LAUSR

Assessment of myocardial perfusion under stress and rest conditions using various imaging modalities is the mainstay in the workup of coronary artery disease. Traditionally, the presence of relative regional perfusion defects has been the central concept behind myocardial perfusion imaging. Regional perfusion analysis is imperfect due to its relative nature, because the presence, severity, and extent of perfusion defects do not account for possible differences in absolute myocardial blood flow (MBF) at rest or stress. For example, if absolute flow is impaired globally (e.g., triple vessel disease), a comparison of the best and worst perfused regions will underestimate the severity of flow-limiting disease. Hence, information about absolute MBF and myocardial flow reserve (MFR) is desirable. Single-photon emission computerized tomography-myocardial perfusion imaging (SPECT-MPI) has traditionally been the workhorse for relative perfusion imaging, but several studies have shown that relative perfusion imaging may underestimate extent of disease. Furthermore, the Tc flow tracers available for SPECT-MPI are limited by a relatively low first-pass extraction fraction at high flow rates, thus limiting the precision and accuracy of these tracers for estimation of myocardial perfusion especially during stress. With the advent and increasing availability of cardiac positron emission tomography (PET), quantification of absolute MBF and MFR has been shown to be accurate and simplified. Several studies have also shown that these measures are of diagnostic and prognostic significance beyond relative perfusion imaging. These data have resulted in a paradigm change whereby incorporation of absoluteMBFandMFRmeasures to the relative perfusion data helps better phenotyping of flow abnormalities in patients leading to improved risk stratification. Although very appealing in concept the measurement of the myocardial blood flow involves several different steps all of which can potentially lead to variability in MBF and MFR measurements apart from true variability. Figure 1 highlights the potential sources of variability in measurement of MBF.