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Cross-field strength and multi-vendor reliability of MagDensity for MRI-based quantitative breast density analysis
Jia Ying1,2, Renee Cattell2,3, Chuan Huang1,4
1Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, United States of America.
Plos One
|June 24, 2025
Summary
MagDensity, a novel MRI technique, offers reliable breast density (BD) quantification across different scanners. Calibration effectively reduces scanner variability, paving the way for broader clinical use in breast cancer risk assessment.
Area of Science:
- Medical Imaging
- Radiology
- Biophysics
Background:
- Breast density (BD) is a critical factor in breast cancer risk assessment.
- Current BD assessment methods lack automation, quantification, and cross-platform consistency.
- Magnetic resonance imaging (MRI) offers potential for quantitative BD measurement.
Purpose of the Study:
- To evaluate the reliability and cross-platform consistency of MagDensity, an MRI-based quantitative BD measure.
- To assess MagDensity's performance across different MRI scanner platforms (Siemens and GE).
Main Methods:
- Ten healthy volunteers underwent fat-water MRI scans on three different scanners (3T Siemens Prisma, 3T Siemens Biograph mMR, 1.5T GE Signa).
- Scans were performed on the same day within a three-hour window to minimize variations.
- MagDensity technique involved automated segmentation and volumetric water fraction quantification.
Main Results:
- High intra-vendor consistency was observed between the two 3T Siemens scanners (Pearson's r > 0.99).
- Initial cross-platform differences between 3T Siemens and 1.5T GE scanners were reduced to within ±0.2% after linear calibration.
- Strong inter-scanner correlation (Pearson's r > 0.97) was maintained after calibration.
Conclusions:
- MagDensity demonstrates strong intra-vendor consistency and promising cross-platform reliability.
- Scanner-related variability in BD quantification can be effectively mitigated through calibration.
- This technique advances consistent MRI-based BD quantification, supporting potential clinical implementation.
