Feasibility of using cross-sectional area of masticatory muscles to predict sarcopenia in healthy aging subjects

Abstract

Determination of sarcopenia is crucial in identifying patients at high risk of adverse health outcomes. Recent studies reported a significant decline in masticatory muscle (MM) function in patients with sarcopenia. This study aimed to analyze the cross-sectional area (CSA) of MMs on computed tomography (CT) images and to explore their potential to predict sarcopenia. The study included 149 adult subjects retrospectively (59 males, 90 females, mean age 57.4 ± 14.8 years) who underwent head and neck CT examination for diagnostic purposes. Sarcopenia was diagnosed on CT by measuring CSA of neck muscles at the C3 vertebral level and estimating skeletal muscle index. CSA of MMs (temporal, masseter, medial pterygoid, and lateral pterygoid) were measured bilaterally on reference CT slices. Sarcopenia was diagnosed in 67 (45%) patients. Univariate logistic regression analysis demonstrated a significant association between CSA of all MMs and sarcopenia. In the multivariate logistic regression model, only masseter CSA, lateral pterygoid CSA, age, and gender were marked as predictors of sarcopenia. These parameters were combined in a regression equation, which showed excellent sensitivity and specificity in predicting sarcopenia. The masseter and lateral pterygoid CSA can be used to predict sarcopenia in healthy aging subjects with a high accuracy.