Computer-Aided Diagnosis

Breast density estimation from high spectral and spatial resolution MRI

[+] Author Affiliations
Hui Li, William A. Weiss, Milica Medved, Hiroyuki Abe, Gillian M. Newstead, Gregory S. Karczmar, Maryellen L. Giger

University of Chicago, Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States

J. Med. Imag. 3(4), 044507 (Dec 28, 2016). doi:10.1117/1.JMI.3.4.044507
History: Received August 19, 2016; Accepted December 5, 2016
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Abstract.  A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists’ breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 (p<0.0001) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 (p<0.0001) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 (p=0.0076) was observed between HiSS-based breast density estimations and radiologists’ BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Hui Li ; William A. Weiss ; Milica Medved ; Hiroyuki Abe ; Gillian M. Newstead, et al.
"Breast density estimation from high spectral and spatial resolution MRI", J. Med. Imag. 3(4), 044507 (Dec 28, 2016). ; http://dx.doi.org/10.1117/1.JMI.3.4.044507


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