Anders T Bråten, Fredrik E Fossan, Lucas O Muller, Arve Jørgensen, Knut H Stensæth, Leif R Hellevik, Rune Wiseth
{"title":"用于诊断血流动力学显著性冠状动脉疾病的自动计算机断层扫描衍生分数血流储备模型：一项前瞻性验证研究。","authors":"Anders T Bråten, Fredrik E Fossan, Lucas O Muller, Arve Jørgensen, Knut H Stensæth, Leif R Hellevik, Rune Wiseth","doi":"10.1093/ehjimp/qyae102","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>This study aims to assess the diagnostic performance of a novel computed tomography-derived fractional flow reserve (CT-FFR) algorithm and to compare its accuracy at three predefined sites: (i) at the location of invasive FFR measurements (CT-FFR<sub>atloc</sub>), (ii) at selected sites determined by an automated module integrated within the algorithm (CT-FFR<sub>auto</sub>), and (iii) distally in the vessel (CT-FFR<sub>distal</sub>).</p><p><strong>Methods and results: </strong>We prospectively recruited 108 consecutive patients with stable symptoms of coronary artery disease and at least one suspected obstructive lesion on coronary computed tomography angiography (CCTA). CT-FFR was validated against invasive FFR as gold standard using FFR ≤ 0.80 to define myocardial ischaemia. CT-FFR<sub>atloc</sub> showed good correlation with invasive FFR (<i>r</i> = 0.67) and improved the ability to detect myocardial ischaemia compared with CCTA at both lesion [area under the curve (AUC) 0.83 vs. 0.65, <i>P</i> < 0.001] and patient level (AUC 0.87 vs. 0.74, <i>P</i> = 0.007). CT-FFR<sub>auto</sub> demonstrated similar diagnostic accuracy to CT-FFR<sub>atloc</sub> and significantly improved specificity compared with CT-FFR<sub>distal</sub> (86% vs. 49%, <i>P</i> < 0.001). High end CT quality improved the diagnostic performance of CT-FFR<sub>auto</sub>, demonstrating an AUC of 0.92; similarly, the performance was improved in patients with low-to-intermediate coronary artery calcium score with an AUC of 0.88.</p><p><strong>Conclusion: </strong>Implementing an automated module to determine the site of CT-FFR evaluations was feasible, and CT-FFR<sub>auto</sub> demonstrated comparable diagnostic accuracy to CT-FFR<sub>atloc</sub> when assessed against invasive FFR. Both CT-FFR<sub>atloc</sub> and CT-FFR<sub>auto</sub> improved the diagnostic performance compared with CCTA and improved specificity compared with CT-FFR<sub>distal</sub>. High end CT quality and low-to-intermediate calcium burden improved the diagnostic performance of our algorithm.</p><p><strong>Clinicaltrialsgov identifier: </strong>NCT03045601.</p>","PeriodicalId":94317,"journal":{"name":"European heart journal. Imaging methods and practice","volume":"2 3","pages":"qyae102"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11502147/pdf/","citationCount":"0","resultStr":"{\"title\":\"Automated computed tomography-derived fractional flow reserve model for diagnosing haemodynamically significant coronary artery disease: a prospective validation study.\",\"authors\":\"Anders T Bråten, Fredrik E Fossan, Lucas O Muller, Arve Jørgensen, Knut H Stensæth, Leif R Hellevik, Rune Wiseth\",\"doi\":\"10.1093/ehjimp/qyae102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>This study aims to assess the diagnostic performance of a novel computed tomography-derived fractional flow reserve (CT-FFR) algorithm and to compare its accuracy at three predefined sites: (i) at the location of invasive FFR measurements (CT-FFR<sub>atloc</sub>), (ii) at selected sites determined by an automated module integrated within the algorithm (CT-FFR<sub>auto</sub>), and (iii) distally in the vessel (CT-FFR<sub>distal</sub>).</p><p><strong>Methods and results: </strong>We prospectively recruited 108 consecutive patients with stable symptoms of coronary artery disease and at least one suspected obstructive lesion on coronary computed tomography angiography (CCTA). CT-FFR was validated against invasive FFR as gold standard using FFR ≤ 0.80 to define myocardial ischaemia. CT-FFR<sub>atloc</sub> showed good correlation with invasive FFR (<i>r</i> = 0.67) and improved the ability to detect myocardial ischaemia compared with CCTA at both lesion [area under the curve (AUC) 0.83 vs. 0.65, <i>P</i> < 0.001] and patient level (AUC 0.87 vs. 0.74, <i>P</i> = 0.007). CT-FFR<sub>auto</sub> demonstrated similar diagnostic accuracy to CT-FFR<sub>atloc</sub> and significantly improved specificity compared with CT-FFR<sub>distal</sub> (86% vs. 49%, <i>P</i> < 0.001). High end CT quality improved the diagnostic performance of CT-FFR<sub>auto</sub>, demonstrating an AUC of 0.92; similarly, the performance was improved in patients with low-to-intermediate coronary artery calcium score with an AUC of 0.88.</p><p><strong>Conclusion: </strong>Implementing an automated module to determine the site of CT-FFR evaluations was feasible, and CT-FFR<sub>auto</sub> demonstrated comparable diagnostic accuracy to CT-FFR<sub>atloc</sub> when assessed against invasive FFR. Both CT-FFR<sub>atloc</sub> and CT-FFR<sub>auto</sub> improved the diagnostic performance compared with CCTA and improved specificity compared with CT-FFR<sub>distal</sub>. High end CT quality and low-to-intermediate calcium burden improved the diagnostic performance of our algorithm.</p><p><strong>Clinicaltrialsgov identifier: </strong>NCT03045601.</p>\",\"PeriodicalId\":94317,\"journal\":{\"name\":\"European heart journal. Imaging methods and practice\",\"volume\":\"2 3\",\"pages\":\"qyae102\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11502147/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European heart journal. Imaging methods and practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/ehjimp/qyae102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European heart journal. Imaging methods and practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ehjimp/qyae102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Automated computed tomography-derived fractional flow reserve model for diagnosing haemodynamically significant coronary artery disease: a prospective validation study.
Aims: This study aims to assess the diagnostic performance of a novel computed tomography-derived fractional flow reserve (CT-FFR) algorithm and to compare its accuracy at three predefined sites: (i) at the location of invasive FFR measurements (CT-FFRatloc), (ii) at selected sites determined by an automated module integrated within the algorithm (CT-FFRauto), and (iii) distally in the vessel (CT-FFRdistal).
Methods and results: We prospectively recruited 108 consecutive patients with stable symptoms of coronary artery disease and at least one suspected obstructive lesion on coronary computed tomography angiography (CCTA). CT-FFR was validated against invasive FFR as gold standard using FFR ≤ 0.80 to define myocardial ischaemia. CT-FFRatloc showed good correlation with invasive FFR (r = 0.67) and improved the ability to detect myocardial ischaemia compared with CCTA at both lesion [area under the curve (AUC) 0.83 vs. 0.65, P < 0.001] and patient level (AUC 0.87 vs. 0.74, P = 0.007). CT-FFRauto demonstrated similar diagnostic accuracy to CT-FFRatloc and significantly improved specificity compared with CT-FFRdistal (86% vs. 49%, P < 0.001). High end CT quality improved the diagnostic performance of CT-FFRauto, demonstrating an AUC of 0.92; similarly, the performance was improved in patients with low-to-intermediate coronary artery calcium score with an AUC of 0.88.
Conclusion: Implementing an automated module to determine the site of CT-FFR evaluations was feasible, and CT-FFRauto demonstrated comparable diagnostic accuracy to CT-FFRatloc when assessed against invasive FFR. Both CT-FFRatloc and CT-FFRauto improved the diagnostic performance compared with CCTA and improved specificity compared with CT-FFRdistal. High end CT quality and low-to-intermediate calcium burden improved the diagnostic performance of our algorithm.
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