Comparative Definitions for Moderate-Severe Ischemia in Stress Nuclear, Echocardiography, and Magnetic Resonance Imaging

Abstract

The lack of standardized reporting of the magnitude of ischemia on noninvasive imaging contributes to variability in translating the severity of ischemia across stress imaging modalities. We identified the risk of coronary artery disease (CAD) death or myocardial infarction (MI) associated with ≥10% ischemic myocardium on stress nuclear imaging as the risk threshold for stress echocardiography and cardiac magnetic resonance. A narrative review revealed that ≥10% ischemic myocardium on stress nuclear imaging was associated with a median rate of CAD death or MI of 4.9%/year (interquartile range: 3.75% to 5.3%). For stress echocardiography, ≥3 newly dysfunctional segments portend a median rate of CAD death or MI of 4.5%/year (interquartile range: 3.8% to 5.9%). Although imprecisely delineated, moderate-severe ischemia on cardiac magnetic resonance may be indicated by ≥4 of 32 stress perfusion defects or ≥3 dobutamine-induced dysfunctional segments. Risk-based thresholds can define equivalent amounts of ischemia across the stress imaging modalities, which will help to translate a common understanding of patient risk on which to guide subsequent management decisions.

Stress Echocardiography Positivity Predicts Cancer Death

“…The clinical meaning of the prognostic stratification is based not only on statistical but also on biological plausibility 14. From the pathophysiological viewpoint, it is consistent with our current knowledge of ischemic heart disease that SE positivity mirrors the functional impact of underlying CAD, which is the strongest predictor of future cardiovascular events 15. With longer follow‐up times of expanding cohorts becoming available, now additional, more refined analyses also can be made.…”

Cardiac magnetic resonance imaging derived quantification of myocardial ischemia and scar improves risk stratification and patient management in stable coronary artery disease

“…Hence, the presented approach of quantification may underestimate the real extent of ischemia in comparison to nuclear perfusion techniques due to incomplete coverage of the left ventricle. With regard to this problem, Shaw et al [5] recently suggested an approach to overcome the difficulty of modality specific thresholds. They defined high risk CAD patients as those with a probability of having an adverse event being about 5% per year [5].…”

“…Consequently, a majority of available studies treat ischemia and necrosis as categorical variables without taking into account, extent or severity. It has been suggested that this additional information may serve as an important factor for correct risk stratification in CAD [5,21]. The objective of the present study was to elaborate a CMR algorithm for the quantification of ischemia and necrosis based on standard first-pass perfusion imaging and to establish it's implications on risk prediction improvement.…”

“…For these patients, current practice guidelines strongly support the use of stress imaging modalities for diagnosis and correct risk stratification prior to invasive coronary X-ray angiography [2][3][4]. There exists inconsistency across the different imaging modalities on how to assess and report the extent and severity of myocardial ischemia and necrosis [5]. This fact may explain the variability in management decisions and the high frequency of absent obstructive CAD on diagnostic coronary angiography [6].…”

Serial imaging and outcome prediction

“…4 Comparison of two sets of images performed at two different time intervals is inherently complicated by the fact that the changes in myocardial perfusion or MBF are not only the result of the specific intervention (for example statin therapy) but are also influenced by biological variability and by the precision and accuracy of the method used. 3,[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] Visual methods might be accurate but not reproducible, and automated methods might be reproducible but not precise. 20,21 A common practice is to compare patient data to a normal database, but alternative methods are available that compare the two sets of images to each other directly rather than comparing each to a normal database.…”