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Proceedings Paper

Automated quantification of adipose and skeletal muscle tissue in whole-body MRI data for epidemiological studies
Author(s): Diana Wald; Birgit Teucher; Julien Dinkel; Rudolf Kaaks; Stefan Delorme; Hans-Peter Meinzer; Tobias Heimann
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Paper Abstract

The ratio between the amount of adipose and skeletal muscle tissue is an important determinant of metabolic health. Recent developments in MRI technology allow whole body scans to be performed for accurate assessment of body composition. In the present study, a total of 194 participants underwent a 2-point Dixon MRI sequence of the whole body. A fully automated image segmentation method quantifies the amount of adipose and skeletal muscle tissue by applying standard image processing techniques including thresholding, region growing and morphological operators. The adipose tissue is further divided into subcutaneous and visceral adipose tissue by using statistical shape models. All images were visually inspected. The quantitative analysis was performed on 44 whole-body MRI data using manual segmentations as ground truth data. We achieved 3.3% and 6.3% of relative volume difference between the manual and automated segmentation of subcutaneous and visceral adipose tissue, respectively. The validation of skeletal muscle tissue segmentation resulted in a relative volume difference of 7.8 ± 4.2% and a volumetric overlap error of 6.4 ± 2.3 %. To our knowledge, we are first to present a fully automated method which quantifies adipose and skeletal muscle tissue in whole-body MRI data. Due to the fully automated approach, results are deterministic and free of user bias. Hence, the software can be used in large epidemiological studies for assessing body fat distribution and the ratio of adipose to skeletal muscle tissue in relation to metabolic disease risk.

Paper Details

Date Published: 23 February 2012
PDF: 7 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 831519 (23 February 2012); doi: 10.1117/12.911290
Show Author Affiliations
Diana Wald, Deutsches Krebsforschungszentrum (Germany)
Birgit Teucher, Deutsches Krebsforschungszentrum (Germany)
Julien Dinkel, Deutsches Krebsforschungszentrum (Germany)
Rudolf Kaaks, Deutsches Krebsforschungszentrum (Germany)
Stefan Delorme, Deutsches Krebsforschungszentrum (Germany)
Hans-Peter Meinzer, Deutsches Krebsforschungszentrum (Germany)
Tobias Heimann, Deutsches Krebsforschungszentrum (Germany)


Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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