To explore the diagnostic and evaluation value of musculoskeletal ultrasound elastography in the standing position for nonspecific low back pain (NLBP).

A total of 16 patients with NLBP, who had not received treatment within two weeks prior to enrollment, were recruited as the observation group from Shanghai Ruijin Rehabilitation Hospital between June 2024 and June 2025, and 8 healthy people in the same period were selected as the control group. Before treatment or during physical examination, basic data such as gender, age, and body mass index (BMI) were collected, and musculoskeletal ultrasound related indicators (thickness of transversus abdominis, elastic modulus of transversus abdominis, thickness of lumboiliocostoid muscle, elastic modulus of lumboiliocostoid muscle) were measured in standing position. At the same time, the visual analogue scale (VAS) was used to evaluate the degree of pain in the observation group. R 4.5.2 software was used for statistical analysis and diagnostic modeling, and the receiver operating characteristic (ROC) curve was drawn. The area under curve (AUC), sensitivity, specificity and cut-off value of each diagnostic model were calculated, and the diagnostic efficacy of each model was compared.

There was no significant difference in gender, age, and BMI between the observation group and the control group (P>0.05). There was no significant difference in the thickness of transversus abdominis and lumboiliocostalis between the observation group and the control group (P>0.05). The elastic modulus of transverse abdominis in the observation group was significantly lower than that in the control group, and the elastic modulus of lumboiliocostalis in the observation group was significantly higher than that in the control group, and the differences were statistically significant (P<0.05). Pearson correlation analysis showed that among the diagnostic models, the quadratic power model of elastic modulus ratio (the ratio between the elastic modulus of transverse abdominis muscle and the elastic modulus of lumboiliocostoid muscle) had the best diagnostic performance, with an AUC of 1.000, followed by the elastic modulus of lumboiliocostoid muscle and elastic modulus ratio model, with AUC of 0.852 and 0.812, respectively. In addition, the VAS score of the observation group was positively correlated with the elastic modulus of the lumbar iliocostalis muscle in the standing position (P<0.001), and the VAS score of the observation group was negatively correlated with the ratio of elastic modulus in the standing position (P<0.001). In the control group, the ratio of elastic modulus in standing position was between 1.22 and 1.90, while in the observation group, the ratio was between 0.50 and 1.22 or >1.90.

The ratio of the elastic modulus of the transverse abdominis muscle to that of the lumboiliocostoid muscle measured by ultrasound in standing position can be used as an objective parameter, which is correlated with the subjective VAS score of NLBP patients, suggesting that the evaluation of muscle and bone elastography in standing position is expected to be one of the objective evaluation methods for NLBP patients, and provide quantitative basis for early diagnosis, efficacy evaluation and rehabilitation plan development.

This paper systematically evaluates the efficacy and safety of the domestic electromagnetic muscle toning device called NEOSCULPT, which is based on high-intensity focused electromagnetic field (HIFEM) technology for abdominal and gluteal contouring.

A prospective self-controlled clinical trial was conducted in two phases (gluteal and abdominal), each involving 32 healthy subjects. All subjects received targeted electromagnetic interventions twice a week for 30 minutes each session over a period of 4 weeks. Body circumference measurements, MRI imaging analysis, body composition analysis, and blood and urine biochemical tests were performed at baseline, at the end of the intervention, and one month post-intervention. Adverse events were recorded.

Following the gluteal intervention, the average overall hip circumference increased by 2.2% (P<0.001), and the average waist-to-hip ratio in females improved by 6.7% (P<0.01). Following the abdominal intervention, male subjects showed a 6.3% increase in abdominal muscle area (P<0.01) and a 10.4% decrease in fat area (P<0.001); female subjects showed an 11.8% increase in abdominal muscle area (P<0.001) and a 7.5% decrease in fat area (P<0.01). The overall efficacy rate for muscle enhancement and fat reduction was 80%, with an average reduction of 1% in total body fat percentage (P<0.001) and an average reduction of 8.2% in abdominal subcutaneous fat thickness (P<0.001). These effects were generally maintained during the follow-up period. Apart from a physiological increase in creatine kinase levels post-exercise, no abnormal fluctuations were observed in blood and urine biochemical parameters. Only one case experienced changes in renal function, which recovered after treatment, with no serious adverse events occurring.

The NEOSCULPT electromagnetic muscle toning device significantly increased participants' gluteal circumference and improved gluteal firmness, while simultaneously achieving dual effects of abdominal muscle growth and fat reduction, with excellent clinical application safety. These findings provide high-quality evidence-based support for the clinical application of domestically produced non-invasive muscle enhancement devices.

Evaluate the diagnostic performance of a deep learning model in assisting primary care ultrasound doctors in differentiating benign and malignant breast nodules.

This study retrospectively collected female patients who were diagnosed with BI-RADS category 3 and 4 breast nodules during routine ultrasound examinations at Shanghai Sixth People's Hospital from September 2022 to September 2024. The clinical data and ultrasound images of these patients were collected.. Five deep learning models (GoogLeNet, VGG11, AlexNet, ResNet-34, ViT) were constructed, and the optimal model was selected based on metrics such as area under curve (AUC). Visual heatmaps of the ultrasound images were generated using the optimal model. Community ultrasound physicians independently reviewed the images without knowledge of the pathological results. Two weeks later, the physicians re-reviewed the images with the assistance of the generated heatmaps. Diagnostic performance was compared among three approaches: deep learning model alone, physician independent review, and deep learning-assisted physician review, using accuracy, sensitivity, specificity, and precision as metrics.

A total of 430 patients with breast nodules were included and divided into a training set (n=301) and a validation set (n=129). Among the different learning models constructed based on breast ultrasound images, the ResNet-34 model performed best in predicting benign and malignant breast nodules, with AUC, accuracy, and sensitivity superior to other models in both the training and validation sets. Therefore, the ResNet-34 model was selected as the optimal model. Among the three approaches, the diagnostic efficacy of independent review by primary care physicians was the lowest. The deep learning model slightly outperformed primary care physicians in terms of accuracy, sensitivity, and precision, while the diagnostic efficacy of the deep learning model assisting ultrasound physicians in reading was the strongest, with all evaluation indicators significantly improved. In terms of the improvement rate, the sensitivity and F1 value showed the most significant increase, rising by 34.3% and 29.9% respectively.

Deep learning models based on ultrasound images can effectively distinguish the benign and malignant nature of breast nodules. Combined with the generated visual heatmaps, they can significantly enhance the diagnostic efficacy of assisting primary ultrasound physicians in distinguishing between benign and malignant breast nodules, providing valuable guidance for selecting treatment plans for patients with breast nodules.

To construct a full life cycle quality management model for traditional Chinese medicine (TCM) diagnostic and treatment equipment and evaluate its application effects.

A total of 357 TCM diagnostic and treatment equipment units under management and 360 patients receiving physiotherapy at a tertiary Class-A TCM hospital were selected as the research subjects. From January to December 2024, the traditional equipment management model was implemented for these 357 units, and 180 patients were included as the traditional equipment management group; from January to June 2025, the full life cycle quality management model was implemented for the same 357 units, with the information management platform as the core hub and the unique electronic identity file of the equipment as the data mainline, covering the entire process of procurement and acceptance, usage monitoring, preventive maintenance, fault response and scrap replacement, and 180 patients were included as the full life cycle quality management group. Monthly average failure rate, intact rate, idle rate, preventive maintenance execution rate, adverse event incidence, maintenance response time, and patient clinical efficacy were compared between the two groups.

Compared with the traditional equipment management group (2.35%, 3.08%, 2.80%), the full life cycle quality management group showed significantly lower monthly average failure rate (0.67%), idle rate (0.56%), and adverse event incidence (0.56%); maintenance response time was shorter [(2.00±0.45)h vs. (6.48±1.23)h]; intact rate (96.64% vs. 85.15%) and preventive maintenance execution rate (95.52% vs. 68.35%) were markedly higher; and the total clinical effective rate (93.33% vs. 78.33%) was significantly improved. All differences were statistically significant (P<0.05).

Compared with the traditional management model, the full life cycle quality management model for TCM diagnostic and treatment equipment significantly reduces equipment failure rates and adverse event incidence, enhances operational efficiency and patient clinical outcomes, and demonstrates considerable value for broader implementation.

To investigate the prognostic value of pre-treatment skeletal muscle index at the third lumbar vertebra (L3-SMI) for survival in patients with cervical cancer, and to analyze its predictive performance across different International Federation of Gynecology and Obstetrics (FIGO) stages.

Clinical data and imaging studies of patients with cervical cancer diagnosed and treated at Hunan Cancer Hospital from January 2014 to December 2019 were retrospectively collected. Skeletal muscle was segmented at the mid-vertebral level of the third lumbar vertebra, and skeletal muscle area (SMA) was measured. L3-SMI was calculated as SMA divided by body surface area (BSA). The optimal cut-off value of L3-SMI for predicting overall survival (OS) in cervical cancer patients was determined using receiver operating characteristic (ROC) curve analysis. Survival differences between patients with different L3-SMI levels were compared using the Kaplan-Meier method and Log-Rank test. The independent prognostic value of L3-SMI was analyzed using the Cox proportional hazards regression model.

A total of 207 patients were enrolled in this study. Survival analysis showed that L3-SMI was not significantly correlated with OS in the early-stage group (FIGO stages I and IIA, P>0.05), but was significantly correlated with OS in the advanced-stage group (FIGO stages IIB, III and IV, P<0.05). The optimal cut-off value of L3-SMI for predicting OS in advanced-stage patients was 39.8 cm²/m², with an area under curve (AUC) of 0.668. Accordingly, 101 advanced-stage patients were divided into the high L3-SMI group (≥39.8 cm²/m², n=51) and the low L3-SMI group (<39.8 cm²/m², n=50). Kaplan-Meier analysis demonstrated that patients in the high L3-SMI group had significantly better OS than those in the low L3-SMI group, with a statistically significant difference (Log-Rank χ²=8.20, P=0.004 2). Multivariate Cox regression analysis revealed that low L3-SMI remained an independent risk factor for OS in advanced-stage patients after adjusting for age, FIGO stage, and pathological type (HR=2.561, 95%CI: 1.040~6.336, P=0.039).

Pre-treatment L3-SMI is an independent prognostic factor for survival in patients with advanced-stage cervical cancer (FIGO stage IIB and above), and this biomarker has clinical value in predicting the prognosis of advanced cervical cancer patients.

To investigate the clinical efficacy of a 10-day intervention combining progressive core training with individually adjusted intensity, neuromuscular electrical stimulation (NMES), and manual therapy.

A total of 50 postpartum patients with diastasis recti abdominis (DRA) who visited the Pelvic Floor Clinic of our hospital from December 2024 to January 2026 were enrolled and randomly divided into a control group and an experimental group, with 25 cases in each group. The control group received NMES and manual therapy, while the experimental group received progressive core training in addition to the same NMES and manual therapy. Both groups were treated once daily for 10 consecutive days. The inter-rectus distance (IRD), abdominal circumference, and Oswestry disability index (ODI) scores were compared between the two groups before and after the intervention.

After 10 consecutive days of intervention, both groups showed significant improvements in IRD measured at three sites (4.5 cm above the umbilicus, at the umbilicus, and 4.5 cm below the umbilicus), abdominal circumference, and ODI scores compared with baseline (all P<0.001). Compared with the control group, the experimental group demonstrated significantly greater improvements in IRD at all three sites, abdominal circumference, and ODI scores after the intervention (all P<0.05).

Under the regimen of once-daily intervention for 10 consecutive days, the combination of progressive core training, NMES, and manual therapy effectively reduces IRD and abdominal circumference, and improves low back pain-related functional disability in postpartum patients with diastasis recti abdominis.

To investigate the application value of dual-energy X-ray absorptiometry (DXA) combined with magnetic resonance imaging (MRI) in evaluating the fracture severity and predicting the functional prognosis in patients with osteoporotic vertebral compression fracture (OVCF).

70 patients with OVCF admitted to our hospital from December 2023 to July 2025 were included. All patients underwent DXA and MRI examinations, recording imaging parameters such as bone mineral density (BMD) values, T values, vertebral compression rate, bone marrow edema volume, and signal intensity ratio. According to the Genant semi quantitative method, the patients were divided into mild group, moderate group, and severe group. Compare the differences in imaging parameters, visual analogue scale (VAS) scores, and Oswestry disability index (ODI) among patients with different fracture severity. Pearson analysis was used to evaluate the correlation between imaging parameters, VAS scores, and ODI. According to the ODI improvement rate at 6 months after treatment, the patients were divided into good prognosis group and poor prognosis group. Multivariate logistic regression analysis was used to identify independent risk factors for poor prognosis. Receiver operating characteristic (ROC) curves were used to evaluate the predictive value of each indicator and combined model for poor prognosis.

With the fracture severity increased, the BMD and T values gradually decreased, the vertebral compression rate, bone marrow edema volume, signal intensity ratio, VAS scores, and ODI gradually increased in the three groups, the differences were statistically significant (P<0.05). Pearson correlation analysis showed that BMD values were negatively correlated with VAS scores and ODI (P<0.05), the bone marrow edema volume was positively correlated with VAS scores and ODI (P<0.05). Multivariate logistic regression analysis indicated that T values (OR=2.416, 95%CI: 1.213~4.798), vertebral compression ratio (OR=3.121, 95%CI: 1.472~6.618), and bone marrow edema volume (OR=2.183, 95%CI: 1.134~4.209) were independent risk factors for poor prognosis (P<0.05). ROC curve analysis showed that the area under curve (AUC) of T values, vertebral compression ratio, and bone marrow edema volume for predicting the poor prognosis were 0.763, 0.781, and 0.752, while the AUC of the combined model was 0.892.

T values, vertebral compression rate, and bone marrow edema volume are closely related to the fracture severity and functional prognosis in patients with OVCF. DXA combined with MRI can comprehensively evaluate OVCF from multiple dimensions such as bone mass, vertebral structure, and bone marrow response, which is helpful in predicting the prognosis, and has important value in guiding individualized clinical treatment.

To analyze the differences in fat deposition in the pancreas, kidneys and vertebral bodies between patients with metabolic syndrome (MetS) and healthy subjects using the mDixon-Quant quantitative technique, and to investigate metabolic parameters among MetS patients with different visceral fat deposition patterns.

This prospective study enrolled 58 MetS patients admitted to the Department of Endocrinology, the Second Affiliated Hospital of Mudanjiang Medical University between June 2023 and September 2024 into the MetS group. Meanwhile, 52 healthy volunteers were recruited as the control group. The fat fraction (FF) and T2* values of the pancreas, renal cortex, renal medulla and vertebral bodies were measured via mDixon-Quant sequence. Clinical data including waist circumference, body mass index (BMI), triglycerides, total cholesterol and high-density lipoprotein cholesterol were collected. The K-means clustering algorithm was applied to stratify MetS patients into subgroups according to fat deposition patterns, and metabolic indicators were compared across subgroups.

Waist circumference, BMI, triglyceride levels, as well as FF values of the pancreas, renal cortex and vertebral bodies were significantly higher in the MetS group than in the control group, whereas high-density lipoprotein cholesterol levels and T2* values of the pancreas, renal cortex and renal medulla were markedly lower (all P<0.05). Clustering analysis classified MetS patients into three phenotypes: multi-organ fat deposition, pancreas-skeleton predominant fat deposition, and kidney-predominant fat deposition. Patients with multi-organ fat deposition exhibited significantly higher waist circumference, triglycerides and total cholesterol compared with the other two subgroups (P<0.05).

The FF values of the pancreas, kidneys and vertebral bodies are significantly elevated in MetS patients. Among all phenotypes, individuals with multi-organ fat deposition present higher triglyceride and total cholesterol concentrations. The concept of multi-organ synergistic lesions can provide imaging evidence for precise subtyping and risk stratification of metabolic syndrome.