Cardiovascular Imaging Techniques to Assess Microvascular Dysfunction

Abstract

The understanding of microvascular dysfunction (MVD) without evidence of epicardial coronary artery disease (CAD) pales in comparison to the understanding of obstructive epicardial CAD. A primary limitation in the past had been the lack of development of noninvasive methods of detecting and quantifying MVD. This limitation has particularly affected our ability to study the pathophysiology, morbidity, and treatment of this disease. More recently, almost all of the non-invasive cardiac imaging modalities have been used to quantify blood flow and advance our understanding of MVD.

The current understanding of the symptoms, prognosis, and treatment strategies in ischemic heart disease resulting primarily from abnormalities of the coronary microcirculation pales in comparison to that of epicardial coronary artery stenosis. Contemporary consensus statements and guidelines direct assessment and treatment of epicardial coronary artery disease and resultant myocardial ischemia in a variety of clinical situations [1,2,3]. With both invasive and noninvasive testing, the identification of epicardial ischemic disease is better established than for the detection of microvascular disease. Beneficial treatment strategies are available for epicardial stenosis whose significance can be fully evaluated by direct angiographic visualization with functional assessment determined by either perfusion imaging or invasive techniques to obtain fractional flow reserve (FFR), coronary flow reserve (CFR) or indices of microvascular resistance (IMR)[4,5,6]. Recognizing microvascular dysfunction (MVD) has required significant advancements in technology before reliable and reproducible measurements could be made so that prognostic and therapeutic trials could be pursued [7,8]. There is a growing interest in diagnosing and treating MVD as more patients are diagnosed with angina without obstructive coronary disease (ANOCA) or ischemia without obstructive coronary disease (INOCA). Furthermore, MVD may play a vital role in the pathophysiological mechanisms of certain diseases such as heart failure with preserved ejection fraction or takotsubos cardiomyopathy[9; 10]. The diagnosis of MVD is often challenging and can exist in the setting of obstructive epicardial disease and non-obstructive disease[11]. In this manuscript, we will provide a comprehensive review of the multiple imaging modalities that assess coronary MVD in the absence of obstructive epicardial disease.

Defining Coronary Microvascular Dysfunction

Before understanding the underlying technicalities required to quantify MVD, baseline knowledge of the functional anatomy of the coronary circulation is required (Figure 1). There are three components of the coronary arterial vasculature that are subdivided by the size of the arterial structure, its capacitance, and its resistance to myocardial blood flow (MBF)[12]. The initial component is the epicardial coronary arterial tree (5mm to 400μm in diameter), which have a near negligible coronary resistance in the absence of stenosis and are essentially conductive vessels. The prearteriole vessels follow (100 to 400μm in size); these are still largely extramyocardial and primarily respond to flow and intravascular pressure to deliver a narrow pressure range to the arterioles [12]. The third and distal component is the intramural arterioles (40 to 100μm), which have the primary responsibility of matching blood supply to myocardial oxygen consumption. The distal capillary and venule systems are low resistance capacitance vessels, holding up to 90% of the total intramyocardial blood volume [13]. The pressure gradient between the aortic root and the right atrium is the primary driving force of flow across the myocardium[14]. MBF is defined as the amount of flow through the coronary vessels over time, and is typically expressed as blood flow per gram of myocardium [12].

Figure 1: Coronary circulation schematic.

Components of the coronary circulation (a). Schematic of the macrocirculation (b) and microcirculation(c). FFR-fractional flow reserve, IMR- index of microvasculatory resistance, CFR-coronary flow reserve.

(Permission obtained and adapted from De Bruyne, B et al. Microvascular (Dys)Function and Clinical Outcome in Stable Coronary Disease J Am Coll Cardiol. 2016; 67(10):1170–1172. and Taqueti VR, et al. Coronary Microvascular Disease Pathogenic Mechanisms and Therapeutic Options: JACC State-of-the-Art Review. J Am Coll Cardiol. 2018 Nov 27;72(21):2625–2641.)

Under normal conditions, there are elegant mechanisms of autoregulation in the prearteriolar and arteriolar microcirculation that allow for stable coronary blood flow across a large range of perfusion pressures [12,15]. For example, in the setting of hypotension, the driving pressure would decrease and thenautoregulatory mechanisms would subsequently decrease microvascular resistance to attempt to maintain adequate blood flow [14]. There are multiple autoregulatory mechanisms aimed atmanipulating arterial tone. There is myogenic constriction of the distal prearterioles in response to increased pressure. Arterioles can decrease or increase their diameter in response to flow changes, leading to shear stress which induces dilation of larger conductive vessels. In addition, arterioles can regulate blood flow in response to metabolites formed when myocardial oxygen demand increases [16].

In the setting of coronary MVD, there can be a disruption of these adaptive mechanisms, which can be assessed via various noninvasive provocative tests. One such test is sympathetic stimulation using cold pressor testing. The sympathetic response from a cold stimulus will increase myocardial work and thus a proportionate increase in MBF by metabolically-initiated endothelium-related vasodilator forces in the microvasculature [14,17]. Inotropic stimulation with dobutamine can increase myocardial blood flow via increased myocardial oxygen demand[14]. However, these methods are not commonly used and therefore the Coronary Vasomotion Disorders International Study Group created a consensus statement summarizing recommended invasive and noninvasive methods for detecting endothelial-dependent and endoethelial-independent MVD [18]. Many of these noninvasive methods will be discussed within this review. The most common noninvasive method to assess MVD is to administer a vasodilating compound such as intravenous (IV) adenosine to cause maximal hyperemia. It should be noted that this is not a specific test of endothelial function, as adenosine is not an endothelial-mediated vasodilating compound. However, there may be some indirect endothelial activation via shear stress from an increase in the rate-pressure product by the systemic effects of IV adenosine when comparing to intracoronary administration of adenosine[19]. MVD is a broad based term; in the absence of obstructive coronary disease, it includes any pathology that may disrupt the microvasculature, including endothelial dysfunction, coronary spasm, inflammation and atherosclerosis [20]. Changes in arteriolar diameter or microvascular rarefaction with diffuse fibrosis, such as in HFpEF, has been associated with MVD[21, 22]. A reduction in the ratio between maximal hyperemic coronary flow and baseline coronary flow indicates a reduced coronary flow reserve (CFR). CFR can vary based on sex, age, and the modality used for measurement [23,24]. Importantly, CFR is a composite measure of epicardial stenosis severity and microvascular dysfunction; however in the setting of normal epicardial coronaries, an abnormal CFR represents MVD [12,25]. The value that represents an abnormal CFR has differed between studies with values ranging from 1.5 to 2.5 have been used in prognostic studies [20,26,27].

Traditionally, the term CFR has referred to the invasive measurement of flow reserve, while noninvasive measuring methods, as will be discussed in this review, refer to CFR as myocardial perfusion reserve (MPR). This distinction occurs as the measurement is made through changes in myocardial perfusion rather than direct measurement at the level of the coronaries. There are other potentially important imaging parameters also being studied such as microcirculatory blood volume or microvascular blood volume and intramyocardial blood volume[28,29,30]. It has been shown that changes in these parameters or reduction in these parameters can be associated with coronary MVD[31].

Quantifying MBF: Arterial Input Function and Compartmental Kinetics

Quantifying MPR with techniques such as PET, first-pass perfusion CMR, and CT perfusion require models that describe the kinetics of the contrast agent as a function of time. The concentration-time curves at rest and with vasodilation can vary due to variables such as contrast bolus timing, contrast injection speed, and cardiac output. These parameters must be accounted for to avoid significant variability in the absolute quantification of MBF. The arterial input function (AIF) is a time-dependent radiotracer or contrast concentration input into the tissue of interest that accounts for variables related to the injection of the contrast or radiotracer that can effect MBF quantification [32]. For absolute quantification of MBF, the AIF can be measured in the left ventricular (LV) cavity or in the left atrium (Figure 2). With kinetic modeling, the concentration of tracer or contrast in the myocardium, also known as the tissue function (TF) is obtained using the AIF and an established kinetic compartmental model to allow fitting of concentration-time curves [33,34].

Figure 2: Time Intensity Curves.

Schematic of time intensity curves for the arterial input function (AIF) and the tissue function (TF) in a normal coronary segment and an abnormal coronary segment (a). CMR obtained stress AIF and TF signal intensity curves (b). PET stress/rest perfusion imaging with resulting AIF and myocardial time intensity curves (c).

(Permission obtained and adapted from Patel, AR et al. Assessment of advanced coronary artery disease: advantages of quantitative cardiac magnetic resonance perfusion analysis. J Am Coll Cardiol. 2010; 56(7):561–9.)

Along with the AIF, compartmental modeling, which mathematically describes the kinetics of a contrast agent or radiotracer in a biological tissue of interest, is commonly used to accurately quantify MBF. With radiotracers, different tracers demonstrate different behaviors and each tracer is associated with a particular compartmental model [35]. For example, a two compartmental model (blood and tissue compartments) is typically used for the radiotracers ²⁰¹Thallium and ¹³N-Ammonia. Therefore, variability in radiotracer kinetics, along with other specified characteristics to be discussed later, are important to obtain an accurate MPR. Similar methods of compartmental modeling and contrast kinetics are applicable in cardiac magnetic resonance imaging (CMR) derived MPR.

Additionally, blood flow can be derived through several methods without the use of compartmental modeling. Zieler’s central volume principle has been used in CMR as a non-compartmental based method for MBF quantification [36]. It enables quantification of MBF using a simple deconvolution operation using assumptions made from myocardial tracer residue curves and AIF[37]. In addition, other methods that do not require compartmental modeling (discussed below) include the use of freely diffusible tracers such as water in the case of arterial spin labeling (ASL) for CMR and the use of intravascular microbubbles in contrast echocardiography[38,39].

Multimodality Noninvasive Assessment of MVD

Echocardiography

In 1998, Wei et al demonstrated a novel method to quantify both MBF using contrast echocardiography (CE) with the use of a constant venous infusion of air-filled albumin microbubbles [38]. The ability to quantify perfusion was based on two characteristics of the microbubble contrast agent. The “new” generation of microbubbles contained a higher molecular weight gas and thus was non-diffusible and less soluble, allowing for myocardial opacification [40,41]. Secondly, the microbubbles could be destroyed with ultrasound[42]. These properties allowed calculation of MBF by obtaining the mean velocity of myocardial microbubbles and the microvascular cross sectional area. The mean velocity was obtained by measuring the rate of reappearance of microbubbles after destruction with ultrasound in the setting of a constant microbubble venous infusion. The cross sectional area was obtained by measuring the microbubble concentration in the myocardium and is essentially a CE measurement of the myocardial blood volume (MBV) [38]. This method was validated against positron emission tomography (PET) with a correlation coefficient of 0.88 when measuring MBF in healthy volunteers [43].

Potential benefits of the CE approach include that it is a low risk bedside procedure, relatively inexpensive, and has limited adverse effects. The potential adverse effects from contrast microbubbles are minimal, and there is no radiation exposure as compared to PET [44]. However a number of limitations have prevented its widespread use. Echocardiography is operator-dependent and demonstrates considerable intra-observer and inter-observer variability [45]. Echocardiography can be hindered by artifacts, particularly in the setting of obesity and lung disease. Another technical issue is movement of the imaging frame during replenishment of microbubbles, which can lead to difficulty with post-processing. The use of microbubbles for myocardial perfusion assessment is currently not reimbursed in the United States, further hampering its clinical adoption. Finally, these modalities have had success in the evaluation of obstructive disease or post-PCI microvascular assessment, but in the setting of normal coronaries and anginal symptoms they have not shown widespread clinical utility [46,47].

Another echocardiographic method of MBF assessment uses transthoracic Doppler echocardiography (TTDE) to calculate the coronary flow velocity reserve (CFVR) [48,49]. CFVR is obtained by the ratio of coronary flow velocity at stress and rest obtained by the use of pulse wave Doppler sampling of the proximal left anterior descending artery (Figure 3a). This method correlates well with flow acquired from an intracoronary Doppler wire [48,50]. In addition, abnormal CFVR is associated with adverse cardiovascular events [27,51]. However, TTDE CFVR measurement was poorly correlated (r=0.3) with MPR calculated by PET in an evaluation of women with angina and no obstructive coronary artery disease (CAD) [52]. In the prospective multicenter international PROMIS-HFpEF study, TTDE identified a high prevalence of MVD in patients with heart failure with preserved ejection fraction [53].

Figure 3: Echocardiography derived coronary flow volume reserve and computed tomography of derived coronary luminal volume to myocardial mass.

Using transthoracic doppler echocardiography to obtain mean diastolic velocities at rest and stress allows for the derivation of coronary flow volume reserve (a). Computational modeling allows for calculation of luminal volume to myocardial mass (V/M) ratio (b). Example of V/M ratio and fractional flow reserve in 2 patients with non-obstructive CAD (c). The patient with the reduced FFR has a corresponding reduced V/M ratio. CFVR-coronary flow volume reserve, V-luminal volume, M-myocardial mass, FFR-fractional flow reserve.

(Permission obtained from Kakuta, K et al. Comparison of Coronary Flow Velocity Reserve Measurement by Transthoracic Doppler Echocardiography With 320-Row Multidetector Computed Tomographic Coronary Angiography in the Detection of In-Stent Restenosis in the Three Major Coronary Arteries. Am J Cardiol. 2012;110(1):13–20. and Taylor CA, et al. Effect of the ratio of coronary arterial lumen volume to left ventricle myocardial mass derived from coronary CT angiography on fractional flow reserve. J Cardiovasc Comput Tomogr. 2017; 11(6):429–436.)

Computed Tomography

Computed tomography angiography (CTA) in combination with CT perfusion (CTP) has the potential to be a robust modality for the assessment of microvascular disease. Both coronary anatomical and myocardial perfusion information can be obtained in the same study [54]. There are two primary techniques utilized in CT perfusion (CTP) imaging: static CTP and dynamic CTP. Static CTP only requires a single image at peak myocardial contrast opacification, which is then compared to a single rest image, thus lowering the amount of radiation. However, only semi-quantitative or qualitative perfusion assessment can be performed with this technique. Therefore, dynamic CTP involves obtaining several sequential images over time from first pass to wash to allow for quantitative perfusion[55]. CTP imaging is performed using either retrospective or prospective ECG-triggered image acquisition for approximately 30 seconds after contrast injection both at rest and with vasodilator stress. These images are then analyzed using post-processing software to obtain AIFs and time attenuation curves for the quantification of MBF[56]. Even though this technology can potentially identify MVD, CTA does not have any significant advantages over other imaging modalities and is not currently used in regular clinical practice to assess MVD.

Further functional data regarding the hemodynamic effects of epicardial stenosis can be obtained without stress perfusion imaging through measurement of CTA-derived fractional flow reserve (FFR_CT). Using proprietary software, HeartFlow (Redwood City, CA) derives a 3-dimensional coronary model with advanced mathematics to simulate maximal hyperemia and quantify MBF and FFR_CT at a specified point in the coronary tree [57,58]. FFR_CT showed significantly better diagnostic sensitivity when compared to single photon-emission computed tomography (SPECT) in stable CAD [59]. The relationship between FFR_CT and MVD is not well defined. However, with the same computational mathematical modeling, HeartFlow can derive other potentially useful parameters for assessment of MVD. Interestingly, Nørgaard et al. showed that a low ratio of CTA-derived coronary luminal volume to myocardial mass (V/M) was an independent predictor of ischemia in non-obstructive coronary disease (Figure 3b and c)[60]. To expand on this concept, Grover et al. compared the V/M ratio of 30 patients with ESC guideline-defined microvascular angina [61] to 32 age-matched asymptomatic controls [62]. They showed that both the mean total coronary lumen volume and the mean myocardial mass were lower in the MVD cohort. The mean V/M ratio was also significantly lower in the MVD group (25.6 mm³/g ± 5.9 vs 30.0 mm³/g ± 6.5, p = 0.007) [62].

Although CTA can provide a comprehensive cardiac exam, it has limitations. Radiation exposure is high for a stress/rest perfusion CTA protocol, with similar effective radiation dose as a SPECT rest/stress protocol of 12.7mSv [63]. In addition, the risk of contrast-induced nephropathy restricts use of this technique in chronic kidney disease. There is data suggesting that iodinated contrast may cause vasodilation, leading to the overestimation of coronary blood flow [64,65].

Nuclear Imaging

Cardiac PET is the imaging modality most validated for the quantification of MBF and assessment of MVD [66]. There are several radiotracers used in PET imaging, each with unique characteristics. Ideally, a radiotracer would be freely diffusible with high first pass uptake, rapid clearance rate, insignificant roll off at elevated blood flows, and kinetics that are unaffected by extrinsic factors[44,67]. In addition, the radiotracer should be safe and without side effects and it should not affect flow hemodynamics. The most commonly used PET radiotracers are ¹³N-Ammonia, ⁸²Rubidium, and ¹⁵O-water. ¹⁵O-water is an excellent agent for MBF calculation due to its exceptional first pass uptake of nearly 100% and minimal roll off at higher flows[68,69]. However, due to its low counts and short half-life of 122 seconds, visual assessment of perfusion abnormalities with ¹⁵O-water is extremely limited and not approved for clinical use in perfusion imaging by the FDA[70]. ¹³N-Ammonia has a longer half-life of 2.8 minutes and is better for myocardial perfusion stress imaging. Additionally, it has high first pass uptake, relative low radiation exposure (2mSv), and high myocardial retention, but is limited by the roll off that occurs at high coronary blood flow [67,71]. Unfortunately, ⁸²Rubidium has a lower extraction fraction, more significant roll off at high flows and is associated with higher radiation, making ¹³N-Ammonia the more preferred agent for accurate MBF quantification particularly at high flows [71]. However, ⁸²Rubidium is more commonly used as it requires only an on-site generator as opposed to a cyclotron [71]. It also has been validated against ¹³N-Ammonia[72]. The assessment of MBF by PET is primarily performed by post-processing software that performs automated segmentation and AIF measurements during dynamic first pass scanning (Central Illustration A) [72]. Depending on the radiotracer used, the post processing software will perform the kinetic modeling on the dynamic data to compute the regional and global stress and rest MBF [66,73,74]. The intra-software reproducibility of MBF measurements is reasonable, ranging from 4% to 15%[74,75,76].

Central Illustration: Abnormal MPR in non-obstructive coronary artery disease.

PET quantification of MBF shows reduced MPR of 1.6 in this 48 year old female with non-obstructive CAD (a). Rest and stress CMR derived segmental quantification of myocardial blood flow with a global MPR of 2.1 in a 59 year old male with non-obstructive CAD. LAD-left anterior descending artery, LCX-left circumflex artery, RCA-right coronary artery, TOT-total, MC-motion corrected, Str-Stress, Rst-Rest (b).

Some prospective PET studies correlate microvascular dysfunction, defined as abnormal MPR, with adverse prognosis[77,78]. Using ⁸²Rubidium PET perfusion scanning, Ziadi et al. found incremental prognostic value of MPR over the more routinely used summed stress score (SSS)[78]. They found that the adverse event rate more than doubled with MPR<2 and normal SSS compared to MPR>2[78]. In addition, a minimal increase in troponin without overt obstructive CAD has also been correlated to PET derived abnormal flow reserves and is a poor prognostic indicator [79]. This data has been replicated by other studies showing MBF and MPR to be predictive of adverse outcomes; these parameters may be utilized for risk stratification depending on normal and abnormal stress perfusion[80,81]. PET-derived MPR and MBF have been particularly useful in analyzing different subsets of populations[82]. Abnormal flow reserve in patients without overt CAD was independently associated with diastolic dysfunction and increased risk of HFpEF hospitalizations [83]. There is evidence of abnormal PET-derived MBF in patients with metabolic syndrome and non-insulin-dependent diabetes[84,85]. These findings are particularly profound in women, indicating the potential of important gender-related differences in MVD[82]. Women, despite having less obstructive CAD when compared to men, are burdened by increased symptoms and similar or worse outcomes[86,87]. Also, as recently described, comprehensive quantitative perfusion analysis by PET that includes regional absolute stress flow, relative stress flow, coronary flow reserve, and quantitative subendocardial perfusion gradients can lead to better diagnostic certainty for microvascular dysfunction[88]. It should be noted that clinically used PET protocols are not capable of accurately quantifying vasodilator–induced subepicardial to subendocaridal perfusion gradients due to limitations in spatial resolution. Despite the vast amount of prognostic data in PET-derived blood flows, PET is not without its limitations which include radiation exposure and cost, depending on which radiotracer is utilized[72].

Single-photon emission computed tomography (SPECT) is the most common nuclear cardiovascular imaging modality, but has been limited to date in quantification of myocardial blood flow due to poor camera sensitivity and temporal resolution with the more common Sodium-Iodide (NaI) cameras[44]. However, new cadmium-zinc-telluride detectors have better sensitivity and resolution that will allow for dynamic SPECT imaging and thus quantification of MBF. Early studies show encouraging flow estimates; however, larger multicenter trials are needed to improve the technical aspects of SPECT processing and to compare it to more traditional imaging methods for flow reserve quantification[89,90].

Cardiac MRI

The utility of MBF and MPR quantification by CMR imaging has been demonstrated in several studies with regards to both epicardial stenosis and microvascular angina[91–95]. Similar to PET, CMR stress first-pass perfusion is performed typically with adenosine infusion or following regadenoson bolus injection. Due to the non-linear signal response of CMR perfusion imaging as a function of gadolinium concentration, care must be taken to measure the AIF accurately using either a dual-contrast or dual-bolus approach, and the signal intensity needs to be converted into gadolinium concentration units before modeling. However, development of perfusion mapping techniques may make the conversion of signal intensity curves to gadolinium concentration units unecessary[96]. A number of approaches have been used to determine MBF including Fermi-function deconvolution, compartmental modeling, and distributed parameter models (Central Illustration B) [97].

Initial canine and porcine models assessing CMR-derived MBF showed excellent correlation (r>0.9) with gold standard microsphere analysis[98,99]. Since then, a number of human studies have been performed. In stable CAD, there was good agreement in global MBF measurements between CMR and ¹³N-Ammonia PET with r=0.92[100]. However correlation worsened when comparing regional MBF [101]. When comparing patients with chest pain and risk factors for MVD to normal patients, a significant reduction in stress MBF and global MPR was noted in the MVD group[102]. Liu et al showed reductions in stress MBF and global MPR in patients with non-obstructive CAD, specifically shown in the group with an elevated IMR[102]. IMR is an invasive thermodilutional method to assess for microvascular obstruction and has been shown to effect prognosis after an acute coronary occlusion, and is being used as a measure of MVD in non-obstructive CAD [6,103]. CMR-derived myocardial perfusion reserve index (MPRi) detected MVD defined by invasive coronary reactivity testing with sensitivity and specificity of 73–74% in symptomatic women without CAD [104]. In a similar cohort, impaired MPRi correlated with elevation in native T1 suggesting a possible connection between microvascular disease and diffuse fibrosis [105].

Previously, one of the major limitations of CMR-derived MBF was the amount of time required for post processing due to the lack of automated pipelines. Recently there have been a number of studies assessing automated perfusion mapping. Use of automated inline perfusion mapping showed excellent intrastudy and interstudy repeatability when compared to PET quantitation of myocardial blood flow[106]. Kotecha et al. successfully used automated pixel-wise perfusion mapping to diffentiate MVD from multivessel CAD[107].Hsu et al. recently showed that automated MBF measurements made at the time of first pass perfusion imaging reveal similar results to other studies with regard to reductions in stress MBF and global MPR[96].

There are limitations to CMR-derived MVD assessment, including imaging artifacts, exam length, and lack of widespread availability of quantitative first-pass sequences [44]. In addition, gadolinium has restricted use in class 4 and 5 chronic kidney disease and there is a reduction in the extraction of gadolinium with increasing flow rates, altering the quantification of MBF [44]. However, a recent study revealed promising results with stress T1 parametric mapping as a non-contrast method to identify patients with MVD[107]. In addition, ASL is a non-contrast MRI sequence that imparts a magnetic tag on the freely diffusible water protons of arterial blood that differ from the magnetization of surrounding tissue, thus allowing measurement of the “tagged” flow[108]. Currently ASL is in the technological developmental stage as a non-contrast method for myocardial blood flow quantification[39,108,109].Despite its limitations, one clear advantage with CMR is the lack of radiation exposure. In addition, ongoing advancements in technology will shorten the exam, improve patient tolerability, and likely reduce costs. More studies are needed to show the prognostic benefit and clinical utility of CMR assessment of MVD.

Future Directions

The ultimate goal of identifying coronary microvascular dysfunction is to define prognostic differences, therapeutic interventions, and treatment approaches. Currently, studies that address treatment and interventions are limited by variability in defining MVD and small sample size. There are no studies that define any prognostic benefits from the treatment of MVD [110]. As described earlier, there is a worse prognosis for symptomatic MVD, and therefore, many practioners are using interventions similar to the treatment of non-obstructive single-vessel CAD. This includes lifestyle changes by encouraging diet, exercise, and smoking cessation[111]. In addition, treatment of modifiable risk factors such as hyperlipidemia, hypertension, and diabetes is also pursued.

There is one clinical randomized control trial (NCT#03417388) currently recruiting that will assess the prognostic and symptomatic benefit of intensive treatment with statin, ACEi/ARB, and aspirin versus usual care in women with suspected MVD. This is a proper initial step as a treatment approach, however MVD is more complex and mediated via multiple pathways. Now with noninvasive MPR quantification, accurately identifying patients with MVD should be less intensive; in addition, improvements in MPR can be correlated with symptoms to determine success of a particular treatment. Further studies are needed assessing the targeted treatment of MVD in other pathologies such as HFpEF, which has no clear prognostically beneficial treatments.

Conclusions

A number of imaging methods are presently available to measure MBF in the setting of MVD. MBF assessment in obstructive CAD has demonstrated prognostic and clinical benefit [82]. Recently, more studies have been performed using MBF measures to diagnose symptomatic MVD. Many of the modalities have been validated in the quantification of MBF, an important first step. Quantifiable endpoints will help with future clinical studies. Recent studies have shown success in correlating abnormal MPR to symptoms in non-obstructive CAD. PET imaging has the most clinical and prognostic data compared to the other modalities, but CMR-derived MBF measures are being increasingly used to assess clinical utility and response to treatment. A few algorithms have been proposed in the clinical evaluation of microvascular angina and diagnosis of MVD with the use of PET as the diagnostic imaging modality for the evaluation of perfusion abnormalities and MBF quantification [70,112]. CMR measures of MBF remain in the research realm and are not yet fully vetted for clinical use. Clinically, the type of imaging modality used is dependent on local availability of the technology, as well as risk/benefit analysis and cost to the patient. Additional studies are currently examining integrative imaging approaches and regional versus global MPR assessments; this approach shows promise for improving measurement precision [88]. Even though our understanding of mechanisms and therapy of MVD is significantly less than that for obstructive epicardial disease, advances in cardiac imaging will soon allow improved identification of this disease, ultimately leading to improved therapeutic approaches.

Table 1:

The various cardiac imaging modalities and their advantages and disadvantages

Modality	Technique	Advantages	Disadvantages
Contrast Echocardiography	Constant infusion of echo contrast microbubbles until the cavity is filled, followed by ultrasound destruction of microbubbles.	• Bedside procedure • Minimal risk • No radiation • Relatively inexpensive	• Microbubble use not FDA approved for perfusion (no reimbursement) • Operator dependent • Poor images related to obesity or the presence of lung disease • Very few validation studies for MVD
Transthoracic Doppler echocardiography	Pulsed wave Doppler performed on the proximal left anterior descending artery	• Bedside procedure • Minimal risk • No radiation • Relatively inexpensive • Correlated well with intracoronary Doppler wire	• Operator dependent • Difficult imaging due to obesity or the presence of lung disease • Poor correlation with PET • Very limited data with use in non-obstructive CAD
Computed tomography	Dynamic first pass vasodilator stress and then rest perfusion imaging.	• Anatomical coronary data and perfusion data with the same study	• Perfusion quantification only allowed in high radiation dynamic perfusion imaging • Radiation exposure • Risk of contrast induced nephropathy and contrast allergic reactions • Limited in renal failure • Limited validation in non-obstructive CAD • Limited availability • Iodinated contrast can cause vasodilation leading to overestimation of MBF
Positron emission tomography	Dynamic first pass vasodilator stress and then rest perfusion images.	• Most validated modality for MBF quantification in non-obstructive CAD • Extensive prognostic data • Segmented myocardial blood flow • Relatively low radiation exposure due to radiotracers with short life • Not effected by renal dysfunction • Good reproducibility and accuracy • CT can allow for some anatomic assessment of coronaries	• Radiation exposure • Expensive • Technology is not widely available
SPECT	Dynamic first pass vasodilator stress and then rest perfusion images.	• More widely available than PET and CMR	• Requires new generation cameras • Minimal validation in non-obstructive CAD • Radiation exposure is high
Cardiac Magnetic Resonance Imaging	Dynamic first pass vasodilator stress and then rest perfusion images.	• No radiation exposure • Excellent spatial resolution • Allows for tissue characterization with the same study • Validated against invasive measurements and PET	• Expensive • Technology is not widely available • Very minimal prognostic data • Difficult for patients due to frequent breatholds and length of time of the exam • Limited in renal failure

Table 2:

Suggested future studies for symptomatic MVD without obstructive CAD

• Comparison of all noninvasive methods of MBF quantification to screen for patients with symptomatic MVD in the absence of CAD

• Comparison of CMR versus PET in MVD screening using invasive methods as a gold standard

• Randomized controlled trials assessing the prognostic and symptomatic impact of various pharmacological treatment strategies on symptomatic MVD defined by reduced MPR

• Randomized controlled trials assessing the impact of lifestyle changes including diet, exercise, and smoking cessation on symptomatic MVD defined by reduced MPR

• Assess if specific therapeutic interventions improve quantifiable MPR and determine if any correlation exists with improvement in symptoms, prognosis, or quality of life

• Examine improvements in microcirculation relative to prognosis and symptoms in HFpEF

Highlights.

• In this review we discuss, the nuances of myocardial blood flow and myocardial perfusion reserve quantification in echocardiography, cardiac computed tomography, nuclear imaging, and cardiac magnetic resonance imaging.

• Each modality, with its own advantages and disadvantages, has played a role in the detection of MVD.

• Positron emission tomography derived myocardial blood flow presents the most prognostic data to date related to the impact of MVD.

• Research into MBF quantification by cardiac magnetic resonance imaging is growing as the imaging modality becomes increasingly more accessible.

Abbreviations list

FFR

fractional flow reserve

CFR

coronary flow reserve

IMR

index of microvascular resistance

MVD

microvascular dysfunction

MBF

myocardial blood flow

ASL

arterial spin labeling

MBV

myocardial blood volume

CFVR

coronary flow volume reserve

CTP

computed tomography perfusion

FFR_ct

Computed tomography angiography derived fractional flow reserve

SPECT

single photon emission computed tomography

V/M

luminal volume to myocardial mass ratio