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Performance of a Novel CT-Derived Fractional Flow Reserve Measurement to Detect Hemodynamically Significant Coronary Stenosis
- Title
- Performance of a Novel CT-Derived Fractional Flow Reserve Measurement to Detect Hemodynamically Significant Coronary Stenosis
- Authors
- Kang, Si-Hyuck; Kim, Soo-Hyun; Kim, Sun-Hwa; Chun, Eun Ju; Chung, Woo-Young; Yoon, Chang-Hwan; Park, Sang-Don; Nam, Chang-Wook; Kwon, Ki-Hwan; Doh, Joon-Hyung; Byun, Young-Sup; Bae, Jang-Whan; Youn, Tae-Jin; Chae, In-Ho
- Ewha Authors
- 권기환
- SCOPUS Author ID
- 권기환
- Issue Date
- 2023
- Journal Title
- JOURNAL OF KOREAN MEDICAL SCIENCE
- ISSN
- 1011-8934
1598-6357
- Citation
- JOURNAL OF KOREAN MEDICAL SCIENCE vol. 38, no. 32
- Keywords
- Computed Tomography; Coronary CT Angiography; Fractional Flow Reserve; Coronary Artery Disease
- Publisher
- KOREAN ACAD MEDICAL SCIENCES
- Indexed
- SCIE; SCOPUS; KCI
- Document Type
- Article
- Abstract
- Background: Fractional flow reserve (FFR) based on computed tomography (CT) has been shown to better identify ischemia-causing coronary stenosis. However, this current technology requires high computational power, which inhibits its widespread implementation in clinical practice. This prospective, multicenter study aimed at validating the diagnostic performance of a novel simple CT based fractional flow reserve (CT-FFR) calculation method in patients with coronary artery disease. Methods: Patients who underwent coronary CT angiography (CCTA) within 90 days and invasive coronary angiography (ICA) were prospectively enrolled. A hemodynamically significant lesion was defined as an FFR & LE; 0.80, and the area under the receiver operating characteristic curve (AUC) was the primary measure. After the planned analysis for the initial algorithm A, we performed another set of exploratory analyses for an improved algorithm B. Results: Of 184 patients who agreed to participate in the study, 151 were finally analyzed. Hemodynamically significant lesions were observed in 79 patients (52.3%). The AUC was 0.71 (95% confidence interval [CI], 0.63-0.80) for CCTA, 0.65 (95% CI, 0.56-0.74) for CT-FFR algorithm A (P = 0.866), and 0.78 (95% CI, 0.70-0.86) for algorithm B (P = 0.112). Diagnostic accuracy was 0.63 (0.55-0.71) for CCTA alone, 0.66 (0.58-0.74) for algorithm A, and 0.76 (0.68-0.82) for algorithm B. Conclusion: This study suggests the feasibility of automated CT-FFR, which can be performed on-site within several hours. However, the diagnostic performance of the current algorithm does not meet the a priori criteria for superiority. Future research is required to improve the accuracy.
- DOI
- 10.3346/jkms.2023.38.e254
- Appears in Collections:
- 의과대학 > 의학과 > Journal papers
- Files in This Item:
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