Semiautomatic software for measurement of abdominal muscle and adipose areas using computed tomography: A STROBE-compliant article.
Abdominal Fat
/ diagnostic imaging
Abdominal Muscles
/ diagnostic imaging
Adipose Tissue
/ diagnostic imaging
Adult
Aged
Female
Humans
Image Processing, Computer-Assisted
/ methods
Intra-Abdominal Fat
/ diagnostic imaging
Male
Middle Aged
Multidetector Computed Tomography
/ methods
Observer Variation
Reproducibility of Results
Retrospective Studies
Software
Statistics, Nonparametric
Subcutaneous Fat
/ diagnostic imaging
Journal
Medicine
ISSN: 1536-5964
Titre abrégé: Medicine (Baltimore)
Pays: United States
ID NLM: 2985248R
Informations de publication
Date de publication:
May 2019
May 2019
Historique:
entrez:
31
5
2019
pubmed:
31
5
2019
medline:
8
6
2019
Statut:
ppublish
Résumé
The aim of the study was to introduce our in-house software to measure the muscle and adipose area on axial computed tomography (CT) scans and to compare with various quantification methods.Our institutional review board approved this retrospective study and informed consent was waived. We developed in-house software to identify body composition analysis on CT scan, which semiautomatically operates 3 image processing steps. Abdominal images were obtained using multidetector row CT (MDCT). Two radiologists analyzed the same cross-sectional areas of subcutaneous fat, muscle, and visceral fat using the following techniques: manual measurements, Aquarius, ImageJ, and our newly developed software. We calculated an intraclass correlation coefficient (ICC) for comparison of muscle and fat areas quantified by various measurement methods using a 2-way random model. Interobserver agreement between the radiologists was also evaluated.Agreements in the measurement of subcutaneous fat and muscle areas were excellent among the methods (ICC = 0.962 and 0.897, respectively), and that of the visceral fat area was good (ICC = 0.822). In the subgroup analysis, ICC of the visceral fat area in the female group and in subjects with ascites was slightly lower than the other group (ICC = 0.742 and 0.787, respectively). The correlation coefficients between our software and other methods were relatively high (r = 0.854-0.996). Additionally, ICCs between both observers of our program for quantification of subcutaneous fat, muscle, and visceral fat areas were 0.999, 0.980, and 0.999, respectively.In conclusion, our method showed be reliable in quantifying muscle and adipose tissue using cross-sectional areas of MDCT with high reproducibility.
Identifiants
pubmed: 31145342
doi: 10.1097/MD.0000000000015867
pii: 00005792-201905310-00072
pmc: PMC6708812
doi:
Types de publication
Comparative Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e15867Références
J Gerontol A Biol Sci Med Sci. 2006 Oct;61(10):1059-64
pubmed: 17077199
Ann Surg Oncol. 2011 Dec;18(13):3579-85
pubmed: 21822551
Comput Biol Med. 1989;19(1):61-70
pubmed: 2917462
Gut. 2009 Jun;58(6):839-44
pubmed: 19174415
Diabetes Care. 1999 Sep;22(9):1471-8
pubmed: 10480511
Clin Mol Hepatol. 2016 Mar;22(1):1-6
pubmed: 27044760
Acad Radiol. 2006 Aug;13(8):963-8
pubmed: 16843848
Radiology. 1999 Apr;211(1):283-6
pubmed: 10189485
Appl Physiol Nutr Metab. 2008 Oct;33(5):997-1006
pubmed: 18923576
J Gerontol A Biol Sci Med Sci. 2012 Jan;67(1):48-55
pubmed: 21393423
Liver Transpl. 2013 Nov;19(11):1172-80
pubmed: 23960026
Clin Nutr. 2003 Dec;22(6):553-9
pubmed: 14613758
J Appl Physiol (1985). 1998 Jul;85(1):115-22
pubmed: 9655763
Am J Clin Nutr. 2007 Sep;86(3):633-8
pubmed: 17823427
Gut. 2010 Mar;59(3):341-7
pubmed: 19837679
Nutrition. 2015 Jan;31(1):193-9
pubmed: 25441595
Am J Hum Biol. 1999;11(1):61-68
pubmed: 11533934
Liver Transpl. 2012 Oct;18(10):1209-16
pubmed: 22740290
Arch Intern Med. 2005 Apr 11;165(7):777-83
pubmed: 15824297
Clin Gastroenterol Hepatol. 2012 Feb;10(2):166-73, 173.e1
pubmed: 21893129
Comput Methods Programs Biomed. 2017 Jun;144:97-104
pubmed: 28495009
Am J Clin Nutr. 2000 Feb;71(2):485-90
pubmed: 10648262
J Appl Physiol (1985). 2004 Dec;97(6):2333-8
pubmed: 15310748
J Am Geriatr Soc. 2007 May;55(5):769-74
pubmed: 17493199
J Digit Imaging. 2017 Aug;30(4):487-498
pubmed: 28653123
Nutr J. 2011 May 15;10:49
pubmed: 21569630
Radiology. 2019 Mar;290(3):669-679
pubmed: 30526356
IEEE Trans Image Process. 1998;7(3):359-69
pubmed: 18276256
J Obes. 2014;2014:495084
pubmed: 24782922
J Clin Gastroenterol. 2013 Nov-Dec;47(10):861-70
pubmed: 23751844
J Cachexia Sarcopenia Muscle. 2018 Oct;9(5):860-870
pubmed: 30371017
Clin Liver Dis. 2012 Feb;16(1):95-131
pubmed: 22321468
Arq Gastroenterol. 2006 Oct-Dec;43(4):269-74
pubmed: 17406753
Lancet Oncol. 2008 Jul;9(7):629-35
pubmed: 18539529
Nutrition. 1993 Sep-Oct;9(5):452-9
pubmed: 8286886
Int J Obes (Lond). 2008 Dec;32 Suppl 7:S76-82
pubmed: 19136995
Diabetes Care. 2003 Feb;26(2):372-9
pubmed: 12547865
Hepatology. 2005 Feb;41(2):257-64
pubmed: 15660389
Obesity (Silver Spring). 2007 Feb;15(2):370-6
pubmed: 17299110
IEEE J Transl Eng Health Med. 2018 Jun 28;6:1800610
pubmed: 30057864