What is the clinical evidence from this study?

Study design: Observational. Population: Coronary Artery Disease (n=150). Intervention: Computational fluid dynamics-based virtual FFR (AngioBC) vs. Invasive Fractional Flow Reserve (FFR). Primary outcome: Correlation between virtual FFR and invasive FFR (R2 0.99, p=0.00434).

January 27, 2025Open Access

Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve

AEArshia EskandariK.N.Toosi University of Technology SMSara MalekK.N.Toosi University of Technology AJAlireza JabbariIsfahan University of Medical Sciences

Key Result

The AngioBC computational methodology accurately predicted patient-specific fractional flow reserve values compared to invasive measurements, achieving an R2 of 0.99 and MSE of 6.186e-7 (p = 0.00434).

Study Design

Type

Observational (n=150)

Multicenter

Structured PICO

Does a non-invasive computational FFR methodology accurately predict invasive FFR in patients admitted for cardiovascular assessment?

Population

150 participants admitted to the Rajaie Cardiovascular, Medical, and Research Center

Intervention

Non-invasive computational FFR prediction methodology using three-dimensional geometry reconstruction and computational fluid dynamics simulations

Comparator

Invasive Fractional flow reserve (FFR)

Outcome

Accuracy of virtual FFR values compared to clinically reported patient-specific FFR valuessurrogate

A novel computational fluid dynamics-based methodology accurately and efficiently predicts invasive FFR, potentially offering a reliable non-invasive diagnostic tool for coronary artery disease.

Main Result

Effect estimate: R2 0.99

p-value: p=0.00434

Limitations

Initial catheterization is necessary for geometry reconstruction by introducing contrast agents into the vessel.
Lack of long-term evaluations to assess the method's performance over time and in diverse clinical settings.

Abstract

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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