Abstract
BackgroundMachine-Learning Computed Tomography-Based Fractional Flow Reserve (CT-FFRML) is a novel tool for the assessment of hemodynamic relevance of coronary artery stenoses. We examined the diagnostic performance of CT-FFRML compared to stress perfusion cardiovascular magnetic resonance (CMR) and tested if there is an additional value of CT-FFRML over coronary computed tomography angiography (cCTA).MethodsOur retrospective analysis included 269 vessels in 141 patients (mean age 67 ± 9 years, 78% males) who underwent clinically indicated cCTA and subsequent stress perfusion CMR within a period of 2 months. CT-FFRML values were calculated from standard cCTA.ResultsCT-FFRML revealed no hemodynamic significance in 79% of the patients having ≥ 50% stenosis in cCTA. Chi2 values for the statistical relationship between CT-FFRML and stress perfusion CMR was significant (p < 0.0001). CT-FFRML and cCTA (≥ 70% stenosis) provided a per patient sensitivity of 88% (95%CI 64–99%) and 59% (95%CI 33–82%); specificity of 90% (95%CI 84–95%) and 85% (95%CI 78–91%); positive predictive value of 56% (95%CI 42–69%) and 36% (95%CI 24–50%); negative predictive value of 98% (95%CI 94–100%) and 94% (95%CI 90–96%); accuracy of 90% (95%CI 84–94%) and 82% (95%CI 75–88%) when compared to stress perfusion CMR. The accuracy of cCTA (≥ 50% stenosis) was 19% (95%CI 13–27%). The AUCs were 0.89 for CT-FFRML and 0.74 for cCTA (≥ 70% stenosis) and therefore significantly different (p < 0.05).ConclusionCT-FFRML compared to stress perfusion CMR as the reference standard shows high diagnostic power in the identification of patients with hemodynamically significant coronary artery stenosis. This could support the role of cCTA as gatekeeper for further downstream testing and may reduce the number of patients undergoing unnecessary invasive workup.
Highlights
Machine-Learning Computed Tomography-Based Fractional Flow Reserve (CT-FFRML) is a novel tool for the assessment of hemodynamic relevance of coronary artery stenoses
Stress perfusion cardiovascular magnetic resonance (CMR) was performed in 164 patients showing a coronary artery disease (CAD) with at least one stenosis of unclear hemodynamic significance.17 cases were excluded, because the interprocedural time of 2 months between coronary computed tomography angiography (cCTA) and CMR was exceeded
CT-FFRML was calculated in 269 vessels (64%) having stenosis with unclear hemodynamic relevance as prespecified in the study design (Fig. 1)
Summary
Machine-Learning Computed Tomography-Based Fractional Flow Reserve (CT-FFRML) is a novel tool for the assessment of hemodynamic relevance of coronary artery stenoses. We examined the diagnostic performance of CT-FFRML compared to stress perfusion cardiovascular magnetic resonance (CMR) and tested if there is an additional value of CT-FFRML over coronary computed tomography angiography (cCTA). Several studies including DEFER have recently challenged this perception by showing futility or even harm of PCI in patients with CAD without hemodynamically significant stenosis. [4] In the recent decade, coronary computed tomography angiography (cCTA) has established itself as a powerful tool for the noninvasive assessment of coronary stenosis, in patients with low-to-intermediate pretest probability. Stress perfusion cardiovascular magnetic resonance imaging (CMR) is an established functional non-invasive method to guide coronary revascularization. It enables the detection of myocardial ischemia based on the first-pass kinetics of gadolinium contrast agent after adenosin-induced vasodilatation. Despite its high diagnostic power reported in a number of studies, CMR has limitations that prevent it from becoming the standard method of ischemia assessment. [11,12,13,14]
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