Cardiovasc Imaging Asia.  2025 Jan;9(1):2-8. 10.22468/cvia.2024.00129.

Machine Learning-Based Computed Tomography-Derived Fractional Flow Reserve Predicts Need for Coronary Revascularisation Prior to Transcatheter Aortic Valve Implantation

• Leung KDD
• Ng PP
• Chow BCK
• Chiu KWH
• Mahboobani NR
• Cheng YW
• Wong ECY
• Chan AKC
• Chui ASF
• Lee MKY
• Lee JCY

• KMID: 2565386
• DOI: http://doi.org/10.22468/cvia.2024.00129

Abstract

Objective
Patients with severe symptomatic aortic stenosis are assessed for coronary artery disease (CAD) prior to transcatheter aortic valve implantation (TAVI) with treatment implications. Invasive coronary angiography (ICA) is the recommended modality but is associated with peri-procedural complications. Integrating machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) into existing TAVI-planning CT protocol may aid exclusion of significant CAD and thus avoiding ICA in selected patients.
Materials and Methods
A single-center, retrospective study was conducted, 41 TAVI candidates with both TAVI-planning CT and ICA performed were analyzed. CT datasets were evaluated by a ML-based CT-FFR software. Beta-blocker and nitroglycerin were not administered in these patients. The primary outcome was to identify significant CAD. The diagnostic performance of CT-FFR was compared against ICA.
Results
On per-patient level, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy were 89%, 94%, 80%, 97% and 93%, respectively. On per-vessel level, the sensitivity, specificity, PPV, NPV and diagnostic accuracy were 75%, 94%, 67%, 96% and 92%, respectively. The area under the receiver operative characteristics curve per individual coronary vessels yielded overall 0.90 (95% confidence interval 85%–95%). ICA may be avoided in up to 80% of patients if CT-FFR results were negative.
Conclusion
ML-based CT-FFR can provide accurate screening capabilities for significant CAD thus avoiding ICA. Its integration to existing TAVI-planning CT is feasible with the potential of improving the safety and efficiency of pre-TAVI CAD assessment.

Keyword

Aortic valve stenosis; Coronary artery disease; Coronary stenosis; Transcatheter aortic valve replacement; Fractional flow reserve, myocardial