Quantitative analysis of breast parenchymal patterns using 3D fibroglandular tissues segmented based on MRI

Abstract

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.

Figure 1

Three case examples are demonstrated, including one fatty breast (top row), one Type I case (intermingled pattern, middle row), and one Type C case (central pattern, bottom row). For each case, five axial view MR images from five imaging slices selected from superior to inferior directions are shown. There are no breast lesions on these images. The percent density is 5.4% for the fatty breast, 14.1% for the Type I case, and 13.9% for the Type C case.

Figure 2

The bar plot for comparing the (a) age, (b) fibroglandular tissue volume, and (c) the percent density among three subject groups. The fatty breast group (indicated as Type F) is significantly older, and has the smallest fibroglandular tissue volume and the lowest percent density compared to the intermingled type (Type I) and the central type (Type C). The Type I and Type C groups have comparable age, fibroglandular tissue volume, and the percent density, thus they cannot be separated based on these parameters.

Figure 3

Illustration of the calculation of the circularity and the convexity index. Only one slice is shown here as an example, but the analysis was performed in 3D. For circularity, a sphere with effective diameter D_eff is drawn, and the ratio between the fibroglandular tissue volume within the sphere and the total fibroglandular tissue volume is calculated as the circularity index. The intermingled pattern (top) has a circularity index of 0.42 and the central pattern (bottom) has a higher index of 0.86. For convexity, the minimum convex hull is drawn, and the ratio between the total fibroglandular tissue volume and the convex hall volume is calculated as the convexity index. The intermingled pattern (top) has a convexity index of 0.36 and the central pattern (bottom) has a higher index of 0.73.

Figure 4

Histogram of four morphological parameters differentiating the intermingled pattern (Type I, dashed curve) and the central pattern (Type C, solid curve), (a) circularity index, (b) convexity index, (c) irregularity index, and (d) compactness index. The intermingled pattern group has lower circularity and convexity, and higher irregularity and compactness compared to the central pattern group. The cases with high and low indices are illustrated in Figs. 5678.

Figure 5

The circularity index is sensitive to the spherical vs nonspherical shapes. The top case is an intermingled pattern with percent density=9.6% and circularity index=0.29, ranking 33 in all 230 cases. The bottom case is a central pattern with a similar percent density=9.8%, and a higher circularity index=0.58, ranking 187 in all 230 cases.

Figure 6

The convexity index is sensitive to the convex vs concave shapes. The top case is an intermingled pattern with percent density=10.9% and convexity index=0.20, ranking #30 in all 230 cases. The bottom case is a central pattern with percent density=11.6%, and a higher convexity index=0.46, ranking #180 in all 230 cases.

Figure 7

The irregularity index is sensitive to the irregular vs smooth margins. The top case is an intermingled pattern with percent density=15.1% and irregularity index=0.74, ranking #190 in all 230 cases. The bottom case is a central pattern with percent density=15.6%, and a lower irregularity index=0.54, ranking #26 in all 230 cases.

Figure 8

The compactness index is sensitive to both shape and margin. Round shape with smooth margin has a relatively low compactness index. The top case is an intermingled pattern with percent density=12.9% and compactness index=17.5, ranking #180 in all 230 cases. The bottom case is a central pattern with the percent density=11.8%, and a lower compactness index=6.7, ranking #32 in all 230 cases.

Figure 9

The ROC curves. When only using the compactness index the AUC is 0.84, and when using all four morphology parameters combined, the AUC is improved to 0.94.