Noninvasive Grading of Liver Fibrosis Based on Texture Analysis From MRI-Derived Radiomics.

ABSTRACT: Given the increasing global prevalence of metabolic syndrome, this study aimed to assess the potential of MRI-derived radiomics in noninvasively grading fibrosis. The study included 79 prospectively enrolled participants who had undergone MRE due to known or suspected liver disease between November 2022 and September 2023. Among them, 48 patients were diagnosed with histopathologically confirmed liver fibrosis. A total of 107 radiomic features per patient were extracted from MRI imaging. The dataset was then divided into training and test sets for model development and validation. Stepwise feature reduction was employed to identify the most relevant features and subsequently used to train a gradient-boosted tree model. The gradient-boosted tree model, trained on the training cohort with id

SUBMITTER: Gotta J 

PROVIDER: S-EPMC11659494 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature