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Abstract #2472

The test-retest reliability of fat-water ratio MRI derived breast density measurements and automated breast segmentation

Jie Ding1, Patricia A Thompson2, Marilyn T Marron3, Maria Altbach3,4, Denise Roe3,5, Jean-Philippe Galons4, Cynthia A Thomson3, Fang Wang6, Alison Stopeck7, and Chuan Huang1,8,9

1Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States, 2Pathology, Stony Brook Medicine, Stony Brook, NY, United States, 3Cancer Center, University of Arizona, Tucson, AZ, United States, 4Medical Imaging, University of Arizona, Tucson, AZ, United States, 5Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, United States, 6Stony Brook Medicine, Stony Brook, NY, United States, 7Hematology and Oncology, Stony Brook Medicine, Stony Brook, NY, United States, 8Radiology, Stony Brook Medicine, Stony Brook, NY, United States, 9Psychiatry, Stony Brook Medicine, Stony Brook, NY, United States

It has been shown that breast density (BD) value derived from fat-water-ratio MRI (FWR-MRI) strongly correlates with standard digital mammogram derived BD. The fact that no ionizing radiation is associated with FWR-MRI makes it a lower-risk modality for long term BD monitoring and clinical trials. However, data regarding the individual and group level variability and reliability of this method needs to be established. Conventional approaches for FWR-MRI derived BD rely on manually drawn regions-of-interest. These processes are cumbersome and prone to measurement bias, which may limit the application of FWR-MRI derived BD. Automated breast segmentation has been proposed to resolve this problem and limited results to date are promising. Additional data including an evaluation of BD reliability from manual versus automated measurements is still needed. In this study, we evaluate the test-retest reliability of the FWR-MRI derived BD and the quality of data using manual versus automated breast segmentation. Our results demonstrate the high reliability of the FWR-MRI derived BD measure, Fra80, with a typical error of less than 0.02 for both automated and manual breast segmentation. Moreover, our automated breast segmentation protocol yields more reliable Fra80 BD measures compared to the labor-intense manual segmentation method.

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