Value of Computed Tomography-Based Computational Fluid Dynamics in the Prediction of Acute Coronary Syndrome

Abstract

BACKGROUND: This study investigated the ability of coronary computed tomography angiography (CCTA)-derived computational fluid dynamics (CFD) parameters to identify lesions associated with subsequent acute coronary syndrome (ACS). METHODS AND RESULTS: ) into a model containing clinical and anatomical variables significantly improved ACS prediction (area under the curve 0.862 vs. 0.781; P=0.044). CONCLUSIONS: CCTA-derived CFD parameters are independently associated with the development of ACS. Integrating multiple CFD metrics enhances the predictive performance beyond traditional clinical and anatomical characteristics, supporting their potential role in risk stratification.

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BibTeX RIS

BibTeX

@article{ding2026value,
  title = {{Value of Computed Tomography-Based Computational Fluid Dynamics in the Prediction of Acute Coronary Syndrome}},
  author = {Yipu Ding and Zinuan Liu and Ziqiang Guo and Dongkai Shan and Xi Wang and Guanxi Chen and Tao Li and Xingli Liu and Zhihong Lin and Qi Gao and Yundai Chen and Tianwen Han and Junjie Yang},
  journal = {Circulation Journal},
  year = {2026},
  month = jul,
  doi = {10.1253/circj.cj-25-1055},
  url = {https://www.jstage.jst.go.jp/article/circj/advpub/0/advpub_CJ-25-1055/_article},
  note = {CC BY-NC-ND},
}

RIS

TY  - JOUR
TI  - Value of Computed Tomography-Based Computational Fluid Dynamics in the Prediction of Acute Coronary Syndrome
AU  - Yipu Ding
AU  - Zinuan Liu
AU  - Ziqiang Guo
AU  - Dongkai Shan
AU  - Xi Wang
AU  - Guanxi Chen
AU  - Tao Li
AU  - Xingli Liu
AU  - Zhihong Lin
AU  - Qi Gao
AU  - Yundai Chen
AU  - Tianwen Han
AU  - Junjie Yang
PY  - 2026
DA  - 2026/07/14
JO  - Circulation Journal
DO  - 10.1253/circj.cj-25-1055
UR  - https://www.jstage.jst.go.jp/article/circj/advpub/0/advpub_CJ-25-1055/_article
AB  - BACKGROUND: This study investigated the ability of coronary computed tomography angiography (CCTA)-derived computational fluid dynamics (CFD) parameters to identify lesions associated with subsequent acute coronary syndrome (ACS). METHODS AND RESULTS: ) into a model containing clinical and anatomical variables significantly improved ACS prediction (area under the curve 0.862 vs. 0.781; P=0.044). CONCLUSIONS: CCTA-derived CFD parameters are independently associated with the development of ACS. Integrating multiple CFD metrics enhances the predictive performance beyond traditional clinical and anatomical characteristics, supporting their potential role in risk stratification.
SN  - 1347-4820
SN  - 1346-9843
ER  -

Abstract

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