Anders T Bråten, Fredrik E Fossan, Lucas O Muller, Arve Jørgensen, Knut H Stensæth, Leif R Hellevik, Rune Wiseth
{"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}
引用次数: 0
Abstract
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.