Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion

• Published in: Quantitative imaging in medicine and surgery Vol. 13; no. 6; pp. 3630 - 3643
• Main Authors: Yan, Hankun, Zhao, Na, Geng, Wenlei, Yu, Xianbo, Gao, Yang, Lu, Bin
• Format: Journal Article
• Language: English
• Published: China AME Publishing Company 01.06.2023
• Subjects: Original; coronary computed tomography angiography (CCTA); machine learning; fractional flow reserve (FFR); Plaque
• ISSN: 2223-4292; 2223-4306
• DOI: 10.21037/qims-22-1049

This study sought to evaluate the association between coronary plaque characteristics, changes in the fractional flow reserve (FFR) derived from computed tomography across the lesion (ΔFFR ), and lesion-specific ischemia using the FFR in patients with suspected or known coronary artery disease. The study assessed coronary computed tomography (CT) angiography stenosis, plaque characteristics, ΔFFR , and FFR in 164 vessels of 144 patients. Obstructive stenosis was defined as stenosis ≥50%. An area under the receiver -operating characteristics curve (AUC) analysis was conducted to define the optimal thresholds for ΔFFR and the plaque variables. Ischemia was defined as a FFR of ≤0.80. The optimal cut-off value of ΔFFR was 0.14. Low-attenuation plaque (LAP) ≥76.23 mm and a percentage aggregate plaque volume (%APV) ≥28.91% can be used to predict ischemia independent of other plaque characteristics. The addition of LAP ≥76.23 mm and %APV ≥28.91% improved the discrimination (AUC, 0.742 0.649, P=0.001) and reclassification abilities [category-free net reclassification index (NRI), 0.339, P=0.027; relative integrated discrimination improvement (IDI) index, 0.093, P<0.001] of the assessments compared to the stenosis evaluation alone, and the addition of information about ΔFFR ≥0.14 further increased the discrimination (AUC, 0.828 0.742, P=0.004) and reclassification abilities (NRI, 1.029, P<0.001; relative IDI, 0.140, P<0.001) of the assessments. The addition of the plaque assessment and ΔFFR to the stenosis assessments improved the identification of ischemia compared to the stenosis assessment alone.