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

Author:

Borda Miguel German123,Duque Gustavo45,Pérez‐Zepeda Mario Ulises67ORCID,Baldera Jonathan Patricio18,Westman Eric9,Zettergren Anna10,Samuelsson Jessica10,Kern Silke1011,Rydén Lina10,Skoog Ingmar1011,Aarsland Dag112

Affiliation:

1. Centre for Age‐Related Medicine (SESAM) Stavanger University Hospital Stavanger Norway

2. Semillero de Neurociencias y Envejecimiento, Ageing Institute, Medical School Pontificia Universidad Javeriana Bogotá Colombia

3. Faculty of Health Sciences University of Stavanger Stavanger Norway

4. Research Institute of the McGill University Health Centre Montreal Québec Canada

5. Dr. Joseph Kaufmann Chair in Geriatric Medicine, Department of Medicine McGill University Montreal Québec Canada

6. Instituto Nacional de Geriatría, Dirección de Investigación Ciudad de México México

7. Centro de Investigación en Ciencias de la Salud (CICSA), FCS Universidad Anáhuac México Campus Norte Huixquilucan México

8. Escuela de Estadística de la Universidad Autónoma de Santo Domingo Santo Domingo República Dominicana

9. Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society Karolinska Institutet Stockholm Sweden

10. Institute of Neuroscience and Physiology, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden

11. Department of Psychiatry, Cognition and Old Age Psychiatry Sahlgrenska University Hospital Mölndal Sweden

12. Department of Old Age Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience King's College London London UK

Abstract

AbstractBackgroundSarcopenia 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.MethodsThe 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.ResultsThe 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.ConclusionsALSTI 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.

Funder

Alzheimerfonden

Vetenskapsrådet

Stiftelsen Psykiatriska Forskningsfonden

Demensfonden

Helse Vest

King's College London

Publisher

Wiley

Subject

Physiology (medical),Orthopedics and Sports Medicine

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