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Reproducible automated breast density measure with no ionizing radiation using fat-water decomposition MRI
- Source :
- Journal of Magnetic Resonance Imaging. 48:971-981
- Publication Year :
- 2018
- Publisher :
- Wiley, 2018.
-
Abstract
- BACKGROUND Increased breast density is a significant independent risk factor for breast cancer, and recent studies show that this risk is modifiable. Hence, breast density measures sensitive to small changes are desired. PURPOSE Utilizing fat-water decomposition MRI, we propose an automated, reproducible breast density measurement, which is nonionizing and directly comparable to mammographic density (MD). STUDY TYPE Retrospective study. POPULATION 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). FIELD STRENGTH/SEQUENCE The majority of MRI scans (59 scans) were performed with a 1.5T GE Signa scanner using radial IDEAL-GRASE sequence, while the remaining (seven scans) were performed with a 3T Siemens Skyra using 3D Cartesian 6-echo GRE sequence with a similar fat-water separation technique. ASSESSMENT 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-based breast density (MRD) to be comparable to MD. A previous breast density measurement, Fra80-the ratio of breast voxels with
- Subjects :
- education.field_of_study
Reproducibility
business.industry
Intraclass correlation
Concordance
Population
computer.software_genre
medicine.disease
Pearson product-moment correlation coefficient
030218 nuclear medicine & medical imaging
03 medical and health sciences
symbols.namesake
0302 clinical medicine
Breast cancer
Voxel
030220 oncology & carcinogenesis
symbols
Medicine
Radiology, Nuclear Medicine and imaging
Stage (cooking)
business
education
Nuclear medicine
computer
Subjects
Details
- ISSN :
- 10531807
- Volume :
- 48
- Database :
- OpenAIRE
- Journal :
- Journal of Magnetic Resonance Imaging
- Accession number :
- edsair.doi...........67ada8ed7e9b3dbd79fea94230fb92d1