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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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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
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author Yan, Hankun
Zhao, Na
Geng, Wenlei
Yu, Xianbo
Gao, Yang
Lu, Bin
author_facet Yan, Hankun
Zhao, Na
Geng, Wenlei
Yu, Xianbo
Gao, Yang
Lu, Bin
author_sort Yan, Hankun
collection PubMed
description 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.
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spelling pubmed-102399862023-06-06 Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion Yan, Hankun Zhao, Na Geng, Wenlei Yu, Xianbo Gao, Yang Lu, Bin Quant Imaging Med Surg Original Article 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. AME Publishing Company 2023-04-20 2023-06-01 /pmc/articles/PMC10239986/ /pubmed/37284071 http://dx.doi.org/10.21037/qims-22-1049 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Yan, Hankun
Zhao, Na
Geng, Wenlei
Yu, Xianbo
Gao, Yang
Lu, Bin
Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion
title Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion
title_full Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion
title_fullStr Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion
title_full_unstemmed Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion
title_short Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion
title_sort identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion
topic Original Article
url 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
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