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Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve
Arshia Eskandari1, Sara Malek1, Alireza Jabbari1
1Department of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, Iran.
Insights
A new non-invasive method accurately calculates Fractional flow reserve (FFR) using computational fluid dynamics, offering a user-friendly tool for diagnosing coronary artery disease and predicting mortality risk.
Area of Science:
- Cardiovascular Medicine
- Biomedical Engineering
- Computational Fluid Dynamics
Background:
- Left anterior descending (LAD) coronary artery obstruction is a significant predictor of mortality.
- Invasive Fractional flow reserve (FFR) is the standard for assessing Coronary Artery Disease (CAD) risk.
- Current non-invasive methods lack definitive reliability for clinical planning.
Purpose of the Study:
- To develop and validate a reliable, non-invasive methodology for calculating FFR.
- To assess the potential of computational fluid dynamics (CFD) for patient-specific CAD risk stratification.
- To provide clinicians with a user-friendly tool for improved diagnostic capabilities.
Main Methods:
- Three-dimensional geometry reconstruction from patient data.
- Computational fluid dynamics (CFD) simulations optimized for computation time.
- Validation of the computational model against invasive FFR results from 150 participants.
Main Results:
- The proposed methodology achieved virtual FFR values closely matching clinically reported patient-specific FFR.
- Statistical validation showed a Mean Squared Error (MSE) of 6.186e-7 and R-squared (R2) of 0.99 (p = 0.00434).
- The approach demonstrated reliable results across all 150 patients.
Conclusions:
- The developed non-invasive CFD-based FFR calculation is computationally and clinically user-friendly.
- The methodology requires minimal processing time (approx. 15 minutes on a standard desktop).
- This approach holds significant potential to aid clinicians in diagnosing coronary artery disease.
Background:
Obstruction within the left anterior descending coronary artery (LAD) is prevalent, serving as a prominent and independent predictor of mortality. Invasive Fractional flow reserve (FFR) is the gold standard for Coronary Artery Disease risk assessment. Despite advances in computational and imaging techniques, no definitive methodology currently assures clinicians of reliable, non-invasive strategies for future planning.
Method:
The present research encompassed a cohort of 150 participants who were admitted to the Rajaie Cardiovascular, Medical, and Research Center. The method includes a three-dimensional geometry reconstruction, computational fluid dynamics simulations, and methodology optimization for the computation time. Four patients are analyzed within this study to showcase the proposed methodology. The invasive FFR results reported by the clinic have validated the optimized model.
Results:
The computational FFR data derived from all methodologies are compared with those reported by the clinic for each case. The chosen methodology has yielded virtual FFR values that exhibit remarkable proximity to the clinically reported patient-specific FFR values, with the MSE of 6.186e-7 and R2 of 0.99 (p = 0.00434).
Conclusion:
This approach has shown reliable results for all 150 patients. The results are both computationally and clinically user-friendly, with the accumulative pre and post-processing time of 15 min on a desktop computer (Intel i7 processor, 16 GB RAM). The proposed methodology has the potential to significantly assist clinicians with diagnosis.
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