Correction to: Multi-View Feature Transformation Based SVM+ for Computer-Aided Diagnosis of Liver Cancers With Ultrasound Image.

Presents corrections to the paper, Multi-View Feature Transformation Based SVM+ for Computer-Aided Diagnosis of Liver Cancers With Ultrasound Image.

An approach to managing gallbladder polyps for the general practitioner.

BACKGROUND: Gallbladder polyps are increasingly being identified due to the widespread use of abdominal ultrasound imaging. They are concerning lesions due to their potential malignant risk. It is hoped that managing them correctly will play a role in improving poor survival rates of gallbladder cancer. Awareness of these lesions is lacking. Management continues to be guided by expert opinion and observational studies and a number of consensus statements exist. OBJECTIVE: This paper reviews and summarises the current literature and provides an approach for general practitioners based on the available guidance. DISCUSSION: Although minor variation exists between consensus statements, the risk of malignancy for gallbladder polyps is still largely dictated by size, with those ≤5 mm generally considered to pose little risk and not requiring follow-up, whereas those ≥10 mm considered at greater risk and requiring referral for cholecystectomy.

Characterizing Sentinel Lymph Node Status in Breast Cancer Patients Using a Deep-Learning Model Compared With Radiologists' Analysis of Grayscale Ultrasound and Lymphosonography.

ABSTRACT: The objective of the study was to use a deep learning model to differentiate between benign and malignant sentinel lymph nodes (SLNs) in patients with breast cancer compared to radiologists' assessments.Seventy-nine women with breast cancer were enrolled and underwent lymphosonography and contrast-enhanced ultrasound (CEUS) examination after subcutaneous injection of ultrasound contrast agent around their tumor to identify SLNs. Google AutoML was used to develop image classification model. Grayscale and CEUS images acquired during the ultrasound examination were uploaded with a data distribution of 80% for training/20% for testing. The performance metric used was area under precision/recall curve (AuPRC). In addition, 3 radiologists assessed SLNs as normal or abnormal based on a clinical established classification. Two-hundred seventeen SLNs were divided in 2 for model development; model 1 included all SLNs and model 2 had an equal number of benign and malignant SLNs. Validation results model 1 AuPRC 0.84 (grayscale)/0.91 (CEUS) and model 2 AuPRC 0.91 (grayscale)/0.87 (CEUS). The comparison between artificial intelligence (AI) and readers' showed statistical significant differences between all models and ultrasound modes; model 1 grayscale AI versus readers, P = 0.047, and model 1 CEUS AI versus readers, P < 0.001. Model 2 r grayscale AI versus readers, P = 0.032, and model 2 CEUS AI versus readers, P = 0.041.The interreader agreement overall result showed κ values of 0.20 for grayscale and 0.17 for CEUS.In conclusion, AutoML showed improved diagnostic performance in balance volume datasets. Radiologist performance was not influenced by the dataset's distribution.

Utilizing machine learning for early screening of thyroid nodules: a dual-center cross-sectional study in China.

Background: Thyroid nodules, increasingly prevalent globally, pose a risk of malignant transformation. Early screening is crucial for management, yet current models focus mainly on ultrasound features. This study explores machine learning for screening using demographic and biochemical indicators. Methods: Analyzing data from 6,102 individuals and 61 variables, we identified 17 key variables to construct models using six machine learning classifiers: Logistic Regression, SVM, Multilayer Perceptron, Random Forest, XGBoost, and LightGBM. Performance was evaluated by accuracy, precision, recall, F1 score, specificity, kappa statistic, and AUC, with internal and external validations assessing generalizability. Shapley values determined feature importance, and Decision Curve Analysis evaluated clinical benefits. Results: Random Forest showed the highest internal validation accuracy (78.3%) and AUC (89.1%). LightGBM demonstrated robust external validation performance. Key factors included age, gender, and urinary iodine levels, with significant clinical benefits at various thresholds. Clinical benefits were observed across various risk thresholds, particularly in ensemble models. Conclusion: Machine learning, particularly ensemble methods, accurately predicts thyroid nodule presence using demographic and biochemical data. This cost-effective strategy offers valuable insights for thyroid health management, aiding in early detection and potentially improving clinical outcomes. These findings enhance our understanding of the key predictors of thyroid nodules and underscore the potential of machine learning in public health applications for early disease screening and prevention.

Diagnostic performance of ultrasonography in pre-operative assessment of lymph nodes in patients with cervical cancer.

OBJECTIVES: To assess the diagnostic performance of ultrasonography in pre-operative assessment of lymph nodes in patients with cervical cancer, to compare the outcomes for pelvic and para-aortic regions, and to detect macrometastases and micrometastases separately. METHODS: Patients were retrospectively included if they met the following inclusion criteria: pathologically verified cervical cancer; ultrasonography performed by one of four experienced sonographers; surgical lymph node staging, at least in the pelvic region-sentinel lymph node biopsy or systematic pelvic lymphadenectomy or debulking. The final pathological examination was the reference standard. RESULTS: 390 patients met the inclusion criteria between 2009 and 2019. Pelvic node macrometastases (≥2 mm) were confirmed in 54 patients (13.8%), and micrometastases (≥0.2 mm and <2 mm) in another 21 patients (5.4%). Ultrasonography had sensitivity 72.2%, specificity 94.0%, and area under the curve (AUC) 0.831 to detect pelvic macrometastases, while sensitivity 53.3%, specificity 94.0%, and AUC 0.737 to detect both pelvic macrometastases and micrometastases (pN1). Ultrasonography failed to detect pelvic micrometastases, with sensitivity 19.2%, specificity 85.2%, and AUC 0.522. There was no significant impact of body mass index on diagnostic accuracy. Metastases in para-aortic nodes (macrometastases only) were confirmed in 16 of 71 patients who underwent para-aortic lymphadenectomy. Ultrasonography yielded sensitivity 56.3%, specificity 98.2%, and AUC 0.772 to identify para-aortic node macrometastases. CONCLUSION: Ultrasonography performed by an experienced sonographer can be considered a sufficient diagnostic tool for pre-operative assessment of lymph nodes in patients with cervical cancer, showing similar diagnostic accuracy in detection of pelvic macrometastases as reported for other imaging methods (18F-fluorodeoxyglucose positron emission tomography/CT or diffusion-weighted imaging/MRI). It had low sensitivity for detection of small-volume macrometastases (largest diameter <5 mm) and micrometastases. The accuracy of para-aortic assessment was comparable to that for pelvic lymph nodes, and assessment of the para-aortic region should be an inseparable part of the examination protocol.

[Development of a grading diagnostic model for schistosomiasis-induced liver fibrosis based on radiomics and clinical laboratory indicators].

OBJECTIVE: To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. METHODS: Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People's Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients'radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients'radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. RESULTS: The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = -5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. CONCLUSIONS: The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.

[Diagnostic Value of Ultrasound for Thyroid Nodules With a Spoke-Wheel Blood Flow Pattern].

Objective To explore the diagnostic value of ultrasound for thyroid nodules with a spoke-wheel blood flow pattern.Methods The clinical data of the patients with thyroid nodules presenting a spoke-wheel blood flow pattern examined by ultrasound were collected,and the gray-scale ultrasound features of the nodules were recorded.The diagnostic performance of the Thyroid Imaging Reporting and Data System by American College of Radiology (ACR TI-RADS),Chinese Thyroid Imaging Reporting and Data System (C-TIRADS),and combined specific indicators for the thyroid nodules with a spoke-wheel blood flow pattern was evaluated by comparison with the pathological results,which was regarded as the gold standard.Results A total of 64 patients with thyroid nodules were finally included,including 47 patients with malignant nodules and 17 patients with benign nodules.In addition to the general ultrasound features,central scar mostly appeared in malignant nodules (χ2=5.968,P=0.015),while central coarse calcification was more common in benign nodules (χ2=10.899,P=0.001).After the combination of central scar and central gross calcification,the diagnostic performance of ACR TI-RADS and C-TIRADS was improved (both P<0.001).Conclusions When the thyroid nodule shows a spoke-wheel blood flow pattern,one should be cautious of the possibility of malignancy.Combining central scar and central coarse calcification can improve the accuracy of ultrasonic diagnosis.

[SOP Leading symptom: flank pain]. / SOP Leitsymptom Flankenschmerzen.

In addition to triggers such as ureteral stones or pyelonephritis, the common symptom of flank pain can be associated with a whole range of conditions. This SOP is intended to give doctors in the emergency department an overview of the possible causes. Based on medical history, clincal examination including sonography and laboratory diagnostics, important differential diagnoses are addressed and an imaging algorithm is presented.

Combining CEUS and ultrasound parameters in thyroid nodule and cancer diagnosis: a TIRADS-based evaluation.

Contrast-enhanced ultrasonography (CEUS) has been established as a diagnostic tool for assessing microvascularization, essential for understanding angiogenesis in neoplastic development. AIM: This study assesses the effectiveness of CEUS as a supplementary tool to TIRADS in enhancing the ultrasound-based diagnosis of thyroid cancer. METHODS AND MATERIALS: Over one year, 157 nodules in 133 patients, with predominantly solid thyroid nodules, were examined using ultrasound and CEUS and underwent thyroidectomy, allowing for a comparison of ultrasound findings with pathological reports. RESULTS: Thyroid cancer was identified in 31.21% (49/157) of cases. Significant CEUS high-risk features included inhomogeneous enhancement, enhancement defects, and complete hypoenhancement (AUC 0.818, 0.767, 0.864 respectively). Nodules exhibiting any of these features were classified as high-risk in CEUS. The diagnostic performance of TIRADS improved when combined with CEUS, with AUC increasing from 0.707 to 0.840 and improved sensitivity. CONCLUSION: The integration of CEUS with TIRADS significantly enhances the diagnostic accuracy and specificity in identifying thyroid cancer. This combination proves to be a more effective method for risk stratification and diagnosis, highlighting the value of CEUS as an adjunctive tool in thyroid cancer evaluation.

The urgent need to extend the appropriate use of ultrasound in Africa and worldwide. Overview, experiences and perspectives.

It is known that in African countries the health condition is problematic, both from a diagnostic and therapeutic point of view. Patients have to travel long distances to access medical care. Many cannot afford the cost of transportation to a medical facility. Ultrasound its into the scenario of healthcare imaging with limited resources, as an effective, economical, repeatable diagnostic tool, requiring low maintenance. Ultrasound tools in fact are relatively cheap and machines are easy to move, making them adapt to be taken to a rural setting where they are most needed. However ultrasound exams are not easy to perform and they need an adequate training. The spread of POCUS (point-of-care "focused" ultrasound) worldwide could be useful in Africa to identify high-risk patients. These cases selected in rural setting by POCUS can be referred to hospitals for further treatment. To deal with these situations it is necessary to form doctors and/or paramedical staff capable of guaranteeing a qualitatively adequate service. Therefore the need for basic training is greater in developing countries. Sharing successful educational strategies should advance the integration of ultrasound into the university medical school curricula. This will ensure that recently qualified doctors can practice their basic skills accurately and independently.

Double contrast-enhanced ultrasonography improves diagnostic accuracy of T staging compared with multi-detector computed tomography in gastric cancer patients.

BACKGROUND: Gastric cancer (GC) is the most common malignant tumor and ranks third for cancer-related deaths among the worldwide. The disease poses a serious public health problem in China, ranking fifth for incidence and third for mortality. Knowledge of the invasive depth of the tumor is vital to treatment decisions. AIM: To evaluate the diagnostic performance of double contrast-enhanced ultrasonography (DCEUS) for preoperative T staging in patients with GC by comparing with multi-detector computed tomography (MDCT). METHODS: This single prospective study enrolled patients with GC confirmed by preoperative gastroscopy from July 2021 to March 2023. Patients underwent DCEUS, including ultrasonography (US) and intravenous contrast-enhanced ultrasonography (CEUS), and MDCT examinations for the assessment of preoperative T staging. Features of GC were identified on DCEUS and criteria developed to evaluate T staging according to the 8th edition of AJCC cancer staging manual. The diagnostic performance of DCEUS was evaluated by comparing it with that of MDCT and surgical-pathological findings were considered as the gold standard. RESULTS: A total of 229 patients with GC (80 T1, 33 T2, 59 T3 and 57 T4) were included. Overall accuracies were 86.9% for DCEUS and 61.1% for MDCT (P < 0.001). DCEUS was superior to MDCT for T1 (92.5% vs 70.0%, P < 0.001), T2 (72.7% vs 51.5%, P = 0.041), T3 (86.4% vs 45.8%, P < 0.001) and T4 (87.7% vs 70.2%, P = 0.022) staging of GC. CONCLUSION: DCEUS improved the diagnostic accuracy of preoperative T staging in patients with GC compared with MDCT, and constitutes a promising imaging modality for preoperative evaluation of GC to aid individualized treatment decision-making.

A machine learning model based on clinical features and ultrasound radiomics features for pancreatic tumor classification.

Objective: This study aimed to construct a machine learning model using clinical variables and ultrasound radiomics features for the prediction of the benign or malignant nature of pancreatic tumors. Methods: 242 pancreatic tumor patients who were hospitalized at the First Affiliated Hospital of Guangxi Medical University between January 2020 and June 2023 were included in this retrospective study. The patients were randomly divided into a training cohort (n=169) and a test cohort (n=73). We collected 28 clinical features from the patients. Concurrently, 306 radiomics features were extracted from the ultrasound images of the patients' tumors. Initially, a clinical model was constructed using the logistic regression algorithm. Subsequently, radiomics models were built using SVM, random forest, XGBoost, and KNN algorithms. Finally, we combined clinical features with a new feature RAD prob calculated by applying radiomics model to construct a fusion model, and developed a nomogram based on the fusion model. Results: The performance of the fusion model surpassed that of both the clinical and radiomics models. In the training cohort, the fusion model achieved an AUC of 0.978 (95% CI: 0.96-0.99) during 5-fold cross-validation and an AUC of 0.925 (95% CI: 0.86-0.98) in the test cohort. Calibration curve and decision curve analyses demonstrated that the nomogram constructed from the fusion model has high accuracy and clinical utility. Conclusion: The fusion model containing clinical and ultrasound radiomics features showed excellent performance in predicting the benign or malignant nature of pancreatic tumors.

Intensive Surveillance of Porcine-Rhesus Kidney Xenotransplant Using Different Ultrasound Techniques.

BACKGROUND: Significant progress has been made in kidney xenotransplantation in the past few years, and this field is accelerating towards clinical translation. Therefore, surveillance of the xenograft with appropriate tools is of great importance. Ultrasonography has been widely used in kidney allotransplantation and served as an economical and non-invasive method to monitor the allograft. However, questions remain whether the ultrasonographic criteria established for human kidney allograft could also be applied in xenotransplantation. METHODS: In the current study, we established a porcine-rhesus life sustaining kidney xenotransplantation model. The xenograft underwent intensive surveillance using gray-scale, colorful Doppler ultrasound as well as 2D shear wave elastography. The kidney growth, blood perfusion, and cortical stiffness were measured twice a day. These parameters were compared with the clinical data including urine output, chemistry, and pathological findings. RESULTS: The observation continued for 16 days after transplantation. Decline of urine output and elevated serum creatinine were observed on POD9 and biopsy proven antibody-mediated rejection was seen on the same day. The xenograft underwent substantial growth, with the long axis length increased by 32% and the volume increased by threefold at the end of observation. The resistive index of the xenograft arteries elevated in response to rejection, together with impaired cortical perfusion, while the peak systolic velocity (PSV) was not compromised. The cortical stiffness also increased along with rejection. CONCLUSION: In summary, the ultrasound findings of kidney xenograft shared similarities with those in allograft but possessed some unique features. A modified criteria needs to be established for further application of ultrasound in kidney xenotransplantation.

A new nomogram based on ultrasound and clinical features for distinguishing epididymal tuberculosis and nontuberculous epididymitis.

Using ultrasound findings and clinical characteristics, we constructed and validated a new nomogram for distinguishing epididymal tuberculosis from nontuberculous epididymitis, both of which share similar symptoms. We retrospectively examined data of patients with epididymal tuberculosis and nontuberculous epididymitis hospitalized between January 1, 2013, and March 31, 2023. Eligible patients were randomly assigned to derivation and validation cohorts (ratio, 7:3). We drew a nomogram to construct a diagnostic model through multivariate logistic regression and visualize the model. We used concordance index, calibration plots, and decision curve analysis to assess the discrimination, calibration, and clinical usefulness of the nomogram, respectively. In this study, 136 participants had epididymal tuberculosis and 79 had nontuberculous epididymitis. Five variables-C-reactive protein level, elevated scrotal skin temperature, nodular lesion, chronic infection, and scrotal skin ulceration-were significant and used to construct the nomogram. Concordance indices of the derivation and validation cohorts were 0.95 and 0.96, respectively (95% confidence intervals, 0.91-0.98 and 0.92-1.00, respectively). Decision curve analysis of this nomogram revealed that it helped differentiate epididymal tuberculosis from nontuberculous epididymitis. This nomogram may help clinicians distinguish between epididymal tuberculosis and nontuberculous epididymitis, thereby increasing diagnosis accuracy.

Improving lung point-of-care ultrasound (POCUS) training and accreditation - a multidisciplinary, multi-centre and multi-pronged approach to development and delivery using the action learning process.

BACKGROUND: Point-of-Care Ultrasound (POCUS) consists of a range of increasingly important imaging modalities across a variety of specialties. Despite a variety of accreditation pathways available in the UK, lung POCUS training remains difficult to deliver and accreditation rates remain suboptimal. We describe a multidisciplinary, multi-centre, and multi-pronged approach to lung POCUS education within a region. METHODS: A survey was conducted in a region. From these results, bottlenecks were identified for improvement. We utilised key stages in an established accreditation pathway, and the Action Learning process. Analysing participant feedback, consensus amongst the team, regional educational needs, and leveraging the expertise within the faculty, we implemented several solutions which were multidisciplinary, multi-centre, and multi-pronged. We also set up a database across several accreditation pathways to facilitate supervision and assessment of rotational trainees. RESULTS: Utilising the Action Learning process, we implemented several improvements at elements of the lung ultrasound accreditation pathways. An initial regional survey identified key barriers to accreditation: lack of courses (52%), lack of mentors (93%), and difficulty arranging directly supervised scans (73%). A multidisciplinary team of trainers was assembled. Regular courses were organised and altered based on feedback and anecdotal educational needs within the region. Courses were set up to also facilitate continuing professional development and exchange of knowledge and ideas amongst trainers. The barrier of supervision was removed through the organisation of regular supervision sessions, facilitating up to fifty scans per half day per trainer. We collected feedback from courses and optimised them. Remote mentoring platforms were utilised to encourage asynchronous supervision. A database of trainers was collated to facilitate triggered assessments. These approaches promoted a conducive environment and a commitment to learning. Repeat survey results support this. CONCLUSION: Lung ultrasound accreditation remains a complex educational training pathway. Utilising an education framework, recruiting a multidisciplinary team, ensuring a multi-pronged approach, and fostering a commitment to learning can improve accreditation success.

Use of ultrasound imaging Omics in predicting molecular typing and assessing the risk of postoperative recurrence in breast cancer.

BACKGROUND: The aim of this study is to assess the efficacy of a multiparametric ultrasound imaging omics model in predicting the risk of postoperative recurrence and molecular typing of breast cancer. METHODS: A retrospective analysis was conducted on 534 female patients diagnosed with breast cancer through preoperative ultrasonography and pathology, from January 2018 to June 2023 at the Affiliated Cancer Hospital of Xinjiang Medical University. Univariate analysis and multifactorial logistic regression modeling were used to identify independent risk factors associated with clinical characteristics. The PyRadiomics package was used to delineate the region of interest in selected ultrasound images and extract radiomic features. Subsequently, radiomic scores were established through Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM) methods. The predictive performance of the model was assessed using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was calculated. Evaluation of diagnostic efficacy and clinical practicability was conducted through calibration curves and decision curves. RESULTS: In the training set, the AUC values for the postoperative recurrence risk prediction model were 0.9489, and for the validation set, they were 0.8491. Regarding the molecular typing prediction model, the AUC values in the training set and validation set were 0.93 and 0.92 for the HER-2 overexpression phenotype, 0.94 and 0.74 for the TNBC phenotype, 1.00 and 0.97 for the luminal A phenotype, and 1.00 and 0.89 for the luminal B phenotype, respectively. Based on a comprehensive analysis of calibration and decision curves, it was established that the model exhibits strong predictive performance and clinical practicability. CONCLUSION: The use of multiparametric ultrasound imaging omics proves to be of significant value in predicting both the risk of postoperative recurrence and molecular typing in breast cancer. This non-invasive approach offers crucial guidance for the diagnosis and treatment of the condition.

Comparison of different types of ultrasound probes for lung ultrasound in neonates-A prospective randomized comparison study.

OBJECTIVE: To determine the effect of different types of probes for lung ultrasound in neonates. DESIGN: Prospective, blinded, randomized, comparative study between 2020 and 2022. SETTING: Single-center study at a third level neonatal unit. PATIENTS: Hemodynamically stable infants with either nasal continuous positive airway pressure, high flow nasal cannula or without respiratory support. INTERVENTION: Lung ultrasound using either an echo or microconvex probe. As control, the linear probe was used. MAIN OUTCOME MEASURES: Primary outcome measure was neonatologist performed lung ultrasound (NPLUS) score. Secondary outcome measures were number of B-Lines, thickness of the pleural line and subjective image quality. Furthermore, correlation between NPLUS results and clinical data was assessed. RESULTS: A total of 1584 video loops from 66 patients, with a mean corrected gestational age of 33.8 weeks (SD 4.23) and weight of 1950g (SD 910), respectively, were analyzed. NPLUS score was estimated lower with the echo- and microconvex probe compared to the linear probe, with a coefficient of -2.95 (p < 0.001) and -1.09 (p = 0.19), respectively. Correlation between the pulse oximetric saturation/fraction of inspired oxygen ratio and NPLUS score was moderately strong and best using the microconvex probe (Spearman's rho = -0.63, p<0.001). CONCLUSION: Our results not only confirm the current recommendations, but also demonstrate the extent of the varying results when different probes are used. The differences we discovered call for caution in interpreting scores, especially in the context of guiding therapies and communicating prognoses. Finally, the correlation between NPLUS score and clinical parameters contributes to validating the use of this diagnostic tool.

Trends in childhood intussusception in a Nigerian tertiary hospital.

Background: Early presentation, high rate of successful non-operative treatment, low morbidity and mortality in childhood intussusception is common in High and Upper Middle-Income Countries but not in many Lower middle- and Low-income countries. Aim: To assess the trends in the profile, treatment modalities and outcomes of intussusception in our hospital. Materials and methods: Retrospective study over a 12-year period divided into two 6-year periods. Data entry/analysis was done using SPSS and various indices were compared between these two periods. Two-tailed t-test for two independent means was used to compare means while two-tailed Fisher exact tests were used to compare categorical variables. Results were presented as tables, means, ranges, percentages and a p-value less than 0.05 was deemed statistically significant. Results: There was a significant increase in the proportion of successful non-operative treatment (18.6% vs 34%, p=0.03), reduction in the incidence of operative manual reduction (27.1% vs 12.8%; p=0.026), reduction in operative treatment (78.5% vs 63.9%, p=0.034), increased utilization of pre-intervention ultrasound (75% vs96.7%, p<0.0001) and reduction in hospital stay duration (10.47 ±7.95days vs 7.24±4.86 days; p=0.004). Conclusions: Contribution of successful non-operative treatment to the overall treatment of intussusception significantly increased while that of operative manual reduction significantly reduced and bowel resection showed no change. Preoperative utilization of ultrasonography significantly increased while mean duration of admission reduced significantly, but late presentation, morbidity and mortality rates had no significant changes.

Evaluation of the Relationship between Acromiohumeral Distance and Supraspinatus Tendon Thickness Measured by Ultrasonography and Rotator Cuff Pathologies, Pain, and Function.

PURPOSE OF THE STUDY: In this study, we aimed to evaluate acromiohumeral distance (AHD) and supraspinatus tendon (ST) thickness measurements and their relationship with pain and function in ST pathologies. MATERIAL AND METHODS: The study included 111 patients and 25 healthy controls (HC). Patients were divided into 3 groups according to their diagnosis: non-tear tendinopathy (NTT), partial thickness tear (PTT), and full thickness tear (FTT). The AHD and ST thickness of the participants were measured with ultrasound. The pain and functional status of the patients were evaluated with the Numeric Rating Scale (NRS), The QuickDASH shortened version of the DASH Outcome Measure - Disabilities of the Arm Shoulder and Hand (QDASH), and Simple Shoulder Test (SST). RESULTS: The AHD value was significantly higher in the NTT group (p=0.000). The AHD value was significantly lower in the FTT group (p=0.000). ST thickness value was significantly lower in the PTT group compared to the NTT group (p=0.000). There was a positive correlation between ST thickness and BMI (r=0.553,p<0.01). There was a negative correlation between ST thickness and SST and a positive correlation between ST thickness (r=-0.223,p<0.05) and QDASH (r=0.276,p<0.05). CONCLUSIONS: We found that AHD and SST thicknesses significantly differed in the NTT, PTT, FTT, and HC groups. This difference may be important for diagnosis. In addition, the effect of obesity on ST thickness and the relationship between ST thickness and functional scores may be considered. Weight control may be effective at this point. KEY WORDS: acromiohumeral distance, supraspinatus tendon thickness, ultrasound.

Efficacy and safety of ultrasound-guided percutaneous radiofrequency ablation for synovial hyperplasia.

PURPOSE: This study aimed to investigate the efficacy and safety of ultrasound-guided percutaneous radiofrequency ablation (RFA) for the treatment of synovial hyperplasia in the knee joints of antigen-induced arthritis (AIA) model rabbits. METHODS: Forty Japanese large-eared white rabbits were divided into AIA and control groups. After successful induction of the AIA model, the knee joints were randomly assigned to RFA and non-RFA groups. The RFA group underwent ultrasound-guided RFA to treat synovial hyperplasia in the knee joint. Dynamic observation of various detection indices was conducted to evaluate the safety and effectiveness of the RFA procedure. RESULTS: Successful synovial ablation was achieved in the RFA group, with no intraoperative or perioperative mortality. Postoperative the circumference of the knee joint reached a peak before decreasing in the third week after surgery. The incidence and diameter of postoperative skin ulcers were not significantly different compared to the non-RFA group (p > .05). Anatomical examination revealed an intact intermuscular fascia around the ablated area in the RFA group. The ablated synovial tissue initially presented as a white mass, which subsequently liquefied into a milky white viscous fluid. Gross articular cartilage was observed, along with liquefied necrosis of the synovium on pathological histology and infiltration of inflammatory cells in the surrounding soft tissue. CONCLUSION: The experimental results demonstrated that ultrasound-guided RFA of the knee in the treatment of synovial hyperplasia in AIA model animals was both effective and safe.