Half-body MRI volumetry of abdominal adipose tissue in patients with obesity

2Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: The purpose of this study was to determine to what extent the whole volumes of abdominal subcutaneous (ASAT) and visceral adipose tissue (VAT) of patients with obesity can be predicted by using data of one body half only. Such a workaround has already been reported for dual-energy x-ray absorption (DEXA) scans and becomes feasible whenever the field of view of an imaging technique is not large enough. Methods: Full-body abdominal MRI data of 26 patients from an obesity treatment center (13 females and 13 males, BMI range 30.8-41.2 kg/m2, 32.6-61.5 years old) were used as reference (REF). MRI was performed with IRB approval on a clinical 1.5 T MRI (Achieva dStream, Philips Healthcare, Best, Netherlands). Segmentation of adipose tissue was performed with a custom-made Matlab software tool. Statistical measures of agreement were the coefficient of determination R 2 of a linear fit. Results: Mean ASATREF was 12,976 (7812-24,161) cm3 and mean VATREF was 4068 (1137-7518) cm3. Mean half-body volumes relative to the whole-body values were 50.8% (48.2-53.7%) for ASATL and 49.2% (46.3-51.8%) for ASATR. Corresponding volume fractions were 56.4% (51.4-65.9%) for VATL and 43.6% (34.1-48.6%) for VATR. Correlations of ASATREF with ASATL as well as with ASATR were both excellent (R 2 > 0.99, p < 0.01). Corresponding correlations of VATREF were marginally lower (R 2 = 0.98 for VATL, p < 0.01, and R 2 = 0.97 for VATR, p < 0.01). Conclusions: In conclusion, abdominal fat volumes can be reliably assessed by half-body MRI data, in particular the subcutaneous fat compartment.

Cite

CITATION STYLE

APA

Linder, N., Solty, K., Hartmann, A., Eggebrecht, T., Blüher, M., Stange, R., & Busse, H. (2019). Half-body MRI volumetry of abdominal adipose tissue in patients with obesity. BMC Medical Imaging, 19(1). https://doi.org/10.1186/s12880-019-0383-8

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free