A high-fidelity geometric multiscale hemodynamic model for predicting myocardial ischemia

Background and Objectives: Coronary computed tomography angiography (CCTA) derived fractional flow reserve (CT-FFR) requires a maximal hyperemic state to be modeled by assuming the total coronary re-sistance decreased to a constant 0.24 of that under the resting state. However, this assumption neglects the vasodilator capacity of individual patients. Herein, we proposed a high-fidelity geometric multiscale model (HFMM) to characterize coronary pressure and flow under the resting state, seeking to better pre-dict myocardial ischemia by using CCTA-derived instantaneous wave-free ratio (CT-iFR).Methods: Fifty-seven patients (62 lesions) who had undergone CCTA and were then referred to invasive FFR were prospectively enrolled. The coronary microcirculation resistance hemodynamic model (RHM) under the resting condition was established on a patient-specific basis. Coupled with a closed-loop ge-ometric multiscale model (CGM) of their individual coronary circulations, the HFMM model was estab-lished to non-invasively derive the CT-iFR from CCTA images.Results: With the invasive FFR being the reference standard, accuracy of the obtained CT-iFR in identify-ing myocardial ischemia was greater than those of the CCTA and non-invasively derived CT-FFR (90.32% vs. 79.03% vs. 84.3%). The overall computational time of CT-iFR was 61 +/- 6 min, faster than that of the CT-FFR (8 h). The sensitivity, specificity, positive predictive value, and negative predictive value of the CT-iFR in discriminating an invasive FFR > 0.8 were 78% (95% CI: 40-97%), 92% (95% CI: 82-98%), 64% (95% CI: 39-83%), and 96% (95% CI:88-99%), respectively.Conclusions: A high-fidelity geometric multiscale hemodynamic model was developed for rapid and ac-curate estimation of CT-iFR. Compared with CT-FFR, CT-iFR is of less computational cost and enables as-sessment of tandem lesions.(c) 2023 Elsevier B.V. All rights reserved.

Automated summary

This study proposed a high-fidelity geometric multiscale model (HFMM) to characterize coronary pressure and flow under the resting state, aiming to better predict myocardial ischemia using CT-iFR. Through prospective enrollment of 57 patients, it was found that CT-iFR had greater accuracy in identifying myocardial ischemia compared to CCTA and CT-FFR. Furthermore, the computational time of CT-iFR was faster.