CFD Computation of Flow Fractional Reserve (FFR) in Coronary Artery Trees Using a Novel Physiologically Based Algorithm (PBA) Under 3D Steady and Pulsatile Flow Conditions.
Nursultan AlzhanovEddie Yin Kwee NgXiaohui SuYong ZhaoPublished in: Bioengineering (Basel, Switzerland) (2023)
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.
Keyphrases
- coronary artery
- pulmonary artery
- machine learning
- computed tomography
- image quality
- systematic review
- dual energy
- deep learning
- randomized controlled trial
- heart failure
- molecular dynamics
- electronic health record
- coronary artery disease
- magnetic resonance
- aortic valve
- artificial intelligence
- pulmonary hypertension
- pet ct
- big data
- neural network
- blood brain barrier
- pulmonary arterial hypertension
- aortic stenosis