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Adipose tissue distribution in children: Automated quantification using water and fat MRI
Author(s) -
Kullberg Joel,
Karlsson AnnKatrine,
Stokland Eira,
Svensson PärArne,
Dahlgren Jovanna
Publication year - 2010
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.22193
Subject(s) - adipose tissue , magnetic resonance imaging , subcutaneous adipose tissue , medicine , automated method , segmentation , scanner , nuclear medicine , distribution (mathematics) , radiology , biomedical engineering , computer science , mathematics , artificial intelligence , mathematical analysis
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 ≥ 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. J. Magn. Reson. Imaging 2010. © 2010 Wiley‐Liss, Inc.