Cross-field strength and multi-vendor reliability of MagDensity for MRI-based quantitative breast density analysis

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PURPOSE: Breast density (BD) is a significant risk factor for breast cancer, yet current assessment methods lack automation, quantification, and cross-platform consistency. This study aims to evaluate the reliability and cross-platform consistency of MagDensity, a novel magnetic resonance imaging (MRI)-based quantitative BD measure, across different imaging platforms. METHODS: Ten healthy volunteers participated in this prospective study, undergoing fat-water MRI scans on three scanners: 3T Siemens Prisma, 3T Siemens Biograph mMR, and 1.5T GE Signa. Great effort was made to schedule all scans within a narrow three-hour window on the same day to minimize any potential intra- or inter-day variations, requiring substantial logistical coordination. BD was assessed using the MagDensity technique, which included combining magnitude and phase images, applying a fat-water separation technique, employing an automated whole-breast segmentation algorithm, and quantifying the volumetric water fraction. Agreement between measures across scanners was analyzed using mean differences, two-tailed t-tests, Pearson's correlation, and Bland-Altman analysis. RESULTS: MagDensity measures obtained from the two 3T Siemens scanners demonstrated no statistically significant differences, with high correlation (Pearson's r > 0.99) and negligible mean differences (< 0.2%). Cross-platform comparison between the 3T Siemens and the 1.5T GE scanners showed larger mean differences (< 4.2%). However, after applying linear calibration, these variations were reduced to within ±0.2%, with strong inter-scanner correlation maintained (Pearson's r > 0.97). CONCLUSION: MagDensity showed strong intra-vendor consistency and promising cross-platform reliability after leave-one-out calibration. While full standardization remains a long-term goal, these findings provide clear evidence that scanner-related variability can be effectively mitigated through calibration. This technique offers a step further toward more consistent MRI-based BD quantification and may help enable broader clinical implementation.

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