A potential bioelectrical impedance equation for estimating skeletal muscle area using computed tomography in colorectal cancer

Bioelectrical impedance analysis (BIA) requires validated equations tailored to specific populations and devices to estimate body composition. In this study, we aimed to develop a predictive equation for BIA to evaluate skeletal muscle area (SMA) using computed tomography (CT) as the reference method. This is bi-center cross-sectional study, involving 211 patients. BIA was conducted using a tetrapolar model, measuring resistance (R), and reactance (Xc) values. The equation was developed using a linear regression model, maintaining variables that best correlate to SMA<sub>CT</sub>. Validity was assessed using Bland-Altman plots and bootstrapping resampling method. Lins' concordance correlation coefficient (CCC), root mean squared error (RMSE), and mean absolute error (MAE) were calculated before and after resampling. The proposed equation included sex, age, weight, height, resistance and reactance. This model accounted for more than 85% of the variability in SMA<sub>CT</sub> (R<sup>2</sup> <sub>adjusted</sub> = 0.86), with a RMSE of 10.37 cm<sup>2</sup> and MAE of 8.28 cm<sup>2</sup>. SMA<sub>BIA</sub> was highly correlated with SMA<sub>CT</sub> (ρ = 0.93, P < .001). Bland-Altman plots and CCC (0.92) demonstrated a moderate agreement between SMA<sub>BIA</sub> and SMA<sub>CT</sub>. The newly proposed BIA equation demonstrated potential for predicting SMA<sub>CT</sub> as the reference standard. Our hypothesis requires further investigation in both healthy and clinical populations.

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Publication Details

Journal
Scientific Reports
Published
2025-09-25
DOI
https://doi.org/10.1038/s41598-025-17872-8
Primary Topic
Body Composition Measurement Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

A potential bioelectrical impedance equation for estimating skeletal muscle area using computed tomography in colorectal cancer

Ana Paula Trussardi Fayh, Amanda de Sousa Rebouças, Nilian Carla Souza, Sílvia Fernandes Maurício et al.
Scientific Reports
Body Composition Measurement Techniques
article

A potential bioelectrical impedance equation for estimating skeletal muscle area using computed tomography in colorectal cancer

Ana Paula Trussardi Fayh, Amanda de Sousa Rebouças, Nilian Carla Souza, Sílvia Fernandes Maurício, Alcides da Silva Diniz, Marı́a Cristina González, Carla M. Prado, Galtieri Otávio Cunha de Medeiros, Rodrigo Albert Baracho Rüegg, Nithaela Alves Bennemann, Jarson P Costa-Pereira
article en

Abstract

Bioelectrical impedance analysis (BIA) requires validated equations tailored to specific populations and devices to estimate body composition. In this study, we aimed to develop a predictive equation for BIA to evaluate skeletal muscle area (SMA) using computed tomography (CT) as the reference method. This is bi-center cross-sectional study, involving 211 patients. BIA was conducted using a tetrapolar model, measuring resistance (R), and reactance (Xc) values. The equation was developed using a linear regression model, maintaining variables that best correlate to SMA<sub>CT</sub>. Validity was assessed using Bland-Altman plots and bootstrapping resampling method. Lins' concordance correlation coefficient (CCC), root mean squared error (RMSE), and mean absolute error (MAE) were calculated before and after resampling. The proposed equation included sex, age, weight, height, resistance and reactance. This model accounted for more than 85% of the variability in SMA<sub>CT</sub> (R<sup>2</sup> <sub>adjusted</sub> = 0.86), with a RMSE of 10.37 cm<sup>2</sup> and MAE of 8.28 cm<sup>2</sup>. SMA<sub>BIA</sub> was highly correlated with SMA<sub>CT</sub> (ρ = 0.93, P < .001). Bland-Altman plots and CCC (0.92) demonstrated a moderate agreement between SMA<sub>BIA</sub> and SMA<sub>CT</sub>. The newly proposed BIA equation demonstrated potential for predicting SMA<sub>CT</sub> as the reference standard. Our hypothesis requires further investigation in both healthy and clinical populations.

Scientific ReportsVol. 15(1)
Universidade Federal de Ouro Preto (BR), University of Alberta (CA), Universidade Federal de Pelotas (BR), Universidade Federal de Pernambuco (BR), Universidade Federal do Rio Grande do Norte (BR), Hospital Universitário Onofre Lopes (BR), Instituto Nacional de Câncer - INCA (BR)
Canada Research Chairs, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 67%
Body Composition Measurement Techniques
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