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◆ Computers in Biology and Medicine2025-10-08· Medicine

Computational assessment of fibromuscular dysplasia-related renal artery stenosis

Luca Soliveri, Maria Stoenoiu, Michela Bozzetto, Francesco Meris, Tom Robberechts, Frank Hammer, Étienne Danse, Laurent Toubiana, Andrzej Januszewicz, Magdalena Januszewicz, Andrea Remuzzi, Anna Caroli, Alexandre Persu

原始摘要(英文原文)· Original abstract
BACKGROUND: Fibromuscular dysplasia (FMD) is a potentially curable cause of renovascular hypertension, primarily affecting middle-aged women. Percutaneous angioplasty is the recommended treatment for patients with hemodynamically significant renal artery stenosis (RAS). However, no established non-invasive method currently exists to estimate the pressure drop across stenosis and assess its hemodynamic impact. This study aimed to assess the clinical applicability of an image-based computational fluid dynamic (CFD) pipeline, functioning as a digital twin of the renal vasculature, for non-invasive assessment of fractional flow reserve (FFR) and trans-stenotic pressure drop in patients with FMD-related RAS. METHODS: This retrospective study included 10 middle-aged women: six with FMD-related stenosis (two focal and four multifocal), two with atherosclerotic RAS and two healthy volunteers. For each subject, a patient-specific 3D surface model of the renal vasculature was reconstructed from medical images and CFD simulations were performed using Simvascular. FFR and trans-stenotic pressure drop were assessed across each renal artery. RESULTS: The imaged-based CFD pipeline was feasible for all 10 subjects. A wide range of FFR (0.57 - >0.95) and pressure drops (11-73 mmHg) was observed across subjects, depending on the phenotype and severity of stenosis. The computed pressure drops and FFR values were consistent with the clinical decision on revascularization (AUC = 0.988), supporting the diagnostic relevance of the model. CONCLUSION: The proposed pipeline represents a promising non-invasive approach to assess the hemodynamic significance of RAS due to FMD. As a digital twin for personalized cardiovascular medicine, it could serve as valuable tool for selecting patients requiring angioplasty and predicting revascularization outcomes.
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