1983; Solomon et al., 1985; Jackowski et al., 1990; Schwartz et al., 2000; Prunell et al., 2003; Lee et al., 2009; Cai J. et al., 2012). Interestingly, cisterna magna double injection models show a less dramatic increase, from 60 to 67 mmHg (Lee et al., 2009; Cai J. et al., 2012), followed by a reduction in ICP that remains consistently above baseline at 20–26 mmHg (Lee et al., 2009; Cai J. et al., 2012). In prechiasmatic cistern injections, the ICP rises to 46–107 mm Hg following injection, decreasing to values between 11 and 19 mmHg over time (Piepgras et al., 1995; Prunell et al., 2002, 2003; Jeon et al., 2010). Finally, in endovascular perforation models, the ICP acutely rises to values between 27 and 110 mmHg, subsequently decreasing to between 17 and 32 mmHg, which is higher than what is observed in injection models (Bederson et al., 1998; Schwartz et al., 2000; Prunell et al., 2003; Park et al., 2008; Lee et al., 2009; Westermaier et al., 2009a,b; Feiler et al., 2010).

Cerebral perfusion pressure in rodent models of SAH

To date, direct measurement of CPP in rodents has not been described. Indirect quantification of CPP is possible via Equation (1). In this simple calculation, CPP is derived from the ICP and MABP, parameters that are easily measured using the methods outlined herein. Both MABP and ICP increase following SAH; however, the rise in MABP does not match that of ICP. Consequently, the CPP immediately following SAH falls. If the ICP rise is high enough, it may cause death due to lack of cerebral perfusion. Figure 2 depicts the pathophysiologic pattern of an immediate decrease in CPP after SAH, followed by a return to baseline levels within 1 h.

In cisterna magna single injection models, there is an acute 20–85% decrease in CPP, with recovery to baseline within about 1 h (Lacy and Earle, 1983; Jackowski et al., 1990; Prunell et al., 2003; Lee et al., 2009). The only study measuring CPP in a double injection model showed an acute decrease to 27% of baseline values, with a subsequent return to 92% of starting CPP (Lee et al., 2009). It is reasonable to suggest that the greater degree of hemorrhage in the double injection model prevents a return of CPP to initial values. Finally, in prechiasmatic cistern injection models, CPP acutely decreases to 23–49% of initial values, with recovery to baseline shortly thereafter (Piepgras et al., 1995; Prunell et al., 2003). In contrast to the injection models, more CPP data is available for studies inducing SAH using endovascular perforation. This model exhibits the greatest degree of CPP change; however, values are often inconsistent or contradictory. Acutely, there is a drastic decrease from 7 to 54% of initial CPP, followed by a return to 55–100% of baseline within an 1 h (Bederson et al., 1995, 1998; Prunell et al., 2003; Lee et al., 2009; Westermaier et al., 2009a,b; Feiler et al., 2010). One study even noted an extreme rise in ICP to 150 mmHg, resulting in a rapid drop of CPP and subsequent death of the rodents (Lee et al., 2009). Ultimately, the larger magnitude of CPP change observed in endovascular perforation models likely results from to the inability to control the degree of hemorrhage after filament insertion, in addition to the possibility of a longer duration of insult compared with injection models.

Mean arterial blood pressure in rodent models of SAH

As reflected In Figure 2, MABP typically rises acutely following experimental SAH to preserve CPP and falls to baseline or near baseline levels thereafter, similar to the clinical counterpart.

The magnitude of the MABP increase observed in rodent studies varies with the SAH model and is typically measured by either a tail artery catheter, tail cuff sphygmomanometer (Sugawara et al., 2008; Zhao et al., 2011), femoral artery cannula (Lacy and Earle, 1983; Delgado et al., 1985; Jackowski et al., 1990; Schwartz et al., 2000; Prunell et al., 2003), or a radiotelemetry system (MacMillan et al., 2002; Pemberton et al., 2002; Zoerle et al., 2015). In 1992, Rasmussen et al. showed that the autoregulation of MABP and CBF was markedly disturbed as far as 5 d beyond induction of SAH in a single injection cisterna magna model, hypothesizing that such prolonged disturbance could possibly be due to delayed CV (Rasmussen et al., 1992). In additional single injection cisterna magna studies, the MABP acutely rose to 105–150% of baseline value immediately after SAH (Lacy and Earle, 1983; Delgado et al., 1985; Jackowski et al., 1990; Schwartz et al., 2000; Prunell et al., 2003). Regardless of this instance, the MABP values for single injection cisterna magna models predominantly returned to baseline values over time (Delgado et al., 1985; Jackowski et al., 1990; Prunell et al., 2003; Lee et al., 2009). In double injection cisterna magna models, only one study recorded MABP data, showing an acute 90% decrease, followed by a return to initial values, further demonstrating that autoregulatory mechanisms may be disrupted following SAH induction (Lee et al., 2009). In prechiasmatic cistern injection models, MABP rises to 109–127% of baseline values, followed by recovery to initial MABP (Prunell et al., 2002, 2003; Jeon et al., 2010; Cai J. et al., 2012).

Endovascular perforation models generally produce higher transient MABPs than injection models. However, these results vary greatly depending on the size of the suture employed (Prunell et al., 2003; Lee et al., 2009). For example, perforation with a 4-0 prolene suture will not significantly raise the MABP, while a 3-0 suture will produce a MABP higher than that induced by a 300 μL autologous blood injection in the cisterna magna (Schwartz et al., 2000). Furthermore, one study recorded a transient drop in blood pressure after perforation rather than the expected rise (Park et al., 2008). As in the case of the similar prechiasmatic cistern study, this drop may be attributed to a failure in autoregulatory mechanisms due to the hemorrhagic insult. Overall, following SAH induced by endovascular perforation, MABP will typically increase to 105–140% of baseline values (Schwartz et al., 2000; Prunell et al., 2003; Park et al., 2008; Lee et al., 2009; Westermaier et al., 2009a,b; Feiler et al., 2010). Unlike other models, the recovery is not always to initial values, but between 89 and 117% of MABP recorded prior to SAH induction (Schwartz et al., 2000; Prunell et al., 2003; Park et al., 2008; Lee et al., 2009; Westermaier et al., 2009a,b; Feiler et al., 2010).

Comparison of pathophysiology in preclinical models and clinical SAH

Previous studies that utilized preclinical models of SAH have shown large variability in the absolute values of physiological parameters following induction of SAH both across and within different models. Whereas in clinical SAH the absolute value of these parameters typically depends on the magnitude of the hemorrhage, in preclinical models it can be influenced by a number of different factors, such as the model and surgical procedures used, anesthetics used, and measurement methods, particularly in the endovascular perforation model. On the other hand, trends in the relative change in these physiological parameters after the initial insult generally tend to be preserved between preclinical models of SAH and clinical SAH. In general, these variables can be assessed in rodent models of SAH, and new techniques are emerging to allow for more accurate measurement of such parameters. In optimizing these protocols, experimental methods should be standardized such that the data obtained in experimental models can not only be linked to functional outcomes in rodents, but can also be reliably correlated with the clinical picture of SAH in humans.

Mortality and functional outcomes in rodent models of SAH

Assessment of neurological function in rodent models of SAH

Studies of experimental SAH in rodents frequently include documentation of changes in rodent body weight. A reduction in weight after SAH tends to correlate with an overall decrease in neurological function. Overall, there is no apparent difference in magnitude of weight loss among the SAH models. In rats, weight loss following surgery ranged from 5 to 12%, regardless of which method was used to induce SAH (Delgado et al., 1985; Rasmussen et al., 1992; Glenn et al., 2002; Parra et al., 2002; Prunell et al., 2002; Kojima et al., 2005; Takata et al., 2008; Lee et al., 2009; Jeon et al., 2010). Uniquely, one endovascular perforation study conducted in the mouse showed a weight loss of ~20%, slightly higher than that seen in the rat models (Feiler et al., 2010).

Motor ability is another functional parameter observed after SAH, whether assessed with specific tests or with general observations of animal motility. The majority of studies showed that rodents are drowsy after surgery, but very few experience focal deficits or paralysis for up to 15 d past surgery (Barry et al., 1979; Delgado et al., 1985; Solomon et al., 1987; Swift and Solomon, 1988; Rasmussen et al., 1992; Bederson et al., 1995; Piepgras et al., 1995; Gules et al., 2002; Lin et al., 2003; Altay et al., 2009; Lee et al., 2009; Raslan et al., 2012). While, other investigations have reported rodent paresis following SAH (Prunell et al., 2003; Kojima et al., 2005; Lee et al., 2008; Raslan et al., 2012). For example, a study of the three major SAH models showed hemiparesis in 33% of rodents injected in the prechiasmatic cistern, compared with 14% in the single injection cisterna magna model and 11% in the perforation model (Prunell et al., 2003). Additionally, Kojimia et al. observed a light paresis in 36% of rodents subjected to endovascular perforation, attributing it to cerebral ischemia following SAH (Kojima et al., 2005).

Motor and behavioral function can be compositely evaluated with scoring systems analogous to those used clinically. A test developed by Bederson et al. (1986) observes forelimb flexion, resistance to lateral pushing, and circling behavior of rodents. Animals that have experienced ischemic events will incur a higher score on the Bederson scale (Rademaker et al., 2002b). Many protocols modify the scale to easily and serially detect neurological impairments after SAH (Parra et al., 2002; Vatter et al., 2006; Feiler et al., 2010; Güresir et al., 2010, 2012); however, the scales are limited due to the subjectivity in assessing each mouse, introducing variation in scores from observer to observer (Rosengart et al., 2007). Because of this setback, study results can be contradictory: some show the greatest decline in scores between 0 and 3 d following SAH with subsequent improvement (Parra et al., 2002; Vatter et al., 2006; Feiler et al., 2010), while others observe the most severe deficits at 5 d after SAH (Güresir et al., 2010, 2012). The worst neurological scores incurred on the Bederson scale occur between 0 and 5 d and are correlated with maximum CV (Vatter et al., 2006). Another scoring system is described by Garcia et al. which assesses motor activity through observations of spontaneous activity, symmetry of movement in the extremities, forepaw outstretching, climbing, lateral push, and vibrissae touch response (Garcia et al., 1995). Perforation models show a deficit by these criteria 1 d after SAH, which recovered thereafter, reaching near baseline levels at 7 d (Sugawara et al., 2008; Tiebosch et al., 2013). Using this scale, Cai et al. compared the prechiasmatic cistern injection model to the cisterna magna model, where the former had lower neurological scores at 3 d, although there was no significant difference between the groups (Cai J. et al., 2012). Additionally, a similar scoring system described by Feldmen et al. was used to compare a double to single hemorrhage cisterna magna model at 1 and 2 d, and weeks 1, 2, and 3 after SAH (Feldman et al., 1996; Boyko et al., 2013). Similar deficits resulted between both hemorrhage groups at 24 h after each injection, but deficits were attenuated by 1 week (Boyko et al., 2013).

Other tests include the use of apparatuses like grids, cylinders, ledge-tapered balance beams, pellet retrieval reaching chambers, staircases and ladder rungs to assess motor function (Rosengart et al., 2007). Sensorimotor function can be tested on apparatuses like the accelerated rotarod (Dunham and Miya, 1957). The use of these tests involves pre-training rodents for specific tasks before induction of SAH, followed by serial testing each day after hemorrhage (Takata et al., 2008; Silasi and Colbourne, 2009). Some studies have revealed an immediate decrease in function following SAH, with progressive improvement over a period of 4 weeks (Takata et al., 2008). In contrast, others observe no significant differences in skills with measurements conducted until 3 weeks following SAH (Silasi and Colbourne, 2009).

In addition to motor and sensorimotor assessment, cognitive impairments in spatial and working memory can be evaluated using the Morris Water Maze (MWM) task (Morris, 1984). The MWM involves placing animals in a round pool filled with opaque water and observing the rodents as they swim to a submerged platform to escape the water. Parameters such as initial heading angle, escape latency, swim time, and path length are measured and correlate to spatial learning and working memory functions. Trials with the MWM show increases in both swim time and distance between 3 and 5 weeks after SAH (Takata et al., 2008; Silasi and Colbourne, 2009). Another study showed increased escape latency at 2–5 d after hemorrhage; however, the increase in escape time was attributed to subacute motor deficits rather than memory deficits (Jeon et al., 2010). The same study showed no other deficits in working or reference memory on days 6–8, postulating that the neurologic deficits take more time to manifest (Jeon et al., 2010).

In addition to the cognitive function assessments, affective behavior tests include forced swim, elevated plus maze, sucrose preference, and open field tests (Boyko et al., 2013). Notably, rats that had undergone a double hemorrhage had worse deficits compared to single hemorrhage rats (Boyko et al., 2013).

Cerebral vasospasm and delayed neurological deficits in rodent models of SAH

To accurately depict the clinical course of SAH in humans, delayed CV in rodents should result in neurological deficits due to cerebral ischemia. For example, Parra and colleagues showed a correlation between proximal MCA diameter and neurological score in a perforation model, indicating that CV played a role in neurological deficits following SAH in this model (Parra et al., 2002). Additionally, a cisterna magna model showed the worst neurological deficit at 5 d concurrent with the maximal degree of CV (Güresir et al., 2010, 2012). In a comparison of injection models, there was delayed CV at 3 d and 7 d with marked neurological deficits also appearing at 3 d (Cai J. et al., 2012). Departing from these trends, some injection models showed the greatest CV at 5 d, but yielded the worst neurological deficit at 0–3 d with attenuation by 5 d (Vatter et al., 2006; Lee et al., 2008). In the same manner, a prechiasmatic cistern model showed CV at 8 d, but no change in a working memory task completed that same day (Jeon et al., 2010). Although this case did not exhibit working memory defects, a spatial learning deficit manifested at 5 d, the final day of serial measurements of this parameter (Jeon et al., 2010). CV was not assessed at 5 d, inhibiting the correlation between spatial learning deficits and documented arterial narrowing.

In addition to these acute and subacute correlations, future studies are necessary that observe the effect of CV on long-term outcomes after SAH in rodents. Working and spatial memory tasks carried out weeks after hemorrhage result in significant neurological deficits (Takata et al., 2008; Silasi and Colbourne, 2009; Boyko et al., 2013), despite the fact that CV is largely attenuated in rodents roughly 1 week following SAH. These observations could be a result of neuronal death induced by DCI following CV, but additional studies are necessary to establish this correlation. Although studies have evaluated acute brain damage following hemorrhage with MRI (Van Den Bergh et al., 2005; Vatter et al., 2006; Güresir et al., 2010, 2012; Tiebosch et al., 2013), the damage has not been assessed during the weeks to months after the initial bleed. Further studies are necessary to evaluate the extent of neuronal damage in the rodent brain at these time points and its relation to longitudinal neurological function and overall survival.

Mortality in rodent models of SAH

Rodent models of SAH exhibit a wide range of mortality (Table 6). Cisterna magna single injection models produce 0–16% mortality (Delgado et al., 1985; Solomon et al., 1985; Ram et al., 1991; Glenn et al., 2002; Gules et al., 2002; Lin et al., 2003; Prunell et al., 2003; Turowski et al., 2007; Munoz-Sanchez et al., 2012a; Boyko et al., 2013), while cisterna magna double injection models exhibit a greater range of 0–43% rate within the first few days (Glenn et al., 2002; Gules et al., 2002; Weidauer et al., 2006; Lee et al., 2008, 2009; Cai J. et al., 2012). At a later time point of 9 d following hemorrhage, mortality was as high as 53% in one double injection model (Vatter et al., 2006). The discrepancy in ranges between the two models is likely due to the amount of blood injected, with more blood increasing mortality risk. The prechiasmatic cistern injection model shows a higher mortality than the cisterna magna models, likely due to the hemorrhage location and smaller volume of the prechiasmatic cistern. In this model, mortality ranges from 10 to 33% within several days following hemorrhage (Prunell et al., 2002, 2003; Sabri et al., 2009; Jeon et al., 2010; Cai J. et al., 2012). However, mortality varies depending on the volume of blood administered. For example, Prunell and colleagues showed that a volume of 300 μL of autologous blood produces almost 100% mortality in rats 1 week post-injection, while 200 μL produces only 25% mortality (Prunell et al., 2002). Compared with injection models, endovascular perforation yields a higher mortality, with rates ranging from 16 to 66% (Bederson et al., 1995, 1998; Gules et al., 2002; Prunell et al., 2003; Kojima et al., 2005; Van Den Bergh et al., 2005; Park et al., 2008; Sugawara et al., 2008; Lee et al., 2009; Silasi and Colbourne, 2009; Feiler et al., 2010; Tiebosch et al., 2013).

Table 6.

Summary of mortality itemized by the model used for SAH induction in published studies that used various strains of mice or rats.

Rodent Number Mortality References Comment
CISTERNA MAGNA-SINGLE INJECTION
Wistar rats 13 23 Munoz-Sanchez et al., 2012a 3 SAH rats died during procedure, 1 within 48 h; 1 sham rat died
Wistar rats 7 0 Turowski et al., 2007 1 rat died due to anesthesia
SD rats 22 0 Glenn et al., 2002 1 rat died due to cannulation complications
SD rats 25 0 Ram et al., 1991 Some rats died during photography of the BA
SD rats 52 12 Delgado et al., 1985 0.3 mL blood injection + angiography at 5, 10, 15, 30, 60, 90 min and 1, 2, 3, 5, 7 d post-surgery; deaths attributed to respiratory failure secondary to obstruction of the tracheal tube
6 0 0.07 mL injection of blood + angiography at 10 min and 2 d post-surgery
8 0 0.3 mL injection of blood, no angiography
SD rats 6 0 Solomon et al., 1985
C57Bl/6 mice 59 2 Lin et al., 2003 1 mouse died of respiratory failure immediately following SAH, 1 died of internal bleeding from an IP injection
SD rats 7 0 Prunell et al., 2003
SD rats 10 0 Gules et al., 2002
CISTERNA MAGNA-DOUBLE INJECTION
SD rats 8 and 14* 25 and 43* Güresir et al., 2010 3 d sacrifice; 5 d sacrifice*
SD rats 15 or 54* 40 or 2* Lee et al., 2008 0.3/0.2 mL of blood injection; 0.2/0.1 mL blood injection*
SD rats 45 47 Vatter et al., 2006 6 rats died within 6 h of second blood injection, 5 rats between 2 and 3 d, 9 rats between 3 and 5 d, 1 rat at 6 d
SD rats 57 23 Cai J. et al., 2012 Mortality defined as death within 48 h of surgery
SD rats 23 0 Lee et al., 2009
SD rats 11 9 Gules et al., 2002 Death occurred on the 3rd day after the second injection of blood
SD rats 19 21 Wang et al., 2010 Mortality defined as death within 120 h of surgery
SD rats 30 20 Zhang D. et al., 2015 Mortality defined as death within 48 h of surgery
SD rats 48 0 Zhao et al., 2016
SD rats 25 20 Zhang D. et al., 2015 Mortality defined as death within 72 h of surgery
PRECHIASMATIC CISTERN-SINGLE INJECTION
SD rats 54 13 Cai J. et al., 2012 Mortality defined as death within 48 h of surgery
SD rats 13 31 Jeon et al., 2010 Death occurred within 24 h of surgery
CD1 mice 10 10 Sabri et al., 2009 Death occurred within 24 h of surgery
SD rats 12 25 Prunell et al., 2003
SD rats 4, 4*, 12# 100, 50*, 25# Prunell et al., 2002 Groups injected with 0.3 mL, 0.25 mL*, and 0.2 mL# autologous blood
SD rats 194 19 Zhang D. et al., 2015
SD rats 4 Ansar and Edvinsson, 2008 Did not report sample size
SD rats 44 18 Zhang X. S. et al., 2015
ENDOVASCULAR PERFORATION
SD rats 25 57 Gules et al., 2002 4 animals died within 6 h, 6 within 6–24 h, and 3 within 24-48 h
SD rats 41 44 Lee et al., 2009 Death occurred within 24 h of arterial puncture; 7 rats died due to cardiac arrest following hemorrhage, the rest generally within 6 h
SD rats 45 20 Park et al., 2008 Mortality defined as death within 48 h of surgery
95 46 Mortality defined as death within 48 h of surgery
SD rats 32 16 Sugawara et al., 2008 Stratifying mortality into the degree of hemorrhage gives a mortality of 0, 11, and 23.5 for rats that had mild, moderate, and severe SAH, respectively.
SD rats 21 57 Bederson et al., 1998 Mortality defined as death within 24 h of surgery at sacrifice point
23 65 Animals sacrificed 60 min after surgery
11 45
Wistar rats 30 43 and 57 Tiebosch et al., 2013 Mortality defined as death within 48 h of surgery
SD rats 46 33 Silasi and Colbourne, 2009 All but two rats died within 12 h of surgery
SD rats 16 44 Prunell et al., 2003 86 of these rats died within 24 h
C57Bl/6 mice 10 30 Feiler et al., 2010 1 mouse died at 1 d, 2 mice died at 2 d
SD rats 16 50 Bederson et al., 1995 Death occurred within 24 h of surgery
Wistar rats 14 21 Kojima et al., 2005 Death occurred within 12 h of surgery
C57Bl/6 mice 58 19 Egashira et al., 2015a Death occurred within 24 h of surgery
SD rats 12 17 Suzuki et al., 2010 Mortality defined as death within 24 h of surgery
12 25 Mortality defined as death within 48 h of surgery
12 17 Mortality defined as death within 120 h of surgery
33 24 Mortality defined as death within 24 h of surgery
SD rats 35 34 Topkoru et al., 2013 Death occurred within 72 h of surgery
C57Bl/6 mice 10 10 Bühler et al., 2015 Death occurred within 7 d of surgery
C57Bl/6 mice 23 9 Sheng et al., 2011 Death occurred within 72 h of surgery
SD rats 10 50 Hockel et al., 2012 Death occurred within 72 h of surgery
SD rats 50 18 He et al., 2012 Did not specify the time points used for calculating mortality
SD rats 39 38 Li et al., 2012 Did not specify the time points used for calculating mortality
C57Bl/6 mice 17 24 Egashira et al., 2015b Death occurred within 24 h of surgery
10 20 Death occurred within 8 d of surgery
SD rats 39 15 Hasegawa et al., 2011 Mortality defined as death within 72 h of surgery
SD rats 34 29 Duris et al., 2011 Mortality defined as death within 6 h of surgery
SD rats 27 7 Ostrowski et al., 2006 Mortality defined as death within 6 h of surgery
SD rats 116 25 Shishido et al., 2015 Mortality defined as death within 24 h of surgery
SD rats 15 and 15 40 and 20 Hollig et al., 2015 Mortality defined as death within 24 h of surgery
SD rats 9 33 Xu et al., 2015 Death occurred within 24 h of surgery
SD rats 122 42 Huang et al., 2015 Did not specify the time points used for calculating mortality

Information presented includes rodent strain, number of animals that died, and the percent of animals that died. Notes are included if the study mentions that animals died during a study procedure, if the investigators used a different definition for mortality, or if animals died within a short time period after the surgical procedure. SD, Sprague Dawley; BA, basilar artery.

Comparison of functional outcomes and mortality in preclinical models and clinical SAH

Similar to the physiological parameters previously discussed, functional outcomes and mortality in preclinical models of SAH appear to be highly variable within and across models. This is due in part to subjective nature of the tests and lack of inter-observer reliability, varied methods used to induce experimental SAH, varied mode of determining functional outcomes and time point used to assess mortality. It is clear that no studies exist to determine functional outcomes and mortality at long-term time points, something that is needed to assess the worthiness of the existing preclinical models in replicating the human disease process. Commonly, functional outcomes and mortality following clinical SAH is related to specific pathological factors, such as the extent of insult, and the occurrence of EBI, CV, and DCI, and baseline function must be taken into account. Although assessments of post-SAH functional outcomes have their limitations, the lack of focal deficits in the majority of preclinical studies does replicate the clinical counterpart. Finally, the biggest downfalls of preclinical models is their lack of replication of delayed neurological deficits coinciding with the onset of DCI, which are major contributors to poor outcomes following clinical SAH.

Conclusions

Many rodent models of SAH and variations thereof exist in current preclinical experimentation. The most commonly used are the prechiasmatic and cisterna magna blood injection models and the endovascular perforation model. Each protocol offers its own advantages and disadvantages in observing outcomes of EBI, CV, physiologic parameters like CBF, and neurological deficits. However, all these models lack the spontaneous rupture of an intracranial aneurysm, which is needed for better replication of the early and delayed clinical aSAH pathophysiology. Furthermore, the lack of standardized procedures in the currently available models has led to considerable variation in the reporting of important outcomes, such as the onset, location, severity, and time course of CV making it difficult to compare across studies and to translate findings to clinical practice. Nonetheless, the prechiasmatic cistern anterior circulation model has been proposed as the most translational model in terms of reproducibility and outcomes (Attia and Loch MacDonald, 2015). With further optimization and continued research, a rodent model that parallels human SAH can be established. If this is achieved, translational capacity of preclinical models can be maximized and clinical interventions will improve as a result.

Author contributions

All contributed to the design of the paper, participated in the search, compiled the tables, designed the figure, drafted, and reviewed the final version of the paper.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

This work was supported by NIH grants F31NS086441 (JL), R01NS046400 (SD), and R21NS095166 (BH, SD), Brain Aneurysm Foundation Awards (BH, SD), and the McKnight Brain Research Foundation, Brain and Spinal Cord Injury Research Trust Fund (SD). The authors wish to thank the University of Florida Center for Translational Research in Neurodegenerative Disease for additional support.

References

  1. Alkan T., Korfali E., Kahveci N. (2002). Experimental subarachnoid haemorrhage models in rats. Acta Neurochir. Suppl. 83, 61–69. 10.1007/978-3-7091-6743-4_11 [DOI] [PubMed] [Google Scholar]
  2. Al-Khindi T., MacDonald R. L., Schweizer T. A. (2010). Cognitive and functional outcome after aneurysmal subarachnoid hemorrhage. Stroke 41, e519–e536. 10.1161/STROKEAHA.110.581975 [DOI] [PubMed] [Google Scholar]
  3. Altay T., Smithason S., Volokh N., Rasmussen P. A., Ransohoff R. M., Provencio J. J. (2009). A novel method for subarachnoid hemorrhage to induce vasospasm in mice. J. Neurosci. Methods 183, 136–140. 10.1016/j.jneumeth.2009.06.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Amann K., Haas C. S., Zeiler G. A., Benz K., Bader B. L., Hartner A., et al. (2009). Lack of nidogen-2 increases blood pressure, glomerular and tubulointerstitial damage in DOCA-salt hypertension. Eur. J. Clin. Invest. 39, 116–125. 10.1111/j.1365-2362.2008.02065.x [DOI] [PubMed] [Google Scholar]
  5. Ansar S., Edvinsson L. (2008). Subtype activation and interaction of protein kinase C and mitogen-activated protein kinase controlling receptor expression in cerebral arteries and microvessels after subarachnoid hemorrhage. Stroke 39, 185–190. 10.1161/STROKEAHA.107.487827 [DOI] [PubMed] [Google Scholar]
  6. Asleh R., Marsh S., Shilkrut M., Binah O., Guetta J., Lejbkowicz F., et al. (2003). Genetically determined heterogeneity in hemoglobin scavenging and susceptibility to diabetic cardiovascular disease. Circ. Res. 92, 1193–1200. 10.1161/01.RES.0000076889.23082.F1 [DOI] [PubMed] [Google Scholar]
  7. Attia M. S., Loch MacDonald R. (2015). Anterior circulation model of subarachnoid hemorrhage in mice. Acta Neurochir. Suppl. 120, 311–314. 10.1007/978-3-319-04981-6_53 [DOI] [PubMed] [Google Scholar]
  8. Badjatia N., Topcuoglu M. A., Buonanno F. S., Smith E. E., Nogueira R. G., Rordorf G. A., et al. (2005). Relationship between hyperglycemia and symptomatic vasospasm after subarachnoid hemorrhage. Crit. Care Med. 33, 1603–1609; 10.1097/01.CCM.0000168054.60538.2B [DOI] [PubMed] [Google Scholar]
  9. Barry K. J., Gogjian M. A., Stein B. M. (1979). Small animal model for investigation of subarachnoid hemorrhage and cerebral vasospasm. Stroke 10, 538–541. 10.1161/01.STR.10.5.538 [DOI] [PubMed] [Google Scholar]
  10. Bederson J. B., Germano I. M., Guarino L. (1995). Cortical blood flow and cerebral perfusion pressure in a new noncraniotomy model of subarachnoid hemorrhage in the rat. Stroke 26, 1086–1091. discussion: 1091–1082. 10.1161/01.STR.26.6.1086 [DOI] [PubMed] [Google Scholar]
  11. Bederson J. B., Levy A. L., Ding W. H., Kahn R., Diperna C. A., Jenkins A. L., III, et al. (1998). Acute vasoconstriction after subarachnoid hemorrhage. Neurosurgery 42, 352–360; discussion: 360–352. 10.1097/00006123-199802000-00091 [DOI] [PubMed] [Google Scholar]
  12. Bederson J. B., Pitts L. H., Tsuji M., Nishimura M. C., Davis R. L., Bartkowski H. (1986). Rat middle cerebral artery occlusion: evaluation of the model and development of a neurologic examination. Stroke 17, 472–476. 10.1161/01.STR.17.3.472 [DOI] [PubMed] [Google Scholar]
  13. Biller J., Godersky J. C., Adams H. P., Jr. (1988). Management of aneurysmal subarachnoid hemorrhage. Stroke 19, 1300–1305. 10.1161/01.STR.19.10.1300 [DOI] [PubMed] [Google Scholar]
  14. Boswell S., Thorell W., Gogela S., Lyden E., Surdell D. (2013). Angiogram-negative subarachnoid hemorrhage: outcomes data and review of the literature. J. Stroke Cerebrovasc. Dis. 22, 750–757. 10.1016/j.jstrokecerebrovasdis.2012.02.001 [DOI] [PubMed] [Google Scholar]
  15. Boyko M., Azab A. N., Kuts R., Gruenbaum B. F., Gruenbaum S. E., Melamed I., et al. (2013). The neuro-behavioral profile in rats after subarachnoid hemorrhage. Brain Res. 1491, 109–116. 10.1016/j.brainres.2012.10.061 [DOI] [PubMed] [Google Scholar]
  16. Britz G. W., Meno J. R., Park I. S., Abel T. J., Chowdhary A., Nguyen T. S., et al. (2007). Time-dependent alterations in functional and pharmacological arteriolar reactivity after subarachnoid hemorrhage. Stroke 38, 1329–1335. 10.1161/01.STR.0000259853.43084.03 [DOI] [PubMed] [Google Scholar]
  17. Buehler P. W., Abraham B., Vallelian F., Linnemayr C., Pereira C. P., Cipollo J. F., et al. (2009). Haptoglobin preserves the CD163 hemoglobin scavenger pathway by shielding hemoglobin from peroxidative modification. Blood 113, 2578–2586. 10.1182/blood-2008-08-174466 [DOI] [PubMed] [Google Scholar]
  18. Bühler D., Azghandi S., Schüller K., Plesnila N. (2015). Effect of decompressive craniectomy on outcome following subarachnoid hemorrhage in mice. Stroke 46, 819–826. 10.1161/STROKEAHA.114.007703 [DOI] [PubMed] [Google Scholar]
  19. Caeiro L., Santos C. O., Ferro J. M., Figueira M. L. (2011). Neuropsychiatric disturbances in acute subarachnoid haemorrhage. Eur. J. Neurol. 18, 857–864. 10.1111/j.1468-1331.2010.03271.x [DOI] [PubMed] [Google Scholar]
  20. Cai C. Y., Ma W. H., Deng L. (2012). [Effects of ligustrazine injection on IL-2, IL-10, and IFN-gamma in patients undergoing spinal operation after autologous blood transfusion]. Zhongguo Zhong Xi Yi Jie He Za Zhi 32, 474–477. [PubMed] [Google Scholar]
  21. Cai J., Sun Y., Yuan F., Chen L., He C., Bao Y., et al. (2012). A novel intravital method to evaluate cerebral vasospasm in rat models of subarachnoid hemorrhage: a study with synchrotron radiation angiography. PLoS ONE 7:e33366. 10.1371/journal.pone.0033366 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Cammermeyer J. (1961). Frequency of meningoencephalitis and hydrocephalus in dogs. J. Neuropathol. Exp. Neurol. 20, 386–398. 10.1097/00005072-196107000-00003 [DOI] [PubMed] [Google Scholar]
  23. Cánovas D., Gil A., Jato M., de Miquel M., Rubio F. (2012). Clinical outcome of spontaneous non-aneurysmal subarachnoid hemorrhage in 108 patients. Eur. J. Neurol. 19, 457–461. 10.1111/j.1468-1331.2011.03542.x [DOI] [PubMed] [Google Scholar]
  24. Cedzich C., Roth A. (2005). Neurological and psychosocial outcome after subarachnoid haemorrhage, and the hunt and hess scale as a predictor of clinical outcome. Zentralbl. Neurochir. 66, 112–118. 10.1055/s-2005-836477 [DOI] [PubMed] [Google Scholar]
  25. Chaichana K. L., Levy A. P., Miller-Lotan R., Shakur S., Tamargo R. J. (2007). Haptoglobin 2-2 genotype determines chronic vasospasm after experimental subarachnoid hemorrhage. Stroke 38, 3266–3271. 10.1161/STROKEAHA.107.490003 [DOI] [PubMed] [Google Scholar]
  26. Chang C. Z., Wu S. C., Chang C. M., Lin C. L., Kwan A. L. (2015a). Arctigenin, a potent ingredient of Arctium lappa L., induces endothelial nitric oxide synthase and attenuates subarachnoid hemorrhage-induced vasospasm through PI3K/Akt pathway in a rat model. Biomed Res. Int. 2015:490209. 10.1155/2015/490209 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Chang C. Z., Wu S. C., Kwan A. L., Lin C. L. (2015b). 4'-O-β-D-glucosyl-5-O-methylvisamminol, an active ingredient of Saposhnikovia divaricata, attenuates high-mobility group box 1 and subarachnoid hemorrhage-induced vasospasm in a rat model. Behav. Brain Funct. 11:28. 10.1186/s12993-015-0074-8 [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]
  28. Chu A. C., Wong G. K., Lam S. W., Wong A., Ngai K., Poon W. S., et al. (2015a). Cognitive impairment in aneurysmal subarachnoid hemorrhage patients with delayed cerebral infarction: prevalence and pattern. Acta Neurochir. Suppl. 120, 303–306. 10.1007/978-3-319-04981-6_51 [DOI] [PubMed] [Google Scholar]
  29. Chu A., Gozal D., Cortese R., Wang Y. (2015b). Cardiovascular dysfunction in adult mice following postnatal intermittent hypoxia. Pediatr. Res. 77, 425–433. 10.1038/pr.2014.197 [DOI] [PubMed] [Google Scholar]
  30. Clark J. F., Sharp F. R. (2006). Bilirubin oxidation products (BOXes) and their role in cerebral vasospasm after subarachnoid hemorrhage. J. Cereb. Blood Flow Metab. 26, 1223–1233. 10.1038/sj.jcbfm.9600280 [DOI] [PubMed] [Google Scholar]
  31. Connolly E. S., Jr., Rabinstein A. A., Carhuapoma J. R., Derdeyn C. P., Dion J., Higashida R. T., et al. (2012). Guidelines for the management of aneurysmal subarachnoid hemorrhage: a guideline for healthcare professionals from the American Heart Association/american Stroke Association. Stroke 43, 1711–1737. 10.1161/STR.0b013e3182587839 [DOI] [PubMed] [Google Scholar]
  32. Delgado T. J., Brismar J., Svendgaard N. A. (1985). Subarachnoid haemorrhage in the rat: angiography and fluorescence microscopy of the major cerebral arteries. Stroke 16, 595–602. 10.1161/01.STR.16.4.595 [DOI] [PubMed] [Google Scholar]
  33. de Olmos J. S., Beltramino C. A., De Olmos De Lorenzo S. (1994). Use of an amino-cupric-silver technique for the detection of early and semiacute neuronal degeneration caused by neurotoxicants, hypoxia, and physical trauma. Neurotoxicol. Teratol. 16, 545–561. 10.1016/0892-0362(94)90033-7 [DOI] [PubMed] [Google Scholar]
  34. Dhar R., Scalfani M. T., Zazulia A. R., Videen T. O., Derdeyn C. P., Diringer M. N. (2012). Comparison of induced hypertension, fluid bolus, and blood transfusion to augment cerebral oxygen delivery after subarachnoid hemorrhage. J. Neurosurg. 116, 648–656. 10.3171/2011.9.JNS11691 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Diringer M. N. (2009). Management of aneurysmal subarachnoid hemorrhage. Crit. Care Med. 37, 432–440. 10.1097/CCM.0b013e318195865a [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Diringer M. N., Bleck T. P., Claude Hemphill J., III., Menon D., Shutter L., Vespa P., et al. (2011). Critical care management of patients following aneurysmal subarachnoid hemorrhage: recommendations from the Neurocritical Care Society's Multidisciplinary Consensus Conference. Neurocrit. Care 15, 211–240. 10.1007/s12028-011-9605-9 [DOI] [PubMed] [Google Scholar]
  37. Dombovy M. L., Drew-Cates J., Serdans R. (1998). Recovery and rehabilitation following subarachnoid haemorrhage: part, II. long-term follow-up. Brain Inj. 12, 887–894. [DOI] [PubMed] [Google Scholar]
  38. Dreier J. P., Windmüller O., Petzold G., Lindauer U., Einhäupl K. M., Dirnagl U. (2002). Ischemia triggered by red blood cell products in the subarachnoid space is inhibited by nimodipine administration or moderate volume expansion/hemodilution in rats. Neurosurgery 51, 1457–1465. Discussion: 1465–1457. 10.1227/01.NEU.0000309123.22032.55 [DOI] [PubMed] [Google Scholar]
  39. Dunham N. W., Miya T. S. (1957). A note on a simple apparatus for detecting neurological deficit in rats and mice. J. Am. Pharm. Assoc. Am. Pharm. Assoc. 46, 208–209. 10.1002/jps.3030460322 [DOI] [PubMed] [Google Scholar]
  40. Duris K., Manaenko A., Suzuki H., Rolland W. B., Krafft P. R., Zhang J. H. (2011). α7 nicotinic acetylcholine receptor agonist PNU-282987 attenuates early brain injury in a perforation model of subarachnoid hemorrhage in rats. Stroke 42, 3530–3536. 10.1161/STROKEAHA.111.619965 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Egashira Y., Shishido H., Hua Y., Keep R. F., Xi G. (2015a). New grading system based on magnetic resonance imaging in a mouse model of subarachnoid hemorrhage. Stroke 46, 582–584. 10.1161/STROKEAHA.114.007834 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Egashira Y., Zhao H., Hua Y., Keep R. F., Xi G. (2015b). White matter injury after subarachnoid hemorrhage: role of blood-brain barrier disruption and matrix metalloproteinase-9. Stroke 46, 2909–2915. 10.1161/STROKEAHA.115.010351 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Fassbender K., Hodapp B., Rossol S., Bertsch T., Schmeck J., Schütt S., et al. (2000). Endothelin-1 in subarachnoid hemorrhage: an acute-phase reactant produced by cerebrospinal fluid leukocytes. Stroke 31, 2971–2975. 10.1161/01.STR.31.12.2971 [DOI] [PubMed] [Google Scholar]
  44. Feiler S., Friedrich B., Schöller K., Thal S. C., Plesnila N. (2010). Standardized induction of subarachnoid hemorrhage in mice by intracranial pressure monitoring. J. Neurosci. Methods 190, 164–170. 10.1016/j.jneumeth.2010.05.005 [DOI] [PubMed] [Google Scholar]
  45. Feldman Z., Gurevitch B., Artru A. A., Oppenheim A., Shohami E., Reichenthal E., et al. (1996). Effect of magnesium given 1 hour after head trauma on brain edema and neurological outcome. J. Neurosurg. 85, 131–137. 10.3171/jns.1996.85.1.0131 [DOI] [PubMed] [Google Scholar]
  46. Fisher C. M., Kistler J. P., Davis J. M. (1980). Relation of cerebral vasospasm to subarachnoid hemorrhage visualized by computerized tomographic scanning. Neurosurgery 6, 1–9. 10.1227/00006123-198001000-00001 [DOI] [PubMed] [Google Scholar]
  47. Garcia J. H., Wagner S., Liu K. F., Hu X. J. (1995). Neurological deficit and extent of neuronal necrosis attributable to middle cerebral artery occlusion in rats. Statistical validation. Stroke 26, 627–634; discussion: 635. 10.1161/01.STR.26.4.627 [DOI] [PubMed] [Google Scholar]
  48. Gavrieli Y., Sherman Y., Ben-Sasson S. A. (1992). Identification of programmed cell death in situ via specific labeling of nuclear DNA fragmentation. J. Cell Biol. 119, 493–501. 10.1083/jcb.119.3.493 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Glenn T. C., Patel A. B., Martin N. A., Samii A., De Jesus C., Hovda D. A. (2002). Subarachnoid hemorrhage induces dynamic changes in regional cerebral metabolism in rats. J. Neurotrauma 19, 449–466. 10.1089/08977150252932406 [DOI] [PubMed] [Google Scholar]
  50. Gorelick P. B., Hier D. B., Caplan L. R., Langenberg P. (1986). Headache in acute cerebrovascular disease. Neurology 36, 1445–1450. 10.1212/WNL.36.11.1445 [DOI] [PubMed] [Google Scholar]
  51. Greenberg R. K., Srivastava S. D., Ouriel K., Waldman D., Ivancev K., Illig K. A., et al. (2000). An endoluminal method of hemorrhage control and repair of ruptured abdominal aortic aneurysms. J. Endovasc. Ther. 7, 1–7. 10.1177/152660280000700101 [DOI] [PubMed] [Google Scholar]
  52. Gules I., Satoh M., Clower B. R., Nanda A., Zhang J. H. (2002). Comparison of three rat models of cerebral vasospasm. Am. J. Physiol. Heart Circ. Physiol. 283, H2551–H2559. 10.1152/ajpheart.00616.2002 [DOI] [PubMed] [Google Scholar]
  53. Güresir E., Raabe A., Jaiimsin A., Dias S., Raab P., Seifert V., et al. (2010). Histological evidence of delayed ischemic brain tissue damage in the rat double-hemorrhage model. J. Neurol. Sci. 293, 18–22. 10.1016/j.jns.2010.03.023 [DOI] [PubMed] [Google Scholar]
  54. Güresir E., Vasiliadis N., Dias S., Raab P., Seifert V., Vatter H. (2012). The effect of common carotid artery occlusion on delayed brain tissue damage in the rat double subarachnoid hemorrhage model. Acta Neurochir. 154, 11–19. 10.1007/s00701-011-1191-2 [DOI] [PubMed] [Google Scholar]
  55. Hackett M. L., Anderson C. S. (2000). Health outcomes 1 year after subarachnoid hemorrhage: an international population-based study. The australian cooperative research on subarachnoid hemorrhage study group. Neurology 55, 658–662. 10.1212/WNL.55.5.658 [DOI] [PubMed] [Google Scholar]
  56. Handa H., Hashimoto N., Nagata I., Hazama F. (1983). Saccular cerebral aneurysms in rats: a newly developed animal model of the disease. Stroke 14, 857–866. 10.1161/01.STR.14.6.857 [DOI] [PubMed] [Google Scholar]
  57. Hartner A., Cordasic N., Rascher W., Hilgers K. F. (2009). Deletion of the alpha8 integrin gene does not protect mice from myocardial fibrosis in DOCA hypertension. Am. J. Hypertens. 22, 92–99. 10.1038/ajh.2008.309 [DOI] [PubMed] [Google Scholar]
  58. Hasegawa Y., Suzuki H., Altay O., Zhang J. H. (2011). Preservation of tropomyosin-related kinase B (TrkB) signaling by sodium orthovanadate attenuates early brain injury after subarachnoid hemorrhage in rats. Stroke 42, 477–483. 10.1161/STROKEAHA.110.597344 [DOI] [PubMed] [Google Scholar]
  59. Hashimoto N., Handa H., Nagata I., Hazama F. (1984). Animal model of cerebral aneurysms: pathology and pathogenesis of induced cerebral aneurysms in rats. Neurol. Res. 6, 33–40. 10.1080/01616412.1984.11739661 [DOI] [PubMed] [Google Scholar]
  60. He J., Liu M., Liu Z., Luo L. (2015). Recombinant osteopontin attenuates experimental cerebral vasospasm following subarachnoid hemorrhage in rats through an anti-apoptotic mechanism. Brain Res. 1611, 74–83. 10.1016/j.brainres.2015.03.015 [DOI] [PubMed] [Google Scholar]
  61. He Z., Ostrowski R. P., Sun X., Ma Q., Huang B., Zhan Y., et al. (2012). CHOP silencing reduces acute brain injury in the rat model of subarachnoid hemorrhage. Stroke 43, 484–490. 10.1161/STROKEAHA.111.626432 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Hockel K., Schöller K., Trabold R., Nussberger J., Plesnila N. (2012). Vasopressin V1a receptors mediate posthemorrhagic systemic hypertension thereby determining rebleeding rate and outcome after experimental subarachnoid hemorrhage. Stroke 43, 227–232. 10.1161/STROKEAHA.111.626168 [DOI] [PubMed] [Google Scholar]
  63. Hoh B. L., Velat G. J., Wilmer E. N., Hosaka K., Fisher R. C., Scott E. W. (2010). A novel murine elastase saccular aneurysm model for studying bone marrow progenitor-derived cell-mediated processes in aneurysm formation. Neurosurgery 66, 544–550. discussion: 550. 10.1227/01.NEU.0000365616.46414.2B [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Höllig A., Weinandy A., Nolte K., Clusmann H., Rossaint R., Coburn M. (2015). Experimental subarachnoid hemorrhage in rats: comparison of two endovascular perforation techniques with respect to success rate, confounding pathologies and early hippocampal tissue lesion pattern. PLoS ONE 10:e0123398. 10.1371/journal.pone.0123398 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Hosaka K., Hoh B. L. (2014). Inflammation and cerebral aneurysms. Transl. Stroke Res. 5, 190–198. 10.1007/s12975-013-0313-y [DOI] [PubMed] [Google Scholar]
  66. Huang C. Y., Wang L. C., Shan Y. S., Pan C. H., Tsai K. J. (2015). Memantine attenuates delayed vasospasm after experimental subarachnoid hemorrhage via modulating endothelial nitric oxide synthase. Int. J. Mol. Sci. 16, 14171–14180. 10.3390/ijms160614171 [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Hütter B. O., Gilsbach J. M., Kreitschmann I. (1995). Quality of life and cognitive deficits after subarachnoid haemorrhage. Br. J. Neurosurg. 9, 465–475. 10.1080/02688699550041106 [DOI] [PubMed] [Google Scholar]
  68. Izzy S., Muehlschlegel S. (2014). Cerebral vasospasm after aneurysmal subarachnoid hemorrhage and traumatic brain injury. Curr. Treat. Options Neurol. 16:278. 10.1007/s11940-013-0278-x [DOI] [PubMed] [Google Scholar]
  69. Jackowski A., Crockard A., Burnstock G., Russell R. R., Kristek F. (1990). The time course of intracranial pathophysiological changes following experimental subarachnoid haemorrhage in the rat. J. Cereb. Blood Flow Metab. 10, 835–849. 10.1038/jcbfm.1990.140 [DOI] [PubMed] [Google Scholar]
  70. Jeon H., Ai J., Sabri M., Tariq A., MacDonald R. L. (2010). Learning deficits after experimental subarachnoid hemorrhage in rats. Neuroscience 169, 1805–1814. 10.1016/j.neuroscience.2010.06.039 [DOI] [PubMed] [Google Scholar]
  71. Kanematsu Y., Kanematsu M., Kurihara C., Tada Y., Tsou T. L., Van Rooijen N., et al. (2011). Critical roles of macrophages in the formation of intracranial aneurysm. Stroke 42, 173–178. 10.1161/STROKEAHA.110.590976 [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Kim C., Cervós-Navarro J. (1991). Spontaneous saccular cerebral aneurysm in a rat. Acta Neurochir. (Wien) 109, 63–65. 10.1007/BF01405700 [DOI] [PubMed] [Google Scholar]
  73. Klanke B., Cordasic N., Hartner A., Schmieder R. E., Veelken R., Hilgers K. F. (2008). Blood pressure versus direct mineralocorticoid effects on kidney inflammation and fibrosis in DOCA-salt hypertension. Nephrol. Dial. Transplant 23, 3456–3463. 10.1093/ndt/gfn301 [DOI] [PubMed] [Google Scholar]
  74. Ko S. B., Choi H. A., Helbok R., Kurtz P., Schmidt J. M., Badjatia N., et al. (2016). Acute effects of intraventricular nicardipine on cerebral hemodynamics: a preliminary finding. Clin. Neurol. Neurosurg. 144, 48–52. 10.1016/j.clineuro.2016.02.037 [DOI] [PubMed] [Google Scholar]
  75. Kojima J., Katayama Y., Moro N., Kawai H., Yoneko M., Mori T. (2005). Cerebral salt wasting in subarachnoid hemorrhage rats: model, mechanism, and tool. Life Sci. 76, 2361–2370. 10.1016/j.lfs.2004.11.010 [DOI] [PubMed] [Google Scholar]
  76. Kolias A. G., Sen J., Belli A. (2009). Pathogenesis of cerebral vasospasm following aneurysmal subarachnoid hemorrhage: putative mechanisms and novel approaches. J. Neurosci. Res. 87, 1–11. 10.1002/jnr.21823 [DOI] [PubMed] [Google Scholar]
  77. Kreiter K. T., Copeland D., Bernardini G. L., Bates J. E., Peery S., Claassen J., et al. (2002). Predictors of cognitive dysfunction after subarachnoid hemorrhage. Stroke 33, 200–208. 10.1161/hs0102.101080 [DOI] [PubMed] [Google Scholar]
  78. Lacy P. S., Earle A. M. (1983). A small animal model for electrocardiographic abnormalities observed after an experimental subarachnoid hemorrhage. Stroke 14, 371–377. 10.1161/01.STR.14.3.371 [DOI] [PubMed] [Google Scholar]
  79. Larsson C., Rönnberg J., Forssell A., Nilsson L. G., Lindberg M., Angquist K. A. (1989). Verbal memory function after subarachnoid haemorrhage determined by the localisation of the ruptured aneurysm. Br. J. Neurosurg. 3, 549–560. 10.3109/02688698909002846 [DOI] [PubMed] [Google Scholar]
  80. Lee J. Y., Huang D. L., Keep R., Sagher O. (2008). Characterization of an improved double hemorrhage rat model for the study of delayed cerebral vasospasm. J. Neurosci. Methods 168, 358–366. 10.1016/j.jneumeth.2007.10.029 [DOI] [PubMed] [Google Scholar]
  81. Lee J. Y., Sagher O., Keep R., Hua Y., Xi G. (2009). Comparison of experimental rat models of early brain injury after subarachnoid hemorrhage. Neurosurgery 65, 331–343. discussion: 343. 10.1227/01.NEU.0000345649.78556.26 [DOI] [PubMed] [Google Scholar]
  82. Leonardo C. C., Robbins S., Doré S. (2012). Translating basic science research to clinical application: models and strategies for intracerebral hemorrhage. Front. Neurol. 3:85. 10.3389/fneur.2012.00085 [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Li B., Luo C., Tang W., Chen Z., Li Q., Hu B., et al. (2012). Role of HCN channels in neuronal hyperexcitability after subarachnoid hemorrhage in rats. J. Neurosci. 32, 3164–3175. 10.1523/JNEUROSCI.5143-11.2012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Li Q., Chen Y., Li B., Luo C., Zuo S., Liu X., et al. (2016). Hemoglobin induced NO/cGMP suppression deteriorate microcirculation via pericyte phenotype transformation after subarachnoid hemorrhage in rats. Sci. Rep. 6:22070. 10.1038/srep22070 [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Li Q., Lv F., Yao G., Li Y., Xie P. (2014). 64-section multidetector CT angiography for evaluation of intracranial aneurysms: comparison with 3D rotational angiography. Acta Radiol. 55, 840–846. 10.1177/0284185113506138 [DOI] [PubMed] [Google Scholar]
  86. Lin C. L., Calisaneller T., Ukita N., Dumont A. S., Kassell N. F., Lee K. S. (2003). A murine model of subarachnoid hemorrhage-induced cerebral vasospasm. J. Neurosci. Methods 123, 89–97. 10.1016/S0165-0270(02)00344-8 [DOI] [PubMed] [Google Scholar]
  87. Lindberg M., Angquist K. A., Fodstad H., Fugl-Meyer K., Fugl-Meyer A. R. (1992). Self-reported prevalence of disability after subarachnoid haemorrhage, with special emphasis on return to leisure and work. Br. J. Neurosurg. 6, 297–304. 10.3109/02688699209023787 [DOI] [PubMed] [Google Scholar]
  88. Lord A. S., Fernandez L., Schmidt J. M., Mayer S. A., Claassen J., Lee K., et al. (2012). Effect of rebleeding on the course and incidence of vasospasm after subarachnoid hemorrhage. Neurology 78, 31–37. 10.1212/WNL.0b013e31823ed0a4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Luft A. R., Buitrago M. M., Torbey M., Bhardwaj A., Razumovsky A. (2004). Biphasic cerebral blood flow velocity profile in patients with aneurysmal subarachnoid hemorrhage. Neurocrit. Care 1, 455–459. 10.1385/NCC:1:4:455 [DOI] [PubMed] [Google Scholar]
  90. Luo C., Yao X., Li J., He B., Liu Q., Ren H., et al. (2016). Paravascular pathways contribute to vasculitis and neuroinflammation after subarachnoid hemorrhage independently of glymphatic control. Cell Death Dis. 7:e2160. 10.1038/cddis.2016.63 [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. MacDonald R. L., Diringer M. N., Citerio G. (2014). Understanding the disease: aneurysmal subarachnoid hemorrhage. Intensive Care Med. 40, 1940–1943. 10.1007/s00134-014-3483-5 [DOI] [PubMed] [Google Scholar]
  92. MacDonald R. L., Hunsche E., Schüler R., Wlodarczyk J., Mayer S. A. (2012). Quality of life and healthcare resource use associated with angiographic vasospasm after aneurysmal subarachnoid hemorrhage. Stroke 43, 1082–1088. 10.1161/STROKEAHA.111.634071 [DOI] [PubMed] [Google Scholar]
  93. MacDonald R. L., Weir B. K. (1991). A review of hemoglobin and the pathogenesis of cerebral vasospasm. Stroke 22, 971–982. 10.1161/01.STR.22.8.971 [DOI] [PubMed] [Google Scholar]
  94. MacMillan C. S., Wild J. M., Wardlaw J. M., Andrews P. J., Marshall I., Easton V. J. (2002). Traumatic brain injury and subarachnoid hemorrhage: in vivo occult pathology demonstrated by magnetic resonance spectroscopy may not be “ischaemic”. A primary study and review of the literature. Acta Neurochir. 144, 853–862; discussion: 862. 10.1007/s00701-002-0966-x [DOI] [PubMed] [Google Scholar]
  95. Makino H., Tada Y., Wada K., Liang E. I., Chang M., Mobashery S., et al. (2012). Pharmacological stabilization of intracranial aneurysms in mice: a feasibility study. Stroke 43, 2450–2456. 10.1161/STROKEAHA.112.659821 [DOI] [PMC free article] [PubMed] [Google Scholar]
  96. Marder C. P., Narla V., Fink J. R., Tozer Fink K. R. (2014). Subarachnoid hemorrhage: beyond aneurysms. AJR Am. J. Roentgenol. 202, 25–37. 10.2214/AJR.12.9749 [DOI] [PubMed] [Google Scholar]
  97. McGeoch G., Lainchbury J., Town G. I., Toop L., Espiner E., Richards A. M. (2002). Plasma brain natriuretic peptide after long-term treatment for heart failure in general practice. Eur. J. Heart Fail. 4, 479–483. 10.1016/S1388-9842(02)00027-2 [DOI] [PubMed] [Google Scholar]
  98. McMullan J. T., Knight W. A., Clark J. F., Beyette F. R., Pancioli A. (2010). Time-critical neurological emergencies: the unfulfilled role for point-of-care testing. Int. J. Emerg. Med. 3, 127–131. 10.1007/s12245-010-0177-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  99. Meguro T., Clower B. R., Carpenter R., Parent A. D., Zhang J. H. (2001). Improved rat model for cerebral vasospasm studies. Neurol. Res. 23, 761–766. 10.1179/016164101101199144 [DOI] [PubMed] [Google Scholar]
  100. Miller B. A., Turan N., Chau M., Pradilla G. (2014). Inflammation, vasospasm, and brain injury after subarachnoid hemorrhage. Biomed. Res. Int. 2014:384342. 10.1155/2014/384342 [DOI] [PMC free article] [PubMed] [Google Scholar]
  101. Morris R. (1984). Developments of a water-maze procedure for studying spatial learning in the rat. J. Neurosci. Methods 11, 47–60. 10.1016/0165-0270(84)90007-4 [DOI] [PubMed] [Google Scholar]
  102. Muñoz-Sánchez M. A., Egea-Guerrero J. J., Revuelto-Rey J., Moreno-Valladares M., Murillo-Cabezas F. (2012a). A new percutaneous model of Subarachnoid Haemorrhage in rats. J. Neurosci. Methods 211, 88–93. 10.1016/j.jneumeth.2012.08.010 [DOI] [PubMed] [Google Scholar]
  103. Muñoz-Sanchez M. A., Murillo-Cabezas F., Egea-Guerrero J. J., Gascón-Castillo M. L., Cancela P., Amaya-Villar R., et al. (2012b). [Emergency transcranial doppler ultrasound: predictive value for the development of symptomatic vasospasm in spontaneous subarachnoid hemorrhage in patients in good neurological condition]. Med. Intensiva 36, 611–618. 10.1016/j.medin.2012.01.013 [DOI] [PubMed] [Google Scholar]
  104. Nishizawa S., Laher I. (2005). Signaling mechanisms in cerebral vasospasm. Trends Cardiovasc. Med. 15, 24–34. 10.1016/j.tcm.2004.12.002 [DOI] [PubMed] [Google Scholar]
  105. Nuki Y., Tsou T. L., Kurihara C., Kanematsu M., Kanematsu Y., Hashimoto T. (2009). Elastase-induced intracranial aneurysms in hypertensive mice. Hypertension 54, 1337–1344. 10.1161/HYPERTENSIONAHA.109.138297 [DOI] [PMC free article] [PubMed] [Google Scholar]
  106. Ostrowski R. P., Tang J., Zhang J. H. (2006). Hyperbaric oxygen suppresses NADPH oxidase in a rat subarachnoid hemorrhage model. Stroke 37, 1314–1318. 10.1161/01.STR.0000217310.88450.c3 [DOI] [PubMed] [Google Scholar]
  107. Park I. S., Meno J. R., Witt C. E., Suttle T. K., Chowdhary A., Nguyen T. S., et al. (2008). Subarachnoid hemorrhage model in the rat: modification of the endovascular filament model. J. Neurosci. Methods 172, 195–200. 10.1016/j.jneumeth.2008.04.027 [DOI] [PubMed] [Google Scholar]
  108. Parra A., McGirt M. J., Sheng H., Laskowitz D. T., Pearlstein R. D., Warner D. S. (2002). Mouse model of subarachnoid hemorrhage associated cerebral vasospasm: methodological analysis. Neurol. Res. 24, 510–516. 10.1179/016164102101200276 [DOI] [PubMed] [Google Scholar]
  109. Pemberton C. J., Yandle T. G., Espiner E. A. (2002). Immunoreactive forms of natriuretic peptides in ovine brain: response to heart failure. Peptides 23, 2235–2244. 10.1016/S0196-9781(02)00263-2 [DOI] [PubMed] [Google Scholar]
  110. Peña-Silva R. A., Chalouhi N., Wegman-Points L., Ali M., Mitchell I., Pierce G. L., et al. (2015). Novel role for endogenous hepatocyte growth factor in the pathogenesis of intracranial aneurysms. Hypertension 65, 587–593. 10.1161/HYPERTENSIONAHA.114.04681 [DOI] [PMC free article] [PubMed] [Google Scholar]
  111. Peña Silva R. A., Kung D. K., Mitchell I. J., Alenina N., Bader M., Santos R. A., et al. (2014). Angiotensin 1-7 reduces mortality and rupture of intracranial aneurysms in mice. Hypertension 64, 362–368. 10.1161/HYPERTENSIONAHA.114.03415 [DOI] [PMC free article] [PubMed] [Google Scholar]
  112. Penn D. L., Witte S. R., Komotar R. J., Sander Connolly E., Jr. (2015). Pathological mechanisms underlying aneurysmal subarachnoid haemorrhage and vasospasm. J. Clin. Neurosci. 22, 1–5. 10.1016/j.jocn.2014.05.025 [DOI] [PubMed] [Google Scholar]
  113. Piepgras A., Thomé C., Schmiedek P. (1995). Characterization of an anterior circulation rat subarachnoid hemorrhage model. Stroke 26, 2347–2352. 10.1161/01.STR.26.12.2347 [DOI] [PubMed] [Google Scholar]
  114. Pluta R. M., Hansen-Schwartz J., Dreier J., Vajkoczy P., MacDonald R. L., Nishizawa S., et al. (2009). Cerebral vasospasm following subarachnoid hemorrhage: time for a new world of thought. Neurol. Res. 31, 151–158. 10.1179/174313209X393564 [DOI] [PMC free article] [PubMed] [Google Scholar]
  115. Prunell G. F., Mathiesen T., Diemer N. H., Svendgaard N. A. (2003). Experimental subarachnoid hemorrhage: subarachnoid blood volume, mortality rate, neuronal death, cerebral blood flow, and perfusion pressure in three different rat models. Neurosurgery 52, 165–175; discussion: 175–176. 10.1227/00006123-200301000-00022 [DOI] [PubMed] [Google Scholar]
  116. Prunell G. F., Mathiesen T., Svendgaard N. A. (2002). A new experimental model in rats for study of the pathophysiology of subarachnoid hemorrhage. Neuroreport 13, 2553–2556. 10.1097/00001756-200212200-00034 [DOI] [PubMed] [Google Scholar]
  117. Qin Y., Gu J. W., Li G. L., Xu X. H., Yu K., Gao F. B. (2015). Cerebral vasospasm and corticospinal tract injury induced by a modified rat model of subarachnoid hemorrhage. J. Neurol. Sci. 358, 193–200. 10.1016/j.jns.2015.08.1536 [DOI] [PubMed] [Google Scholar]
  118. Rademaker M. T., Charles C. J., Cooper G. J., Coy D. H., Espiner E. A., Lewis L. K., et al. (2002a). Combined angiotensin-converting enzyme inhibition and adrenomedullin in an ovine model of heart failure. Clin. Sci. 102, 653–660. 10.1042/cs1020653 [DOI] [PubMed] [Google Scholar]
  119. Rademaker M. T., Charles C. J., Cooper G. J., Coy D. H., Espiner E. A., Lewis L. K., et al. (2002b). Combined endopeptidase inhibition and adrenomedullin in sheep with experimental heart failure. Hypertension 39, 93–98. 10.1161/hy0102.099197 [DOI] [PubMed] [Google Scholar]
  120. Rademaker M. T., Charles C. J., Espiner E. A., Fisher S., Frampton C. M., Kirkpatrick C. M., et al. (2002c). Beneficial hemodynamic, endocrine, and renal effects of urocortin in experimental heart failure: comparison with normal sheep. J. Am. Coll. Cardiol. 40, 1495–1505. 10.1016/S0735-1097(02)02170-8 [DOI] [PubMed] [Google Scholar]
  121. Rademaker M. T., Charles C. J., Espiner E. A., Nicholls M. G., Richards A. M. (2002d). Long-term adrenomedullin administration in experimental heart failure. Hypertension 40, 667–672. 10.1161/01.HYP.0000037132.90640.26 [DOI] [PubMed] [Google Scholar]
  122. Ram Z., Sahar A., Hadani M. (1991). Vasospasm due to massive subarachnoid haemorrhage–a rat model. Acta Neurochir. 110, 181–184. 10.1007/BF01400688 [DOI] [PubMed] [Google Scholar]
  123. Raslan F., Albert-Weißenberger C., Westermaier T., Saker S., Kleinschnitz C., Lee J. Y. (2012). A modified double injection model of cisterna magna for the study of delayed cerebral vasospasm following subarachnoid hemorrhage in rats. Exp. Transl. Stroke Med. 4:23. 10.1186/2040-7378-4-23 [DOI] [PMC free article] [PubMed] [Google Scholar]
  124. Rasmussen G., Hauerberg J., Waldemar G., Gjerris F., Juhler M. (1992). Cerebral blood flow autoregulation in experimental subarachnoid haemorrhage in rat. Acta Neurochir. 119, 128–133. 10.1007/BF01541796 [DOI] [PubMed] [Google Scholar]
  125. Ravnik J., Starovasnik B., Sesok S., Pirtosek Z., Svigelj V., Bunc G., et al. (2006). Long-term cognitive deficits in patients with good outcomes after aneurysmal subarachnoid hemorrhage from anterior communicating artery. Croat. Med. J. 47, 253–263. [PMC free article] [PubMed] [Google Scholar]
  126. Richardson J. T. (1991). Cognitive performance following rupture and repair of intracranial aneurysm. Acta Neurol. Scand. 83, 110–122. 10.1111/j.1600-0404.1991.tb04659.x [DOI] [PubMed] [Google Scholar]
  127. Rincon F., Rossenwasser R. H., Dumont A. (2013). The epidemiology of admissions of nontraumatic subarachnoid hemorrhage in the United States. Neurosurgery 73, 217–222. discussion: 212–213. 10.1227/01.neu.0000430290.93304.33 [DOI] [PubMed] [Google Scholar]
  128. Rinne P., Penttinen A. M., Nordlund W., Ahotupa M., Savontaus E. (2013). α-MSH analogue attenuates blood pressure elevation in DOCA-salt hypertensive mice. PLoS ONE 8:e72857. 10.1371/journal.pone.0072857 [DOI] [PMC free article] [PubMed] [Google Scholar]
  129. Rosengart A. J., Schultheiss K. E., Tolentino J., MacDonald R. L. (2007). Prognostic factors for outcome in patients with aneurysmal subarachnoid hemorrhage. Stroke 38, 2315–2321. 10.1161/STROKEAHA.107.484360 [DOI] [PubMed] [Google Scholar]
  130. Ruzevick J., Jackson C., Pradilla G., Garzon-Muvdi T., Tamargo R. J. (2013). Aneurysm formation in proinflammatory, transgenic haptoglobin 2-2 mice. Neurosurgery 72, 70–76; discussion: 76. 10.1227/NEU.0b013e318276b306 [DOI] [PubMed] [Google Scholar]
  131. Sabri M., Jeon H., Ai J., Tariq A., Shang X., Chen G., et al. (2009). Anterior circulation mouse model of subarachnoid hemorrhage. Brain Res. 1295, 179–185. 10.1016/j.brainres.2009.08.021 [DOI] [PubMed] [Google Scholar]
  132. Sakurada O., Kennedy C., Jehle J., Brown J. D., Carbin G. L., Sokoloff L. (1978). Measurement of local cerebral blood flow with iodo [14C] antipyrine. Am. J. Physiol. 234, H59–H66. 10.1152/ajpheart.1978.234.1.H59 [DOI] [PubMed] [Google Scholar]
  133. Schmued L. C., Albertson C., Slikker W., Jr. (1997). Fluoro-Jade: a novel fluorochrome for the sensitive and reliable histochemical localization of neuronal degeneration. Brain Res. 751, 37–46. 10.1016/S0006-8993(96)01387-X [DOI] [PubMed] [Google Scholar]
  134. Schneider M. P., Boesen E. I., Pollock D. M. (2007). Contrasting actions of endothelin ETA and ETB receptors in cardiovascular disease. Annu. Rev. Pharmacol. Toxicol. 47, 731–759. 10.1146/annurev.pharmtox.47.120505.105134 [DOI] [PMC free article] [PubMed] [Google Scholar]
  135. Schwartz A. Y., Masago A., Sehba F. A., Bederson J. B. (2000). Experimental models of subarachnoid hemorrhage in the rat: a refinement of the endovascular filament model. J. Neurosci. Methods 96, 161–167. 10.1016/S0165-0270(00)00156-4 [DOI] [PubMed] [Google Scholar]
  136. Shen J., Pan J. W., Fan Z. X., Xiong X. X., Zhan R. Y. (2013). Dissociation of vasospasm-related morbidity and outcomes in patients with aneurysmal subarachnoid hemorrhage treated with clazosentan: a meta-analysis of randomized controlled trials. J. Neurosurg. 119, 180–189. 10.3171/2013.3.JNS121436 [DOI] [PubMed] [Google Scholar]
  137. Sheng H., Reynolds J. D., Auten R. L., Demchenko I. T., Piantadosi C. A., Stamler J. S., et al. (2011). Pharmacologically augmented S-nitrosylated hemoglobin improves recovery from murine subarachnoid hemorrhage. Stroke 42, 471–476. 10.1161/STROKEAHA.110.600569 [DOI] [PMC free article] [PubMed] [Google Scholar]
  138. Shimada R., Nemoto S., Ozawa H., Katsumata T. (2015). Surgical treatment of a mycotic pseudoaneurysm of the transverse arch using a rifampicin-impregnated dacron patch in an infant. J. Card. Surg. 30, 281–283. 10.1111/jocs.12492 [DOI] [PubMed] [Google Scholar]
  139. Shishido H., Egashira Y., Okubo S., Zhang H., Hua Y., Keep R. F., et al. (2015). A magnetic resonance imaging grading system for subarachnoid hemorrhage severity in a rat model. J. Neurosci. Methods 243, 115–119. 10.1016/j.jneumeth.2015.01.035 [DOI] [PMC free article] [PubMed] [Google Scholar]
  140. Siasios I., Kapsalaki E. Z., Fountas K. N. (2013). Cerebral vasospasm pharmacological treatment: an update. Neurol. Res. Int. 2013:571328. 10.1155/2013/571328 [DOI] [PMC free article] [PubMed] [Google Scholar]
  141. Siddiq F., Chaudhry S. A., Tummala R. P., Suri M. F., Qureshi A. I. (2012). Factors and outcomes associated with early and delayed aneurysm treatment in subarachnoid hemorrhage patients in the United States. Neurosurgery 71, 670–677. discussion: 677–678. 10.1227/NEU.0b013e318261749b [DOI] [PubMed] [Google Scholar]
  142. Silasi G., Colbourne F. (2009). Long-term assessment of motor and cognitive behaviours in the intraluminal perforation model of subarachnoid hemorrhage in rats. Behav. Brain Res. 198, 380–387. 10.1016/j.bbr.2008.11.019 [DOI] [PubMed] [Google Scholar]
  143. Siler D. A., Martini R. P., Ward J. P., Nelson J. W., Borkar R. N., Zuloaga K. L., et al. (2015). Protective role of p450 epoxyeicosanoids in subarachnoid hemorrhage. Neurocrit. Care 22, 306–319. 10.1007/s12028-014-0011-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  144. Sobey C. G., Faraci F. M. (1998). Subarachnoid haemorrhage: what happens to the cerebral arteries? Clin. Exp. Pharmacol. Physiol. 25, 867–876. [DOI] [PubMed] [Google Scholar]
  145. Solomon R. A., Antunes J. L., Chen R. Y., Bland L., Chien S. (1985). Decrease in cerebral blood flow in rats after experimental subarachnoid hemorrhage: a new animal model. Stroke 16, 58–64. 10.1161/01.STR.16.1.58 [DOI] [PubMed] [Google Scholar]
  146. Solomon R. A., Lovitz R. L., Hegemann M. T., Schuessler G. B., Young W. L., Chien S. (1987). Regional cerebral metabolic activity in the rat following experimental subarachnoid hemorrhage. J. Cereb. Blood Flow Metab. 7, 193–198. 10.1038/jcbfm.1987.44 [DOI] [PubMed] [Google Scholar]
  147. Starke R. M., Chalouhi N., Ding D., Raper D. M., McKisic M. S., Owens G. K., et al. (2014a). Vascular smooth muscle cells in cerebral aneurysm pathogenesis. Transl. Stroke Res. 5, 338–346. 10.1007/s12975-013-0290-1 [DOI] [PubMed] [Google Scholar]
  148. Starke R. M., Raper D. M., Ding D., Chalouhi N., Owens G. K., Hasan D. M., et al. (2014b). Tumor necrosis factor-alpha modulates cerebral aneurysm formation and rupture. Transl. Stroke Res. 5, 269–277. 10.1007/s12975-013-0287-9 [DOI] [PubMed] [Google Scholar]
  149. Sugawara T., Ayer R., Jadhav V., Zhang J. H. (2008). A new grading system evaluating bleeding scale in filament perforation subarachnoid hemorrhage rat model. J. Neurosci. Methods 167, 327–334. 10.1016/j.jneumeth.2007.08.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  150. Sumner M. J., Cannon T. R., Mundin J. W., White D. G., Watts I. S. (1992). Endothelin, ETA., and ETB receptors mediate vascular smooth muscle contraction. Br. J. Pharmacol. 107, 858–860. 10.1111/j.1476-5381.1992.tb14537.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  151. Sutherland B. A., Rabie T., Buchan A. M. (2014). Laser Doppler flowmetry to measure changes in cerebral blood flow. Methods Mol. Biol. 1135, 237–248. 10.1007/978-1-4939-0320-7_20 [DOI] [PubMed] [Google Scholar]
  152. Suzuki H., Hasegawa Y., Kanamaru K., Zhang J. H. (2010). Mechanisms of osteopontin-induced stabilization of blood-brain barrier disruption after subarachnoid hemorrhage in rats. Stroke 41, 1783–1790. 10.1161/STROKEAHA.110.586537 [DOI] [PMC free article] [PubMed] [Google Scholar]
  153. Swift D. M., Solomon R. A. (1988). Subarachnoid hemorrhage fails to produce vasculopathy or chronic blood flow changes in rats. Stroke 19, 878–882. 10.1161/01.STR.19.7.878 [DOI] [PubMed] [Google Scholar]
  154. Tada Y., Kanematsu Y., Kanematsu M., Nuki Y., Liang E. I., Wada K., et al. (2011). A mouse model of intracranial aneurysm: technical considerations. Acta Neurochir. Suppl. 111, 31–35. 10.1007/978-3-7091-0693-8_6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  155. Tada Y., Wada K., Shimada K., Makino H., Liang E. I., Murakami S., et al. (2014). Roles of hypertension in the rupture of intracranial aneurysms. Stroke 45, 579–586. 10.1161/STROKEAHA.113.003072 [DOI] [PMC free article] [PubMed] [Google Scholar]
  156. Takanashi Y., Ishida T., Meguro T., Kirchmeier M. J., Allen T. M., Zhang J. H. (2001). Intrathecal application with liposome-entrapped Fasudil for cerebral vasospasm following subarachnoid hemorrhage in rats. J. Clin. Neurosci. 8, 557–561. 10.1054/jocn.2001.0998 [DOI] [PubMed] [Google Scholar]
  157. Takata K., Sheng H., Borel C. O., Laskowitz D. T., Warner D. S., Lombard F. W. (2008). Long-term cognitive dysfunction following experimental subarachnoid hemorrhage: new perspectives. Exp. Neurol. 213, 336–344. 10.1016/j.expneurol.2008.06.009 [DOI] [PubMed] [Google Scholar]
  158. Thampatty B. P., Sherwood P. R., Gallek M. J., Crago E. A., Ren D., Hricik A. J., et al. (2011). Role of endothelin-1 in human aneurysmal subarachnoid hemorrhage: associations with vasospasm and delayed cerebral ischemia. Neurocrit. Care 15, 19–27. 10.1007/s12028-011-9508-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  159. Tiebosch I. A., Van Den Bergh W. M., Bouts M. J., Zwartbol R., Van Der Toorn A., Dijkhuizen R. M. (2013). Progression of brain lesions in relation to hyperperfusion from subacute to chronic stages after experimental subarachnoid hemorrhage: a multiparametric MRI study. Cerebrovasc. Dis. 36, 167–172. 10.1159/000352048 [DOI] [PubMed] [Google Scholar]
  160. Topkoru B. C., Altay O., Duris K., Krafft P. R., Yan J., Zhang J. H. (2013). Nasal administration of recombinant osteopontin attenuates early brain injury after subarachnoid hemorrhage. Stroke 44, 3189–3194. 10.1161/STROKEAHA.113.001574 [DOI] [PMC free article] [PubMed] [Google Scholar]
  161. Turowski B., Hänggi D., Beck A., Aurich V., Steiger H. J., Moedder U. (2007). New angiographic measurement tool for analysis of small cerebral vessels: application to a subarachnoid haemorrhage model in the rat. Neuroradiology 49, 129–137. 10.1007/s00234-006-0168-y [DOI] [PubMed] [Google Scholar]
  162. Van Den Bergh W. M., Schepers J., Veldhuis W. B., Nicolay K., Tulleken C. A., Rinkel G. J. (2005). Magnetic resonance imaging in experimental subarachnoid haemorrhage. Acta Neurochir. 147, 977–983. discussion: 983. 10.1007/s00701-005-0539-x [DOI] [PubMed] [Google Scholar]
  163. Van Gijn J., Rinkel G. J. (2001). Subarachnoid haemorrhage: diagnosis, causes and management. Brain 124, 249–278. 10.1093/brain/124.2.249 [DOI] [PubMed] [Google Scholar]
  164. Vatter H., Weidauer S., Konczalla J., Dettmann E., Zimmermann M., Raabe A., et al. (2006). Time course in the development of cerebral vasospasm after experimental subarachnoid hemorrhage: clinical and neuroradiological assessment of the rat double hemorrhage model. Neurosurgery 58, 1190–1197; discussion: 1190–1197. 10.1227/01.NEU.0000199346.74649.66 [DOI] [PubMed] [Google Scholar]
  165. Veelken J. A., Laing R. J., Jakubowski J. (1995). The Sheffield model of subarachnoid hemorrhage in rats. Stroke 26, 1279–1283. discussion: 1284. 10.1161/01.STR.26.7.1279 [DOI] [PubMed] [Google Scholar]
  166. Velat G. J., Kimball M. M., Mocco J. D., Hoh B. L. (2011). Vasospasm after aneurysmal subarachnoid hemorrhage: review of randomized controlled trials and meta-analyses in the literature. World Neurosurg. 76, 446–454. 10.1016/j.wneu.2011.02.030 [DOI] [PubMed] [Google Scholar]
  167. Vellimana A. K., Milner E., Azad T. D., Harries M. D., Zhou M. L., Gidday J. M., et al. (2011). Endothelial nitric oxide synthase mediates endogenous protection against subarachnoid hemorrhage-induced cerebral vasospasm. Stroke 42, 776–782. 10.1161/STROKEAHA.110.607200 [DOI] [PMC free article] [PubMed] [Google Scholar]
  168. Vergouwen M. D., de Haan R. J., Vermeulen M., Roos Y. B. (2010). Effect of statin treatment on vasospasm, delayed cerebral ischemia, and functional outcome in patients with aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis update. Stroke 41, e47–e52. 10.1161/STROKEAHA.109.556332 [DOI] [PubMed] [Google Scholar]
  169. Verlooy J., Van Reempts J., Haseldonckx M., Borgers M., Selosse P. (1991). Singlet oxygen induced cerebral vasospasm: an experimental study in rats. Acta Neurol. Belg. 91, 151–157. [PubMed] [Google Scholar]
  170. Voldby B., Enevoldsen E. M. (1982). Intracranial pressure changes following aneurysm rupture. Part 1: clinical and angiographic correlations. J. Neurosurg. 56, 186–196. 10.3171/jns.1982.56.2.0186 [DOI] [PubMed] [Google Scholar]
  171. Wada K., Hattori K., Araki Y., Noda T., Maki H., Oyama H., et al. (2014). [A case of moyamoya disease with a subarachnoid hemorrhage treated with endovascular technique]. No Shinkei Geka 42, 1027–1033. 10.11477/mf.1436200026 [DOI] [PubMed] [Google Scholar]
  172. Wada K., Makino H., Shimada K., Shikata F., Kuwabara A., Hashimoto T. (2013). Translational research using a mouse model of intracranial aneurysm. Transl. Stroke Res. 5, 248–251. 10.1007/s12975-013-0296-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  173. Wang Z., Chen G., Zhu W. W., Zhou D. (2010). Activation of nuclear factor-erythroid 2-related factor 2 (Nrf2) in the basilar artery after subarachnoid hemorrhage in rats. Ann. Clin. Lab. Sci. 40, 233–239. [PubMed] [Google Scholar]
  174. Weidauer S., Vatter H., Dettmann E., Seifert V., Zanella F. E. (2006). Assessment of vasospasm in experimental subarachnoid hemorrhage in rats by selective biplane digital subtraction angiography. Neuroradiology 48, 176–181. 10.1007/s00234-005-0021-8 [DOI] [PubMed] [Google Scholar]
  175. Westermaier T., Jauss A., Eriskat J., Kunze E., Roosen K. (2009a). Acute vasoconstriction: decrease and recovery of cerebral blood flow after various intensities of experimental subarachnoid hemorrhage in rats. J. Neurosurg. 110, 996–1002. 10.3171/2008.8.JNS08591 [DOI] [PubMed] [Google Scholar]
  176. Westermaier T., Jauss A., Eriskat J., Kunze E., Roosen K. (2009b). Time-course of cerebral perfusion and tissue oxygenation in the first 6 h after experimental subarachnoid hemorrhage in rats. J. Cereb. Blood Flow Metab. 29, 771–779. 10.1038/jcbfm.2008.169 [DOI] [PubMed] [Google Scholar]
  177. Wong G. K., Zhu X. L., Ng H. K., Yu S. C., Poon W. S. (2008). Vermal hemorrhage with fourth ventricle extension due to ruptured posterior inferior cerebellar artery aneurysm. J. Clin. Neurosci. 15, 203–205. 10.1016/j.jocn.2006.05.009 [DOI] [PubMed] [Google Scholar]
  178. Xu H., Testai F. D., Valyi-Nagy T., N Pavuluri M., Zhai F., Nanegrungsunk D., et al. (2015). VAP-1 blockade prevents subarachnoid hemorrhage-associated cerebrovascular dilating dysfunction via repression of a neutrophil recruitment-related mechanism. Brain Res. 1603, 141–149. 10.1016/j.brainres.2015.01.047 [DOI] [PubMed] [Google Scholar]
  179. Young P. J., Bowling W. M. (2012). Midlevel practitioners can safely place intracranial pressure monitors. J. Trauma Acute Care Surg. 73, 431–434. 10.1097/TA.0b013e318262437b [DOI] [PubMed] [Google Scholar]
  180. Zhang D., Yan H., Li H., Hao S., Zhuang Z., Liu M., et al. (2015). TGFbeta-activated Kinase 1 (TAK1) Inhibition by 5Z-7-Oxozeaenol Attenuates Early Brain Injury after Experimental Subarachnoid Hemorrhage. J. Biol. Chem. 290, 19900–19909. 10.1074/jbc.M115.636795 [DOI] [PMC free article] [PubMed] [Google Scholar]
  181. Zhang X. S., Zhang X., Zhang Q. R., Wu Q., Li W., Jiang T. W., et al. (2015). Astaxanthin reduces matrix metalloproteinase-9 expression and activity in the brain after experimental subarachnoid hemorrhage in rats. Brain Res. 1624, 113–124. 10.1016/j.brainres.2015.07.020 [DOI] [PubMed] [Google Scholar]
  182. Zhang Z. D., Yamini B., Komuro T., Ono S., Johns L., Marton L. S., et al. (2001). Vasospasm in monkeys resolves because of loss of and encasement of subarachnoid blood clot. Stroke 32, 1868–1874. 10.1161/01.STR.32.8.1868 [DOI] [PubMed] [Google Scholar]
  183. Zhang Z. Y., Yang M. F., Wang T., Li D. W., Liu Y. L., Zhang J. H., et al. (2015). Cysteamine alleviates early brain injury via reducing oxidative stress and apoptosis in a rat experimental subarachnoid hemorrhage model. Cell. Mol. Neurobiol. 35, 543–553. 10.1007/s10571-014-0150-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  184. Zhao J., Zhou D., Guo J., Ren Z., Zhou L., Wang S., et al. (2011). Efficacy and safety of fasudil in patients with subarachnoid hemorrhage: final results of a randomized trial of fasudil versus nimodipine. Neurol. Med. Chir. (Tokyo) 51, 679–683. 10.2176/nmc.51.679 [DOI] [PubMed] [Google Scholar]
  185. Zhao X. D., Mao H. Y., Lv J., Lu X. J. (2016). Expression of high-mobility group box-1 (HMGB1) in the basilar artery after experimental subarachnoid hemorrhage. J. Clin. Neurosci. 27, 161–165. 10.1016/j.jocn.2015.06.034 [DOI] [PubMed] [Google Scholar]
  186. Zoerle T., Lombardo A., Colombo A., Longhi L., Zanier E. R., Rampini P., et al. (2015). Intracranial pressure after subarachnoid hemorrhage. Crit. Care Med. 43, 168–176. 10.1097/CCM.0000000000000670 [DOI] [PubMed] [Google Scholar]

Articles from Frontiers in Molecular Neuroscience are provided here courtesy of Frontiers Media SA

RESOURCES