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> Continuous improvement is better than delayed perfection. > > —Mark TwainThe evaluation of patients with suspected but not yet confirmed of coronary artery disease (CAD) has become increasingly complex in the past decade.1 Multiple noninvasive modalities are now available with individual strengths and weaknesses. Decision making on noninvasive testing when evaluating stable chest pain is further complicated by the observed sex disparity in the clinical presentation, risk factors, and varied role of microvascular dysfunction.2See Article by Penagaluri et al Coronary computed tomographic angiography (CCTA) is an excellent tool in the exclusion of CAD with unparalleled diagnostic performance3–5 and provide valuable prognostic information.6,7 However the utility of CCTA continues to have 2 important limitations: (1) low specificity in the presence of CAD and (2) lack of lesion-specific physiological assessment. More recently, the introduction of myocardial CT perfusion imaging (CTP) has been shown to augment the information provided by CCTA alone by providing a physiological measure of the significance of a coronary artery stenosis. In the multicentered CORE320 trial (Computed Tomography Angiography and Perfusion to Assess Coronary Artery Stenosis Causing Perfusion Defects by Single Photon Emission Computed Tomography), a combined CCTA-CTP strategy significantly improved the specificity of CCTA alone from 54% to 73%, using invasive coronary angiography and single photon emission CT as the reference standard.8In this issue of Circulation: Cardiovascular Imaging , Penagaluri et al9 performed an important subanalysis of the CORE320 trial evaluating the diagnostic performance of CCTA-CTP strategy stratified by sex. Interestingly, CTP provided a significant improvement in the discrimination of ischemia in women but not in men (AUC, 0.92 for …

circulation. cardiovascular imaging

Developing a Deeper Understanding of Sex Differences in the Diagnostic Performance of Computed Tomographic Perfusion Imaging Toward a More Personalized Approach