Abstract
Introduction:
Given the considerable time and research cost of analyzing biomedical images to quantify adipose tissue volumes, automated image analysis methods are highly desirable. Hippo Fat™ is a new software program designed to automatically quantify adipose tissue areas from magnetic resonance images without user inputs. Hippo Fat™ has yet to be independently validated against commonly used image analysis software programs.
Objective:
Our aim was to compare estimates of VAT (visceral adipose tissue) and SAT (subcutaneous adipose tissue) using the new Hippo Fat™ software against those from a widely used, validated, computer-assisted manual method (slice-O-matic version 4.2, Tomovision, Montreal, CA, USA) to assess its potential utility for large-scale studies.
Methods:
A Siemens Magnetom Vision 1.5-T whole-body scanner and a T1-weighted fast-spin echo pulse sequence were used to collect multiple, contiguous axial images of the abdomen from a sample of 40 healthy adults (20 men) aged 18–77 years of age, with mean body mass index of 29 kg/m2 (range=19–43 kg/m2).
Results:
Hippo Fat™ provided estimates of VAT and SAT that were highly correlated with estimates using slice-O-matic (R2>0.9). Average VAT was 9.4% lower and average SAT was 3.7% higher using Hippo Fat™ compared to slice-O-matic; the overestimation of SAT tended to be greater among individuals with greater adiposity. Individual-level differences for VAT were also substantial; Hippo Fat™ gave estimates of VAT ranging from 1184 cm3 less to 566 cm3 more than estimates for the same person using slice-O-matic.
Conclusion:
Hippo Fat™ provides a rapid method of quantifying total VAT, although the method does not provide estimates that are interchangeable with slice-O-matic at either the group (mean) or individual level.
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Acknowledgements
This work was supported by Grants HD12252 and DK064870 from the National Institutes of Health, Bethesda, MA, USA.
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Demerath, E., Ritter, K., Couch, W. et al. Validity of a new automated software program for visceral adipose tissue estimation. Int J Obes 31, 285–291 (2007). https://doi.org/10.1038/sj.ijo.0803409
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DOI: https://doi.org/10.1038/sj.ijo.0803409
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