Quantification of breast tissue index from MR data using fuzzy clustering

Abstract

The study objective was to develop a segmentation technique to quantify breast tissue and total breast volume from magnetic resonance imaging (MRI) data to obtain a breast tissue index (BTI) related to breast density. Our goal is to quantify MR breast density to improve breast cancer risk assessment for certain high-risk populations for whom mammography is of limited usefulness due to high breast density. A semi-automatic 3D segmentation technique was implemented based on a fuzzy c-means technique (FCM) to segment fibroglandular tissue from fat in the breast images. After validation on a phantom, our FCM technique was first used to test the breast tissue measures reproducibility in two consecutive MR examinations of the same patients. The technique was then applied to measure the BTI on 10 high-risk patients. Results of BTI obtained with the semi-automated FCM method were compared with BTI results for the same patients using two other techniques, manual delineation and global threshold. BTI measures correlated well with mammographic densities (Pearson coefficients r = 0.78 using MR manual delineation, and r = 0.75 using MR FCM). The breast tissue index could therefore become a common measure for future studies of using noncontrast MRI data.

Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction

“…Klifa [15] et al present a segmentation technique based on fuzzy clustering to quantify breast density from MRI data. Oliver et al [16] suggest an approach based on gross segmentation and the extraction of texture features of pixels with similar tissue appearance.…”

Consistency of breast density measured from the same women in four different MR scanners

“…5 Other methods that can measure quantitative breast density have been developed and evaluated; including volumetric measurements made based on 3D MRI. [6][7][8][9][10][11][12][13][14][15] However, so far there have not been published results demonstrating the association between MRIbased density parameters and cancer risk.…”

Differences in breast density assessment using mammography, tomosynthesis and MRI and their implications for practice

“…MRI has been used to calculate the water content of a human breast via slices or slabs and with segmentation of 3D images with tailored sequences [24][25][26][27][28][29][30]. It has been shown that percent MRI-density correlates strongly with mammographic PD; however, MRI, as also discussed above for DBT, has been shown to underestimate breast density compared with conventional mammography.…”