Sarcopenia is an age-related syndrome characterized by a progressive and generalized loss of skeletal muscle mass, strength and function. It is associated with various adverse clinical outcomes, including fracture, falls and mortality (1–3). Sarcopenia is particularly prevalent among elderly patients with cancer (4,5) and can occur across all types of cancer. Studies indicate that cancer patients with low skeletal muscle mass during treatment face increased risks of mortality, cancer recurrence and lower quality of life (6–8). A systematic meta-analysis of 39 studies involving 8,966 cancer patients revealed an overall pooled sarcopenia prevalence of 42% [95% confidence interval (CI) 0.36–0.48; P<0.001], with substantial heterogeneity across cancer subtypes (8). Consistent with these findings, a review revealed a particularly high prevalence of sarcopenia (approaching 70%) in patients with esophageal, gastrointestinal, lung, head and neck malignancies, compared with a moderate prevalence (~50%) in those with breast, renal cell and hematologic cancers (9). These tumor-specific prevalence patterns exhibited correlations with disease stage, progression kinetics and the severity of nutritional and absorptive dysfunction. Although the pathogenesis of sarcopenia is not well understood, early identification of at-risk patients and timely intervention can markedly reduce the risk of adverse clinical outcomes.

The diagnosis of sarcopenia requires assessing muscle mass, muscle strength and physical performance (10). The assessment of muscle mass is a critical component in the clinical diagnosis of sarcopenia (1,11). Currently, the measurement of the cross-sectional area (CSA) of the third lumbar vertebra (L3) using computed tomography (CT) or magnetic resonance imaging (MRI) is considered a reliable method for assessing muscle mass. However, taking into account the expense, convenience, radiation exposure and equipment availability, various alternative methods have been developed, such as calf circumference (CC), mid-upper arm circumference and surrogate vertebral measurements. The present review summarized current methods for measuring skeletal muscle mass, aiming to early identify potential sarcopenia cases and facilitate timely intervention.

CT and MRI are widely used in clinical practice to assess muscle mass (30–32). CT can be targeted to show different body components by setting different thresholds, where the threshold for muscle tissue is −29~150 Hounsfield units (33,34). MRI relies on instrument-based marking or manual labeling of muscle tissue for accurate measurement (30). CT or MRI assessment of muscle mass usually involves measuring the skeletal muscle CSA from a single image. This value is then adjusted for height to calculate the skeletal muscle index (SMI, cm/m²) (35). Therefore, muscle mass measurements using CT or MRI require both the selection of experienced staff to circle the muscle area and, more importantly, the selection of appropriate and typical vertebrae to measure the CSA of the muscle. In addition to measuring skeletal muscle CSA for MRI, advanced MRI sequences can also enable the estimation of body composition in combination with the assessment of muscle mass abnormalities. This combined approach enhances the diagnostic accuracy of sarcopenia in aging patients (36). Xiao et al (35) show that CT-based diagnosis of sarcopenia can help to predict clinical outcomes and prognosis in surgical patients and illustrate that CT is intuitive, rapid and accurate in the diagnosis of sarcopenia. Beyond CSA measurement, CT can assess muscle steatosis by measuring intermuscular adipose tissue area or identifying muscle mass loss (37). Despite their advantages in sarcopenia diagnosis, CT and MRI are not widely used for screening due to their high cost, time consumption and ionizing radiation (in the case of CT) and the need for specialized technical expertise (35,36).

US enables evaluation of muscle echotexture by detecting variations in intramuscular fat and connective tissue composition. Recently, the Sarcopenia Group of the European Geriatric Society published a consensus protocol for the detection of sarcopenia using ultrasound, including the measurements of CSA, muscle thickness, echo intensity, muscle wing angle and muscle bundle length (55). While the quadriceps remain the most studied muscle group, uncertainty persists regarding optimal anatomical measurement sites for assessing total skeletal muscle mass. Perkisas et al (56) concluded that muscle mass decreases before the number of muscle fibers is lost, which could be a reliable indicator of early signs of sarcopenia in the elderly. Although human errors in the interpretation of ultrasound results, might affect the formulation of unified diagnostic criteria, ultrasound still has the potential to become a tool for early screening and clinical diagnosis of sarcopenia due to its advantages of being non-invasive, painless, non-ionizing radiation and low-cost.

DXA is currently widely used in body composition measurement due to its accuracy and repeatability. DXA enables simultaneous quantification of fat mass, appendicular skeletal muscle mass (ASM), fat-free mass (FFM) and bone mineral content. Studies demonstrate strong concordance between DXA-derived non-fat/adipose tissue measurements and corresponding values obtained via CT or MRI (1,57). ASMI measured by DXA varied in different study populations, with cut-off values ranging from 5.86 kg/m²−7.40 kg/m² in males and from 4.42 kg/m²−5.67 kg/m² in females (58). Based on available studies, EWGSOP2 has established the cut-off value for DXA to assess low muscle mass as ASMI <7.0 kg/m² for males and <5.5 kg/m² for females (59). The AWGS has established DXA cut-off values for assessing low muscle mass as ASMI <7.0 kg/m² for males and <5.7 kg/m² for females (60).

Nevertheless, DXA is unable to assess intramuscular fat infiltration (myosteatosis), which limits muscle quality evaluation. Furthermore, DXA measurements can be inaccurate due to variations in body thickness, fluid retention conditions (e.g., renal/hepatic dysfunction) and fluctuations in hydration status.

BIA is widely used for body composition assessment, indirectly calculating muscle mass using specific formulas. Cheng et al (57) demonstrated that BIA initially overestimates muscle mass but aligns closely with DXA measurements after adjustment, making it a rapid and reliable tool for sarcopenia screening. Compared with DXA, BIA is a simple measurement method with the advantages of being non-invasive, radiation-free and fast, making it an improved better choice for muscle mass screening of sarcopenia.

Although the AWGS2019 diagnostic criteria for sarcopenia define low muscle mass as muscle mass measured by BIA <7.0 kg/m² for males and <5.7 kg/m² for females (61), there is no diagnostic criterion for low muscle mass determined by BIA in EWGSOP2. This may be due to the heterogeneity of low muscle mass cut-off values among different ethnicities. Therefore, the cut-off values for low muscle mass range from 7.4 kg/m²−9.31 kg/m² for males and from 5.14 kg/m²−7.4 kg/m² for females, as shown in Table IV.

The use of different evaluation instruments results in significant differences in cut-off values because different formulas are used to measure muscle mass. In the future, more studies should focus on establishing a unified and standardized instrument to explore the cut-off values for low muscle mass in different ethnicities, for the purpose of improving the sensitivity and specificity of sarcopenia screening. In general, BIA is a convenient and simple tool for measuring muscle mass and can be used in muscle mass screening for sarcopenia. However, it should be noted that muscle mass measurements by BIA are susceptible to the hydration status of patients, leading to inaccurate muscle mass values. Therefore, BIA is not recommended for patients with edema.

Sarcopenia, a syndrome characterized by progressive and generalized loss of skeletal muscle mass and function, has gained recognition as a critical determinant of health in older adults (62). Accurate assessment of muscle mass is crucial for the diagnosis, monitoring and management of sarcopenia, markedly influencing clinical decision-making and patient outcomes (63). Anthropometric measurements such as CC, mid-upper arm circumference and the Yubi-wakka test, offer non-invasive, rapid and cost-effective approaches for sarcopenia screening (15). These methods are particularly valuable in both in community and hospital settings, enabling widespread screening initiatives (61). However, while the Yubi-wakka test shows good applicability in Asian populations, further validation in diverse ethnic groups is needed to ensure its global applicability (64). BIA is a widely used tool for assessing body composition, including muscle mass, owing to its ease of use and non-invasive nature. However, variability in BIA devices and methodologies can affect the accuracy and reliability of measurements, highlighting the need for standardization in sarcopenia diagnosis (65,66). Cut-off values for BIA in sarcopenia screening exhibit variability, with suggested thresholds being <7.0 kg/m² for men and <5.5 or 5.7 kg/m² for women (61). The EWGSOP recommends DXA for muscle mass assessment (39), due to its precision and ability to evaluate regional lean mass. However, its high cost and limited availability may restrict its use in routine clinical practice (67). The cut-off values for DXA in sarcopenia diagnosis are <7.0 kg/m² for men and <5.4 kg/m² for women. However, these thresholds may not be universally applicable across diverse populations (68). Imaging techniques such as CT and MRI provide detailed visualization of muscle mass and quality, making them valuable tools in sarcopenia research and clinical practice (31). The use of skeletal muscle mass measured at the L3 level serves as a common reference standard. However, the lack of standardized cut-off values and variability in the selection of vertebral levels and muscles for assessment pose significant challenges (69). Future research should prioritize the establishment of standardized criteria to enable more consistent diagnosis and monitoring of sarcopenia (70–72). US is emerging as a promising tool for sarcopenia assessment, offering a non-invasive, portable and repeatable method to evaluate muscle mass and quality (25). Its potential for real-time imaging and the absence of radiation exposure represent significant advantages. However, US results are operator-dependent and further research is required to establish its reliability and validity in sarcopenia assessment (55). Despite the variety of available methods, several challenges persist, such as the lack of standardized cut-off values across methodologies, the reliance on equipment that may not be universally accessible and the dependence on techniques requiring specialized training (63). The comparative merits and drawbacks of these measurement approaches are detailed in Table V. Additionally, the heterogeneity in sarcopenia presentation across diverse populations underscores the need for more inclusive research to ensure diagnostic accuracy (73). Given the limitations of individual methods, a combined approach may offer a more comprehensive assessment of sarcopenia. Integrating anthropometric measures with BIA or imaging techniques can yield a more accurate representation of muscle mass and function (58,74). Future research should explore the integration of these methods to improve diagnostic accuracy and enhance clinical applicability. The field of sarcopenia assessment is rapidly evolving, necessitating innovative approaches that balance accuracy with practicality for widespread implementation. The development of emerging technologies, such as advanced imaging software and machine learning algorithms, holds promise for delivering more precise and accessible methods for sarcopenia diagnosis (75). Furthermore, incorporation of biomarkers and genetic factors into the assessment framework could enable a more comprehensive understanding of sarcopenia (76).

Sarcopenia is a prevalent condition among cancer patients, with significant implications for clinical outcomes. Current evidence establishes CT as the most widely adopted and clinically validated modality for body composition assessment in this population. The systematic review by McGovern et al (77) highlights that low SMI and skeletal muscle density, as assessed by CT, are prevalent across malignancies, independent of disease stage. However, the review underscores the lack of standardized thresholds for defining sarcopenia in oncology, with studies employing heterogeneous cut-offs. By contrast, Ubachs et al (78) provide compelling evidence for the prognostic value of CT-based assessments, demonstrating significant associations between both SMI [P=0.02; hazard ratio (HR): 1.17; 95% CI: 1.03–1.33] and skeletal muscle radiation attenuation (P<0.001; HR: 1.14; 95% CI: 1.08–1.20) with overall survival. The study highlights the particular clinical utility of CT in ovarian cancer, where ascites-related weight masking renders anthropometric measurements unreliable for nutritional assessment. The applicability of sarcopenia assessment varies markedly across cancer types, with methodology selection often dictated by anatomical considerations. Notably, studies in head and neck cancers predominantly employ cervical skeletal muscle index (C3 SMI) measurements, whereas investigations of gastrointestinal malignancies typically utilize lumbar skeletal muscle index (L3 SMI), reflecting site-specific clinical relevance (8). Other tools such as DXA (limited by hydration status), MRI (costly) and US (operator-dependent) are less robust for cancer-specific prognostication. Anthropometrics (such as CC) are accessible but lack precision. A meta-analysis by Zhang et al (8) systematically compared prognostic capabilities across skeletal muscle quantification methods, revealing that while L3 SMI remains the preferred modality for cross-cancer applications due to its standardized implementation, C3 SMI emerges as particularly predictive of mortality outcomes in head and neck malignancies; a finding that aligns with the anatomical and pathophysiological characteristics of these tumors. However, C3 SMI limited application in non-head/neck cancers restricts broader generalizability. Future research should prioritize tumor-specific diagnostic thresholds and multimodal assessment frameworks to optimize SMI assessment in cancer patients.

Normative values and cut-off criteria for muscle mass exhibit variations across ethnicities, sexes and age groups. However, a number of countries, including China, currently lack clinically validated cut-off standards and population-specific reference values derived from rigorous methodologies. To address this gap, future research is needed to determine benchmarks across diverse populations using advanced technologies, large-scale studies and high-quality methodologies. Future research should define clinically supported indices, such as FFM index in different ethnic groups, to determine sex- and age-specific normal ranges and clinically supported indices for diagnosing reduced muscle mass.

The present review presented a systematic evaluation framework that innovatively combined both conventional and emerging assessment modalities, thereby offering distinct methodological advantages compared with previous works by Muraki (methodological analysis) (79) and Li et al (technical imaging review) (80). The present review broadened the assessment paradigm by incorporating low-cost clinical tools including anthropometric measurements (such as CC) and validated self-assessment methods (such as the Yubi-wakka test), implemented through standardized diagnostic criteria (AWGS 2019) to enhance clinical utility across diverse settings without compromising diagnostic accuracy. Furthermore, the present review assessed multi-modal strategies, such as combining BIA with anthropometry, to improve accuracy while addressing limitations such as hydration effects or positioning errors, often overlooked in prior studies, with particular emphasis on population-specific validation for Asian cohorts to address diagnostic heterogeneity and technical rigor. Notably, the present review bridged research and practice by advocating harmonized protocols that balance gold-standard imaging (such as L3-CT) with scalable tools (such as US and CC), while also exploring emerging technologies such as machine learning for muscle segmentation. By comprehensively integrating multiple assessment approaches, our study extends the current evaluative paradigm to improve clinical utility.

While current methods provide valuable tools for both clinical practice and research, there remains a critical need for further standardization, validation and innovation. Future research should focus on the development and validation of assessment methods that are accessible, reliable and applicable across diverse populations, improving the care and outcomes for individuals affected by sarcopenia.