About this trial
This study aims to evaluate the clinical value of multimodal ultrasound for assessing muscle mass in patients with metabolic diseases, including metabolic syndrome, type 2 diabetes, and simple obesity. Skeletal muscle is the largest metabolic organ in the human body and plays a critical role in glucose metabolism. Muscle mass reduction is common in patients with metabolic diseases and is associated with insulin resistance, poor disease control, and increased risk of complications. Currently available methods for muscle assessment, such as dual-energy X-ray absorptiometry (DXA), computed tomography (CT), and magnetic resonance imaging (MRI), have limitations including high cost, radiation exposure, or poor portability, making them unsuitable for routine bedside monitoring.
Multimodal ultrasound combines B-mode imaging, shear-wave elastography, superb microvascular imaging, and artificial intelligence analysis to provide a comprehensive evaluation of muscle morphology, stiffness, microcirculation, and quality. This non-invasive, radiation-free, and portable technique may serve as an ideal tool for muscle assessment in clinical practice.
This prospective observational study will enroll 320 participants divided into four groups: metabolic syndrome (n=80), type 2 diabetes (n=80), simple obesity (n=80), and healthy controls (n=80). All participants will undergo baseline assessments including clinical data collection, biochemical tests, muscle function tests (handgrip strength, gait speed, Short Physical Performance Battery \[SPPB\]), multimodal ultrasound examination (muscle thickness, cross-sectional area, echo intensity, shear wave velocity, Young's modulus, microvascular density), and DXA measurement as the reference standard. The three metabolic disease groups will be followed prospectively for 12 months with repeat assessments at 6 and 12 months.
The primary objectives are to determine diagnostic thresholds of multimodal ultrasound parameters for detecting metabolic sarcopenia; to establish correlation between ultrasound parameters and metabolic indicators (blood glucose, glycated hemoglobin \[HbA1c\], homeostatic model assessment of insulin resistance \[HOMA-IR\], lipids); to develop a combined diagnostic model integrating ultrasound and clinical parameters; and to evaluate the predictive value of baseline ultrasound parameters for 12-month disease progression and complications. The findings will provide a non-invasive, convenient, and widely applicable tool for early screening, risk stratification, and therapeutic monitoring of muscle abnormalities in patients with metabolic diseases.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Diagnosis of metabolic syndrome according to the Chinese Consensus on Diagnosis and Management of Metabolic Syndrome (2020 edition), meeting at least 3 of the following 5 criteria: abdominal obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL-C.
Diagnosis of type 2 diabetes according to the ADA 2023 diagnostic criteria, with disease duration of at least 1 year.
Body mass index (BMI) >= 28 kg/m², without hypertension, hyperglycemia, dyslipidemia, or other metabolic abnormalities.
Healthy volunteers without metabolic diseases, muscle diseases, chronic liver or kidney dysfunction, malignancies, cardiovascular diseases, or neurological disorders, and without long-term use of corticosteroids or other medications affecting muscle metabolism.
Disqualifiers
Severe hepatic or renal failure, malignancy, stroke, severe cardiovascular disease, or autoimmune diseases.
Long-term use of corticosteroids, muscle relaxants, or other medications affecting muscle metabolism.
Presence of movement disorders, joint diseases, muscle injury, muscular dystrophy, or other conditions affecting muscle function.
Pregnancy or lactation.
Trial population
Adult patients diagnosed with metabolic syndrome, type 2 diabetes, or simple obesity, as well as healthy volunteers, recruited from the Endocrinology Department and Physical Examination Center of Zhangzhou Hospital, Fujian Medical University. All participants must meet the specified inclusion and exclusion criteria. The three metabolic disease groups will be matched with healthy controls by age and sex. A total of 320 participants (80 per group) will be enrolled.
Trial design
Cohort
Prospective
Treatments tested in this trial
Not listed
Trial groups
Trial outcomes
Primary outcomes
Area under the ROC curve (AUC) of multimodal ultrasound for detecting metabolic sarcopenia
Area under the receiver operating characteristic curve (AUC) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Sensitivity of multimodal ultrasound for detecting metabolic sarcopenia
Sensitivity (true positive rate) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Specificity of multimodal ultrasound for detecting metabolic sarcopenia
Specificity (true negative rate) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Positive predictive value of multimodal ultrasound for detecting metabolic sarcopenia
Positive predictive value of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
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