In silico trials of acute ischemic stroke: predicting the total potential for improvement to patient functional outcomes

TL;DR

This study employs in silico trials to quantify the maximum potential improvement in functional outcomes for acute ischemic stroke patients through optimized recanalisation and treatment timing, demonstrating the value of virtual models in therapy development.

Contribution

It introduces a novel in silico trial framework for predicting maximum patient outcome improvements in stroke treatment development.

Findings

57% achieve functional independence with full recanalisation within 4 hours

Recanalisation has a greater impact than early treatment alone

In silico models effectively predict patient outcomes and therapy potential

Abstract

This study uses in silico trials (ISTs) to quantify the potential for benefit due to improved recanalisation outcomes and shorter time to treatment for acute ischaemic stroke (AIS) patients. We use an IST framework to run trials on cohorts of virtual patients with early and late treatment after stroke onset, and with successful (full) and unsuccessful (no) recanalisation outcomes. Using a virtual population of AIS patients, and in silico models of blood flow, perfusion, and tissue death, we predict the functional independence of each patient at 90 days using the modified Rankin Scale (mRS). Results predict 57% of the virtual population achieve functional independence with full recanalisation and a treatment time of 4 hours or less, compared to 29% with no recanalisation and more than 4 hours to treatment. Successful recanalisation was more beneficial than faster treatment: the best-case common odds ratio (improved mRS) due to recanalisation was 2.7 compared to 1.6 for early treatment. This study provides a proof-of-concept for a novel use-case of ISTs: quantifying the maximum potential for improvement to patient outcomes. This would be useful during early stages of therapy development, to determine the target populations and therapy goal with the greatest potential for population improvements.