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Adipose tissue distribution in children: automated quantification using water and fat MRI
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology, Radiology.
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2010 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 32, no 1, 204-210 p.Article in journal (Refereed) Published
Abstract [en]

PURPOSE: To develop and validate a method for rapid acquisition and automated processing of magnetic resonance (MR) images for analysis of abdominal adipose tissue distribution in children. MATERIALS AND METHODS: The study included 21 (10 girls, 11 boys) healthy 5-year-old children. Rapid water and fat MR imaging (6 sec) was performed using a 2-point-Dixon technique on a 1.5T MR scanner using an 8-channel cardiac coil. An automated image processing algorithm was developed for automated segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT), respectively. The results from the fully automated analysis were compared to those from a semiautomated analysis, performed by three operators, from the same images. RESULTS: The automated analysis was seen to give results with strong correlation to the reference measurements (r >or= 0.997); however, the SAT volume was underestimated by 9.4 +/- 3.8%. The accuracy of the automated segmentation of VAT and SAT (TP: true positive, FP: false positive, mean +/- SD, %) was TP: 83.6 +/- 8.5, FP: 12.7 +/- 6.8; and TP: 89.9 +/- 3.6, FP: 0.7 +/- 0.3, respectively. CONCLUSION: A method for rapid imaging and fully automated postprocessing of abdominal adipose tissue distribution is presented. The method allows robust and time-efficient measurement of adipose tissue distribution in young children.

Place, publisher, year, edition, pages
2010. Vol. 32, no 1, 204-210 p.
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Medical and Health Sciences
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URN: urn:nbn:se:uu:diva-130474DOI: 10.1002/jmri.22193ISI: 000279439600025PubMedID: 20575078OAI: oai:DiVA.org:uu-130474DiVA: diva2:349735
Available from: 2010-09-08 Created: 2010-09-08 Last updated: 2017-12-12Bibliographically approved

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Kullberg, Joel

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