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Tailored Calibration Approach for Hemodynamic Boundary Conditions in CT-FFR.

Created on 13 Aug 2026

Authors

Yoon A Kim, Daebeom Park, Doyeon Hwang, Seokhun Yang, Sang-Hyeon Park, Chang-Wook Nam, Joon-Hyung Doh, Hyun Kuk Kim, Yongcheol Kim, Eun Ju Chun, Bon-Kwon Koo

Published in

Korean circulation journal. Jul 02, 2026. Epub Jul 02, 2026.

Abstract

Computed tomography-derived fractional flow reserve (CT-FFR) uses standardized boundary conditions that cannot represent individual patient characteristics. We developed a calibration method to individualize boundary conditions using invasive fractional flow reserve (FFR) measurement. This study assessed the feasibility and impact on prediction of lesion-specific pressure drops (ΔFFR), post-percutaneous coronary intervention (PCI) FFR, and high-risk plaque (HRP) discrimination.
This retrospective multicenter study analyzed 79 patients with single left anterior descending lesions. Lumped parameter models were used to calibrate optimal boundary conditions by iteratively minimizing differences between invasive FFR and CT-FFR. HRP was assessed using an artificial intelligence-enabled analysis system, defined as low attenuation plaque, positive remodeling, or both. Discrimination performance was evaluated using ΔCT-FFR and CT-FFR gradient.
In 79 patients (median age 65.5 years, 77.2% male), median angiographic percent diameter stenosis 60.0%, median invasive FFR was 0.83 and CT-FFR was 0.81 before calibration. Following calibration, FFR correlation improved from 0.590 to 0.997 (p<0.001). ΔFFR correlation increased from 0.490 to 0.823 (p<0.001). Post-PCI validation showed correlation improvement from 0.440 to 0.871 (p=0.002). HRP discrimination improved for ΔCT-FFR (area under the curve [AUC], 0.62 to 0.70; p=0.018) and CT-FFR gradient (AUC, 0.62 to 0.69; p=0.032).
Individualized boundary condition calibration using invasive FFR enables accurate prediction of lesion-specific hemodynamics and post-intervention physiology, showing potential for enhanced procedural planning and risk stratification in patients undergoing coronary angiography.

PMID:
42586543
Bibliographic data and abstract were imported from PubMed on 13 Aug 2026.

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