A Novel Demography-Based Approach to Define Patient-Specific Outflow Boundary Conditions in CT-Based FFR Computations

The proposed demography-based MFR model significantly improves FFR computation accuracy compared with a typical conventional model that assumes constant, healthy and population average MFR. Although its diagnostic accuracy is slightly lower than that of CT-FFR calibrated with patient-specific perfusion imaging data (91 vs. 100%), the demography-based model offers a substantial practical advantage by not requiring additional non-standard data acquisition, such as perfusion imaging. Consequently, it shows strong potential as a practical enhancement to conventional CT-FFR algorithms.

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Publication Details

Journal
Annals of Biomedical Engineering
Published
2026-03-03
DOI
https://doi.org/10.1007/s10439-026-04002-2
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

A Novel Demography-Based Approach to Define Patient-Specific Outflow Boundary Conditions in CT-Based FFR Computations

Ernest W. C. Lo, Leon Paixão Menezes, Ryo Torii, Francesca Pugliese
Annals of Biomedical Engineering
Advanced MRI Techniques and Applications
article

A Novel Demography-Based Approach to Define Patient-Specific Outflow Boundary Conditions in CT-Based FFR Computations

Ernest W. C. Lo, Leon Paixão Menezes, Ryo Torii, Francesca Pugliese
article en

Abstract

The proposed demography-based MFR model significantly improves FFR computation accuracy compared with a typical conventional model that assumes constant, healthy and population average MFR. Although its diagnostic accuracy is slightly lower than that of CT-FFR calibrated with patient-specific perfusion imaging data (91 vs. 100%), the demography-based model offers a substantial practical advantage by not requiring additional non-standard data acquisition, such as perfusion imaging. Consequently, it shows strong potential as a practical enhancement to conventional CT-FFR algorithms.

Annals of Biomedical Engineering
Queen Mary University of London (GB), Barts Health NHS Trust (GB), Torrington Hospital (GB), UCL Biomedical Research Centre (GB), William Harvey Research Institute (GB), University College London (GB)
Openalex Percentile: Top 37%
Advanced MRI Techniques and Applications
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