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Developing a non-invasive diagnostic framework for the fractional flow reserve quantification in left coronary
M Fernandes1,2, F P Oliveira1,2, N D Ferreira3
1Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto, Portugal.
Insights
This study introduces a new computational tool to predict fractional flow reserve (FFR) non-invasively using CT scans. The tool shows high accuracy and stability, offering a promising alternative to invasive methods for diagnosing coronary artery disease (CAD).
Area of Science:
- Cardiovascular Imaging and Modeling
- Computational Fluid Dynamics (CFD)
- Medical Device Technology
Background:
- Coronary artery disease (CAD) is a leading cause of mortality worldwide.
- Current hemodynamic assessment via invasive fractional flow reserve (FFR) presents significant costs and clinical challenges.
- Non-invasive diagnostic alternatives are highly sought after for CAD assessment.
Purpose of the Study:
- To develop and validate a novel computational tool for non-invasively predicting patient-specific FFR from CT-derived coronary models.
- To assess the accuracy and stability of the developed tool compared to invasive FFR and commercial software.
Main Methods:
- Utilized patient-specific 3D coronary models segmented from CT scans.
- Employed computational fluid dynamics (CFD) with physiologically informed boundary conditions and a viscoelastic blood model.
- Simulated hyperemic conditions and compared predictions against invasive FFR and HeartFlow® data in 12 patients.
Main Results:
- Achieved a high correlation (R² = 0.978) with invasive FFR measurements.
- Demonstrated a low average relative error (3.86% ± 2.01%) and negligible bias (-0.015) via Bland-Altman analysis.
- Exhibited improved stability and lower variability compared to commercial HeartFlow® data.
Conclusions:
- The developed numerical tool shows significant potential for accurately approximating hyperemic coronary dynamics non-invasively.
- This framework offers a cost-effective, on-site solution for assessing stenosis severity and aiding CAD diagnosis.
- Further validation through larger, multi-center clinical trials is necessary to establish definitive accuracy and generalizability.
Introduction:
Coronary artery disease (CAD) remains the leading global cause of death. Hemodynamic assessment is typically performed using fractional flow reserve (FFR); however, its invasive nature entails substantial costs and clinical challenges. Non-invasive alternatives are therefore highly desirable. Advances in cardiac imaging, particularly computed tomography (CT), now provide detailed coronary data that can serve as the foundation for computational modeling. This research proposes and validates a tool to numerically predict FFR in patient-specific LCA 3D models segmented from CT scans.
Methods:
Using CFD in ANSYS® Fluent, the developed tool employs physiologically informed boundary conditions, a Womersley velocity profile at the inlet and a three-element Windkessel model at the outlets, alongside a simplified Phan-Thien Tanner (sPTT) viscoelastic rheology model for blood. Simulations were conducted under hyperemic conditions to align with how the FFR is currently measured. The non-invasive FFR predictions on 12 patients were compared against both invasive gold standards and commercial HeartFlow® data (Mountain View, CA, USA).
Results And Discussion:
The numerical results showed a remarkable correlation with invasive measurements (R2 = 0.978) and a low average relative error of 3.86% ± 2.01%. Additionally, Bland-Altman analysis indicated high diagnostic precision with a negligible mean bias of -0.015. These metrics suggest improved stability compared to HeartFlow®, which showed higher variability (20.84% ± 34.79%) in the cohort of this study. These results are promising; however, given the limited cohort size (12 patients), they should be interpreted as a preliminary proof-of-concept validation rather than a definitive clinical benchmark. The findings of this study suggest that the developed numerical tool has the potential to approximate hyperemic coronary dynamics in a way that is close to the real physiology. Moreover, the developed framework has the potential to be used on-site in medical facilities without costs to assess the functional severity of stenoses and aid the diagnosis of CAD. Larger multi-center clinical trials are required to fully establish the accuracy and generalizability of this tool.
