Multiparametric Approach to the Colorectal Cancer Phenotypes Integrating Morphofunctional Assessment and Computer Tomography

Abstract

(1) Background: Accurate body composition assessment in CCR patients is crucial due to the high prevalence of malnutrition, sarcopenia, and cachexia affecting survival. This study evaluates the correlation between body composition assessed by CT imaging as a reference technique, BIVA, nutritional ultrasound, and handgrip strength in CCR patients. (2) Methods: This retrospective study included CCR patients assessed by the Endocrinology and Nutrition Services of Virgen de la Victoria in Malaga and Vall d’Hebron in Barcelona from October 2018 to July 2023. Assessments included anthropometry, BIVA, NU, HGS, and AI-assisted CT analysis at the L3 level for body composition. Pearson’s analysis determined the correlation of CT-derived variables with BIVA, NU, and HGS. (3) Results: A total of 267 CCR patients (mean age 68.2 ± 10.9 years, 61.8% men) were studied. Significant gender differences were found in body composition and strength. CT-SMI showed strong correlations with body cell mass (r = 0.65), rectus femoris cross-sectional area (r = 0.56), and handgrip strength (r = 0.55), with a Cronbach’s alpha of 0.789. CT-based adipose tissue measurements showed significant correlations with fat mass (r = 0.56), BMI (r = 0.78), A-SAT (r = 0.49), and L-SAT (r = 0.66). Regression analysis indicated a high predictive power for CT-SMI, explaining approximately 80% of its variance (R2 = 0.796). (4) Conclusions: Comprehensive screening of colorectal cancer patients through BIVA, NU, HGS, and CT optimizes the results of the evaluation. These methods complement each other in assessing muscle mass, fat distribution, and nutritional status in CCR. When CT is unavailable or bedside assessment is needed, HGS, BIVA, and NU provide an accurate assessment of body composition.