- 著者
- 
             
             Hiroyuki Omori
             
             Yoshiaki Kawase
             
             Takuya Mizukami
             
             Toru Tanigaki
             
             Tetsuo Hirata
             
             Munenori Okubo
             
             Hiroki Kamiya
             
             Akihiro Hirakawa
             
             Masanori Kawasaki
             
             Takeshi Kondo
             
             Takahiko Suzuki
             
             Hitoshi Matsuo
             
          
- 出版者
- The Japanese Circulation Society
- 雑誌
- Circulation Journal (ISSN:13469843)
- 巻号頁・発行日
- pp.CJ-22-0771,  (Released:2023-03-28)
- 参考文献数
- 22
- 被引用文献数
- 
             
             
             2
             
             
          
        
        Background: Angiographic fractional flow reserve (angioFFR) is a novel artificial intelligence (AI)-based angiography-derived fractional flow reserve (FFR) application. We investigated the diagnostic accuracy of angioFFR to detect hemodynamically relevant coronary artery disease.Methods and Results: Consecutive patients with 30–90% angiographic stenoses and invasive FFR measurements were included in this prospective, single-center study conducted between November 2018 and February 2020. Diagnostic accuracy was assessed using invasive FFR as the reference standard. In patients undergoing percutaneous coronary intervention, gradients of invasive FFR and angioFFR in the pre-senting segments were compared. We assessed 253 vessels (200 patients). The accuracy of angioFFR was 87.7% (95% confidence interval [CI] 83.1–91.5%), with a sensitivity of 76.8% (95% CI 67.1–84.9%), specificity of 94.3% (95% CI 89.5–97.4%), and area under the curve of 0.90 (95% CI 0.86–0.93%). AngioFFR was well correlated with invasive FFR (r=0.76; 95% CI 0.71–0.81; P<0.001). The agreement was 0.003 (limits of agreement: −0.13, 0.14). The FFR gradients of angioFFR and invasive FFR were comparable (n=51; mean [±SD] 0.22±0.10 vs. 0.22±0.11, respectively; P=0.87).Conclusions: AI-based angioFFR showed good diagnostic accuracy for detecting hemodynamically relevant stenosis using invasive FFR as the reference standard. The gradients of invasive FFR and angioFFR in the pre-stenting segments were comparable.