Quantitative Assessment of Coronary Microvascular Function: Dynamic Single-Photon Emission Computed Tomography, Positron Emission Tomography, Ultrasound, Computed Tomography, and Magnetic Resonance Imaging

Abstract

A healthy, functional microcirculation in combination with nonobstructed epicardial coronary arteries is the prerequisite of normal myocardial perfusion. Quantitative assessment in myocardial perfusion and determination of absolute myocardial blood flow can be achieved noninvasively using dynamic imaging with multiple imaging modalities. Extensive evidence supports the clinical value of noninvasively assessing indices of coronary flow for diagnosing coronary microvascular dysfunction; in certain diseases, the degree of coronary microvascular impairment carries important prognostic relevance. Although, currently positron emission tomography is the most commonly used tool for the quantification of myocardial blood flow, other modalities, including single-photon emission computed tomography, computed tomography, magnetic resonance imaging, and myocardial contrast echocardiography, have emerged as techniques with great promise for determination of coronary microvascular dysfunction. The following review will describe basic concepts of coronary and microvascular physiology, review available modalities for dynamic imaging for quantitative assessment of coronary perfusion and myocardial blood flow, and discuss their application in distinct forms of coronary microvascular dysfunction.

Keywords: coronary flow reserve; coronary microvascular function; microvascular dysfunction; myocardial blood flow; myocardial perfusion imaging.

Figure 1

Functional components of the coronary arterial system. 3D volume rendering of contrast microCT of porcine heart (top left), with maximum intensity projection of axial slice (top right), and ultra-high resolution microCT images (bottom right). The porcine heart was perfused with 5% bismuth containing casting medium. The functional components of the coronary vascular tree are defined based on segregation of vascular tree by vascular diameter. Under physiological conditions the majority of intramyocardial blood volume (IMBV) resides in arterioles and capillaries, whereas the most important contributors to coronary resistance are pre-arterioles and arterioles. Epicardial coronaries contribute to resistance and IMBV minimally.

Figure 2

Coronary autoregulation and determinants of coronary flow reserve (CFR). Over the autoregulation range (the plateau of the autoregulation curve) coronary flow remains relatively constant despite changes in coronary perfusion pressure. CFR is determined by maximum hyperemic blood flow (solid red line) divided by baseline flow (solid green line). Increasing metabolic demand and reduced oxygen/nutrient delivery result in compensatory rise in baseline coronary flow (dashed green line). Increased baseline flow leads to a reduced CFR presuming stable or reduced hyperemic flow. Reduction in hyperemic coronary flow (dashed red line) can be induced by reduced diastolic filling time or coronary microvascular disease, and will also result in a decreased CFR.

Figure 3

Relationship between myocardial blood flow and tracer uptake for common SPECT and PET radiotracers demonstrates a roll-off phenomenon at high flow rates, as uptake of some radiotracers becomes diffusion limited at higher flows. This results in reduced accuracy in the quantification of hyperemic coronary flow and CFR. Adapted from Salerno M. et al Circ Cardiovasc Imaging. 2009 Sep;2(5):412–24.

Figure 4

Schematic display of tissue compartment models used in quantitative analysis of dynamic PET imaging of selected PET radiotracers with unique properties. ¹⁵O water is a freely diffusible agent, as the blood concentration (CB(t)) is determined by an independent model, the 1 tissue compartment model is used (left panel). ¹³N ammonia readily diffuses across cell membranes, gets metabolically trapped in the myocardium (compartment 2) with high retention rate (middle panel). Following injection and diffusion through capillary membranes,¹⁸F-Flurpiridaz gets trapped intracellularly in the mitochondria by irreversible binding to mitochondrial complex-1 (right panel).

Figure 5

Illustration of kinetic modeling of PET radiotracers. Shown are typical factors and corresponding factor images associated with ⁸²Rb (A) and ¹³N-ammonia (B) from dynamic PET studies in same subject. AU = arbitrary units; MYO = whole myocardium. This research was originally published in JNM. El Fakhri G, Kardan A, Sitek A, Dorbala S, Abi-Hatem N, Lahoud Y, Fischman A, Coughlan M, Yasuda T and Di Carli MF. Reproducibility and accuracy of quantitative myocardial blood flow assessment with (82)Rb PET: comparison with (13)N-ammonia PET. J Nucl Med. 2009;50:1062–71. © by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Figure 6

CT perfusion imaging of a patient who underwent dynamic contrast CT imaging for suspected coronary artery disease. No visual perfusion defect was detected. (a) and (b) are the color maps for myocardial blood flow and myocardial blood volume, respectively. Global left ventricular myocardial blood flow and volume were 157.7 mL/100 mL/min and 19.3 mL/100 mL, respectively. Adapted from Vliegenthart R, J Cardiovasc Comput Tomogr. 2016;10:301–8.

Figure 7

Quantitative MRI myocardial perfusion at rest and during adenosine in a 31 year old male patient with HOCM. Top panel demonstrates the signal intensity (SI) curves (in arbitrary units [a.u.]) during the first pass of a contrast agent bolus in the hypertrophied basal myocardial segment (marked as *). Bottom panel represents the SI curves in the blood pool used as the arterial input function. Adapted from Petersen SE, Circulation. 2007;115:2418–25.

Figure 8

Contrast echocardiography for assessment of flow and intramyocardial blood volume. Microbubbles are delivered as a constant infusion, and myocardial contrast echocardiography performed using different pulsing intervals. In Fig 8A the elevation (thickness) of the ultrasound beam is represented as E. If all the microbubbles in the elevation are destroyed by a single pulse of ultrasound at t₀, then replenishment of the beam elevation (d₁ through d₄), will depend on the velocity of microbubbles and the ultrasound pulse interval t. In Fig 8B the relationship between video intensity (y-axis) and pulsing interval (x-axis) are plotted. When the pulse interval exceeds T, the video intensity will remain constant. This plateau phase will reflect the effective microbubble concentration within the myocardial microcirculation. The myocardial video intensity versus pulsing interval plots are fitted to an exponential function: y = A(1 − e^−βt), where A is the plateau video intensity reflecting the microvascular cross-sectional area, and β reflects the rate of rise of video intensity and, hence, microbubble velocity. In acute pre-clinical validation studies, an excellent correlations were found between microsphere flow and β, as well as flow and the product of A and β. Fig 8C depicts a relationship between radiolabeled microsphere–derived myocardial blood flow (x axis) and A × β derived on MCE (y axis) in experimental animals following intracoronary delivery of a vasodilator. Fig 8D depicts the relation between the ratio of radiolabeled microsphere– derived myocardial blood flow from the stenotic and non-stenotic beds (x axis) and the A × β ratio derived on MCE from the stenotic and non-stenotic territory (y axis) in another group of animals with coronary stenoses. Adapted from Wei K, Circulation. 1998;97:473–483.

Figure 9

Annualized cardiac mortality among patients with diabetes mellitus (DM) or CAD. Adjusted cardiac mortality among patients with CAD (i.e., history of coronary revascularization or myocardial infarction) without DM (orange), DM patients without CAD who have impaired coronary flow reserve (CFR; red), DM patients without CAD who have preserved CFR (blue), and patients without DM or CAD with normal scans (no scar, ischemia, or left ventricular dysfunction; green) presented as survival curves (A) and annualized cardiac mortality rates (B). Data for patients with CAD and DM are also presented for comparison (purple). EF, ejection fraction; NI MPI, normal myocardial perfusion imaging; and CD, cardiac death. Adapted from Murthy VL, Circulation. 2012;126:1858–68.

Figure 10

Conceptual plot of the fractional flow reserve (FFR)–coronary flow velocity reserve (CFVR) relationship. Four main quadrants can be identified by applying the clinically applicable cut-off values for FFR and CFVR, indicated by the dotted lines. Patients in the upper right blue area are characterized by concordantly normal FFR and CFVR, and patients in the red lower left area are characterized by concordantly abnormal FFR and CFVR. Patients in the upper left orange area and lower right light green area are characterized by discordant results between FFR and CFVR, where the combination of an abnormal FFR and a normal CFVR indicates predominant focal epicardial, but nonflow-limiting, coronary artery disease, and the combination of a normal FFR and an abnormal CFVR indicates predominant microvascular involvement in coronary artery disease. The small dark green region in the lower right is characterized by an FFR near 1 and an abnormal CFVR, indicating sole involvement of the coronary microvasculature. The FFR gray zone indicates the equivocal 0.75 to 0.80 FFR range. Adapted from van de Hoef TP, Circ Cardiovasc Interv. 2014 Jun;7(3):301–11.

Figure 11

Expected changes in invasive and noninvasive coronary parameters in focal and diffuse atheroslerosis as well as in coronary microvascular disease (CMVD). In mild non-flow limiting stenosis, microvascular resistance (MVR) is uneffected, the luminal pressure drop is not sufficient to result in abnormal fractional flow reserve (FFR >0.8). Intramyocardial blood volume (IMBV) would be increased slightly secondary to compensatory vasodilation associated with autoregulation. Coronary flow remains normal under resting conditions, and mildly reduced with hyperemic stress. With progression of CAD to severe stenosis, FFR becomes reduced (<0.8) and there is marked increase in IMBV secondary to recruitment and vasodilatation. A severe reduction in baseline flow, hyperemic flow and CFR can be observed. Diffuse non-obstructive atherosclerotic disease is characterized by gradually decreasing intracoronary pressure across the lesion, mildly increased IMBV and normal resting and decreased hyperemic myocardial blood flow contributing to reduced CFR. CMVD on the other hand is associated with marked increase in coronary vascular resistance, maintained coronary perfusion pressure and marked reduction in IMBV. Hyperemic myocardial blood flow becomes comprimised leading to reduced CFR.