Software for automated MRI-based quantification of abdominal fat and preliminary evaluation in morbidly obese patients

Journal of Magnetic Resonance Imaging

Volumn 37, Issue 5, 2013, Pages 1144-1150

  Thörmer, Gregor ^a   Bertram, Henriette Helene ^a   Garnov, Nikita ^a   Peter, Veronika ^a   Schütz, Tatjana ^a   Shang, Edward ^a   Blüher, Matthias ^a   Kahn, Thomas ^a   Busse, Harald ^a  

^a UNIVERSITY HOSPITAL LEIPZIG   (Germany)

Author keywords

adipose tissue; intra abdominal fat; MRI; obesity; software

Indexed keywords

ADULT; ARTICLE; AUTOANALYSIS; AUTOMATION; CLINICAL ARTICLE; COMPUTER PROGRAM; CORRELATION ANALYSIS; FEMALE; HUMAN; IMAGE PROCESSING; INTRAABDOMINAL FAT; MALE; MORBID OBESITY; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; SUBCUTANEOUS FAT; TIME;

ABDOMINAL FAT; ADIPOSITY; ADOLESCENT; ADULT; ALGORITHMS; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; OBESITY, MORBID; OBSERVER VARIATION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE; YOUNG ADULT;

EID: 84876501496     PISSN: 10531807     EISSN: 15222586     Source Type: Journal    
DOI: 10.1002/jmri.23890     Document Type: Article

References (24)

1. World Health Organization. Obesity and overweight. Geneva: WHO. 2011. Available at: http://www.who.int/mediacentre/factsheets/fs311/en/. Accessed 14 March 2012.
2. Wajchenberg BL,. Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. Endocr Rev 2000; 21: 697-738.
3. Miyazaki Y, DeFronzo RA,. Visceral fat dominant distribution in male type 2 diabetic patients is closely related to hepatic insulin resistance, irrespective of body type. Cardiovasc Diabetol 2009; 8: 44.
4. Prentice AM, Jebb SA,. Beyond body mass index. Obes Rev 2001; 2: 141-147.
5. Lancaster JL, Ghiatas AA, Alyassin A, Kilcoyne RF, Bonora E, DeFronzo RA,. Measurement of abdominal fat with T1-weighted MR images. J Magn Reson Imaging 1991; 1: 363-369.
6. Machann J, Thamer C, Schnoedt B, et al. Standardized assessment of whole body adipose tissue topography by MRI. J Magn Reson Imaging 2005; 21: 455-462.
7. Gronemeyer SA, Steen RG, Kauffman WM, Reddick WE, Glass JO,. Fast adipose tissue FAT. assessment by MRI. Magn Reson Imaging 2000; 18: 815-818.
8. Positano V, Gastaldelli A, Sironi AM, Santarelli MF, Lombardi M, Landini L,. An accurate and robust method for unsupervised assessment of abdominal fat by MRI. J Magn Reson Imaging 2004; 20: 684-689.
9. Kullberg J, Ahlström H, Johansson L, Frimmel H,. Automated and reproducible segmentation of visceral and subcutaneous adipose tissue from abdominal MRI. Int J Obes 2007; 31: 1806-1817.
10. Machann J, Thamer C, Stefan N, et al. Follow-up whole-body assessment of adipose tissue compartments during a lifestyle intervention in a large cohort at increased risk for type 2 diabetes. Radiology 2010; 257: 353-363.
11. Bonekamp S, Ghosh P, Crawford S, et al. Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging. Int J Obes 2008; 32: 100-111.
12. Positano V, Cusi K, Santarelli MF, et al. Automatic correction of intensity inhomogeneities improves unsupervised assessment of abdominal fat by MRI. J Magn Reson Imaging 2008; 28: 403-410.
13. Ciesielski KC, Udupa JK, Saha PK, Zhuge Y,. Iterative relative fuzzy connectedness for multiple objects with multiple seeds. Comput Vis Image Underst 2007; 107: 160-182.
14. Kullberg J, Brandberg J, Angelhed J-E, et al. Whole-body adipose tissue analysis: comparison of MRI, CT and dual energy X-ray absorptiometry. Br J Radiol 2009; 82: 123-130.
15. Sturm R,. Increases in morbid obesity in the USA: 2000-2005. Public Health 2007; 121: 492-496.
16. Runkel N, Colombo-Benkmann M, Hüttl TP, et al. Evidence-based German guidelines for surgery for obesity. Int J Colorectal Dis 2011; 26: 397-404.
17. Vovk U, Pernus F, Likar B,. A review of methods for correction of intensity inhomogeneity in MRI. IEEE Trans Med Imaging 2007; 26: 405-421.
18. Kullberg J, Angelhed J-E, Lönn L, et al. Whole-body T1 mapping improves the definition of adipose tissue: consequences for automated image analysis. J Magn Reson Imaging 2006; 24: 394-401.
19. Kullberg J, Johansson L, Ahlström H, et al. Automated assessment of whole-body adipose tissue depots from continuously moving bed MRI: a feasibility study. J Magn Reson Imaging 2009; 30: 185-193.
20. Bezdek JC, Hall LO, Clarke LP,. Review of MR image segmentation techniques using pattern recognition. Med Phys 1993; 20: 1033-1048.
21. Donnelly LF, O'Brien KJ, Dardzinski BJ, et al. Using a phantom to compare MR techniques for determining the ratio of intraabdominal to subcutaneous adipose tissue. AJR Am J Roentgenol 2003; 180: 993-998.
22. Wittsack H-J, Kapitza C, Cohnen M, et al. [Interactive thresholded volumetry of abdominal fat using breath-hold t1-weighted magnetic resonance imaging.] Rofo 2006; 178: 810-815.
23. Elbers JM, Haumann G, Asscheman H, Seidell JC, Gooren LJ,. Reproducibility of fat area measurements in young, non-obese subjects by computerized analysis of magnetic resonance images. Int J Obes Relat Metab Disord 1997; 21: 1121-1129.
24. Peng Q, McColl RW, Wang J, Chia JM, Weatherall PT,. Water-saturated three-dimensional balanced steady-state free precession for fast abdominal fat quantification. J Magn Reson Imaging 2005; 21: 263-271.