Sarcopenia, characterized by a progressive and generalized loss of skeletal muscle mass, strength, and function, has emerged as a major geriatric syndrome with profound health implications. It contributes significantly to frailty, falls, functional decline, disability, hospitalization, and mortality among elderly individuals [1].

The prevalence of sarcopenia is rising globally with increasing life expectancy, emphasizing the urgent need for early diagnosis and effective intervention strategies [2].

Traditional diagnostic modalities for assessing muscle mass include dual-energy X-ray absorptiometry (DEXA), computed tomography (CT), and magnetic resonance imaging (MRI). However, their clinical utility is often limited by cost, accessibility, exposure to ionizing radiation (in case of CT), and logistical barriers, particularly in low-resource settings [3].

In this context, ultrasound-based muscle assessment has emerged as a promising, non-invasive, affordable, and portable alternative for evaluating skeletal muscle mass and architecture. Recent systematic reviews and meta-analyses have validated the accuracy and reliability of ultrasound in diagnosing sarcopenia, underscoring its potential role as a frontline screening tool [4,5].

Among various skeletal muscles, the quadriceps femoris — especially the rectus femoris and vastus intermedius — is of particular interest. Quadriceps muscle atrophy appears early in the sarcopenic process and significantly impacts mobility and independence in elderly adults [2,6].

Ultrasound measurement of quadriceps thickness is simple to perform, reproducible, and correlates strongly with functional outcomes, offering a practical method for early detection of sarcopenia.

Despite accumulating evidence from Western populations, there is limited data on ultrasound-based quadriceps assessment among elderly individuals in the Indian subcontinent. Differences in body composition, nutrition, physical activity levels, and ethnic variations may influence muscle morphology and sarcopenia prevalence, necessitating region-specific research.

In light of these considerations, the present study was undertaken at Patna Medical College and Hospital (PMCH), Patna, Bihar.

The primary objective was to assess quadriceps muscle thickness using ultrasound in elderly adults and to evaluate its association with sarcopenia based on established diagnostic criteria.

Study Design and Setting

This was a cross-sectional observational study conducted at the Department of Geriatrics and Radiology, Patna Medical College and Hospital (PMCH), Patna, Bihar, India, from January 2024 to December 2024.

Study Population

The study enrolled 100 elderly adults aged 60 years and above, attending outpatient clinics or admitted for general medical care.

Participants were recruited consecutively based on eligibility criteria.

Inclusion Criteria

·         Age ≥ 60 years

·         Ability to ambulate independently or with minimal assistance

·         Willingness to participate and provide informed written consent

Exclusion Criteria

·         History of acute illness, trauma, or hospitalization within the past month

·         Presence of neuromuscular disorders affecting lower limb muscles

·         Active malignancy, chronic inflammatory disease, or severe renal/hepatic failure

·         Oedema or localized infections of the thigh precluding accurate ultrasound measurement

Ethical Considerations

The study protocol was reviewed and approved by the Institutional Ethics Committee of Patna Medical College and Hospital.

All participants provided written informed consent prior to enrollment.

Ultrasound Assessment of Quadriceps Muscle Thickness

Quadriceps muscle thickness was assessed using B-mode ultrasonography with a 7.5–10 MHz linear-array transducer.

Measurements were performed with participants lying supine, knees extended but relaxed, and muscles at rest.

·         The anatomical landmark for measurement was defined as the midpoint between the anterior superior iliac spine (ASIS) and the superior border of the patella.

·         Muscle thickness was measured from the superficial fascia of the rectus femoris to the deep fascia of the vastus intermedius.

·         Three measurements were obtained for each participant, and the average value was recorded to minimize intra-observer variability.

·         All ultrasound examinations were performed by a single trained radiologist blinded to the clinical data.

Definition and Diagnosis of Sarcopenia

Sarcopenia was diagnosed based on the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) 2019 criteria.

The diagnostic algorithm incorporated:

·         Low muscle strength, defined by reduced handgrip strength (thresholds: <27 kg for men, <16 kg for women),

·         Low muscle quantity, indicated by reduced quadriceps muscle thickness assessed by ultrasound (population-specific cut-offs were considered where applicable),

·         Physical performance assessment was not included in the primary diagnosis but recorded separately when feasible.

Participants meeting criteria for both low muscle strength and low muscle quantity were classified as having confirmed sarcopenia.

Data Collection

The following variables were recorded for each participant:

·         Demographic data (age, sex)

·         Anthropometric measurements (height, weight, body mass index)

·         Clinical history (comorbidities, medications)

·         Handgrip strength (measured using a calibrated dynamometer)

·         Quadriceps muscle thickness (ultrasound)

Statistical Analysis

Data were entered into Microsoft Excel and analyzed using SPSS version 26.0 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as mean ± standard deviation (SD) or median (interquartile range), depending on the distribution. Categorical variables were summarized as frequencies and percentages.

Comparisons between participants with and without sarcopenia were performed using the Independent Samples t-test or Mann–Whitney U test for continuous variables, and the Chi-square test for categorical variables. The association between quadriceps muscle thickness and sarcopenia status was further evaluated using logistic regression analysis.

Additionally, a receiver operating characteristic (ROC) curve analysis was conducted to assess the discriminative ability of quadriceps muscle thickness in identifying sarcopenia.

A p-value of less than 0.05 was considered statistically significant.

1. Study Population Characteristics

A total of 100 elderly adults were included in the study. The mean age of participants was 68.2 ± 5.9 years, with 52 males (52%) and 48 females (48%). The mean body mass index (BMI) was 23.9 ± 3.4 kg/m². Sarcopenia, diagnosed based on the EWGSOP2 2019 criteria, was identified in 32 participants (32%), while the remaining 68 participants (68%) were classified as non-sarcopenic.

Baseline demographic and clinical characteristics of the study population, stratified according to sarcopenia status, are summarized in Table 1.

Table 1: Baseline Demographic and Clinical Characteristics of the Study Population

2. Quadriceps Muscle Thickness Measurements

Quadriceps muscle thickness, as assessed by ultrasound, was significantly lower among participants with sarcopenia compared to those without sarcopenia. The mean quadriceps thickness in the sarcopenia group was 1.58 ± 0.21 cm, whereas in the non-sarcopenia group it was 2.32 ± 0.27 cm, a difference that was statistically significant (p < 0.001).

The distribution of quadriceps muscle thickness between the two groups is presented in Table 2. A visual comparison is depicted in Figure 1, illustrating the marked reduction in muscle thickness among sarcopenic individuals.

Table 2: Comparison of Quadriceps Muscle Thickness between Sarcopenic and Non-Sarcopenic Participants

3. Association between Quadriceps Muscle Thickness and Sarcopenia

Logistic regression analysis demonstrated a significant association between quadriceps muscle thickness and sarcopenia. Each 1 cm decrease in quadriceps thickness was associated with a 2.47-fold higher odds of having sarcopenia (odds ratio [OR]: 2.47; 95% confidence interval [CI]: 1.65–3.71; p < 0.001).

The details of the logistic regression analysis are presented in Table 3.

Table 3: Logistic Regression Analysis of Quadriceps Muscle Thickness as a Predictor of Sarcopenia

4. Diagnostic Performance of Quadriceps Muscle Thickness

Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of quadriceps muscle thickness in identifying sarcopenia. The area under the ROC curve (AUC) was 0.819, indicating good discriminative ability. An optimal quadriceps muscle thickness cut-off value of 1.85 cm was identified, which provided a sensitivity of 81% and a specificity of 75% for diagnosing sarcopenia.

The ROC curve is illustrated in Figure 2, and detailed diagnostic performance parameters are summarized in Table 4.

Table 4: Diagnostic Performance of Quadriceps Muscle Thickness for Sarcopenia Detection

Summary of Main Findings

In this cross-sectional study involving 100 elderly adults, the prevalence of sarcopenia, diagnosed based on the EWGSOP2 2019 criteria, was found to be 32%.

Quadriceps muscle thickness, assessed via ultrasound, was significantly lower among participants with sarcopenia compared to those without sarcopenia (1.58 ± 0.21 cm vs. 2.32 ± 0.27 cm; p < 0.001).
Logistic regression analysis revealed that each 1 cm decrease in quadriceps thickness was associated with a 2.47-fold increase in the odds of having sarcopenia (p < 0.001).

Receiver operating characteristic (ROC) curve analysis demonstrated that quadriceps muscle thickness had good discriminative ability for sarcopenia detection, with an area under the curve (AUC) of 0.819.

An optimal cut-off value of 1.85 cm provided a sensitivity of 81% and a specificity of 75% for identifying sarcopenia.

The present study demonstrates that ultrasound-based assessment of quadriceps muscle thickness is significantly associated with sarcopenia in elderly adults.

Participants with sarcopenia exhibited markedly reduced quadriceps thickness compared to their non-sarcopenic counterparts. Furthermore, a decrease in quadriceps muscle thickness was independently associated with an increased risk of sarcopenia, and quadriceps thickness showed good discriminative ability for sarcopenia detection with an AUC of 0.819.

Our findings are consistent with previous literature supporting the utility of ultrasound in sarcopenia diagnosis. Sabatino et al. [7] demonstrated that quadriceps muscle thickness assessed by ultrasound, in combination with handgrip strength, predicted mortality among hemodialysis patients, underscoring the prognostic significance of ultrasound-derived muscle metrics. Similarly, Matsui et al. [8] validated the reliability of ultrasound-based cross-sectional area measurement of the quadriceps, reinforcing its application in clinical and research settings.

The quadriceps femoris muscle, particularly the rectus femoris and vastus intermedius, has been identified as a preferential site of early muscle wasting in ageing adults [9]. Its functional relevance in mobility and balance further justifies its selection as a target for sarcopenia assessment. Abe et al. [10] highlighted the clinical relevance of using muscle thickness measurements via ultrasound as a surrogate for muscle mass estimation, emphasizing its feasibility in bedside evaluations.

Moreover, the accuracy and reliability of ultrasound in quantifying skeletal muscle have been extensively validated. Nijholt et al. [11] in a systematic review confirmed that ultrasound is a reliable and valid method for assessing muscle mass in older adults, with good intra- and inter-observer agreement. Recent efforts toward standardization of ultrasound protocols for muscle assessment, as recommended by Perkisas et al. [12], further enhance its clinical applicability.

The optimal cut-off value of 1.85 cm for quadriceps thickness identified in our study is comparable to cut-offs reported in other regional and international studies. While slight differences in thresholds may arise due to variations in ethnicity, nutrition, and physical activity patterns, the consistently observed trend of reduced quadriceps thickness among sarcopenic individuals across populations strengthens the generalizability of our findings [13].

Importantly, our results align with the observation that muscle wasting in ageing is not uniform across all muscle groups. Reimers et al. [14] demonstrated that the quadriceps muscle is more susceptible to age-related atrophy compared to other muscle groups, which supports the targeted use of quadriceps ultrasound as an early diagnostic marker.

The implications of using ultrasound for sarcopenia screening in resource-limited settings, such as India, are considerable. Given its affordability, portability, and non-ionizing nature, ultrasound can facilitate large-scale community screening, especially where access to DEXA or MRI is limited. Takai et al. [15] also supported the applicability of ultrasound muscle thickness measurements as a predictor of fat-free mass in elderly populations, further endorsing its role in routine geriatric assessments.

Nonetheless, this study has certain limitations. Being cross-sectional, causality cannot be established. Muscle quality parameters (such as echogenicity) and longitudinal follow-up of functional outcomes were not evaluated. Future research should focus on longitudinal validation of quadriceps ultrasound parameters against clinical endpoints such as falls, disability, and mortality.

Ultrasound assessment of quadriceps muscle thickness offers a practical, reliable, and effective method for early detection of sarcopenia in elderly adults. Incorporating muscle ultrasound into routine geriatric evaluations can facilitate timely interventions aimed at preserving muscle mass, preventing disability, and improving quality of life in the ageing population.

1.       Wu, S., Nan, J., Chang, J., Jiang, D., Cao, Z., Zhou, S., Feng, H., & Xiao, L. D. (2025). Adherence to exercise intervention for community-dwelling older adults with sarcopenia: A systematic review and meta-analysis. Age and Ageing, 54(4), afaf094. https://doi.org/10.1093/ageing/afaf094

2.       de Frutos-Galindo, I., Catalina-Palomares, D., Yubero-García, P., Botella-Juan, L., Vargas-Caraballo-Lockwood, D., Marcos-Delgado, A., Fernández-Villa, T. (2025). Effects of sleep on sarcopenia in individuals with metabolic syndrome: A systematic review. Semergen, 51(4), 102483. https://doi.org/10.1016/j.semerg.2025.102483

3.       Ibrahim, K., Cox, N. J., Lim, S. E. R., Radcliffe, E., Lundby, C., Prokopidis, K., Thompson, W., Moriarty, F. (2025). The evidence and impact of deprescribing on sarcopenia parameters: A systematic review. BMC Geriatrics, 25(1), 158. https://doi.org/10.1186/s12877-025-05819-7

4.       Fu, H., Wang, L., Zhang, W., Lu, J., & Yang, M. (2022). Diagnostic test accuracy of ultrasound for sarcopenia diagnosis: A systematic review and meta-analysis. Journal of Cachexia, Sarcopenia and Muscle, 14(1), 57–70. https://doi.org/10.1002/jcsm.13149

5.       Hou, S., Zhao, X., Wei, J., & Wang, G. (2025). The diagnostic performance of phase angle for sarcopenia among older adults: A systematic review and diagnostic meta-analysis. Archives of Gerontology and Geriatrics, 131, 105754. https://doi.org/10.1016/j.archger.2025.105754

6.       Nijholt, W., Scafoglieri, A., Jager-Wittenaar, H., Hobbelen, J. S. M., & van der Schans, C. P. (2017). The reliability and validity of ultrasound to quantify muscles in older adults: A systematic review. Journal of Cachexia, Sarcopenia and Muscle, 8(5), 702–712. https://doi.org/10.1002/jcsm.12210

7.       Sabatino, A., Kooman, J., Avesani, C. M., Gregorini, M., Bianchi, S., Regolisti, G., & Fiaccadori, E. (2024). Sarcopenia diagnosed by ultrasound-assessed quadriceps muscle thickness and handgrip strength predicts mortality in patients on hemodialysis. Journal of Nephrology, 37(6), 993–1003. https://doi.org/10.1007/s40620-023-01867-7

8.       Matsui, Y., Takemura, M., Suzuki, Y., Watanabe, T., Maeda, K., Satake, S., & Arai, H. (2024). Evaluation of quadriceps muscle cross-sectional area using an ultrasonic diagnostic equipment with a wide field of view. PLOS ONE, 19(9), e0311043. https://doi.org/10.1371/journal.pone.0311043

9.       Abe, T., Loenneke, J. P., & Thiebaud, R. S. (2014). Ultrasound assessment of skeletal muscle size in sarcopenia research. Clinical Physiology and Functional Imaging, 34(6), 447–456. https://doi.org/10.1111/cpf.12102

10.    Nijholt, W., Scafoglieri, A., Jager-Wittenaar, H., Hobbelen, J. S. M., & van der Schans, C. P. (2017). The reliability and validity of ultrasound to quantify muscles in older adults: A systematic review. Journal of Cachexia, Sarcopenia and Muscle, 8(5), 702–712. https://doi.org/10.1002/jcsm.12210

11.    Perkisas, S., Baudry, S., Bauer, J., Beckwée, D., Cruz-Jentoft, A. J., Piotrowicz, K., ... & De Cock, A. M. (2018). Application of ultrasound for muscle assessment in sarcopenia: Towards standardized measurements. European Geriatric Medicine, 9(6), 739–757. https://doi.org/10.1007/s41999-018-0104-9

12.    Reimers, C. D., Harder, T., & Saxe, H. (1998). Age-related muscle atrophy does not affect all muscles and can partly be compensated by physical activity: An ultrasound study. Journal of Neurology, 245(5), 255–261. https://doi.org/10.1007/s004150050203

13.    Takai, Y., Ohta, M., Akagi, R., Kanehisa, H., Kawakami, Y., & Fukunaga, T. (2013). Applicability of ultrasound muscle thickness measurements for predicting fat-free mass in elderly population. Journal of Nutritional Health and Aging, 17(6), 554–558. https://doi.org/10.1007/s12603-013-0025-5