Value of CT-derived Fractional Flow Reserve in the Context of Outpatient Cardiac CT in Germany: A Propensity Score Matched Analysis

Abstract

Purpose

Coronary artery disease (CAD) remains one of the leading causes of death in Germany. Since outpatient reimbursement for cardiac computed tomography angiography (CCTA) became available in 2024, non-invasive diagnostics have gained importance. CT-derived fractional flow reserve (FFR-CT) may increase the specificity of CCTA and reduce invasive procedures.

Materials and Methods

In this retrospective analysis, 640 consecutive patients with coronary stenosis >25% were included in outpatient CCTA. Among them, 107 underwent additional FFR-CT. After propensity score matching, two cohorts of 105 patients each were available for comparison. The primary endpoint was the positive predictive value (PPV) for hemodynamically relevant stenoses.

Results

Based on propensity score matching, FFR-CT showed a PPV of 88% compared to 73% in the group without FFR-CT. Patients with nonpathological FFR-CT results were mainly managed conservatively, whereas pathological values led to revascularization in more than 70%. In the control group without FFR-CT, invasive coronary angiographies without coronary intervention were significantly more frequent (27%). Correlation between FFR-CT and invasive FFR was strong (r = 0.92; ICC = 0.95).

Conclusion

Integration of FFR-CT in outpatient CCTA seems to improve diagnostic accuracy and reduce invasive procedures. It has the potential to combine anatomical and functional information and optimize treatment decisions in stable CAD.

Key Points

• FFR-CT has the potential to increase diagnostic accuracy and reduce invasive coronary angiographies.

• FFR-CT has a higher positive predictive value than CCTA.

• The correlation between FFR-CT and invasive FFR was high.

• In cases of pathological FFR-CT, revascularization was performed in >70% of patients

Citation Format

• Rottländer D, Fischer C, Mohsen Y et al. Value of CT-derived Fractional Flow Reserve in the Context of Outpatient Cardiac CT in Germany: A Propensity Score Matched Analysis. Rofo 2025; DOI 10.1055/a-2760-5485

Keywords

cardiac - angiography - coronary angiography

• Literatur

• 1 DESTATIS Todesursachenstatistik 2023. Zugriff am 26. August 2025 unter: https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Gesundheit/Todesursachen/_inhalt.html
• 2 Korosoglou G, Thiele H, Silber S. et al. Bedarfs- und leitliniengerechte Diagnostik bei symptomatischer obstruktiver koronarer Herzkrankheit mittels Kardio-CT und MRT. Kardiologie 2023; 17: 406-417
• 3 Knuuti J, Ballo H, Juarez-Orozco LE. et al. The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina. A meta analysis focused on post-test disease probability. Eur Heart J 2018; 39: 3322-3330
• 4 Williams MC, Wereski R, Tuck C. et al. Coronary CT angiography-guided management of patients with stable chest pain: 10-year outcomes from the SCOT-HEART randomised controlled trial in Scotland. Lancet 2025; 405: 329-337
• 5 Marwan M, Achenbach S, Korosoglou G. et al. German cardiac CT registry: Indications, procedural data and clinical consequences in 7061 patients undergoing cardiac computed tomography. Int J Cardiovasc Imaging 2018; 34: 807-819
• 6 Newby DE, Adamson PD, Berry C. et al. Coronary CT angiography and 5-year risk of myocardial infarction. N Engl J Med 2018; 379: 924-933
• 7 Gemeinsamer Bundesausschuss 2024. Zugriff am 16. Mai 2025 unter: https://www.g-ba.de/beschluesse/6418/
• 8 Douglas PS, De Bruyne B, Pontone G. et al. 1-year outcomes of FFRCT-guided care in patients with suspected coronary disease: The PLATFORM study. J Am Coll Cardiol 2016; 68: 433-445
• 9 Fairbairn TA, Mullen L, Nicol E. et al. Implementation of a national AI technology program on cardiovascular outcomes and the health system. Nat Med 2025; 31: 1903-1910
• 10 Karády J, Mayrhofer T, Ivanov A. et al. Cost-effectiveness Analysis of Anatomic vs Functional Index Testing in Patients With Low-Risk Stable Chest Pain. JAMA Netw Open 2020; 3: e2028312
• 11 Mittal TK, Hothi SS, Venugopal V. et al. The Use and Efficacy of FFR-CT: Real-World Multicenter Audit of Clinical Data With Cost Analysis. JACC Cardiovasc Imaging 2023; 16: 1056-1065
• 12 Kloth C, Brendel JM, Kübler J. et al. CT-FFR: How a new technology could transform cardiovascular diagnostic imaging. Rofo 2025;
• 13 Koo BK, Erglis A, Doh JH. et al. Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol 2011; 58: 1989-1997
• 14 Min JK, Leipsic J, Pencina MJ. et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA 2012; 308: 1237-1245
• 15 Nørgaard BL, Leipsic J, Gaur S. et al. Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: The NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). J Am Coll Cardiol 2014; 63: 1145-1155
• 16 Glessgen CG, Boulougouri M, Vallée JP. et al. Artificial intelligence-based opportunistic detection of coronary artery stenosis on aortic computed tomography angiography in emergency department patients with acute chest pain. Eur Heart J Open 2023; 3: oead088
• 17 Brendel JM, Walterspiel J, Hagen F. et al. Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography. Diagn Interv Imaging 2025; 106: 68-75
• 18 Kübler J, Brendel JM, Küstner T. et al. Artificial intelligence-enhanced detection of subclinical coronary artery disease in athletes: Diagnostic performance and limitations. Int J Cardiovasc Imaging 2024; 40: 2503-2511
• 19 Brendel JM, Walterspiel J, Hagen F. et al. Coronary artery disease evaluation during transcatheter aortic valve replacement work-up using photon-counting CT and artificial intelligence. Diagn Interv Imaging 2024; 105: 273-280
• 20 Renker M, Schoepf UJ, Wang R. et al. Comparison of diagnostic value of a novel noninvasive coronary computed tomography angiography method versus standard coronary angiography for assessing fractional flow reserve. Am J Cardiol 2014; 114: 1303-1308
• 21 Lu MT, Ferencik M, Roberts RS. et al. Noninvasive FFR derived from coronary CT angiography: Management and outcomes in the PROMISE trial. JACC Cardiovasc Imaging 2017; 10: 1350-1358
• 22 Patel MR, Nørgaard BL, Fairbairn TA. et al. 1-Year impact on medical practice and clinical outcomes of FFR(CT): The ADVANCE registry. JACC Cardiovasc Imaging 2020; 13: 97-105
• 23 Madsen KT, Noergaard BL, Oevrehus KA. et al. Prognostic value of FFRCT in patients with stable chest pain – a 3-year follow-up of the ADVANCE-DK registry. Eur Heart J 2022; 43
• 24 Nørgaard BL, Gaur S, Fairbairn TA. et al. Prognostic value of coronary computed tomography angiographic derived fractional flow reserve: A systematic review and meta-analysis. Heart 2022; 108: 194-202