Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy patients

Background: Short- and long-term outcomes from endovascular thrombectomy (EVT) for large vessel occlusion stroke remain variable. Imaging predictors are typically defined as acute changes (most commonly ASPECTS at presentation), but there is little information on the impact of imaging assessment of premorbid brain health as a determinant of outcome.

Aims: To examine the impact of automated measures of stroke severity and underlying brain frailty on short- and long-term outcomes in acute stroke treated with EVT.

Methods: In 215 patients with anterior circulation stroke who underwent EVT, automated analysis of presenting non-contrast CT scans determined acute ischemic volume (AIV) and e-ASPECTS as markers of stroke severity, and cerebral atrophy as a marker of brain frailty. Logistic regression identified predictors of NIHSS improvement, mRS at 90 and 30 days, mortality, and sICH.

Results: For long-term outcome, atrophy and presenting NIHSS were significant predictors of mRS 0–2 and death at 90 days, whereas age did not reach significance. For short-term NIHSS improvement, AIV and age were significant predictors.

Conclusion: Combinations of automated software-based imaging analysis and clinical data can be useful for predicting short-term neurological outcomes and may improve long-term prognostication in EVT, providing a basis for future predictive tools built into decision-aiding software.