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Magnetic Resonance Materials in Physics, Biology and Medicine

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11.01.2016 | Research Article

A method for the automatic segmentation of brown adipose tissue

verfasst von: K. N. Bhanu Prakash, Hussein Srour, Sendhil S. Velan, Kai-Hsiang Chuang

Erschienen in: Magnetic Resonance Materials in Physics, Biology and Medicine | Ausgabe 2/2016

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Abstract

Objective

Brown adipose tissue (BAT) plays a key role for thermogenesis in mammals and infants. Recent confirmation of BAT presence in adult humans has aroused great interest for its potential to initiate weight-loss and normalize metabolic disorders in diabetes and obesity. Reliable detection and differentiation of BAT from the surrounding white adipose tissue (WAT) and muscle is critical for assessment/quantification of BAT volume. This study evaluates magnetic resonance (MR) acquisition for BAT and the efficacy of different automated methods for MR features-based BAT segmentation to identify the best suitable method.

Materials and methods

Multi-point Dixon and multi-echo T₂ spin-echo images were acquired from 12 mice using an Agilent 9.4T scanner. Four segmentation methods: multidimensional thresholding (MTh); region-growing (RG); fuzzy c-means (FCM) and neural-network (NNet) were evaluated for the interscapular region and validated against manually defined BAT, WAT and muscle.

Results

Statistical analysis of BAT segmentation yielded a median Dice-Statistical-Index, and sensitivity of 89. 92 % for NNet, 82. 86 % for FCM, 72. 74 % for RG, and 72. 70 %, for MTh, respectively.

Conclusion

This study demonstrates that NNet improves the specificity to BAT from surrounding tissue based on 3-point Dixon and T₂ MRI. This method facilitates quantification and longitudinal measurement of BAT in preclinical-models and human subjects.

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Titel: A method for the automatic segmentation of brown adipose tissue
verfasst von: K. N. Bhanu Prakash
Hussein Srour
Sendhil S. Velan
Kai-Hsiang Chuang
Publikationsdatum: 11.01.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Magnetic Resonance Materials in Physics, Biology and Medicine / Ausgabe 2/2016
Print ISSN: 0968-5243
Elektronische ISSN: 1352-8661
DOI: https://doi.org/10.1007/s10334-015-0517-0

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A method for the automatic segmentation of brown adipose tissue

Abstract

Objective

Materials and methods

Results

Conclusion

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Abstract

Objective

Materials and methods

Results

Conclusion

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