Noninvasive hemodynamic assessment of aortic coarctation: multimodal imaging based-computational fluid dynamics

The gold standard assessment of coarctation of aorta (CoA) was achieved invasively by cardiac catheterization, which is associated with several risks including radiation exposure. The present study aimed to validate a multimodal imaging-based non-invasive computational framework for assessment of trans-coarctation pressure gradients (PG) in patients with severe coarctation of the aorta (CoA). Here we developed a non-invasive computational fluid dynamics (CFD) modeling framework based on multidetector computed tomography angiography (MDCTA) and ultrasound-derived input parameters, which incorporated into a lumped parameter model (LPM) and validated the results against measurements obtained via cardiac catheterization, both preoperatively and postoperatively. We used conventional Doppler estimates to make these correlations and to compare their diagnostic performance in identifying critical PG. The results indicated that for 18 patients with severe CoA the CFD simulation exhibited better concordance and correlation with catheter measurements compared to Doppler gradients (pre-intervention: 58.44 ± 17.77 vs. 55.72 ± 19.71 vs.57.78 ± 18.02 mmHg; post-intervention: 17.94 ± 10.54 vs. 15.65 ± 5.15 vs.20.61 ± 7.43 mmHg). Specifically, the CFD-derived PG showed a stronger correlation with catheter measurements (pre-intervention r = 0.89, post-intervention r = 0.90) than did Doppler-derived PG (pre-intervention r = 0.71, post-intervention r = 0.30). This CFD framework facilitated reliable quantification of PG and visualization of hemodynamic forces in patient-specific geometric models, and suggesting its potential as a non-invasive and effective approach for the assessment of CoA.

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Publication Details

Journal
Scientific Reports
Published
2026-03-09
DOI
https://doi.org/10.1038/s41598-026-42761-z
Primary Topic
Congenital Heart Disease Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Noninvasive hemodynamic assessment of aortic coarctation: multimodal imaging based-computational fluid dynamics

Peixian Gao, Jiayi Liu, Huihui Wang, Ximing Wang et al.
Scientific Reports
Congenital Heart Disease Studies
article

Noninvasive hemodynamic assessment of aortic coarctation: multimodal imaging based-computational fluid dynamics

Peixian Gao, Jiayi Liu, Huihui Wang, Ximing Wang, Mengsi Hu, Zhenxia Mu, Xia Li, Xiufeng Song, Yuezhong Zhang
article en

Abstract

The gold standard assessment of coarctation of aorta (CoA) was achieved invasively by cardiac catheterization, which is associated with several risks including radiation exposure. The present study aimed to validate a multimodal imaging-based non-invasive computational framework for assessment of trans-coarctation pressure gradients (PG) in patients with severe coarctation of the aorta (CoA). Here we developed a non-invasive computational fluid dynamics (CFD) modeling framework based on multidetector computed tomography angiography (MDCTA) and ultrasound-derived input parameters, which incorporated into a lumped parameter model (LPM) and validated the results against measurements obtained via cardiac catheterization, both preoperatively and postoperatively. We used conventional Doppler estimates to make these correlations and to compare their diagnostic performance in identifying critical PG. The results indicated that for 18 patients with severe CoA the CFD simulation exhibited better concordance and correlation with catheter measurements compared to Doppler gradients (pre-intervention: 58.44 ± 17.77 vs. 55.72 ± 19.71 vs.57.78 ± 18.02 mmHg; post-intervention: 17.94 ± 10.54 vs. 15.65 ± 5.15 vs.20.61 ± 7.43 mmHg). Specifically, the CFD-derived PG showed a stronger correlation with catheter measurements (pre-intervention r = 0.89, post-intervention r = 0.90) than did Doppler-derived PG (pre-intervention r = 0.71, post-intervention r = 0.30). This CFD framework facilitated reliable quantification of PG and visualization of hemodynamic forces in patient-specific geometric models, and suggesting its potential as a non-invasive and effective approach for the assessment of CoA.

Scientific Reports
Shandong University (CN), Shandong Provincial Hospital (CN), Affiliated Hospital of Shandong Academy of Medical Sciences (CN), Shandong First Medical University (CN)
Natural Science Foundation of Shandong Province
Good health and well-being
Openalex Percentile: Top 31%
Congenital Heart Disease Studies
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