Quantification of abdominal fat depots in rats and mice during obesity and weight loss interventions

PLoS ONE

Volumn 9, Issue 10, 2014, Pages

  Bhanu Prakash, K N ^a   Gopalan, Venkatesh ^a   Lee, Swee Shean ^a   Velan, S Sendhil ^a  

^a AGENCY FOR SCIENCE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ALGORITHM; ANIMAL EXPERIMENT; ANIMAL MODEL; ANIMAL POSITIONING; ANIMAL TISSUE; ARTICLE; ARTIFACT; AUTOANALYSIS; CALORIC RESTRICTION; CONTROLLED STUDY; CRADLE DISTURBANCE; DIXON IMAGING; ECHOGRAPHY; EX VIVO STUDY; FAST SPIN ECHO; FAT QUANTIFICATION; HYBRID GEODESIC REGION BASED CURVE EVOLUTION ALGORITHM; IMAGE ANALYSIS; INTRAABDOMINAL FAT; KINESIOTHERAPY; LIPID ANALYSIS; LIPID STORAGE; LUMBAR VERTEBRA; MAGNETIC DRIFT; MAGNETIC RESONANCE SEQUENCE; MALE; MOUSE; NOISE; NONHUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; OBESITY; PHYSICAL PARAMETERS; RADIOLOGICAL PARAMETERS; RAT; REPRODUCIBILITY; SUBCUTANEOUS FAT; WEIGHT REDUCTION; ABDOMINAL FAT; ANIMAL; BODY FAT DISTRIBUTION; LIPID DIET; PATHOLOGY;

MUS; RATTUS;

ABDOMINAL FAT; ALGORITHMS; ANIMALS; BODY FAT DISTRIBUTION; DIET, HIGH-FAT; MAGNETIC RESONANCE IMAGING; MICE; OBESITY; RATS; REPRODUCIBILITY OF RESULTS; WEIGHT LOSS;

EID: 84907887481     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0108979     Document Type: Article

References (33)

1. Després JP (2012) Body Fat Distribution and Risk of Cardiovascular Disease: An Update. Circulation (126): 1301-1313.
2. Wagenknecht LE, Langefeld CD, ScherzingerAL, Norris JM, Haffner SM, et al. (2003) Insulin Sensitivity, Insulin Secretion, and Abdominal Fat - The Insulin Resistance Atherosclerosis Study (IRAS) Family Study. Diabetes 52(10): 2490-2496.
3. Goodpaster BH, Thaete FL, Simoneau JA, Kelley DE (1997) Subcutaneous abdominal fat and thigh muscle composition predict insulin sensitivity independently of visceral fat. Diabetes 46: 1579-1585.
4. Garg A (2004) Regional adiposity and insulin resistance. J Clin Endocrinol Metab 89: 4206-4210.
5. Klein S (2004) The case of visceral fat: argument for the defense. J Clin Invest 113: 1530-1532.
6. Ranefall P, Bidar AW, Hockings PD (2009) Automatic segmentation of intra-abdominal and subcutaneous adipose tissue in 3D whole mouse MRI. J Magn Reson Imaging 30: 554-560.
7. Yaligar J, Gopalan V, Kiat OW, Sugii S, Guanghou S, et al. (2014) Evaluation of Dietary Effects on Hepatic Lipids in High Fat and Placebo Diet Fed Rats by In Vivo MRS and LC-MS Techniques. PLOS One 9(3): 14-36, DOI: 10.1371/journal.pone.0091436.
8. Reeder SB, Cruite I, Hamilton G, Sirlin CB (2011) Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy, J Magn Reson Imaging 34(4): 729-749. doi: 10.1002/jmri.22580.
9. Shen W, Punyanitya M, Wang Z, Gallagher D, St-Onge MP, et al. (2004) Visceral adipose tissue: relations between single-slice areas and total volume. Am J Roentgenol 80: 271-278.
10. Bonekamp S, Ghosh P, Crawford S, Solga SF, Horska A, et al. (2008) Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging. Int J Obes 32: 100-111.
11. Armao D, Guyon JP, Firat Z, Brown MA, Semelka RC (2006) Accurate quantification of visceral adipose tissue (VAT) using water-saturation MRI and computer segmentation: preliminary results. J Magn Reson Imaging 23: 736-741.
12. Kullberg J, Ahlstroem H, Johansson L, Frimmel H (2007) Automated and reproducible segmentation of visceral and subcutaneous adipose tissue from abdominal MRI. Int J Obes 31: 1806-1817.
13. Thörmer G, Bertram HH, Peter V, Schütz T, Shang E, et al. (2013) Software for Automated MRI-Based Quantification of Abdominal Fat and Preliminary Evaluation in Morbidly Obese Patients. J Magn Reson Imaging 37: 1144-1155.
14. Tang Y, Sharma P, Marvin D, Simerly NR, Moats A (2011) Automatic Abdominal Fat Assessment in Obese Mice using a Segmental Shape Model. J Magn Reson Imaging 34: 866-873.
15. Kullberg J, Karlsson AK, Stokland E, Svensson PA, Dahlgren J (2010) Adipose tissue distribution in children: automated quantification using water and fat MRI. J Magn Reson Imaging 32: 204-210.
16. Chae Y, Jeong MG, Kim D (2007) Three dimensional volume measurement of mice abdominal fat in magnetic resonance images. In: 9th International Conference on e-Health Networking, Application and Services, Taipei, 252-255.
17. Siegel MJ, Hildebolt CF, Bae KT, Hong C, White NH (2007) Total and intra-abdominal fat distribution in preadolescents and adolescents: measurement with MR imaging. Radiology 242: 846-56.
18. Udupa JK, Samarasekera S (1996) Fuzzy connectedness and object definition: theory, algorithms, and applications in image segmentation. Graph Models Image Process 58: 246-261.
19. Kass M, Witkin A, Terzopoulos D (1987)Snakes: active contour models. Int'l J. Comp. Vis., 1: 321-331.
20. Osher S, Sethian J (1988) Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations. J. Comput. Phys., 79(1): 2-49.
21. Lankton S, Nain D, Yezzi A, Tannenbaum A (2007) Hybrid Geodesic Region-based Curve Evolutions for Image Segmentation. Proceedings of SPIE Medical Imaging, 6510: 65104U-1, doi: 10.1117/12.709700.
22. Lankton S, Tannenbaum A (2008) Localizing Region-Based Active Contours. IEEE Trans on Image Processing 17(11): 2029-2039.
23. Caselles V, Kimmel R, Sapiro G (1997) Geodesic active contours. Int. J. of Computer Vision 22: 61-79.
24. Perona P, Malik J (1990) Scale-space and edge detection using anisotropic diffusion. IEEE Trans on Pattern Analysis and Machine Intelligence 12(7): 629-39.
25. Bezdek JC (1981) Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York.
26. Farvid MS, Ng TW, Chan DC, Barret PH, Watts GF (2005) Association of adiponectin and resistin with adipose tissue compartments, insulin resistance and dyslipidaemia. Diabetes, Obesity and Metabolism 7(4): 406-413. doi: 10.1111/j.1463-1326.2004.00410.x. PMID 15955127.
27. Koch GG (1982) Intraclass correlation coefficient. Encyclopedia of Statistical Sciences 4. New York: John Wiley & Sons: 213-217.
28. Ibrahim MM (2010) Subcutaneous and visceral adipose tissue: structural and functional differences. Obesity Rev 11(1): 11-18. doi: 10.1111/j.1467-789X.2009.00623.x.
29. Li Y, Bujo H, Takahashi K, Shibasaki M, Zhu Y, et al. (2003) Visceral fat: higher responsiveness of fat mass and gene expression to calorie restriction than subcutaneous fat. Exp Biol Med (Maywood) 228(10): 1118-1123.
30. Abe T, Kawakami Y, Sugita M, Fukunaga T (1997) Relationship between training frequency and subcutaneous and visceral fat in women. Medicine and Science in Sports and Exercise 29: 1549-1553.
31. Hickey MS, Houmard JA, Considine RV, Tyndall GL, Midgette JB, et al. (1997) Gender-dependent effects of exercise training on serum leptin levels in humans. Am J Physiol 272(4 Pt 1): E562-566.
32. Elliott JM, Walton DM, Rademaker A, Parrish TB (2013) Quantification of cervical spine muscle fat: a comparison between T1-weighted and multi-echo gradient echo imaging using a variable projection algorithm (VARPRO) BMC Medical Imaging 13: 30. doi: 10.1186/1471-2342-13-30.
33. Wu HH, Lee JH, Nishimura DG (2009) Fat/Water Separation Using a Concentric Rings Trajectory. Magn Reson Med 61(3): 639-649. doi: 10.1002/mrm.21865.