Sarcopenia: ultrasound today, smartphones tomorrow?

Sarcopenia is a chronic disease characterized by a slow and progressive loss in the amount, composition, and function of skeletal muscle in the human body. The clinical implication of this condition is twofold: on the one hand, loss of muscle mass leads to muscle weakness, which in turns leads to reduced mobility and increased proneness to falls and fractures [1]; on the other hand, sarcopenia has been related to the occurrence of mortality, adverse events, and length of hospitalization in patients undergoing surgery for many pathologies [2]. This condition is gaining increasing importance, as it has been estimated that in 2016 sarcopenia was affecting around 20 million people in Europe, with an expected increase to more than 32 million people by 2045 (+ 63.8%), corresponding to overall prevalence rates in the elderly of 20.2% and 22.3%, respectively [3]. Thus, sarcopenia already represents a major medical and social challenge. Currently, sarcopenia can be diagnosed with different modalities. Dual-energy X-ray absorptiometry (DXA) is the most common imaging-based method used in research and clinical practice, as it is simple, available, uses little amount of ionizing radiations, being also accurate and reproducible [4]. Thus, according to the European Working Group on Sarcopenia in Older People, DXA is considered a reliable tool to measure body composition and to obtain data about quantity and distribution of lean, fat, and mineral mass throughout the body [5]. On the other hand, computed tomography (CT) and magnetic resonance imaging (MRI) represent the reference standard for the diagnosis of sarcopenia, as both modalities allow for precise evaluation of body composition and consistency of skeletal muscle on cross-sectional images. However, despite their high diagnostic value, the use of CT and MRI is limited by high burden of ionizing radiations or specific contraindications, respectively, by high costs, and by post-processing image analysis; thus, their use is generally restricted to research settings. Despite being an excellent imaging modality in the evaluation of the musculoskeletal system [6], the use of ultrasound in the assessment of sarcopenic patients is relatively limited to the evaluation of thickness, cross-sectional area, and echo intensity of muscles. Consequently, no diagnostic algorithms currently include ultrasound as one of the possible diagnostic modalities for assessing sarcopenia. This is probably because most of those ultrasound parameters may be dependent on the operator and some of them are not able to fully differentiate minimal variations of muscle condition. In this setting, the pilot work by Sanabria et al [7] postulates the use of a new ultrasound-basedmethod to identify sarcopenia in elderly subjects. This approach was recently used by the same group to calculate breast density [8]. They used a commercially available portable ultrasound system coupled with a simple plastic reflector to obtain the radiofrequency ultrasound data in the calf muscles of 10 elderly women and 11 healthy volunteers. Then, they developed a specific software capable to provide three-dimensional speed of sound calculation from raw ultrasound data. They found that this speed was significantly lower in elderly women than in young controls, yielding the remarkable diagnostic performance of 93.6%. So far, then, this method has been proved to be excellent in differentiating women’s age based on their muscular features, although it does not provide data on sarcopenia itself. I think that small sample size does not represent a limitation of this paper, as statistical significance was achieved for most of the presented comparisons. However, to understand if this method may really help in the diagnosis of sarcopenia, a further study comparing this tool with a more established technique to diagnose sarcopenia and with a more heterogeneous population is warranted. At any rate, these results are interesting and open the possibility of using commercial ultrasound systems to calculate sound This comment refers to the article available at https://doi.org/10.1007/ s00330-018-5742-2.