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A cardiopulmonary exercise test (CPET) is a test assessing an individual's physiological response during exercise. Results may be affected by body composition, which is best evaluated through imaging techniques like magnetic resonance imaging (MRI). The aim of this study was to assess relationships between body composition and indices obtained from CPET. A total of 234 participants (112 female), all aged 50 years, underwent CPETs and whole-body MRI scans (> 1 million voxels). Voxel-wise statistical analysis of tissue volume and fat content was carried out with a method called Imiomics and related to the CPET indices peak oxygen consumption (V̇O_2peak), V̇O_2peak scaled by body weight (V̇O_2kg) and by total lean mass (V̇O_2lean), ventilatory efficiency (V̇E/V̇CO₂-slope), work efficiency (ΔV̇O₂/ΔWR) and peak exercise respiratory exchange ratio (RERpeak). V̇O_2peak showed the highest positive correlation with volume of skeletal muscle. V̇O_2kg negatively correlated with tissue volume in subcutaneous fat, particularly gluteal fat. RERpeak negatively correlated with tissue volume in skeletal muscle, subcutaneous fat, visceral fat and liver. Some associations differed between sexes: in females ΔV̇O₂/ΔWR correlated positively with tissue volume of subcutaneous fat and V̇E/V̇CO₂-slope with tissue volume of visceral fat, and, in males, V̇O_2peak correlated positively to lung volume. In conclusion, voxel-based Imiomics provided detailed insights into how CPET indices were related to the tissue volume and fat content of different body structures.

BACKGROUND: The cardiopulmonary exercise test (CPET) evaluates cardiopulmonary function. In light of the obesity epidemic, it is important to understand how body composition affects interpretation of CPET results. The aim of the present study was to assess the relationship between CPET measures, other than peak oxygen uptake, and body composition.

METHOD: A total of 330 participants, aged 50 years, performed both a CPET and dual-energy X-ray absorptiometry (DXA). From the CPET, peak exercise respiratory exchange ratio (RER), ventilatory efficiency (V̇ _E/V̇ _CO2 slope) and work efficiency (ΔV̇ _O2 /ΔWR) were recorded. Pearson's correlation was used to assess the association between CPET measures and selected body composition measures, including body mass index (BMI), waist circumference, fat mass, lean mass, body fat percentage and percentage trunk fat to fat mass. All analyses were done stratified by sex. A p-value <0.05 defined statistical significance.

RESULTS: RER was negatively correlated with body composition measures; the strongest correlation was observed with waist circumference in females (r= -0.36). V̇ _E/V̇ _CO2 slope had no significant correlations with any body composition measures. ΔV̇ _O2 /ΔWR was positively correlated with the body composition measures; the strongest correlation was observed with BMI (r=0.24). The additive role of percentage body fat and percentage trunk fat were studied in a linear regression model using waist circumference and BMI to predict the aforementioned CPET measures and no additive role was found.

CONCLUSION: RER and ΔV̇ _O2 /ΔWR may be influenced by body composition while V̇ _E/V̇ _CO2 slope is not affected. Adiposity measures from DXA add no additional explanatory value to the CPET measures.