Validation of individualized flow simulations for determining the pressure gradient in patients with renal artery stenosis
- 1Amsterdam UMC
Abstract
ObjectivesTo validate two computational fluid dynamics (CFD) models derived from computed tomography angiography (CTA) for estimating trans-stenotic pressure gradients, using invasive intra-arterial pressure measurements as the reference standard in patients with renal artery stenosis (RAS).
BackgroundWe assessed whether non-invasive assessment of the pressure gradient using CFD could be a reliable alternative to intra-arterial measurements for identifying hemodynamically significant RAS.
MethodsWe performed intra-arterial measurements at rest and during dopamine-induced hyperemia to assess the trans-stenotic pressure gradient in 28 patients with RAS. A pre-intervention CTA scan was used to simulate the pressure gradient with a CFD model using a strategy based on Murrays law (CFD-Mu) and cortical volume (CFD-C). The agreement between the simulated and measured pressure gradients was assessed using intraclass correlation coefficients (ICC), Bland-Altman analysis and diagnostic agreement on the presence of a hemodynamically significant stenosis.
ResultsIn 20 patients, successful measurements and simulations were obtained. The ICC between measured pressure gradient and the CFD pressure gradient was 0.78 and 0.94 during baseline and 0.86 and 0.72 during hyperemia, for CFD-Mu and CFD-C, respectively. The sensitivity of CFD-Mu and CFD-C was 70% for both models at rest and 100% compared to the hyperemic measurements, whereas the specificity was 90% and 70% at rest and 79% and 72% during hyperemia, respectively.
ConclusionsThe results support the use of individualized CFD simulations for hemodynamic assessment of RAS using CTA as input. The CFD models demonstrated high accuracy for the identification of a hemodynamically significant stenosis.
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BibTeX
@misc{bouwmeester2026validation,
title = {{Validation of individualized flow simulations for determining the pressure gradient in patients with renal artery stenosis}},
author = {T. A. Bouwmeester and D. Collard and I. A. J. Zijlstra and E. van Hulst and A. G. B. H. Lamers and L. Vogt and B.-J. H. van den Born and L. van de Velde},
howpublished = {medRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.27.26361537},
url = {https://www.medrxiv.org/content/10.64898/2026.08.27.26361537v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Validation of individualized flow simulations for determining the pressure gradient in patients with renal artery stenosis
AU - T. A. Bouwmeester
AU - D. Collard
AU - I. A. J. Zijlstra
AU - E. van Hulst
AU - A. G. B. H. Lamers
AU - L. Vogt
AU - B.-J. H. van den Born
AU - L. van de Velde
PY - 2026
DA - 2026/08/27
PB - medRxiv
DO - 10.64898/2026.08.27.26361537
UR - https://www.medrxiv.org/content/10.64898/2026.08.27.26361537v1
AB - ObjectivesTo validate two computational fluid dynamics (CFD) models derived from computed tomography angiography (CTA) for estimating trans-stenotic pressure gradients, using invasive intra-arterial pressure measurements as the reference standard in patients with renal artery stenosis (RAS). BackgroundWe assessed whether non-invasive assessment of the pressure gradient using CFD could be a reliable alternative to intra-arterial measurements for identifying hemodynamically significant RAS. MethodsWe performed intra-arterial measurements at rest and during dopamine-induced hyperemia to assess the trans-stenotic pressure gradient in 28 patients with RAS. A pre-intervention CTA scan was used to simulate the pressure gradient with a CFD model using a strategy based on Murrays law (CFD-Mu) and cortical volume (CFD-C). The agreement between the simulated and measured pressure gradients was assessed using intraclass correlation coefficients (ICC), Bland-Altman analysis and diagnostic agreement on the presence of a hemodynamically significant stenosis. ResultsIn 20 patients, successful measurements and simulations were obtained. The ICC between measured pressure gradient and the CFD pressure gradient was 0.78 and 0.94 during baseline and 0.86 and 0.72 during hyperemia, for CFD-Mu and CFD-C, respectively. The sensitivity of CFD-Mu and CFD-C was 70% for both models at rest and 100% compared to the hyperemic measurements, whereas the specificity was 90% and 70% at rest and 79% and 72% during hyperemia, respectively. ConclusionsThe results support the use of individualized CFD simulations for hemodynamic assessment of RAS using CTA as input. The CFD models demonstrated high accuracy for the identification of a hemodynamically significant stenosis.
ER -