Abstract
Purpose
Red blood cells (RBC)-poor thrombi in acute ischemic stroke (AIS) are associated with longer recanalization time for mechanical thrombectomy than RBC-rich thrombi. The purpose of the study was to differentiate between RBC-rich and RBC-poor thrombi using dual energy computed tomography (DECT).
Materials and methods
This retrospective study was conducted on patients with acute arterial occlusion of anterior circulation who underwent DECT cerebral angiography, followed by mechanical thrombectomy with the pathological diagnosis of thrombi, dividing into RBC-rich and RBC-poor thrombi. The CT attenuation values and thrombus enhancement were measured in non-contrast scans and CTA phases at different energy levels and compared between RBC-rich and RBC-poor groups.
Results
Fourteen acute stroke patients were included in the study. There were 7 patients in RBC-rich group and 7 patients in RBC-poor group. The CT attenuation values of RBC-rich thrombi were significantly higher than those of RBC-poor thrombi at energy levels of 40, 50, 60, 70, and 80 KeV, with the most significant difference at 80 KeV (p = 0.032). A cutoff value of 44.1 Hounsfield units (HU) on 80 keV monoenergetic reconstructions was used to distinguish between RBC-rich and RBC-poor thrombi. It achieved an area under the curve (AUC) of 0.878, sensitivity of 85.7%, specificity of 100%, and accuracy of 92.9%. The degree of enhancement was higher in RBC-poor thrombi than in RBC-rich thrombi, without statistically significant difference.
Conclusion
DECT could help differentiate between RBC-rich and RBC-poor thrombi by using CT attenuation values in non-contrast phase at lower energy levels (40–80 KeV).
Keywords: acute ischemic stroke, dual energy computed tomography, computed tomography angiography, thrombus, red blood cells-rich thrombi, red blood cells-poor thrombi
Introduction
AIS is a leading cause of long-term disability and mortality, with increasing incidence over the past decade. Of all strokes, 87% are ischemic, and 10% are hemorrhagic strokes (intracerebral hemorrhage), whereas 3% are subarachnoid hemorrhage (SAH) strokes.1,2 According to the most recent guidelines for the early management of patients with AIS, the standard treatment includes intravenous thrombolytic drugs and mechanical thrombectomy. Before initiating any treatment, non-contrast CT should be performed to exclude intracranial hemorrhage. CTA with computed tomography perfusion (CTP) or magnetic resonance angiography (MRA) with diffusion-weighted magnetic resonance imaging (DW-MRI) helps select candidates for endovascular treatment (EVT) with mechanical thrombectomy. 3
The most common sources of embolism leading to AIS are clots originating from the heart, detached clots from atherosclerotic plaques, and arterial dissection. 4 These clots consist of platelets, fibrin, and RBC and significantly vary in composition. 5 The success of EVT and systemic thrombolytic therapy of AIS is positively associated with RBC fraction of the clots, which roughly correlates with clot density on the unenhanced computed tomography.6–10 However, due to the linear correlation between CT attenuation and hematocrit level, some conditions such as polycythemia or anemia may affect the attenuation of the thrombi in CT study.11,12 On the other hand, it is thought that the fibrin protein has high affinity for iodinated contrast agents and that the fibrin content in blood clots strongly correlates with the contrast uptake. Therefore, contrast-enhanced CT may be advantageous for clot characterization.13–15 Simons et al. 16 found that late phase thrombus (fibrin-dominant or RBC-poor) was associated with longer mean recanalization time for EVT than early phase thrombi (RBC-dominant or RBC-rich). Various studies investigated the association between clot characteristics and treatment outcome on conventional CT and found that clot density on CTA, 17 clot burden score,18,19 length of thrombus,20–23 and thrombus permeability 24 can predict successful recanalization and treatment outcome. Lower clot burden score was associated with a higher rate of hemorrhagic transformation. 19 All of the studies mentioned above were evaluated with conventional CT scans in patients with AIS.
DECT is a novel technique which has benefit over the conventional CT in better contrast appreciation, decreased amount of contrast used in contrast-enhanced CT study, decreased CT dose, and reduced some artifacts. Borggrefe et al. 25 conducted in vitro study using DECT and found association between fibrin and RBC content with the clot contrast uptake and density, respectively, which is consistent with prior studies using conventional CT. 17 To our knowledge, there has been no study of thrombus density measurement using DECT in vivo. This study aimed to differentiate between RBC-rich and RBC-poor thrombi using DECT in vivo. In addition, we aimed to study the correlation between the fibrin component of the thrombi and degree of enhancement using DECT.
Materials and methods
Patient selection
The institutional ethics review board approved this retrospective study. Because of the retrospective nature of the study, the need for informed consent was waived. Adult patients who presented with AIS between January 2019 and September 2019 who visited the emergency department and underwent DE-CTA of the brain within 30 min of the hospital arrival were selected from a maintained database. Note that all CT scans in emergency department in our institution were performed with DECT. The patients with evidence of acute anterior circulation thrombotic occlusion on DE-CTA who underwent digital subtraction angiography (DSA) and EVT with mechanical thrombectomy and had available pathological analysis of the retrieved thrombi were included in the study. Electronic medical records were reviewed for patient demographics, clinical history, National Institutes of Health Stroke Scale (NIHSS), time from symptoms onset to hospital arrival, administration of recombinant tissue plasminogen activator (rtPA), and pathological report of the retrieved thrombi. Fifteen patients were met the inclusion criteria. One patient was excluded from the study because the percentage of the retrieved clot was not reported in the pathological examination.
Pathological examination of the thrombi demonstrated components of RBC, white blood cells (WBC), and fibrin. RBC-rich thrombi were defined as an RBC component of more than 50%. RBC-poor or fibrin-rich thrombi was defined as an RBC component of less than or equal to 50%.
The reports of EVT with mechanical thrombectomy were reviewed. Successful recanalization by mechanical thrombectomy was defined by thrombolysis in cerebral infarction (TICI) score of 2b and 3. Recanalization time was referred to time from groin puncture to thrombus retrieval.
Imaging techniques
All initial CT of brain at the time of presentation at emergency department was done with DECT, since it was the only scanner at the emergency department. Non-contrast DECT and DE-CTA of the brain was acquired on a single source, dual detector CT scanner with rapid kV switching (GE Healthcare, Tokyo, Japan). Scan parameters were tube voltage 80/Sn140 kV, slice thickness 0.625 mm, rotation time 0.35 s, pitch 0.5 and automatic tube current. Iodinated contrast material of 70 mL was injected through an 18-gauge cannula in an antecubital vein at a flow rate of 4 mL/s, followed by 50 mL of saline. Bolus tracking was used for timing with the threshold of 150 HU. The scan was initiated with a delay time of 4 s after the arrival of the bolus in the common carotid artery for CTA or aortic arch for multiphase CTA. Images were reconstructed with a 2.5 mm slice thickness. The post-contrast scan was performed at a delay time of 10–15 min. The multiphase DE-CTA (arterial, venous, and delayed phases) were performed in five patients in order to assess arterial collaterals. However, the first phase of multiphase DE-CTA was comparable to the arterial phase in single phase DE-CTA. Non-contrast DECT, DE-CTA, and arterial phase (first phase) of multiphase DE-CTA were used for measurements in our study.
Follow-up CT of the brain in all patients were done, using non-contrast DECT, 24–48 h after treatment with mechanical thrombectomy or in the presence of worsening neurological examination.
Imaging analysis
DE-CTA images were interpreted by a second-year neuroradiology fellowship and a neuroradiologist with 12 years of experience in brain imaging in consensus. They were blinded to the detailed clinical information, official radiological reports, and pathological reports. The Alberta Stroke Program Early CT in CTA phase (CTA-ASPECT) score, clot location, clot length, clot burden score (CBS), and evidence of hemorrhagic transformation were reviewed on Synapse Picture archiving and communication system (PACS) (FUJIFILM medical system, USA).
Virtual monoenergetic reconstructions on different energy levels (40–100 keV with 10 keV increment) were used for analysis. The clot density in the non-contrast and arterial phases DE-CTA of the brain were measured by a second-year neuroradiology fellowship in two separate sessions (1 month apart). The clot density measurements were done on a working station (Advantage Workstation, version 3.2, GE Healthcare) using thin slices and multiplanar reconstruction (MPR). The clot density was measured at different energy levels (40, 50, 60, 70, 80, 90, and 100 KeV) by manually drawing a circular region of interest (ROI) (ranging from 4.5 to 9.5 mm2) in axial non-contrast DECT scan of the brain. Figure 1 demonstrates different densities of the thrombi at different energy levels, in which lower energy levels exhibit higher thrombus density. For each patient, the ROI was placed over the highest density of the thrombi. The spectral Hounsfield unit curve of measured thrombus densities at different energy levels was generated (Figure 2). The same ROI size was also drawn in the DE-CTA phase and placed over the same thrombus area as identified in a non-contrast DECT to measure the degree of thrombus enhancement (Figure 3).
Figure 1.
Non-contrast DECT brain of a 60 year-old patient presented with acute right hemiparesis shows hyperdense thrombus at the M1 segment of the right MCA. DECT demonstrates different densities of the thrombus at different energy levels of 40 (a), 70 (b), and 100 (c) KeV.
Figure 2.
Measurement of thrombus density on non-contrast DECT of the same patient as Figure 1. The ROI of 7.4 mm2 was drawn at the highest density part of the thrombus. (a) The spectral Hounsfield unit curve of measured thrombus density shows different densities of the thrombus (y-axis) at different energy levels (x-axis); the highest density is at the energy level of 40 KeV (b).
Figure 3.
Measurement of thrombus density on CTA phase of the same patient as Figure 1. The same size of ROI (7.4 mm2) was drawn at the same area as Figure 2. (a) Spectral Hounsfield unit curve of thrombus density on CTA phase shows different densities of the thrombus (y-axis) at different energy levels (x-axis). The highest density is at the energy level of 40 KeV (b).
Since the hematocrit level may affect the measured thrombus density, normalized thrombus density in non-contrast DECT was calculated as measured density (Hounsfield Unit) divided by the hematocrit level. Note that normalized density is not routinely used in emergency condition. We calculated normalized density only for the research.
The degree of thrombus enhancement was calculated as the density of thrombi in CTA phase minus the density in non-contrast phase.
Statistical analysis
All statistical analyses were performed using SPSS version 23.0 statistical software. The thrombus densities on non-contrast DECT in each energy level were compared between RBC-rich and RBC-poor groups using independent t-test. The thrombus enhancement was compared between RBC-rich and RBC-poor groups using Wilcoxon Signed-Rank test. A receiver operating characteristics (ROC) curve was used to determine the cutoff value of thrombus density on non-contrast DECT for differentiating between RBC-rich and RBC-poor thrombi. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. The intra-observer agreement was calculated using Pearson correlation analysis. The p-value of less than 0.05 was defined as statistically significant difference.
Results
A total of 14 patients were included in our study, seven patients had RBC-rich thrombi and seven patients had RBC-poor thrombi. Six patients were male, and eight patients were female, with a mean age of 64.29 ± 14.95 years. The average NIHSS was 15 (range from 6 to 29), and the average CTA-ASPECT score was 8.21 ± 1.53 (range from 5 to 10). Average CBS was 8 (range from 5 to 9). There were three patients treated with rtPA before mechanical thrombectomy. The demographic and clinical characteristics of the patients in RBC-rich and RBC-poor groups are shown in Table 1. The thrombus length, CBS, recanalization time, and hemorrhagic transformation showed no statistically significant difference.
Table 1.
Demographic and clinical characteristics of the study population compared between RBC-rich and RBC-poor groups.
| Characteristic | RBC-rich | RBC-poor | p-value |
|---|---|---|---|
| Sex | |||
| Male (n) | 2 | 4 | 0.592 |
| Female (n) | 5 | 3 | |
| Age (years) a | 62.29 ± 18.16 | 66.29 ± 12.04 | 0.636 |
| Underlying disease (n) | |||
| AF | 0 | 3 | 0.192 |
| DM | 1 | 3 | 0.559 |
| HT | 2 | 6 | 0.103 |
| DLP | 1 | 2 | 1.000 |
| Old CVA | 2 | 1 | 1.000 |
| CTA-ASPECT score a | 8.29 ± 1.5 | 8.14 ± 1.68 | 0.168 |
| Length (mm) a | 13.51 ± 5.79 | 13.51 ± 8.22 | 1.000 |
| CBS a | 8.14 ± 0.69 | 7.86 ± 1.46 | 0.467 |
| Hemorrhagic transformation (n) | 3 | 2 | 1.000 |
| Recanalization time (min) a | 39.71 ± 21.39 | 49.57 ± 15.27 | 0.341 |
AF: Atrial fibrillation; ASPECT: Alberta stroke program early CT; CBS: Clot burden score; CVA: Cerebrovascular accident; DLP: Dyslipidemia; DM: Diabetes mellitus; HT: Hypertension; SD: Standard deviation.
aValues are reported as mean ± SD.
There was significantly higher attenuation of RBC-rich thrombi than those of RBC-poor thrombi at energy levels of 40, 50, 60, 70, and 80 KeV. At 80 KeV, there was the most significant difference in thrombus density between these groups (p = 0.032) (Table 2).
Table 2.
CT attenuation values of RBC-rich and RBC-poor thrombi in non-contrast phase at different energy levels.
| Energy level, KeV | RBC-rich (HU) a | RBC-poor (HU) a | p-value |
|---|---|---|---|
| 40 | 82.34 ± 14.21 | 69.62 ± 4.66 | 0.044 |
| 50 | 68.50 ± 9.72 | 59.26 ± 3.50 | 0.036 |
| 60 | 57.87 ± 7.71 | 50.71 ± 3.74 | 0.047 |
| 70 | 50.31 ± 6.03 | 44.53 ± 2.92 | 0.042 |
| 80 | 47.13 ± 5.37 | 41.65 ± 2.58 | 0.032 |
| 90 | 44.70 ± 5.05 | 40.15 ± 2.41 | 0.053 |
| 100 | 42.85 ± 5.50 | 38.64 ± 2.33 | 0.087 |
aValues are reported as mean ± SD.
ROC curves were created to find CT attenuation cutoff values for differentiating between RBC-rich and RBC-poor thrombi at 40, 50, 60, 70, and 80 KeV energy levels (Figure 4). The ROC curve of CT attenuation value at 80 KeV showed the highest area under the curve (AUC). Therefore, a CT attenuation value of 44.1 HU at 80 KeV monoenergetic reconstructions was selected as a cutoff value for distinguishing between RBC-rich and RBC-poor thrombi, for which it obtained a sensitivity of 85.7%, specificity of 100%, PPV of 100%, NPV of 85.7%, and accuracy of 92.9% (Figure 5).
Figure 4.
ROC curve of thrombus density in non-contrast phase at different energy levels.
Figure 5.
ROC curve of thrombus density in non-contrast phase at 80 KeV.
There is significantly higher CT attenuation normalized by the hematocrit levels of RBC-rich thrombi than those of RBC-poor thrombi at all energy levels (Table 3).
Table 3.
CT attenuation values normalized by the hematocrit levels of RBC-rich and RBC-poor thrombi at different energy levels.
| Energy level, KeV | RBC-rich (HU) a | RBC-poor (HU) a | p-value |
|---|---|---|---|
| 40 | 2.21 ± 0.36 | 1.69 ± 0.25 | 0.009 |
| 50 | 1.85 ± 0.30 | 1.44 ± 0.21 | 0.012 |
| 60 | 1.57 ± 0.27 | 1.23 ± 0.19 | 0.020 |
| 70 | 1.36 ± 0.24 | 1.08 ± 0.14 | 0.019 |
| 80 | 1.28 ± 0.25 | 1.01 ± 0.10 | 0.019 |
| 90 | 1.22 ± 0.25 | 0.97 ± 0.10 | 0.031 |
| 100 | 1.17 ± 0.26 | 0.94 ± 0.09 | 0.043 |
aValues are reported as mean ± SD.
The degree of thrombus enhancement at different energy levels was compared between RBC-rich and RBC-poor thrombi. There was no statistically difference between these two groups, but the RBC-poor thrombi tend to have higher degree of enhancement than in RBC-rich thrombi at all energy levels, without statistically significant difference (Table 4).
Table 4.
Enhancement of RBC-rich and RBC-poor thrombi at different energy levels.
| Energy level, KeV | RBC-rich | RBC-poor | p-value | ||
|---|---|---|---|---|---|
| Min–max (HU) | Mean (HU) a | Min–max (HU) | Mean (HU) a | ||
| 40 | 10.76–142.81 | 48.63 ± 44.88 | 13.2–230.01 | 81.96 ± 74.11 | 0.180 |
| 50 | 6.22–96.1 | 33.45 ± 30.16 | 12.63–149.29 | 53.90 ± 45.79 | 0.180 |
| 60 | 1.51–65.83 | 21.3 ± 20.42 | 7.98–101.19 | 36.38 ± 31.34 | 0.180 |
| 70 | 3.46–51.32 | 17.21 ± 16.21 | 8.08–75.48 | 31.09 ± 22.39 | 0.142 |
| 80 | 1.91–36.42 | 12.84 ± 11.5 | 5.37–53.02 | 23.36 ± 15.34 | 0.142 |
| 90 | 0.41–26.52 | 7.28 ± 6.3 | 2.37–31.75 | 14.58 ± 10.52 | 0.085 |
| 100 | 0.53–18.11 | 5.2 ± 6.82 | 1.56–21.73 | 10.59 ± 8.45 | 0.085 |
aValues are reported as mean ± SD.
Discussion
Our study shows that CT attenuation values in non-contrast phase at 40, 50, 60, 70, and 80 KeV were significantly higher in RBC-rich thrombi than in RBC-poor thrombi (p < 0.05). In contrast, the CT attenuation values in arterial phase were higher in RBC-poor (fibrin-rich) thrombi than in RBC-rich thrombi. These findings correlate with Borggrefe et al. in 2018, which measured thrombus density using DECT in vitro. 25 However, the latter finding in our study is not statistically significant difference.
Furthermore, our study demonstrates that the most statistically significant difference in attenuation values measured on non-contrast DECT between RBC-rich and RBC-poor thrombi is at the energy level of 80 KeV (p = 0.032) which also had the highest AUC. This indicates that the energy level of 80 KeV is the most useful diagnostic energy level to differentiate RBC-rich and RBC-poor thrombi in non-contrast DECT. A cutoff value of 44.1 HU at the energy level of 80 KeV was found to have relatively highest sensitivity, specificity, and accuracy.
Since hematocrit level affects the attenuation in non-contrast CT, we calculated the normalized density of the thrombi in non-contrast DECT. The result also showed that the RBC-rich thrombi had significantly higher attenuation than those of the RBC-poor thrombi, corresponding with the result of non-normalized CT density.
In our study, RBC-poor thrombi (fibrin-rich) were found to have a higher degree of enhancement than RBC-rich thrombi in all energy levels. However, there was no statistically significant difference between these two groups; the findings correspond with prior studies by Yuki et al. in 2012 10 and Simon et al. in 2015. 16 As a result, we could conclude that measurement of thrombus density in non-contrast phase of DECT has the benefit of differentiating between RBC-rich and RBC-poor thrombus rather than measuring thrombus enhancement. It may help prediction of successful recanalization or easiness of mechanical thrombectomy.
There are some limitations to this study. First, the number of patients was relatively small. Further studies may require a larger number of patients, increasing a significant difference in the findings. Second, there was no comparison of thrombus density between conventional CT and DECT in this study because the two techniques could not be performed simultaneously due to the patients’ increment of the radiation dose and weighted average DECT reconstruction is not routinely done in our institution. Last, there was no comparison between the RBC component and clinical outcome because some patients had not sufficient time for follow-up. Further studies focusing on a correlation between CT attenuation of the thrombi and clinical outcome are recommended for better impact on clinical practice.
Conclusion
DECT has a role in differentiating between RBC-rich and RBC-poor thrombi by measuring CT attenuation in non-contrast phase at lower energy levels (40–80 KeV).
Our study recommends using a CT attenuation value of 44.1 HU at the energy level of 80 KeV as a cutoff value for distinguishing between RBC-rich and RBC-poor thrombi.
Footnotes
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
Ethical approval: All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.
ORCID iD
Theeraphol Panyaping https://orcid.org/0000-0002-6051-1772
References
- 1.Benjamin EJ, Muntner P, Bittencourt MS. Heart disease and stroke statistics-2019 update: a report from the American heart association. Circulation 2019; 139: e56–e528. [DOI] [PubMed] [Google Scholar]
- 2.Hanchaiphiboolkul S, Poungvarin N, Nidhinandana S, et al. Prevalence of stroke and stroke risk factors in Thailand: Thai epidemiologic stroke (TES) study. J Med Assoc Thai 2011; 94: 427. [PubMed] [Google Scholar]
- 3.Powers WJ, Rabinstein AA, Ackerson T, et al. Guidelines for the early management of patients with acute ischemic stroke: 2019 update to the 2018 guidelines for the early management of acute ischemic stroke: a guideline for healthcare professionals from the American heart association/American stroke association. Stroke 2019; 50: e344–e418. [DOI] [PubMed] [Google Scholar]
- 4.Morales-Vidal S, Biller J. Stroke pathophysiology. In: Ovbiagele B. (ed). Stroke Management and Recovery. 1st ed. London: Future Medicine, 2013, pp. 6–20. [Google Scholar]
- 5.Niesten JM, van der Schaaf IC, van Dam L, et al. Histopathologic composition of cerebral thrombi of acute stroke patients is correlated with stroke subtype and thrombus attenuation. PLoS One 2014; 9: e88882. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Marder VJ, Chute DJ, Starkman S, et al. Analysis of thrombi retrieved from cerebral arteries of patients with acute ischemic stroke. Stroke 2006; 37: 2086–2093. [DOI] [PubMed] [Google Scholar]
- 7.Jang I-K, Gold HK, Ziskind AA, et al. Differential sensitivity of erythrocyte-rich and platelet-rich arterial thrombi to lysis with recombinant tissue-type plasminogen activator: a possible explanation for resistance to coronary thrombolysis. Circulation 1989; 79: 920–928. [DOI] [PubMed] [Google Scholar]
- 8.Kirchhof K, Sikinger M, Welzel T, et al. Does the result of thrombolysis with recombinant tissue-type plasminogen activator (rt-PA) in rabbits depend on the erythrocyte-and fibrin-content of a thrombus? RoFo 2004; 176: 98–105. [DOI] [PubMed] [Google Scholar]
- 9.Almekhlafi MA, Hu WY, Hill MD, et al. Calcification and endothelialization of thrombi in acute stroke. Ann Neurol 2008; 64: 344–347. [DOI] [PubMed] [Google Scholar]
- 10.Yuki I, Kan I, Vinters H, et al. The impact of thromboemboli histology on the performance of a mechanical thrombectomy device. AJNR Am J Neuroradiol 2012; 33: 643–648. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Rauch RA, Bazan C, Larsson E-M, et al. Hyperdense middle cerebral arteries identified on CT as a false sign of vascular occlusion. AJNR Am J Neuroradiol 1993; 14: 669–673. [PMC free article] [PubMed] [Google Scholar]
- 12.Ben DS, Osseby G, Rezaizadeh-Bourdariat K, et al. Spontaneous hyperdense intracranial vessels seen on CT scan in polycythemia cases. J de radiologie 2003; 84: 605–608. [PubMed] [Google Scholar]
- 13.Jones CI, Goodall AH. Differential effects of the iodinated contrast agents ioxaglate, iohexol and iodixanol on thrombus formation and fibrinolysis. Thromb Res 2003; 112: 65–71. [DOI] [PubMed] [Google Scholar]
- 14.McDonald MM, Archeval-Lao JM, Cai C, et al. Iodinated contrast does not alter clotting dynamics in acute ischemic stroke as measured by thromboelastography. Stroke 2014; 45: 462–466. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Gabriel DA, Jones MR, Reece NS, et al. Platelet and fibrin modification by radiographic contrast media. Circ Res 1991; 68: 881–887. [DOI] [PubMed] [Google Scholar]
- 16.Simons N, Mitchell P, Dowling R, et al. Thrombus composition in acute ischemic stroke: a histopathological study of thrombus extracted by endovascular retrieval. J Neuroradiol 2015; 42: 86–92. [DOI] [PubMed] [Google Scholar]
- 17.Borst J, Berkhemer O, Santos E, et al. Value of thrombus CT characteristics in patients with acute ischemic stroke. AJNR Am J Neuroradiol 2017; 38: 1758–1764. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Tan IY, Demchuk AM, Hopyan J, et al. CT angiography clot burden score and collateral score: correlation with clinical and radiologic outcomes in acute middle cerebral artery infarct. AJNR Am J Neuroradiol 2009; 30: 525–531. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Puetz V, Dzialowski I, Hill MD, et al. Intracranial thrombus extent predicts clinical outcome, final infarct size and hemorrhagic transformation in ischemic stroke: the clot burden score. Int J Stroke 2008; 3: 230–236. [DOI] [PubMed] [Google Scholar]
- 20.Ganeshan R, Nave AH, Scheitz JF, et al. Assessment of thrombus length in acute ischemic stroke by post-contrast magnetic resonance angiography. J Neurointervent Surg 2018; 10: 756–760. [DOI] [PubMed] [Google Scholar]
- 21.Riedel CH, Zimmermann P, Jensen-Kondering U, et al. The importance of size: successful recanalization by intravenous thrombolysis in acute anterior stroke depends on thrombus length. Stroke 2011; 42: 1775–1777. [DOI] [PubMed] [Google Scholar]
- 22.Santos EM, Marquering HA, den Blanken MD, et al. Thrombus permeability is associated with improved functional outcome and recanalization in patients with ischemic stroke. Stroke 2016; 47: 732–741. [DOI] [PubMed] [Google Scholar]
- 23.Rohan V, Baxa J, Tupy R, et al. Length of occlusion predicts recanalization and outcome after intravenous thrombolysis in middle cerebral artery stroke. Stroke 2014; 45: 2010–2017. [DOI] [PubMed] [Google Scholar]
- 24.Chen Z, Shi F, Gong X, et al. Thrombus permeability on dynamic CTA predicts good outcome after reperfusion therapy. AJNR Am J Neuroradiol 2018; 39: 1854–1859. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Borggrefe J, Kottlors J, Mirza M, et al. Differentiation of clot composition using conventional and dual-energy computed tomography. Clin Neuroradiol 2018; 28: 515–522. [DOI] [PubMed] [Google Scholar]