Abstract
Objective: To stent or not to stent remains a difficult decision in patients with renal artery stenosis (RAS). Up to date, no diagnostic test that reliably identifies patients that will benefit from endovascular intervention has been established. Our goal is to develop and validate an image-based flow simulation method for predicting blood pressure improvement after renal arterial revascularization. Design and method: In total 30 patients scheduled for percutaneous renal transluminal angioplasty (PTRA) for atherosclerotic RAS or fibromuscular dysplasia RAS will be included in the HERA-3 study. Baseline imaging consists of computed tomography angiography (CTA). Before and after PTRA duplex ultrasound, renography and 24-h ambulatory blood pressure (ABPM) measurements are obtained. Based on the pre-operative CTA and duplex-imaging, personalized flow simulations are performed using computational fluid dynamics (CFD). During PTRA, pressure-flow measurements are obtained with a 0.014” Combowire (Philips-Volcano) before and after intrarenal dopamine administration. A non-invasive renal fractional flow reserve (rFFR) –the pressure gradient during vasodilation- is derived from the CFD simulation and compared to the invasively measured rFFR for validation. In addition, the renal flow reserve (RFR) -the relative increase in flow during vasodilation relative to resting condition- is obtained. Results: Twelve patients have been included in the study so far. Preliminary results show an encouraging agreement between the CFD-based and invasively measured rFFR. Second, in select cases with an anatomically moderate RAS (65% diameter reduction), a low RFR was found before PTRA, which markedly increased after PTRA. This suggests that a subset of RAS lesions cause a stronger flow impediment than can be expected on anatomic lesion grading. Conclusions: In patients with RAS, it is feasible to obtain the functional flow metrics rFFR and RFR during angiography. Second, preliminary data suggest that the rFFR can be non-invasively estimated using computational flow analysis based on CTA and ultrasound imaging. Future analysis can establish the predictive value of these metrics for predicting blood pressure improvement after PTRAS.
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