Outcome prediction comparison of ischaemic areas' radiomics in acute anterior circulation non-lacunar infarction.

ABSTRACT: The outcome prediction of acute anterior circulation non-lacunar infarction (AACNLI) is important for the precise clinical treatment of this disease. However, the accuracy of prognosis prediction is still limited. This study aims to develop and compare machine learning models based on MRI radiomics of multiple ischaemic-related areas for prognostic prediction in AACNLI. This retrospective multicentre study consecutively included 372 AACNLI patients receiving MRI examinations and conventional therapy between October 2020 and February 2023. These were grouped into training set, internal test set and external test set. MRI radiomics features were extracted from the mask diffusion-weighted imaging, mask apparent diffusion coefficient (ADC) and mask ADC620 by AACNLI segmentations. Grid search p

SUBMITTER: Zhou X 

PROVIDER: S-EPMC11580218 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature