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

Spraker MB, Wootton LS, Hippe DS, Ball KC, Peeken JC, Macomber MW, Chapman TR, Hoff MN, Kim EY, Pollack SM, Combs SE, Nyflot MJ (2019)

Publication Type: Journal article

Publication year: 2019

Journal

Advances in Radiation Oncology American Society for Radiation Oncology

Book Volume: 4

Pages Range: 413-421

Journal Issue: 2

DOI: 10.1016/j.adro.2019.02.003

Abstract

Purpose: Soft tissue sarcomas (STS) represent a heterogeneous group of diseases, and selection of individualized treatments remains a challenge. The goal of this study was to determine whether radiomic features extracted from magnetic resonance (MR) images are independently associated with overall survival (OS) in STS. Methods and Materials: This study analyzed 2 independent cohorts of adult patients with stage II-III STS treated at center 1 (N = 165) and center 2 (N = 61). Thirty radiomic features were extracted from pretreatment T1-weighted contrast-enhanced MR images. Prognostic models for OS were derived on the center 1 cohort and validated on the center 2 cohort. Clinical-only (C), radiomics-only (R), and clinical and radiomics (C+R) penalized Cox models were constructed. Model performance was assessed using Harrell's concordance index. Results: In the R model, tumor volume (hazard ratio [HR], 1.5) and 4 texture features (HR, 1.1-1.5) were selected. In the C+R model, both age (HR, 1.4) and grade (HR, 1.7) were selected along with 5 radiomic features. The adjusted c-indices of the 3 models ranged from 0.68 (C) to 0.74 (C+R) in the derivation cohort and 0.68 (R) to 0.78 (C+R) in the validation cohort. The radiomic features were independently associated with OS in the validation cohort after accounting for age and grade (HR, 2.4; P =.009). Conclusions: 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.

Involved external institutions

Washington University US United States (USA) (US) University of Washington US United States (USA) (US) Harvard University US United States (USA) (US) Technische Universität München (TUM) DE Germany (DE) Aurora St Luke's Medical Center US United States (USA) (US) Fred Hutchinson Cancer Research Center US United States (USA) (US)

How to cite

APA:

Spraker, M.B., Wootton, L.S., Hippe, D.S., Ball, K.C., Peeken, J.C., Macomber, M.W.,... Nyflot, M.J. (2019). MRI Radiomic Features Are Independently Associated With Overall Survival in Soft Tissue Sarcoma. Advances in Radiation Oncology, 4(2), 413-421. https://doi.org/10.1016/j.adro.2019.02.003

MLA:

Spraker, Matthew B., et al. "MRI Radiomic Features Are Independently Associated With Overall Survival in Soft Tissue Sarcoma." Advances in Radiation Oncology 4.2 (2019): 413-421.

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