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

BACKGROUND: 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(CT)), and lesion-specific ischemia using the FFR in patients with suspected or known coronary arter...

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Detalles Bibliográficos
Autores principales: Yan, Hankun, Zhao, Na, Geng, Wenlei, Yu, Xianbo, Gao, Yang, Lu, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239986/
https://www.ncbi.nlm.nih.gov/pubmed/37284071
http://dx.doi.org/10.21037/qims-22-1049
Descripción
Sumario:BACKGROUND: 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(CT)), and lesion-specific ischemia using the FFR in patients with suspected or known coronary artery disease. METHODS: The study assessed coronary computed tomography (CT) angiography stenosis, plaque characteristics, ΔFFR(CT), 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(CT) and the plaque variables. Ischemia was defined as a FFR of ≤0.80. RESULTS: The optimal cut-off value of ΔFFR(CT) was 0.14. Low-attenuation plaque (LAP) ≥76.23 mm(3 )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(3 )and %APV ≥28.91% improved the discrimination (AUC, 0.742 vs. 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(CT) ≥0.14 further increased the discrimination (AUC, 0.828 vs. 0.742, P=0.004) and reclassification abilities (NRI, 1.029, P<0.001; relative IDI, 0.140, P<0.001) of the assessments. CONCLUSIONS: The addition of the plaque assessment and ΔFFR(CT) to the stenosis assessments improved the identification of ischemia compared to the stenosis assessment alone.