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Journal of Imaging Informatics in Medicine

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01-08-2018

Quantitative Volumetric K-Means Cluster Segmentation of Fibroglandular Tissue and Skin in Breast MRI

Authors: Anton Niukkanen, Otso Arponen, Aki Nykänen, Amro Masarwah, Anna Sutela, Timo Liimatainen, Ritva Vanninen, Mazen Sudah

Published in: Journal of Imaging Informatics in Medicine | Issue 4/2018

Abstract

Mammographic breast density (MBD) is the most commonly used method to assess the volume of fibroglandular tissue (FGT). However, MRI could provide a clinically feasible and more accurate alternative. There were three aims in this study: (1) to evaluate a clinically feasible method to quantify FGT with MRI, (2) to assess the inter-rater agreement of MRI-based volumetric measurements and (3) to compare them to measurements acquired using digital mammography and 3D tomosynthesis. This retrospective study examined 72 women (mean age 52.4 ± 12.3 years) with 105 disease-free breasts undergoing diagnostic 3.0-T breast MRI and either digital mammography or tomosynthesis. Two observers analyzed MRI images for breast and FGT volumes and FGT-% from T1-weighted images (0.7-, 2.0-, and 4.0-mm-thick slices) using K-means clustering, data from histogram, and active contour algorithms. Reference values were obtained with Quantra software. Inter-rater agreement for MRI measurements made with 2-mm-thick slices was excellent: for FGT-%, r = 0.994 (95% CI 0.990–0.997); for breast volume, r = 0.985 (95% CI 0.934–0.994); and for FGT volume, r = 0.979 (95% CI 0.958–0.989). MRI-based FGT-% correlated strongly with MBD in mammography (r = 0.819–0.904, P < 0.001) and moderately to high with MBD in tomosynthesis (r = 0.630–0.738, P < 0.001). K-means clustering-based assessments of the proportion of the fibroglandular tissue in the breast at MRI are highly reproducible. In the future, quantitative assessment of FGT-% to complement visual estimation of FGT should be performed on a more regular basis as it provides a component which can be incorporated into the individual’s breast cancer risk stratification.

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Title: Quantitative Volumetric K-Means Cluster Segmentation of Fibroglandular Tissue and Skin in Breast MRI
Authors: Anton Niukkanen
Otso Arponen
Aki Nykänen
Amro Masarwah
Anna Sutela
Timo Liimatainen
Ritva Vanninen
Mazen Sudah
Publication date: 01-08-2018
Publisher: Springer International Publishing
Published in: Journal of Imaging Informatics in Medicine / Issue 4/2018
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI: https://doi.org/10.1007/s10278-017-0031-1

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Quantitative Volumetric K-Means Cluster Segmentation of Fibroglandular Tissue and Skin in Breast MRI

Abstract

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Abstract

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