Cargando…
A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease
Background: The diagnostic accuracy of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA) (FFR-CT) needs to be further improved despite promising results available in the literature. While an innovative myocardial computed tomographic perfusion (CTP)-derived f...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058085/ https://www.ncbi.nlm.nih.gov/pubmed/36983156 http://dx.doi.org/10.3390/jcm12062154 |
_version_ | 1785016532192985088 |
---|---|
author | Gao, Xuelian Wang, Rui Sun, Zhonghua Zhang, Hongkai Bo, Kairui Xue, Xiaofei Yang, Junjie Xu, Lei |
author_facet | Gao, Xuelian Wang, Rui Sun, Zhonghua Zhang, Hongkai Bo, Kairui Xue, Xiaofei Yang, Junjie Xu, Lei |
author_sort | Gao, Xuelian |
collection | PubMed |
description | Background: The diagnostic accuracy of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA) (FFR-CT) needs to be further improved despite promising results available in the literature. While an innovative myocardial computed tomographic perfusion (CTP)-derived fractional flow reserve (CTP-FFR) model has been initially established, the feasibility of CTP-FFR to detect coronary artery ischemia in patients with suspected coronary artery disease (CAD) has not been proven. Methods: This retrospective study included 93 patients (a total of 103 vessels) who received CCTA and CTP for suspected CAD. Invasive coronary angiography (ICA) was performed within 2 weeks after CCTA and CTP. CTP-FFR, CCTA (stenosis ≥ 50% and ≥70%), ICA, FFR-CT and CTP were assessed by independent laboratory experts. The diagnostic ability of the CTP-FFR grouped by quantitative coronary angiography (QCA) in mild (30–49%), moderate (50–69%) and severe stenosis (≥70%) was calculated. The effect of calcification of lesions, grouped by FFR on CTP-FFR measurements, was also assessed. Results: On the basis of per-vessel level, the AUCs for CTP-FFR, CTP, FFR-CT and CCTA were 0.953, 0.876, 0.873 and 0.830, respectively (all p < 0.001). The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of CTP-FFR for per-vessel level were 0.87, 0.88, 0.87, 0.85 and 0.89 respectively, compared with 0.87, 0.54, 0.69, 0.61, 0.83 and 0.75, 0.73, 0.74, 0.70, 0.77 for CCTA ≥ 50% and ≥70% stenosis, respectively. On the basis of per-vessel analysis, CTP-FFR had higher specificity, accuracy and AUC compared with CCTA and also higher AUC compared with FFR-CT or CTP (all p < 0.05). The sensitivity and accuracy of CTP-FFR + CTP + FFR-CT were also improved over FFR-CT alone (both p < 0.05). It also had improved specificity compared with FFR-CT or CTP alone (p < 0.01). A strong correlation between CTP-FFR and invasive FFR values was found on per-vessel analysis (Pearson’s correlation coefficient 0.89). The specificity of CTP-FFR was higher in the severe calcification group than in the low calcification group (p < 0.001). Conclusions: A novel CTP-FFR model has promising value to detect myocardial ischemia in CAD, particularly in mild-to-moderate stenotic lesions. |
format | Online Article Text |
id | pubmed-10058085 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100580852023-03-30 A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease Gao, Xuelian Wang, Rui Sun, Zhonghua Zhang, Hongkai Bo, Kairui Xue, Xiaofei Yang, Junjie Xu, Lei J Clin Med Article Background: The diagnostic accuracy of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA) (FFR-CT) needs to be further improved despite promising results available in the literature. While an innovative myocardial computed tomographic perfusion (CTP)-derived fractional flow reserve (CTP-FFR) model has been initially established, the feasibility of CTP-FFR to detect coronary artery ischemia in patients with suspected coronary artery disease (CAD) has not been proven. Methods: This retrospective study included 93 patients (a total of 103 vessels) who received CCTA and CTP for suspected CAD. Invasive coronary angiography (ICA) was performed within 2 weeks after CCTA and CTP. CTP-FFR, CCTA (stenosis ≥ 50% and ≥70%), ICA, FFR-CT and CTP were assessed by independent laboratory experts. The diagnostic ability of the CTP-FFR grouped by quantitative coronary angiography (QCA) in mild (30–49%), moderate (50–69%) and severe stenosis (≥70%) was calculated. The effect of calcification of lesions, grouped by FFR on CTP-FFR measurements, was also assessed. Results: On the basis of per-vessel level, the AUCs for CTP-FFR, CTP, FFR-CT and CCTA were 0.953, 0.876, 0.873 and 0.830, respectively (all p < 0.001). The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of CTP-FFR for per-vessel level were 0.87, 0.88, 0.87, 0.85 and 0.89 respectively, compared with 0.87, 0.54, 0.69, 0.61, 0.83 and 0.75, 0.73, 0.74, 0.70, 0.77 for CCTA ≥ 50% and ≥70% stenosis, respectively. On the basis of per-vessel analysis, CTP-FFR had higher specificity, accuracy and AUC compared with CCTA and also higher AUC compared with FFR-CT or CTP (all p < 0.05). The sensitivity and accuracy of CTP-FFR + CTP + FFR-CT were also improved over FFR-CT alone (both p < 0.05). It also had improved specificity compared with FFR-CT or CTP alone (p < 0.01). A strong correlation between CTP-FFR and invasive FFR values was found on per-vessel analysis (Pearson’s correlation coefficient 0.89). The specificity of CTP-FFR was higher in the severe calcification group than in the low calcification group (p < 0.001). Conclusions: A novel CTP-FFR model has promising value to detect myocardial ischemia in CAD, particularly in mild-to-moderate stenotic lesions. MDPI 2023-03-09 /pmc/articles/PMC10058085/ /pubmed/36983156 http://dx.doi.org/10.3390/jcm12062154 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gao, Xuelian Wang, Rui Sun, Zhonghua Zhang, Hongkai Bo, Kairui Xue, Xiaofei Yang, Junjie Xu, Lei A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease |
title | A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease |
title_full | A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease |
title_fullStr | A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease |
title_full_unstemmed | A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease |
title_short | A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease |
title_sort | novel ct perfusion-based fractional flow reserve algorithm for detecting coronary artery disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058085/ https://www.ncbi.nlm.nih.gov/pubmed/36983156 http://dx.doi.org/10.3390/jcm12062154 |
work_keys_str_mv | AT gaoxuelian anovelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT wangrui anovelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT sunzhonghua anovelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT zhanghongkai anovelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT bokairui anovelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT xuexiaofei anovelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT yangjunjie anovelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT xulei anovelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT gaoxuelian novelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT wangrui novelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT sunzhonghua novelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT zhanghongkai novelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT bokairui novelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT xuexiaofei novelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT yangjunjie novelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease AT xulei novelctperfusionbasedfractionalflowreservealgorithmfordetectingcoronaryarterydisease |