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Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young women
Author(s): Qinmei Li; James Dormer; Priyanka Daryani; Deji Chen; Zhenfeng Zhang; Baowei Fei
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Paper Abstract

Breast cancer in young women is commonly aggressive, in part because the proportion of high-grade, triple-negative (TN) tumor is too high. There are certain limitations in the detection of biopsies or surgical specimens which only select part of tumor sample tissue and ignore the possible heterogeneity of tumors. In clinical practice, MRI is used for the diagnosis of breast cancer. MRI-based radiomics is a developing approach that may provide not only the diagnostic value for breast cancer but also the predictive or prognostic associations between the images and biological characteristics. In this work, we used radiomics methods to analyze MR images of breast cancer in 53 young women, and correlated the radiomics data with molecular subtypes. The results indicated a significant difference between TN type and non-TN type of breast cancer in young women on the radiomics features based on T2-weighted MR images. This may be helpful for the identification of TN type and guiding the therapeutic strategies.

Paper Details

Date Published: 13 March 2019
PDF: 9 pages
Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 1095044 (13 March 2019); doi: 10.1117/12.2512056
Show Author Affiliations
Qinmei Li, The Univ. of Texas at Dallas (United States)
The Second Affiliated Hospital of Guangzhou Medical Univ. (China)
James Dormer, The Univ. of Texas at Dallas (United States)
Priyanka Daryani, Univ. of Texas Southwestern Medical Ctr. (United States)
Deji Chen, The Second Affiliated Hospital of Guangzhou Medical Univ. (China)
Zhenfeng Zhang, The Second Affiliated Hospital of Guangzhou Medical Univ. (China)
Baowei Fei, The Univ. of Texas at Dallas (United States)
Univ. of Texas Southwestern Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 10950:
Medical Imaging 2019: Computer-Aided Diagnosis
Kensaku Mori; Horst K. Hahn, Editor(s)

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