Title : Proposal for new diagnostic criteria for sarcopenia based on CT imaging in the Saudi population: A novel method in oncology research
Abstract:
Background: Sarcopenia has been shown to be an independent predictor of lower overall survival in oncology patients. Several studies have used computed tomography (CT) to measure psoas muscle surface area to define sarcopenia. However, the cut-off values based on CT imaging remain undetermined in Saudi population. The aim of this study is to provide sex and age specific percentiles for psoas muscle area (PMA), psoas muscle index (PMI) and psoas muscle density (PMD) in Saudi population and to establish a formula to calculate the standard PMA based on individual’s anthropometric measurement.
Methods: Preoperative CT imaging at the third lumbar vertebra level was used to measure PMA, PMI and PMD in 400 adult donors for living donor kidney transplantation (LDKT). We determined the age and sex-specific cut-off values of PMA in order to define low skeletal muscle mass. A formula was generated to calculate the standard PMA using body weight as independent variable and further validated on a new dataset involving individuals from the general population.
Results: Males had significantly higher measurements of PMA among females (10.7 ± 2.7 vs. 5.8 ± 1.9, p<0.0001). PMA was positively correlated with body weight in both genders. The estimated PMA using the generated formula correlated strongly with the manually traced PMA measurements. The mean differences between estimated and measured PMA values were 0.81 ± 1.70 (95%CI, -1.75 to 0.13) among males and 0.17 ± 1.19 (95%CI, -0.49 to 0.83) among females. These outcomes emphasize the validity of our predictive computations.
Conclusion: PMA can be used in opportunistic screening for sarcopenia and as a radiological marker to predict overall survival in oncology patients.
