Using magnetic resonance imaging to measure head muscles: An innovative method to opportunistically determine muscle mass and detect sarcopenia

Abstract

Abstract Background Sarcopenia is associated with multiple adverse outcomes. Traditional methods to determine low muscle mass for the diagnosis of sarcopenia are mainly based on dual‐energy X‐ray absorptiometry (DXA), whole‐body magnetic resonance imaging (MRI) and bioelectrical impedance analysis. These tests are not always available and are rather time consuming and expensive. However, many brain and head diseases require a head MRI. In this study, we aim to provide a more accessible way to detect sarcopenia by comparing the traditional method of DXA lean mass estimation versus the tongue and masseter muscle mass assessed in a standard brain MRI. Methods The H70 study is a longitudinal study of older people living in Gothenburg, Sweden. In this cross‐sectional analysis, from 1203 participants aged 70 years at baseline, we included 495 with clinical data and MRI images available. We used the appendicular lean soft tissue index (ALSTI) in DXA images as our reference measure of lean mass. Images from the masseter and tongue were analysed and segmented using 3D Slicer. For the statistical analysis, the Spearman correlation coefficient was used, and concordance was estimated with the Kappa coefficient. Results The final sample consisted of 495 participants, of which 52.3% were females. We found a significant correlation coefficient between both tongue (0.26) and masseter (0.33) with ALSTI (P < 0.001). The sarcopenia prevalence confirmed using the alternative muscle measure in MRI was calculated using the ALSTI (tongue = 2.0%, masseter = 2.2%, ALSTI = 2.4%). Concordance between sarcopenia with masseter and tongue versus sarcopenia with ALSTI as reference has a Kappa of 0.989 (P < 0.001) for masseter and a Kappa of 1 for the tongue muscle (P < 0.001). Comorbidities evaluated with the Cumulative Illness Rating Scale were significantly associated with all the muscle measurements: ALSTI (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.07–1.26, P < 0.001), masseter (OR 1.16, 95% CI 1.07–1.26, P < 0.001) and tongue (OR 1.13, 95% CI 1.04–1.22, P = 0.002); the higher the comorbidities, the higher the probability of having abnormal muscle mass. Conclusions ALSTI was significantly correlated with tongue and masseter muscle mass. When performing the sarcopenia diagnostic algorithm, the prevalence of sarcopenia calculated with head muscles did not differ from sarcopenia calculated using DXA, and almost all participants were correctly classified using both methods.

Keywords

• dementia
• diagnosis
• geriatrics
• H70
• neurodegenerative disorders
• sarcopenia