Key result
A novel physiologically based algorithm for computing fractional flow reserve demonstrated a 2.33-5.26% discrepancy compared to experimental invasive coronary angiographic data.
A novel physiologically based algorithm for CFD computation of FFR demonstrated high accuracy compared to invasive measurements, offering a reliable alternative to current lumped parameter models.
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PBA may enable non-invasive FFR computation; leaves open prospective clinical validation before practice change.
A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA was based on an extension of Murray's law and additional inlet conditions prescribed iteratively and was implemented in OpenFOAM v1912 for testing and validation. 3D models of CATs were created using CT scans and computational meshes, and the results were compared to invasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between the calculated and experimental FFR was within 2.33-5.26% in the steady-state and transient simulations, respectively, when convergence was reached. The PBA was a reliable and physiologically sound technique compared to a current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for convergence. The accuracy of the PBA method was further confirmed using an FDA nozzle, which demonstrated good alignment with the CFD-validated values.
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Alzhanov et al. (2023) studied Coronary artery disease. Physiologically based algorithm (PBA) for FFR computation vs. Invasive coronary angiographic (ICA) data was evaluated on Discrepancy between calculated and experimental FFR. A novel physiologically based algorithm for computing fractional flow reserve demonstrated a 2.33-5.26% discrepancy compared to experimental invasive coronary angiographic data.
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