Share Email Print
cover

Journal of Medical Imaging

Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data
Author(s): Wentian Guo; Hui Li; Yitan Zhu; Li Lan; Shengjie Yang; Karen Drukker; Elizabeth A. Morris; Elizabeth S. Burnside; Gary J. Whitman; Maryellen L. Giger; Yuan Ji; TCGA Breast Phenotype Research Group
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Genomic and radiomic imaging profiles of invasive breast carcinomas from The Cancer Genome Atlas and The Cancer Imaging Archive were integrated and a comprehensive analysis was conducted to predict clinical outcomes using the radiogenomic features. Variable selection via LASSO and logistic regression were used to select the most-predictive radiogenomic features for the clinical phenotypes, including pathological stage, lymph node metastasis, and status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Cross-validation with receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) was employed as the prediction metric. Higher AUCs were obtained in the prediction of pathological stage, ER, and PR status than for lymph node metastasis and HER2 status. Overall, the prediction performances by genomics alone, radiomics alone, and combined radiogenomics features showed statistically significant correlations with clinical outcomes; however, improvement on the prediction performance by combining genomics and radiomics data was not found to be statistically significant, most likely due to the small sample size of 91 cancer cases with 38 radiomic features and 144 genomic features.

Paper Details

Date Published: 23 September 2015
PDF: 12 pages
J. Med. Img. 2(4) 041007 doi: 10.1117/1.JMI.2.4.041007
Published in: Journal of Medical Imaging Volume 2, Issue 4
Show Author Affiliations
Wentian Guo, The Univ. of Chicago (United States)
Fudan Univ. (China)
Hui Li, The Univ. of Chicago (United States)
Yitan Zhu, NorthShore Univ. HealthSystem (United States)
Li Lan, The Univ. of Chicago (United States)
Shengjie Yang, NorthShore University Health System (United States)
Karen Drukker, The Univ. of Chicago (United States)
Elizabeth A. Morris, Memorial Sloan-Kettering Cancer Ctr. (United States)
Elizabeth S. Burnside, Univ. of Wisconsin Hospitals and Clinics (United States)
Gary J. Whitman, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Maryellen L. Giger, The Univ. of Chicago (United States)
Yuan Ji, The Univ. of Chicago (United States)
NorthShore Univ. HealthSystem (United States)
TCGA Breast Phenotype Research Group, http://www.cancerimagingarchive.net/ (United States)


© SPIE. Terms of Use
Back to Top