OBJECTIVE: : Evaluate the accuracy of CT-derived regional skeletal muscle volume (SMV) measurements to predict whole body SMV in patients with melanoma. METHODS: : 148 patients with advanced melanoma who underwent whole body positron emission tomography/CT were studied. Whole body SMV was measured on CT and used as the reference standard. CT-derived regional measures of SMV were obtained in the thorax, abdomen, pelvis, and lower limbs. Models were developed on a discovery cohort (n-98), using linear regression to model whole body SMV as a function of each regional measure, and clinical factors. Predictive performance of the derived models was evaluated in a validation cohort (n = 50) by estimating the explained variation (R2) of each model. RESULTS: : In the discovery cohort, all regional SMV measurements were significantly associated with whole body SMV [β1 range: 0.673-1.153, all p < 0.001)]. The magnitude of association was greatest for pelvic regional measurements {β = 1.153, [95% confidence interval (0.989, 1.317)]}. Prediction algorithms incorporating clinical variables and regional SMVs were developed to estimate whole body SMV from regional assessments. Using the validation cohort to predict whole body SMV, the R2 values for the pelvic, abdominal and thoracic regional measurements were 0.89, 0.86, 0.78. CONCLUSION: : Regional measures of SMV are strong predictors of whole body SMV in patients with advanced melanoma. ADVANCES IN KNOWLEDGE:: The first study utilizing whole body imaging as a reference standard validating the use of regional SMVs in cancer patients, including validating the use of regional SMVs outside of traditionally assessed areas.
OBJECTIVE: : Evaluate the accuracy of CT-derived regional skeletal muscle volume (SMV) measurements to predict whole body SMV in patients with melanoma. METHODS: : 148 patients with advanced melanoma who underwent whole body positron emission tomography/CT were studied. Whole body SMV was measured on CT and used as the reference standard. CT-derived regional measures of SMV were obtained in the thorax, abdomen, pelvis, and lower limbs. Models were developed on a discovery cohort (n-98), using linear regression to model whole body SMV as a function of each regional measure, and clinical factors. Predictive performance of the derived models was evaluated in a validation cohort (n = 50) by estimating the explained variation (R2) of each model. RESULTS: : In the discovery cohort, all regional SMV measurements were significantly associated with whole body SMV [β1 range: 0.673-1.153, all p < 0.001)]. The magnitude of association was greatest for pelvic regional measurements {β = 1.153, [95% confidence interval (0.989, 1.317)]}. Prediction algorithms incorporating clinical variables and regional SMVs were developed to estimate whole body SMV from regional assessments. Using the validation cohort to predict whole body SMV, the R2 values for the pelvic, abdominal and thoracic regional measurements were 0.89, 0.86, 0.78. CONCLUSION: : Regional measures of SMV are strong predictors of whole body SMV in patients with advanced melanoma. ADVANCES IN KNOWLEDGE:: The first study utilizing whole body imaging as a reference standard validating the use of regional SMVs in cancerpatients, including validating the use of regional SMVs outside of traditionally assessed areas.
Authors: John Vitarello; Marcus D Goncalves; Qin C Zhou; Alexia Iasonos; Darragh F Halpenny; Andrew Plodkowski; Emily Schwitzer; Jennifer J Mueller; Oliver Zivanovic; Lee W Jones; Karen A Cadoo; Jason A Konner Journal: JCSM Clin Rep Date: 2020-11-11
Authors: J Peter Marquardt; Eric J Roeland; Emily E Van Seventer; Till D Best; Nora K Horick; Ryan D Nipp; Florian J Fintelmann Journal: J Cachexia Sarcopenia Muscle Date: 2021-11-02 Impact factor: 12.910