Sarcopenia is a muscle disorder associated with loss of muscle mass, strength and function. Early screening, diagnosis and treatment may improve outcome in different disease conditions. A wide variety of tools for estimation of muscle mass is available and each tool has specific technical requirements. However, different investigational settings and lack of homogeneity of populations influence the definition of gold standards, proving it difficult to systematically adopt these tools. Recently, the European Working Group on Sarcopenia in Older People (EWGSOP) published a revised recommendation (EWGSOP-2) and algorithm for using tools for screening and diagnosing sarcopenia. However, agreement of the EWGSOP2 criteria with other classifications is poor and although an overview of available tools is valuable, for the purpose of clinical decision-making the reverse is useful; a given scenario asks for the most suitable tools. Tools were identified for screening, diagnostics and longitudinal monitoring of muscle mass. For each of these clinical scenarios the most appropriate tools were listed and for each technique their usability is specified based on sensitivity and specificity. Based on this information a specific recommendation is made for each clinical scenario. This narrative review provides an overview of currently available tools and future developments for different clinical scenarios such as screening, diagnosis and longitudinal monitoring of alterations in muscle status. It supports clinical decision-making in choosing the right tools for muscle mass quantification depending on the need within a given clinical scenario as well as the local availability and expertise.

Manual segmentation of muscle and adipose compartments from computed tomography (CT) axial images is a potential bottleneck in early rapid detection and quantification of sarcopenia. A prototype deep learning neural network was trained on a multi-center collection of 3413 abdominal cancer surgery subjects to automatically segment truncal muscle, subcutaneous adipose tissue and visceral adipose tissue at the L3 lumbar vertebral level. Segmentations were externally tested on 233 polytrauma subjects. Although after severe trauma abdominal CT scans are quickly and robustly delivered, with often motion or scatter artefacts, incomplete vertebral bodies or arms that influence image quality, the concordance was generally very good for the body composition indices of Skeletal Muscle Radiation Attenuation (SMRA) (Concordance Correlation Coefficient (CCC) = 0.92), Visceral Adipose Tissue index (VATI) (CCC = 0.99) and Subcutaneous Adipose Tissue Index (SATI) (CCC = 0.99). In conclusion, this article showed an automated and accurate segmentation system to segment the cross-sectional muscle and adipose area L3 lumbar spine level on abdominal CT. Future perspectives will include fine-tuning the algorithm and minimizing the outliers.

Sarcopenia is defined as a loss of muscle mass and function, which can be caused by normal ageing or factors such as physical inactivity. Severe health consequences caused by sarcopenia highlight the need for early identification. Computed Tomography (CT) imaging, often mentioned as the gold standard due to its accuracy, is costly and not routinely performed in daily clinical care. Ultrasound of the rectus femoris, however, is low in costs and easily accessible. The aim is to present the current and most recent literature regarding the diagnostic value of ultrasound measurements of the rectus femoris for the diagnosis of sarcopenia in adults. The databases PubMed and Web of Science were used to search for studies comparing ultrasound of the rectus femoris with a reference test to diagnose sarcopenia in adults. The quality of the final eligible studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies, version 2, tool (QUADAS-2). Six studies were included in this systematic review. The muscle thickness and cross-sectional area of the rectus femoris were assessed and compared with the reference tests CT, Dual-Energy X-ray Absorptiometry (DXA), and Bioelectrical Impedance Analysis (BIA). Half of the studies had a low risk of bias on all QUADAS-2 domains. Three studies reported statistical significant outcomes and diagnostic values ranging from 60 to 81% sensitivity and 51 to 94% specificity. Ultrasound of the rectus femoris muscle to diagnose sarcopenia has been shown to be a promising method in multiple clinical populations. However, there were some limitations such as a high methodological heterogeneity. Future research should develop standardized protocols and determine clear cut-off values to allow for a better implementation of ultrasound in clinical practice.

Microwave-based sensing for tissue analysis is recently gaining interest due to advantages such as non-ionizing radiation and non-invasiveness. We have developed a set of transmission sensors for microwave-based real-time sensing to quantify muscle mass and quality. In connection, we verified the sensors by 3D simulations, tested them in a laboratory on a homogeneous three-layer tissue model, and collected pilot clinical data in 20 patients and 25 healthy volunteers. This report focuses on initial sensor designs for the Muscle Analyzer System (MAS), their simulation, laboratory trials and clinical trials followed by developing three new sensors and their performance comparison. In the clinical studies, correlation studies were done to compare MAS performance with other clinical standards, specifically the skeletal muscle index, for muscle mass quantification. The results showed limited signal penetration depth for the Split Ring Resonator (SRR) sensor. New sensors were designed incorporating Substrate Integrated Waveguides (SIW) and a bandstop filter to overcome this problem. The sensors were validated through 3D simulations in which they showed increased penetration depth through tissue when compared to the SRR. The second-generation sensors offer higher penetration depth which will improve clinical data collection and validation. The bandstop filter is fabricated and studied in a group of volunteers, showing more reliable data that warrants further continuation of this development.

Sarcopenia is related to adverse outcomes in various populations. However, little is known about the prevalence of sarcopenia in polytrauma patients. Identifying the number of patients at risk of adverse outcome will increase awareness to prevent further loss of muscle mass. We utilized data from a regional prospective trauma registry of all polytrauma patients presented between 2015 and 2019 at a single level-I trauma center. Subjects were screened for availability of computed tomography (CT)-abdomen and height in order to calculate skeletal mass index, which was used to estimate sarcopenia. Additional parameters regarding clinical outcome were assessed. Univariate analysis was performed to identify parameters related adverse outcome and, if identified, entered in a multivariate regression analysis. Prevalence of sarcopenia was 33.5% in the total population but was even higher in older age groups (range 60–79 years), reaching 82 % in patients over 80 years old. Sarcopenia was related to 30-day or in-hospital mortality (p = 0.032), as well as age (p < 0.0001), injury severity score (p = 0.026), and Charlson comorbidity index (p = 0.001). Log rank analysis identified sarcopenia as an independent predictor of 30-day mortality (p = 0.032). In conclusion, we observed a high prevalence of sarcopenia among polytrauma patients, further increasing in older patients. In addition, sarcopenia was identified as a predictor for 30-day mortality, underlining the clinical significance of identification of low muscle mass on a CT scan that is already routinely obtained in most trauma patients.