Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young women

Qinmei Li, James Dormer, Priyanka Daryani, Deji Chen, Zhenfeng Zhang, Baowei Fei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2019
Subtitle of host publicationComputer-Aided Diagnosis
EditorsKensaku Mori, Horst K. Hahn
PublisherSPIE
ISBN (Electronic)9781510625471
DOIs
Publication statusPublished - Jan 1 2019
EventMedical Imaging 2019: Computer-Aided Diagnosis - San Diego, United States
Duration: Feb 17 2019Feb 20 2019

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10950
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2019: Computer-Aided Diagnosis
CountryUnited States
CitySan Diego
Period2/17/192/20/19

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ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Cite this

Li, Q., Dormer, J., Daryani, P., Chen, D., Zhang, Z., & Fei, B. (2019). Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young women. In K. Mori, & H. K. Hahn (Eds.), Medical Imaging 2019: Computer-Aided Diagnosis [1095044] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10950). SPIE. https://doi.org/10.1117/12.2512056