Machine learning prediction of brain metastasis invasion pattern on brain magnetic resonance imaging scans.

ABSTRACT:

Background

Brain metastasis invasion pattern (BMIP) is an emerging biomarker associated with recurrence-free and overall survival in patients, and differential response to therapy in preclinical models. Currently, BMIP can only be determined from the histopathological examination of surgical specimens, precluding its use as a biomarker prior to therapy initiation. The aim of this study was to investigate the potential of machine learning (ML) approaches to develop a noninvasive magnetic resonance imaging (MRI)-based biomarker for BMIP determination.

Methods

From an initial cohort of 329 patients, a subset of 132 patients met the inclusion criteria for this retrospective study. We evaluated the ability of an expert neuroradiologist to reliably predict BMIP. Thereafter, the da

SUBMITTER: Najafian K 

PROVIDER: S-EPMC11639946 | biostudies-literature | 2024 Jan-Dec

REPOSITORIES: biostudies-literature