Purpose: Mammographic density and breast parenchymal patterns (the relative distribution of fatty and fibroglandular tissue) have been shown to be associated with the risk of developing breast cancer. Percent breast density as determined by mammography is a well-established risk factor, but on the other hand, studies on parenchymal pattern have been scarce, possibly due to the lack of reliable quantitative parameters that can be used to analyze parenchymal tissue distribution. In this study the morphology of fibroglandular tissue distribution was analyzed using three-dimensional breast MRI, which is not subject to the tissue overlapping problem.
Methods: Four parameters, circularity, convexity, irregularity, and compactness, which are sensitive to the shape and margin of segmented fibroglandular tissue, were analyzed for 230 patients. Cases were assigned to one of two distinct parenchymal breast patterns: Intermingled pattern with intermixed fatty and fibroglandular tissue (Type I, N = 141), and central pattern with confined fibroglandular tissue inside surrounded by fatty tissue outside (Type C, N = 89). For each analyzed parameter, the differentiation between these two patterns was analyzed using a two-tailed t-test based on transformed parameters to normal distribution, as well as distribution histograms and ROC analysis.
Results: These two groups of patients were well matched both in age (50 +/- 11 vs 50 +/- 11) and in fibroglandular tissue volume (Type I: 104 +/- 62 cm3 vs Type C: 112 +/- 73 cm3). Between Type I and Type C breasts, all four morphological parameters showed significant differences that could be used to differentiate between the two breast types. In the ROC analysis, among all four parameters, the "compactness" could achieve the highest area under the curve of 0.84, and when all four parameters were combined, the AUC could be further increased to 0.94.
Conclusions: The results suggest that these morphological parameters analyzed from 3D MRI can be used to distinguish between intermingled and central dense tissue distribution patterns, and hence may be used to characterize breast parenchymal pattern quantitatively. The availability of these quantitative morphological parameters may facilitate the investigation of the relationship between parenchymal pattern and breast cancer risk.