Table 5.
Performance of MRI-based methods to measure fibroglandular tissue percentages compared to mammographic breast density measurements. A review of the literature
| Pertuz et al. [28] | Nayeem et al. [29] | Wang et al. [30] | Tagliafico et al. [41] | Engeland et al. [25] | Petridou et al. [18] | Present study | |
|---|---|---|---|---|---|---|---|
| N of patients (breasts) | 68 (136) | 137 (137) | 99 (99) | 48 (48) | 22 (44) | 40 (80) | 72 (105) |
| Mean age (years) | 52 | 35.9 | 47.2 | 41 | NA | NA | 52.4 |
| MRI field strength, sequence | 1.5-T, non-enhanced T1-W without fat suppression | 1.5 T, 3DGRE and STIR | 1.5-T and 3-T, T1-W non-contrast fat-saturated | 3 T, ideal | 1.5-T, T1-W FLASH-3D | 3-T, spoiled gradient echo | 3-T, T1-W fast field echo |
| Mammography device | FFDM and DBT | FFDM | FFDM | FFDM and DBT | FFDM | FFDM | FFDM and DBT |
| MRI slice (mm) | 2.4–3.5 | 1.5 [3DGRE], 2 [STIR] | 2 | NA | 1.5 | 1.8 | 0.7–4.0 |
| MRI analysis method | Atlas-aided fuzzy C-means method | Curve-fitting algorithm (PeakFit 4.0) | Fuzzy C-means method | Semi-automatic maximum entropy thresholding | Semi-automatic thresholding and segmenting | Automatic segmentation with AMRA sequence | Semi-automatic K-means method with active contour segmentation |
| Mammography analysis method | DBT: fully automated algorithm; FFDM: Volpara 1.5 |
Histogram segmentation method (HSM), mathematical algorithm based on DICOM headers (MATH) | Single-energy X-ray absorptiometry (SXA), Quantra 3.2, Volpara 1.4.3 | Semi-automatic maximum entropy thresholding | Calculation based on DICOM headers and empirical data from literature | Visual evaluation, four-quartile BI-RADS scale | Quantra 2.1.0 |
| Agreement between MRI and mammography: | |||||||
| Breast volume | DBT: r = 0.95 FFDM: r = 0.96 |
3DGRE: r = 0.94 STIR: r = 0.99 |
SXA: R
2 = 0.91 Quantra: R 2 = 0.91 Volpara: R 2 = 0.91 |
NA | NA | NA | FFDM: r = 0.861–0.967 |
| Fibroglandular tissue percentage | DBT: r = 0.88 FFDM: r = 0.84 |
3DGRE: r = 0.84–0.89 STIR: r = 0.83–0.86 |
SXA: R
2 = 0.51 Quantra: R 2 = 0.51 Volpara: R 2 = 0.73 |
DBT: r = 0.95 FFDM: r = 0.87 |
r = 0.94 | r = 0.73–0.75 | FFDM: r = 0.819–0.904 |
| Fibroglandular tissue volume | DBT: r = 0.67 FFDM: r = 0.61 |
3DGRE: r = 0.71–0.91 STIR: r = 0.72–0.87 |
SXA: R
2 = 0.55* Quantra: R 2 = 0.40* Volpara: R 2 = 0.63* |
NA | r = 0.97 | NA | FFDM: r = 0.659–0.811 |
MRI, magnetic resonance imaging; FFDM, full-field digital mammography; DBT, digital breast tomosynthesis; AMRA, advanced MR analytics; Quantra, automated software to assess breast density; Volpara, automated software to assess breast density; SXA, single-energy X-ray absorptiometry
*For logarithmic fibroglandular volume