Anatomy and Physiology

The combination of computed tomography coronary angiography (CTCA) and computed tomography (CT) myocardial perfusion imaging offers the cardiology community a comprehensive tool for the assessment of coronary artery anatomy and physiology. CTCA performs well in ruling out atherosclerotic coronary artery disease as well as differentiating between nonobstructive and potentially obstructive disease. CTCA findings may be used to withdraw physiological testing in patients with normal or nonobstructed coronary vessels. Clinicians may utilize CT perfusion imaging (similarly to established tests like myocardial perfusion scintigraphy, positron emission tomography [PET], stress echocardiography, magnetic resonance imaging [MRI], and more recently CT-derived fractional flow reserve [FFR]) in patients with coronary artery stenoses of indeterminate functional significance, with heavy vessel calcifications preventing reliable evaluation of the vessel lumen, or generally in patients at high risk of obstructive disease. In these settings, the main goal is to identify patients who would benefit from revascularization in addition to medical treatment. The ability to deliver the anatomical and functional aspects of the test in the same session (if required) using the same scanning equipment without the need of a hybrid imaging suite is seen as appealing by some.

In dynamic CT perfusion, myocardial enhancement is sampled over time during the first pass of contrast agent, as opposed to static CT perfusion, where a single dataset is acquired during peak enhancement and analysis is qualitative. Multiple sequential images are obtained at baseline, during contrast arrival, at peak enhancement, and during contrast washout. X-ray attenuation changes in aorta and myocardial tissue are used to construct an arterial input function and tissue time-attenuation curves, respectively. The application of mathematical modelling allows for the estimation of parameters related to myocardial blood flow (MBF), blood volume, perfused capillary blood volume, and flow-extraction product.

A number of observational patient studies showed that CT estimates of blood flow during pharmacological stress had good discriminatory ability to identify functionally significant coronary artery disease, defined according to various reference standards (Table 1).^1-21 Blood flow was lower in territories subtended by atherosclerotic vessels compared with territories supplied by unobstructed vessels. Some studies showed increased estimates of flow from resting to pharmacological stress conditions, lending further support to the biological plausibility of this method.^13,16,19 A recent trial by Lubbers et al.²² in patients with stable angina showed that CTCA and CT perfusion were more efficient in identifying patients requiring revascularization than a diagnostic approach starting with first-line exercise electrocardiography (ECG). This trial, however, used visual adjudication of perfusion defects without reporting MBF. Despite promising results, quantitative CT perfusion still presents some implementation challenges that may have slowed down broad uptake in clinical practice.

Table 1: Studies Evaluating Dynamic CT Perfusion Imaging in Patients With Suspected Coronary Artery Disease

Technical Aspects, Radiation, and Contrast Exposure

A key technical aspect of dynamic perfusion is temporal sampling. This is not the scanner's in-plane temporal resolution, which relates to the gantry rotation time. In-plane temporal resolution of third-generation dual-source CT is approximately 66 ms. In the axial shuttle mode perfusion protocol, however, the scanner's bed needs to shuttle between two positions to acquire end-systolic images, resulting in a time interval between scans of 1 every 2 heartbeats or, for faster heart rates, 1 every 3 heartbeats.^23,24 The frames of the dynamic datasets are typically 1-3 seconds apart to permit the construction and fit of time-attenuation curves while limiting patient radiation exposure. Temporal sampling rate influences the shape of the arterial input function and tissue curves.²⁵ Increasing the number of measurements will make the curves more accurate but at a radiation exposure cost for the patient.

With single-source, wide-detector CT, the in-plane temporal resolution is worse (typically about double) than in dual-source CT, but the coverage along the z-axis is wider; thus, the bed does not move between positions to acquire the heart volume, providing an opportunity to image at every heartbeat.⁸ This also comes at a radiation exposure cost because exposure is proportional to the number of heart frames acquired.

Radiation exposure is also affected by total acquisition time. A typical acquisition time of 15-30 seconds is necessary to capture the arrival and clearance (first pass) of the injected contrast volume.

With the introduction of low kilovoltage techniques, dynamic CT perfusion imaging can be routinely performed with an effective dose of 10 mSv or less (conversion factor k = 0.26). If CTCA is also performed, the exposure will be additional, increasing the total received by the patient.

CT perfusion imaging requires an injection of contrast. A compact bolus accurately defines arterial and tissue peak enhancement for modelling. In patients with impaired kidney function, a double contrast injection may be of concern. CT-derived FFR, which does not require additional scanning, may replace the need of perfusion imaging in a number of situations. It makes sense to consider the implementation of these technologies side by side when addressing the clinical management questions that may arise post-CTCA.

Contrast Kinetic Modelling

It is accepted that the quantitative estimation of a patient's MBF can be useful, at least in selected clinical circumstances. The analysis of regional myocardial perfusion in qualitative or relative terms assumes that the myocardium with the highest uptake is supplied by normal coronary vessels. This assumption does not always hold. Quantification of blood flow may benefit patients with balanced or near-balanced ischaemia from multivessel disease. In these situations, perfusion changes of various extent and severity may be not be visually appreciated with relative perfusion assessment.^15,26

MBF values from CT were often lower than the known physiological range. This was noted more markedly at high flow values during stress, affecting normal myocardium (high flow) more than hypoperfused myocardium.²⁷ For instance, Rossi et al.²¹ found a median subendocardial blood flow of 92 ml/100ml/min downstream to obstructed coronary vessels (defined by stenosis >80% diameter reduction on quantitative coronary angiography or invasive FFR <0.8) and a median flow of 161 ml/100ml/min downstream to unobstructed vessels. The optimal positivity threshold was 106 ml/ml/min. These figures express blood flow per unit of volume of myocardial tissue, but it is possible to derive blood flow per unit of weight of myocardial tissue by multiplying the volume by the density of myocardial tissue (1.05 g/ml) in order to facilitate a comparison with other imaging modalities.²⁸ For CT, this conversion yields a subendocardial blood flow of 97 ml/100g/min downstream to obstructed coronary vessels, a flow of 169 ml/100g/min downstream to unobstructed vessels, and a positivity threshold of 111 ml/100g/min. Earlier studies with ¹⁵O-water PET^29,30 identified normal hyperaemic blood flow in the range 200-500 ml/100g/min, and the threshold to separate perfusion defects from normal myocardium was 200-250 ml/100g/min, highlighting a discrepancy.

¹⁵O-water is the most ideal MBF PET-tracer, freely diffusible and metabolically inert. ¹⁵O-water and ¹⁸F-flurpiridaz result in the highest extraction fraction. Theoretically, tissue perfusion could be estimated from these radiotracers' uptake without the need of applying mathematical modelling because the relationships between PET signal and radiotracer concentration and between radiotracer uptake and perfusion are both linear. Although the first condition holds for all PET tracers as well as iodinated contrast agent, the second does not. Iodinated contrast not only flows in the intravascular (capillary) space but also enters the extravascular extracellular (interstitial) space. The flow-extraction product is not constant across the physiologic range of flow. Most tracers such as ¹³N-ammonia, ⁸²Rb-rubidium, gadolinium, and iodinated contrast have nonlinear, decreasing extraction fraction with increasing blood flow.²⁴ In high-flow conditions (hyperaemic stress, normal myocardium), it is the intravascular flow component that increases the most. In these conditions, intravascular flow has very short transit time (2 seconds or less), which explains why limitations in temporal sampling are particularly detrimental for the estimation of high flows.²⁷

Contrast kinetic modelling is used to reflect this, although modelling cannot remove the constraints of sampling rate and contrast injection setup in clinical practice, balancing such demands with requirements for spatial resolution, coverage, and radiation-exposure reduction. The modelling method for dual-source CT, based on two-compartment, hybrid deconvolution and maximum slope methods, was designed for the 2-3 second sampling rates typical of the axial shuttle mode.²³ This method models the flow-extraction product to yield volume and rate parameters as results but, due to sampling rate limitations, does not include the intravascular mean transit time. Although MBF values appeared underestimated compared with the range previously reported with PET, this method allowed the quantitative identification of significant flow compromise in available validation studies (Table 1).²⁷

Physiological Variability

The available studies used various clinical tests, applying them as standard of reference against dynamic CT perfusion. Some studies used stenosis severity from invasive coronary angiography, some FFR, some a combination of the two, some visual analysis of myocardial perfusion scintigraphy or MRI. Often, these reference standards reflected pathophysiological phenomena not identical to myocardial perfusion. Coronary stenosis severity is weakly associated to its functional significance. FFR reflects the impact of coronary lesions on coronary flow and not necessarily their effect on microcirculation and perfusion. FFR is clinically interpreted as a binary test. MBF is a continuous variable. It is possible that these reference standards, with their clinically driven positivity criteria, biased the diagnostic interpretation of the range of MBF reported to date.

Also, the analysis of CT data was operator-dependent and generally not tested for reproducibility. Quality control was not standardized. Some authors³ sampled blood flow from manually drawn regions of interest positioned on axial images of the chest. In other studies,^{1,2,5,8,10,15} image data were resliced to short- and long-axis views of the left ventricle. Other studies^12,21 used polar-map or bull's eye representations. Individual studies derived blood flow positivity thresholds within their own populations. These are yet to be externally validated for generalizability.

Implementation

Despite these limitations, quantitative perfusion CT is promising. An important step prior to implementation at scale would be to gain insight into the expected physiological range and variability of blood flow across strata of the population, such as men and women of different age, different cardiovascular risk profiles, and co-morbidities, because these may affect MBF. Ongoing efforts toward dose reduction, quality standardization, analysis approaches, and definition of generalizable normative values will increase its clinical use. Multi-centre studies are evaluating its performance in larger population settings.

In a broader landscape, anatomical imaging with CTCA has gained wider acceptance while CT-derived FFR has emerged as a powerful post-processing tool for CTCA that does not require additional scanning. Functional imaging, albeit already established, is under investigation for higher hierarchies of evidence. ISCHEMIA (International Study of Comparative Health Effectiveness With Medical and Invasive Approaches)³¹ is testing the hypothesis that there may be a level of extent/severity of perfusion abnormality above which management with revascularisation has implications in preventing myocardial infarction and death.³² In this landscape, in selected clinical circumstances, the need for a practical tool to quantify MBF may increase in the near future.

Figure 1: A 64-Year-Old Male Patient With Typical Chest Pain

References

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Keywords: Diagnostic Imaging, Cardiac Imaging Techniques, Coronary Artery Disease, Angina, Stable, Echocardiography, Stress, Cardiac Volume, Coronary Angiography, Myocardial Perfusion Imaging, Heart Rate, X-Rays, Coronary Stenosis, Positron-Emission Tomography, Magnetic Resonance Angiography, Perfusion Imaging, Multimodal Imaging, Electrocardiography, Tomography, X-Ray Computed, Aorta, Blood Volume, Fractional Flow Reserve, Myocardial, Microcirculation, Heart Ventricles, Constriction, Pathologic, Risk Factors, Myocardial Ischemia, Myocardium, Myocardial Infarction

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