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A low dimensional surrogate model for a fast estimation of strain in the thrombus during a thrombectomy procedure
Sara Bridio , Giulia Luraghi , Francesco Migliavacca , Sanjay Pant , Alberto García-González, Jose F. Rodriguez Matas
Journal of the Mechanical Behavior of Biomedical Materials, Volume: 137, Start page: 105577
Swansea University Author: Sanjay Pant
Accepted Manuscript under embargo until: 16th November 2023
DOI (Published version): 10.1016/j.jmbbm.2022.105577
BackgroundIntra-arterial thrombectomy is the main treatment for acute ischemic stroke due to large vessel occlusions and can consist in mechanically removing the thrombus with a stent-retriever. A cause of failure of the procedure is the fragmentation of the thrombus and formation of micro-emboli, d...
|Published in:||Journal of the Mechanical Behavior of Biomedical Materials|
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BackgroundIntra-arterial thrombectomy is the main treatment for acute ischemic stroke due to large vessel occlusions and can consist in mechanically removing the thrombus with a stent-retriever. A cause of failure of the procedure is the fragmentation of the thrombus and formation of micro-emboli, difficult to remove. This work proposes a methodology for the creation of a low-dimensional surrogate model of the mechanical thrombectomy procedure, trained on realizations from high-fidelity simulations, able to estimate the evolution of the maximum first principal strain in the thrombus.MethodA parametric finite-element model was created, composed of a tapered vessel, a thrombus, a stent-retriever and a catheter. A design of experiments was conducted to sample 100 combinations of the model parameters and the corresponding thrombectomy simulations were run and post-processed to extract the maximum first principal strain in the thrombus during the procedure. Then, a surrogate model was built with a combination of principal component analysis and Kriging.Results– The surrogate model was chosen after a sensitivity analysis on the number of principal components and was tested with 10 additional cases. The model provided predictions of the strain curves with correlation above 0.9 and a maximum error of 28%, with an error below 20% in 60% of the test cases.ConclusionsThe surrogate model provides nearly instantaneous estimates and constitutes a valuable tool for evaluating the risk of thrombus rupture during pre-operative planning for the treatment of acute ischemic stroke.
Acute ischemic stroke, Thrombectomy, Surrogate modeling, Principal components analysis, Kriging, Finite element method
Faculty of Science and Engineering
This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 777072 and from the MIUR FISR-FISR2019_03221 CECOMES.