| Automated quantification of muscle and fat in the thigh from water-, fat-, and nonsuppressed MR images. | |
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MedLine Citation:
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PMID: 22170747 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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PURPOSE: To introduce and validate an unsupervised muscle and fat quantification algorithm based on joint analysis of water-suppressed (WS), fat-suppressed (FS), and water and fat (nonsuppressed) volumetric magnetic resonance imaging (MRI) of the mid-thigh region. MATERIALS AND METHODS: We first segmented the subcutaneous fat by use of a parametric deformable model, then applied centroid clustering in the feature domain defined by the voxel intensities in WS and FS images to identify the intermuscular fat and muscle. In the final step we computed volumetric and area measures of fat and muscle. We applied this algorithm on datasets of water-, fat-, and nonsuppressed volumetric MR images acquired from 28 participants. RESULTS: We validated our tissue composition analysis against fat and muscle area measurements obtained from semimanual analysis of single-slice mid-thigh computed tomography (CT) images of the same participants and found very good agreement between the two methods. Furthermore, we compared the proposed approach with a variant that uses nonsuppressed images only and observed that joint analysis of WS and FS images is more accurate than the nonsuppressed only variant. CONCLUSION: Our MRI algorithm produces accurate tissue quantification, is less labor-intensive, and more reproducible than the original CT-based workflow and can address interparticipant anatomic variability and intensity inhomogeneity effects. J. Magn. Reson. Imaging 2011;. © 2011 Wiley Periodicals, Inc. |
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Authors:
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Sokratis Makrogiannis; Suraj Serai; Kenneth W Fishbein; Catherine Schreiber; Luigi Ferrucci; Richard G Spencer |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-12-14 |
Journal Detail:
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Title: Journal of magnetic resonance imaging : JMRI Volume: - ISSN: 1522-2586 ISO Abbreviation: - Publication Date: 2011 Dec |
Date Detail:
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Created Date: 2011-12-15 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9105850 Medline TA: J Magn Reson Imaging Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2011 Wiley Periodicals, Inc. |
Affiliation:
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National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA. makrogianniss@mail.nih.gov. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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