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. (c) 2010 Wiley-Liss, Inc.
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. (c) 2010 Wiley-Liss, Inc.
Authors: Michael S Middleton; William Haufe; Jonathan Hooker; Magnus Borga; Olof Dahlqvist Leinhard; Thobias Romu; Patrik Tunón; Gavin Hamilton; Tanya Wolfson; Anthony Gamst; Rohit Loomba; Claude B Sirlin Journal: Radiology Date: 2017-03-09 Impact factor: 11.105
Authors: Cheng William Hong; Soudabeh Fazeli Dehkordy; Jonathan C Hooker; Gavin Hamilton; Claude B Sirlin Journal: Top Magn Reson Imaging Date: 2017-12
Authors: Aziz H Poonawalla; Brett P Sjoberg; Jennifer L Rehm; Diego Hernando; Catherine D Hines; Pablo Irarrazaval; Scott B Reeder Journal: J Magn Reson Imaging Date: 2012-10-10 Impact factor: 4.813