What question did this study set out to answer?

To develop a radiomic classifier that distinguishes between tumor recurrence and treatment effects in brain metastases.

April 19, 2026Open Access

Radiomics-based Differentiation of Recurrent Brain Metastases from Treatment Effects: A Multi-Institutional Comparative Study with Advanced Imaging

HUHyemin UmUniversity of Wisconsin–Madison MIMarwa IsmailUniversity of Wisconsin–Madison VHVirginia HillNorthwestern University

Key Points

To develop a radiomic classifier that distinguishes between tumor recurrence and treatment effects in brain metastases.
Utilized multi-institutional posttreatment MRI data
Constructed a radiomic classifier
Assessed the accuracy of classification against clinical imaging
Successfully differentiated between tumor recurrence and treatment effects
Accurately classified lesions that were indistinguishable in clinical imaging

Abstract

A radiomic classifier constructed from multi-institutional posttreatment MRI data reliably differentiated tumor recurrence from treatment effects in patients with brain metastases and accurately classified lesions that were indistinguishable at clinical imaging.

AI से पूछें

Bookmark

View Full Paper

Cite This Study

Um et al. (Fri,) studied this question.

synapsesocial.com/papers/69e472d8010ef96374d8eb95 https://doi.org/https://doi.org/10.1148/rycan.250435

AI से पूछें

Bookmark

View Full Paper