The Methinks algorithm reliably identified anterior circulation LVO in suspected AIS patients. Its integration may simplify the workflow by facilitating early transfers of high-probability LVO patients, reserving further imaging in patients with discordant clinical and imaging findings.

In AIS patient undergoing reperfusion therapies, the initial core volume assessment‐based deep learning logarithm on non‐contrast CT has shown a significant association with functional outcome at 3 months and sICH.

Among reperfusion treatment patients, ICV assessment-based machine learning algorithm by Methinks on NCCT is capable to predict a favorable outcome even in patients with a favorable ASPECTS score and in both, the early and late time window.

In this study, we developed and validated a deep learning algorithm that demonstrates an at least equivalent performance to CT perfusion in estimating core volume on acute stroke imaging studies in patients with suspected anterior circulation LVO strokes. The algorithm's robust performance holds significant potential in settings with limited access to advanced imaging technologies across diverse healthcare environments.

Our radiomics model can reliably identify RBC and platelet-rich thrombi. Fast identification of thrombus histological components on CT at arrival can help to design the preferred therapeutic strategy

FIV was quantified using Methinks FIV segementation on 24-hour NCCT. Improved clinical outcomes in patients with FPE and cSR patterns seem to be influenced by reduced infarct volume in a stepwise manner (FIV FPE<cSR<PR).

On late window patients, estimation of ICV on NCCT with Methinks Ischemia algorithm seems to be superior to CTP and ASPECTS.

Machine learning analysis of CT at admission reliable classifies thrombi according to their main component. A better understanding of clot composition on a fast and simple way may be relevant on personalizing therapeutic strategies and improving the odds of recanalization in large vessel occlusion stroke.

In patients with stroke, current guidelines recommend non-invasive vascular imaging to identify intracranial vessel occlusions (VO) that may benefit from endovascular treatment (EVT). However, VO can be missed in CT angiography (CTA) readings.

Validation analysis to measure the Methinks NCCT LVO and NCCT ICH accuracy among suspected stroke patients transferred to a Comprehensive Stroke Centre (CSC) in Mexico and the possible impact on the workflow in low and middle income countries (LMIC). Sensitivity and specificity resulted in 100% and 95.8%, respectively. Methinks could save CTA acquisition times of 40 minutes by taking patients directly to the angiosuite for endovascular treatment.

In patients with suspected acute stroke, MethinksLVO software can rapidly and reliably predict LVO.