Comparison of computed tomography and dual-energy X-ray absorptiometry in the evaluation of body composition in patients with obesity

Front Endocrinol (Lausanne). 2023 Jun 26:14:1161116. doi: 10.3389/fendo.2023.1161116. eCollection 2023.

Abstract

Objective: a) To evaluate the accuracy of the pre-existing equations (based on cm2 provided by CT images), to estimate in kilograms (Kg) the body composition (BC) in patients with obesity (PwO), by comparison with Dual-energy X-ray absorptiometry (DXA). b) To evaluate the accuracy of a new approach (based on both cm2 and Hounsfield Unit parameters provided by CT images), using an automatic software and artificial intelligence to estimate the BC in PwO, by comparison with DXA.

Methods: Single-centre cross-sectional study including consecutive PwO, matched by gender with subjects with normal BMI. All the subjects underwent BC assessment by Dual-energy X-ray absorptiometry (DXA) and skeletal-CT at L3 vertebrae. CT images were processed using FocusedON-BC software. Three different models were tested. Model 1 and 2, based on the already existing equations, estimate the BC in Kg based on the tissue area (cm2) in the CT images. Model 3, developed in this study, includes as additional variables, the tissue percentage and its average Hounsfield unit.

Results: 70 subjects (46 PwO and 24 with normal BMI) were recruited. Significant correlations for BC were obtained between the three models and DXA. Model 3 showed the strongest correlation with DXA (r= 0.926, CI95% [0.835-0.968], p<0.001) as well as the best agreement based on Bland - Altman plots.

Conclusion: This is the first study showing that the BC assessment based on skeletal CT images analyzed by automatic software coupled with artificial intelligence, is accurate in PwO, by comparison with DXA. Furthermore, we propose a new equation that estimates both the tissue quantity and quality, that showed higher accuracy compared with those currently used, both in PwO and subjects with normal BMI.

Keywords: body composition; computed tomography; dual-energy X-ray absorptiometry; morbid obesity; obesity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absorptiometry, Photon / methods
  • Artificial Intelligence*
  • Body Composition*
  • Cross-Sectional Studies
  • Humans
  • Obesity / diagnostic imaging
  • Tomography, X-Ray Computed

Grants and funding

This study was supported by grants from the Instituto de Salud Carlos III (Fondo de Investigación Sanitaria, PI20/01806). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.