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Hence, breast density measures sensitive to small changes are desired.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>Utilizing fat\u2010water decomposition MRI, we propose an automated, reproducible breast density measurement, which is nonionizing and directly comparable to mammographic density (MD).<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>Retrospective study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Population<\/jats:title><jats:p>The study included two sample sets of breast cancer patients enrolled in a clinical trial, for concordance analysis with MD (40 patients) and reproducibility analysis (10 patients).<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>The majority of MRI scans (59 scans) were performed with a 1.5T GE Signa scanner using radial IDEAL\u2010GRASE sequence, while the remaining (seven scans) were performed with a 3T Siemens Skyra using 3D Cartesian 6\u2010echo GRE sequence with a similar fat\u2010water separation technique.<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>After automated breast segmentation, breast density was calculated using FraGW, a new measure developed to reliably reflect the amount of fibroglandular tissue and total water content in the entire breast. Based on its concordance with MD, FraGW was calibrated to MR\u2010based breast density (MRD) to be comparable to MD. A previous breast density measurement, Fra80\u2014the ratio of breast voxels with &lt;80% fat fraction\u2014was also calculated for comparison with FraGW.<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Pearson correlation was performed between MD (reference standard) and FraGW (and Fra80). Test\u2013retest reproducibility of MRD was evaluated using the difference between test\u2013retest measures (\u0394<jats:sub>1\u20132<\/jats:sub>) and intraclass correlation coefficient (ICC).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Both FraGW and Fra80 were strongly correlated with MD (Pearson \u03c1: 0.96 vs. 0.90, both <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.0001). MRD converted from FraGW showed higher test\u2013retest reproducibility (\u0394<jats:sub>1\u20132<\/jats:sub> variation: 1.1%\u2009\u00b1\u20091.2%; ICC: 0.99) compared to MD itself (literature intrareader ICC \u22640.96) and Fra80.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>The proposed MRD is directly comparable with MD and highly reproducible, which enables the early detection of small breast density changes and treatment response.<\/jats:p><jats:p><jats:bold>Level of Evidence:<\/jats:bold> 3<\/jats:p><jats:p><jats:bold>Technical Efficacy:<\/jats:bold> Stage 1<\/jats:p><jats:p>J. Magn. Reson. Imaging 2018;48:971\u2013981.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.26041","type":"journal-article","created":{"date-parts":[[2018,4,9]],"date-time":"2018-04-09T20:16:34Z","timestamp":1523304994000},"page":"971-981","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Reproducible automated breast density measure with no ionizing radiation using fat\u2010water decomposition MRI"],"prefix":"10.1002","volume":"48","author":[{"given":"Jie","family":"Ding","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering Stony Brook University Stony Brook New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4762-1392","authenticated-orcid":false,"given":"Alison T.","family":"Stopeck","sequence":"additional","affiliation":[{"name":"Department of Hematology and Oncology Stony Brook Medicine Stony Brook New York USA"},{"name":"Stony Brook University 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