Can machine learning models improve early detection of brain metastases using diffusion weighted imaging-based radiomics?

ABSTRACT:

Background

Metastatic complications are a major cause of cancer-related morbidity, with up to 40% of cancer patients experiencing at least one brain metastasis. Earlier detection may significantly improve patient outcomes and overall survival. We investigated machine learning (ML) models for early detection of brain metastases based on diffusion weighted imaging (DWI) radiomics.

Methods

Longitudinal diffusion imaging from 116 patients previously treated with stereotactic radiosurgery (SRS) for brain metastases were retrospectively analyzed. Clinical contours from 600 metastases were extracted from radiosurgery planning computed tomography, and rigidly registered to corresponding contrast enhanced-T1 and apparent diffusion coefficient (ADC) maps. Contralateral contours locate

SUBMITTER: Madamesila J 

PROVIDER: S-EPMC10722027 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature