Publications by authors named "J Trenkler"
Article Synopsis
- Mechanical thrombectomy using the SOFIA/SOFIA PLUS catheters is being evaluated as a primary treatment for acute ischemic stroke with large vessel occlusion, focusing on its safety and efficacy in a multi-center study involving 246 patients.
- Results show that primary aspiration with the catheters achieved 72.8% complete recanalization and 63.8% of patients were functionally independent after 90 days, with acceptable complication rates.
- The study supports using this technique as a first-line approach in stroke treatment, reinforcing the effectiveness of direct aspiration thrombectomy in managing acute ischemic strokes.
Background: The prognostic roles of clinical and laboratory markers have been exploited to model risk in patients with primary CNS lymphoma, but these approaches do not fully explain the observed variation in outcome. To date, neuroimaging or molecular information is not used. The aim of this study was to determine the utility of radiomic features to capture clinically relevant phenotypes, and to link those to molecular profiles for enhanced risk stratification.
View Article and Find Full Text PDFBackground And Objectives: Perfusion imaging can identify adult patients with salvageable brain tissue who would benefit from thrombectomy in later time windows. The feasibility of obtaining hyperacute perfusion sequences in pediatric stroke is unknown. The aim of this study was to determine whether contrast perfusion imaging delayed time to treatment and to assess perfusion profiles in children with large vessel occlusion stroke.
View Article and Find Full Text PDFArticle Synopsis
- Machine learning can work well, but it often struggles to make accurate predictions on new data, which is called out-of-sample generalizability.
- To solve this problem, researchers are using a method called Federated ML that allows computers to share information about how well they're learning without actually sharing the data itself.
- In a big study with 71 locations around the world, scientists created a model to help detect brain tumors more accurately, showing a significant improvement compared to older methods and hoping to help with rare illnesses and data sharing in healthcare.