Defining Sarcopenia with MRI - Establishing Threshold Values within a Large-Scale Population Study
2016 (English)Conference paper, Abstract (Other academic)
To identify gender specific threshold values for sarcopenia detection for lean thigh muscle tissue volume quantified using MRI.
METHOD AND MATERIALS
Current gender-specific thresholds for sarcopenia detection are based on quantification on appendicular lean tissue normalized with height^2 using DXA (7.26 kg/m2 for men and 5.45 kg/m2 for women). In this study 3514 subjects (1548 males and 1966 females) in the imaging subcohort of UK Biobank with paired DXA and MRI scans were included. The age range was 45 to 78 years. The total lean thigh volume normalized with height2 (TTVi) was determined with a 6 minutes neck to knee 2-point Dixon MRI protocol using a 1.5T MR-scanner (Siemens, Germany) followed by analysis with AMRA® Profiler (AMRA, Sweden). The appendicular lean tissue mass normalized with height2 (ALTMi) was assessed using DXA (GE-Lunar iDXA). Subjects with ALTMi lower than the gender specific threshold were categorized as sarcopenic. Gender specific threshold values were determined for detection of sarcopenic subjects based on TTVi optimizing sensitivity and specificity. Area under receiver operator curve (AUROC) was calculated as well as the linear correlation between TTVi and ALTMi.
A threshold value of TTVi = 3.64 l/m2 provided a sensitivity and specificity of 0.88 for sarcopenia detection in males. The AUROC was 0.96. Similarly, a TTVi < 2.76 l/m2 identified sarcopenic female subjects with a sensitivity and specificity of 0.89. The corresponding AUROC was 0.96. The linear correlation between TTVi and ALTMi was 0.93 (99%CI: 0.93-0.94).
MRI-based quantification of total lean thigh volume normalized with height^2 could be used to categorize sarcopenia in the study group. Threshold values are suggested.
The study suggests that sarcopenia can be diagnosed using a rapid MRI scan with high sensitivity and specificity.
Place, publisher, year, edition, pages
Radiology, Nuclear Medicine and Medical Imaging Medical Image Processing
IdentifiersURN: urn:nbn:se:liu:diva-132409OAI: oai:DiVA.org:liu-132409DiVA: diva2:1045459
Radiological Society of North America 2016, 102nd Scientific Assembly and Annual Meeting, Chicago, Illinois, USA, November 27 - December 2, 2016