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

doi:10.1117/12.2512056

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 proceeding › Conference 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 language	English (US)
Title of host publication	Medical Imaging 2019
Subtitle of host publication	Computer-Aided Diagnosis
Editors	Kensaku Mori, Horst K. Hahn
Publisher	SPIE
ISBN (Electronic)	9781510625471
DOIs	https://doi.org/10.1117/12.2512056
Publication status	Published - Jan 1 2019
Event	Medical Imaging 2019: Computer-Aided Diagnosis - San Diego, United States Duration: Feb 17 2019 → Feb 20 2019

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	10950
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2019: Computer-Aided Diagnosis
Country	United States
City	San Diego
Period	2/17/19 → 2/20/19

Fingerprint

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

Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young women. / Li, Qinmei; Dormer, James; Daryani, Priyanka; Chen, Deji; Zhang, Zhenfeng; Fei, Baowei.

Medical Imaging 2019: Computer-Aided Diagnosis. ed. / Kensaku Mori; Horst K. Hahn. SPIE, 2019. 1095044 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10950).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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 & HK Hahn (eds), Medical Imaging 2019: Computer-Aided Diagnosis., 1095044, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10950, SPIE, Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, United States, 2/17/19. https://doi.org/10.1117/12.2512056

@inproceedings{663bf056e0a548d0972a7b731bacec0d,

title = "Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young women",

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.",

author = "Qinmei Li and James Dormer and Priyanka Daryani and Deji Chen and Zhenfeng Zhang and Baowei Fei",

year = "2019",

month = "1",

day = "1",

doi = "10.1117/12.2512056",

language = "English (US)",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

publisher = "SPIE",

editor = "Kensaku Mori and Hahn, {Horst K.}",

booktitle = "Medical Imaging 2019",

note = "Medical Imaging 2019: Computer-Aided Diagnosis ; Conference date: 17-02-2019 Through 20-02-2019",

}

TY - GEN

T1 - Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young women

AU - Li, Qinmei

AU - Dormer, James

AU - Daryani, Priyanka

AU - Chen, Deji

AU - Zhang, Zhenfeng

AU - Fei, Baowei

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85068140448&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85068140448&partnerID=8YFLogxK

U2 - 10.1117/12.2512056

DO - 10.1117/12.2512056

M3 - Conference contribution

AN - SCOPUS:85068140448

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2019

A2 - Mori, Kensaku

A2 - Hahn, Horst K.

PB - SPIE

T2 - Medical Imaging 2019: Computer-Aided Diagnosis

Y2 - 17 February 2019 through 20 February 2019

ER -

Access to Document

10.1117/12.2512056