Mechanical thrombectomy of distal cerebral vessel occlusions of the anterior circulation.

Mechanical thrombectomy (MT) is frequently performed for distal medium vessel occlusions (DMVO) of the anterior circulation in acute stroke patients. However, evidence for its clinical benefit remains scarce. In this study, we aim to investigate clinical course and safety outcomes of MT in comparison to standard medical therapy (SMT) in DMVO. This single-center retrospective observational study included 138 consecutive patients treated for DMVO of the anterior circulation between 2015 and 2021. To reduce the risk of selection bias, propensity score matching (PSM) of patients with MT versus SMT was performed for the covariates NIHSS and mRS at admission. Out of all 138 patients, 48 (34.8%) received MT and 90 (65.2%) received SMT only. Overall, patients treated with MT showed significantly higher NIHSS and mRS scores at admission. Post 1:1 PSM, there was a trend toward a better NIHSS improvement in patients with MT (median 4 vs. 1, P = 0.1). No significant differences were observed in the occurrence of symptomatic intracranial hemorrhage or mortality between the groups before and after PSM. A subgroup analysis showed significantly higher NIHSS improvement (median 5 versus 1, P = 0.01) for patients with successful MT (≥ mTICI 2b). Mechanical thrombectomy for distal medium vessel occlusions (DMVO) in the anterior circulation appeared safe and feasible. Successful recanalization was associated with clinical improvement. Larger, multi-center, randomized-controlled trials are required to corroborate these findings.

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.

Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer based automated medical image processing is increasingly finding its way into clinical routine. The Ischemic Stroke Lesion Segmentation (ISLES) challenge is a continuous effort to develop and identify benchmark methods for acute and sub-acute ischemic stroke lesion segmentation. Here we introduce an expert-annotated, multicenter MRI dataset for segmentation of acute to subacute stroke lesions ( https://doi.org/10.5281/zenodo.7153326 ). This dataset comprises 400 multi-vendor MRI cases with high variability in stroke lesion size, quantity and location. It is split into a training dataset of n = 250 and a test dataset of n = 150. All training data is publicly available. The test dataset will be used for model validation only and will not be released to the public. This dataset serves as the foundation of the ISLES 2022 challenge ( https://www.isles-challenge.org/ ) with the goal of finding algorithmic methods to enable the development and benchmarking of automatic, robust and accurate segmentation methods for ischemic stroke.