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Topography mapping of whole body adipose tissue using A fully automated and standardized procedure.
J Magn Reson Imaging. 2010 Feb; 31(2):430-9.JM

Abstract

PURPOSE

To obtain quantitative measures of human body fat compartments from whole body MR datasets for the risk estimation in subjects prone to metabolic diseases without the need of any user interaction or expert knowledge.

MATERIALS AND METHODS

Sets of axial T1-weighted spin-echo images of the whole body were acquired. The images were segmented using a modified fuzzy c-means algorithm. A separation of the body into anatomic regions along the body axis was performed to define regions with visceral adipose tissue present, and to standardize the results. In abdominal image slices, the adipose tissue compartments were divided into subcutaneous and visceral compartments using an extended snake algorithm. The slice-wise areas of different tissues were plotted along the slice position to obtain topographic fat tissue distributions.

RESULTS

Results from automatic segmentation were compared with manual segmentation. Relatively low mean deviations were obtained for the class of total tissue (4.48%) and visceral adipose tissue (3.26%). The deviation of total adipose tissue was slightly higher (8.71%).

CONCLUSION

The proposed algorithm enables the reliable and completely automatic creation of adipose tissue distribution profiles of the whole body from multislice MR datasets, reducing whole examination and analysis time to less than half an hour.

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Authors+Show Affiliations

Würslin C
Department of Diagnostic and Interventional Radiology, University of Tübingen, Tübingen, Germany. christian.wuerslin@med.uni-tuebingen.de
Machann J
No affiliation info available
Rempp H
No affiliation info available
Claussen C
No affiliation info available
Yang B
No affiliation info available
Schick F
No affiliation info available

MeSH

Adipose TissueAlgorithmsArtificial IntelligenceBody Fat DistributionGermanyHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificityWhole Body Imaging

Pub Type(s)

Journal Article

Language

eng

PubMed ID

20099357

Citation

Würslin, Christian, et al. "Topography Mapping of Whole Body Adipose Tissue Using a Fully Automated and Standardized Procedure." Journal of Magnetic Resonance Imaging : JMRI, vol. 31, no. 2, 2010, pp. 430-9.
Würslin C, Machann J, Rempp H, et al. Topography mapping of whole body adipose tissue using A fully automated and standardized procedure. J Magn Reson Imaging. 2010;31(2):430-9.
Würslin, C., Machann, J., Rempp, H., Claussen, C., Yang, B., & Schick, F. (2010). Topography mapping of whole body adipose tissue using A fully automated and standardized procedure. Journal of Magnetic Resonance Imaging : JMRI, 31(2), 430-9. https://doi.org/10.1002/jmri.22036
Würslin C, et al. Topography Mapping of Whole Body Adipose Tissue Using a Fully Automated and Standardized Procedure. J Magn Reson Imaging. 2010;31(2):430-9. PubMed PMID: 20099357.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Topography mapping of whole body adipose tissue using A fully automated and standardized procedure. AU - Würslin,Christian, AU - Machann,Jürgen, AU - Rempp,Hansjörg, AU - Claussen,Claus, AU - Yang,Bin, AU - Schick,Fritz, PY - 2010/1/26/entrez PY - 2010/1/26/pubmed PY - 2010/4/16/medline SP - 430 EP - 9 JF - Journal of magnetic resonance imaging : JMRI JO - J Magn Reson Imaging VL - 31 IS - 2 N2 - PURPOSE: To obtain quantitative measures of human body fat compartments from whole body MR datasets for the risk estimation in subjects prone to metabolic diseases without the need of any user interaction or expert knowledge. MATERIALS AND METHODS: Sets of axial T1-weighted spin-echo images of the whole body were acquired. The images were segmented using a modified fuzzy c-means algorithm. A separation of the body into anatomic regions along the body axis was performed to define regions with visceral adipose tissue present, and to standardize the results. In abdominal image slices, the adipose tissue compartments were divided into subcutaneous and visceral compartments using an extended snake algorithm. The slice-wise areas of different tissues were plotted along the slice position to obtain topographic fat tissue distributions. RESULTS: Results from automatic segmentation were compared with manual segmentation. Relatively low mean deviations were obtained for the class of total tissue (4.48%) and visceral adipose tissue (3.26%). The deviation of total adipose tissue was slightly higher (8.71%). CONCLUSION: The proposed algorithm enables the reliable and completely automatic creation of adipose tissue distribution profiles of the whole body from multislice MR datasets, reducing whole examination and analysis time to less than half an hour. SN - 1522-2586 UR - https://www.unboundmedicine.com/medline/citation/20099357/Topography_mapping_of_whole_body_adipose_tissue_using_A_fully_automated_and_standardized_procedure_ L2 - https://doi.org/10.1002/jmri.22036 DB - PRIME DP - Unbound Medicine ER -