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The Application of Computational Fluid Dynamics to Predict Clinical Outcome of Renal Angioplasty in Patients with a Stenosed Renal Artery

Hulst, E. van (2022) The Application of Computational Fluid Dynamics to Predict Clinical Outcome of Renal Angioplasty in Patients with a Stenosed Renal Artery.

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Abstract:Objectives: Identification of patients with renal artery stenosis (RAS) that will respond to renal angioplasty treatment is an ongoing challenge. Patient specific information on the renal haemodynamics could provide insights that may contribute to clinical decision making. Computational fluid dynamics (CFD) is a promising method to determine patient-specific pressure and flow profiles. In this thesis the use of CFD technology in the determination of patient-specific intrarenal pressure and flow parameters will be assessed under resting and hyper-aemic conditions to predict blood pressure and kidney function outcomes after renal angioplasty. Method: A statistical analysis was performed to estimate hyperaemic renal artery flow and renal flow reserve (RFR). A developed CFD model with population averaged and geometric based boundary conditions was validated in 6 patients with RAS. Different simulation methods were explored. Simulated renal fractional flow reserve (rFFR) and translesional pressure gradients were compared to their invasively measured counterpart. In an external data set of 11 patients, simulation results were compared to clinical outcome of renal angioplasty. Results: Hyperaemic renal artery flow and RFR could not be estimated using patient characteristics and the already existing and frequently used parameters to quantify kidney function. The CFD analysis showed that the mean difference between the most accurate simulation method and measurements was -0.013 ± 0.028 for rFFR value and 1.11 ± 2.26 for translesional pressure gradient. The application of the CFD model in the external data set showed a larger clinical response to renal angioplasty in the 5 patients with a rFFR > 0.9 compared to the 6 patients with a rFFR ≥ 0.9. Conclusions: The application of CFD in the renal arteries has the potential to be of great benefit in the selection of patients for renal angioplasty treatment in the future. The results provided in the current thesis demonstrate that CFD is suitable for the non-invasive assessment of renal haemodynamics. Future research should show whether the haemodynamic parameters are appropriate to improve patient selection, in which improved CFD models can accelerate the process.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Programme:Technical Medicine MSc (60033)
Link to this item:https://purl.utwente.nl/essays/93852
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