In-silico trial of intracranial flow diverters replicates and expands insights from conventional clinical trials

Ali Sarrami-Foroushani, Toni Lassila, Michael MacRaild, Joshua Asquith, Kit C. B. Roes, James V. Byrne and Alejandro F. Frangi ()
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Ali Sarrami-Foroushani: University of Leeds
Toni Lassila: University of Leeds
Michael MacRaild: University of Leeds
Joshua Asquith: University of Leeds
Kit C. B. Roes: Radboud University Medical Centre
James V. Byrne: Oxford University
Alejandro F. Frangi: University of Leeds

Nature Communications, 2021, vol. 12, issue 1, 1-12

Abstract: Abstract The cost of clinical trials is ever-increasing. In-silico trials rely on virtual populations and interventions simulated using patient-specific models and may offer a solution to lower these costs. We present the flow diverter performance assessment (FD-PASS) in-silico trial, which models the treatment of intracranial aneurysms in 164 virtual patients with 82 distinct anatomies with a flow-diverting stent, using computational fluid dynamics to quantify post-treatment flow reduction. The predicted FD-PASS flow-diversion success rates replicate the values previously reported in three clinical trials. The in-silico approach allows broader investigation of factors associated with insufficient flow reduction than feasible in a conventional trial. Our findings demonstrate that in-silico trials of endovascular medical devices can: (i) replicate findings of conventional clinical trials, and (ii) perform virtual experiments and sub-group analyses that are difficult or impossible in conventional trials to discover new insights on treatment failure, e.g. in the presence of side-branches or hypertension.

Date: 2021
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DOI: 10.1038/s41467-021-23998-w

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