MRI Radiomic Features Are Independently Associated With Overall Survival in Soft Tissue Sarcoma

201974 citationsJournal Articlegold Open Access

Authors

Matthew B. Spraker · Washington University in St. Louis

Landon S. Wootton · University of Washington

Daniel S. Hippe · University of Washington

Kevin C. Ball · Aurora St. Luke's Medical Center

Jan C. Peeken · German Marine Research Consortium

Meghan W. Macomber · University of Washington

Tobias R. Chapman

Abstract

This study found that radiomic features extracted from MR images are independently associated with OS when accounting for age and tumor grade. The overall predictive performance of 3-year OS using a model based on clinical and radiomic features was replicated in an independent cohort. Optimal models using clinical and radiomic features could improve personalized selection of therapy in patients with STS.

Topics & Keywords

Sarcoma Diagnosis and Treatment Radiomics and Machine Learning in Medical Imaging Bone Tumor Diagnosis and Treatments

UN Sustainable Development Goals

Good health and well-being

Publication Details

Published in: Advances in Radiation Oncology

Volume 4, Issue 2, pp. 413-421

DOI: 10.1016/j.adro.2019.02.003

Field-Weighted Citation Impact: 8.51