Ultrasound-Guided Hydraulic Release Associated With Corticosteroids in Radial Tunnel Syndrome: Description of Technique and Preliminary Clinical Results.

The aim of this study was to describe a perineural ultrasound-guided infiltration technique for management of radial tunnel syndrome and to report its preliminary results in 54 patients. A mixture of a saline solution, a local anesthetic, and a corticosteroid solution was infiltrated in the perineural region at the arcade of Frohse. Pain was reported in 100% of patients before the procedure versus 1.9% after the procedure. Scratch collapse and Cozen test results were positive in 98.1% and 66.7% of patients before infiltration, respectively, versus 5.6% and 9.2% after infiltration. All variables had statistically significant differences between preprocedure and postprocedure evaluations (P < .01).

Artificial intelligence in diagnosing upper limb musculoskeletal disorders: a systematic review and meta-analysis of diagnostic tests.

Purpose: The integration of artificial intelligence (AI) in radiology has revolutionized diagnostics, optimizing precision and decision-making. Specifically in musculoskeletal imaging, AI tools can improve accuracy for upper extremity pathologies. This study aimed to assess the diagnostic performance of AI models in detecting musculoskeletal pathologies of the upper extremity using different imaging modalities. Methods: A meta-analysis was conducted, involving searches on MEDLINE/PubMed, SCOPUS, Cochrane Library, Lilacs, and SciELO. The quality of the studies was assessed using the QUADAS-2 tool. Diagnostic accuracy measures including sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative likelihood ratios (PLR, NLR), area under the curve (AUC), and summary receiver operating characteristic were pooled using a random-effects model. Heterogeneity and subgroup analyses were also included. All statistical analyses and plots were performed using the R software package. Results: Thirteen models from ten articles were analyzed. The sensitivity and specificity of the AI models to detect musculoskeletal conditions in the upper extremity were 0.926 (95% CI: 0.900; 0.945) and 0.908 (95% CI: 0.810; 0.958). The PLR, NLR, lnDOR, and the AUC estimates were found to be 19.18 (95% CI: 8.90; 29.34), 0.11 (95% CI: 0.18; 0.46), 4.62 (95% CI: 4.02; 5.22) with a (P < 0.001), and 95%, respectively. Conclusion: The AI models exhibited strong univariate and bivariate performance in detecting both positive and negative cases within the analyzed dataset of musculoskeletal pathologies in the upper extremity.

Nonsurgical Management of Shoulder Pain in Rotator Cuff Tears: Ultrasound-Guided Biceps Tenotomy Combined With Corticosteroid Injection.

Traditionally, the management of rotator cuff tears in elderly individuals has involved surgical intervention, specifically biceps tenotomy. However, surgical procedures come with inherent medical risks and significant financial costs. As an alternative, ultrasound-guided biceps tenotomy combined with corticosteroid has emerged as a highly effective, well-tolerated, and cost-efficient option. This article aims to describe the procedural technique of nonsurgical management using ultrasound-guided biceps tenotomy combined with corticosteroid injection.

Chilean Market Protein Shakes Composition.

Understanding the nutritional content of protein supplements is crucial for optimal nutritional planning among athletes and other people. Distribution of macronutrients and aminograms in the main products available in the national Chilean market remains unknown. A descriptive cross-sectional study was conducted to identify the main protein supplements available in the Chilean market. Information on macronutrients and aminograms from the nutritional labels of each product was extracted. The analysis considered the content per portion and per 100 g. Cluster analysis models and graphical representations were explored. Eighty protein shakes were assessed in the Santiago de Chile market. The median protein dosage was 32 g (range from 25 to 52), and the median energy value stood at 390 kcal (range from 312 to 514). The median protein content per 100 g of product was found to be 75 g (range from 42.5 to 97.2). The combined median concentration of amino acids was 4749.75 mg. Among these, the essential amino acid L-Tryptophan exhibited the lowest concentration at 1591.50 mg, while the conditional amino acid L-Glutamine had the highest median concentration at 17,336 mg. There was a significant prevalence of animal-derived products, placing specific emphasis on protein supplements that feature elevated levels of the amino acids L-Glutamine and L-Leucine.

The Critical Shoulder Angle: A Significant Radiological Measure in Rotator Cuff vs. Glenohumeral Osteoarthritis in Chilean Patients-A Descriptive Cross-Sectional Study.

Background: Shoulder pain is one of the most important musculoskeletal conditions affecting the upper extremities. Glenohumeral osteoarthritis (GHOA) and rotator cuff injuries (RCIs) are notable for their high prevalence. The critical shoulder angle (CSA) is a significant radiological measure for determining the diagnosis and progression of patients with these conditions. Although there are reports in the international literature about this measure, in our country, guideline values considering these two pathologies are unknown. Objective: Our objective was to assess patients diagnosed with GHOA and RCI using an AP X-ray view and the CSA. Methods: To conduct this, we identified differences between sexes and age categories. Fifty-nine adult patients with GHOA and RCI were included. CSA grades varied depending on the age category and type of injury evaluated. Results: Significant differences between the age ranges of 40 and 54 (p = 0.05), 55-69 (p = 0.001), and 70-84 (p = 0.017) were observed. Conclusions: Patients with RCI tended to be younger and have a higher CSA compared to those with GHOA. It is important to have more normative values and to continue monitoring the critical shoulder angle in these patients.

High-accuracy detection of supraspinatus fatty infiltration in shoulder MRI using convolutional neural network algorithms.

Background: The supraspinatus muscle fatty infiltration (SMFI) is a crucial MRI shoulder finding to determine the patient's prognosis. Clinicians have used the Goutallier classification to diagnose it. Deep learning algorithms have been demonstrated to have higher accuracy than traditional methods. Aim: To train convolutional neural network models to categorize the SMFI as a binary diagnosis based on Goutallier's classification using shoulder MRIs. Methods: A retrospective study was performed. MRI and medical records from patients with SMFI diagnosis from January 1st, 2019, to September 20th, 2020, were selected. 900 T2-weighted, Y-view shoulder MRIs were evaluated. The supraspinatus fossa was automatically cropped using segmentation masks. A balancing technique was implemented. Five binary classification classes were developed into two as follows, A: 0, 1 v/s 3, 4; B: 0, 1 v/s 2, 3, 4; C: 0, 1 v/s 2; D: 0, 1, 2, v/s 3, 4; E: 2 v/s 3, 4. The VGG-19, ResNet-50, and Inception-v3 architectures were trained as backbone classifiers. An average of three 10-fold cross-validation processes were developed to evaluate model performance. AU-ROC, sensitivity, and specificity with 95% confidence intervals were used. Results: Overall, 606 shoulders MRIs were analyzed. The Goutallier distribution was presented as follows: 0 = 403; 1 = 114; 2 = 51; 3 = 24; 4 = 14. Case A, VGG-19 model demonstrated an AU-ROC of 0.991 ± 0.003 (accuracy, 0.973 ± 0.006; sensitivity, 0.947 ± 0.039; specificity, 0.975 ± 0.006). B, VGG-19, 0.961 ± 0.013 (0.925 ± 0.010; 0.847 ± 0.041; 0.939 ± 0.011). C, VGG-19, 0.935 ± 0.022 (0.900 ± 0.015; 0.750 ± 0.078; 0.914 ± 0.014). D, VGG-19, 0.977 ± 0.007 (0.942 ± 0.012; 0.925 ± 0.056; 0.942 ± 0.013). E, VGG-19, 0.861 ± 0.050 (0.779 ± 0.054; 0.706 ± 0.088; 0.831 ± 0.061). Conclusion: Convolutional neural network models demonstrated high accuracy in MRIs SMFI diagnosis.

A New Test for the Advanced Diagnosis of Lateral Elbow Tendinopathy with Concomitant Intrasubstance Tear: Failure to Resist Extension Effort (the Free Test).

Background: Lateral elbow tendinopathy (LET) is one of the most common causes of musculoskeletal pain. The diagnosis is based on the clinical history and different physical maneuvers. Ultrasound (US) is a complementary diagnostic method to detect degenerative tendon changes and intrasubstance tears (IST). To date, there is no available physical maneuver to identify an IST in patients with LET. Aim: To evaluate the diagnostic accuracy of an index test to detect an IST confirmed by ultrasound in patients with LET. Methods: A diagnostic retrospective study was performed. Patients who presented medical records with LET were recruited. Two orthopaedic surgeons developed the physical maneuver. The index test was considered positive when the position failed to resist the wrist extension maximum effort. Clinical findings were associated with confirmation of IST by US. Data were calculated using diagnostic accuracy, sensitivity, and specificity with 95% confidence intervals. Results: Thirty-nine patients (39 elbows) were analyzed, 25 (64%) women and 14 (36%) men, with an average age of 47.7 years. The index test's sensitivity was 0.86 (95% CI, 0.67-0.96). Accuracy was 0.79 (95% CI, 0.64-0.91), and the specificity was 0.64 (95% CI, 0.31-0.89). Conclusion: The index test presented very good sensitivity and good accuracy in patients with LET with US diagnostic confirmation of IST. Level of Evidence: Diagnostic study, Level III.

Lateral elbow tendinopathy and artificial intelligence: Binary and multilabel findings detection using machine learning algorithms.

Background: Ultrasound (US) is a valuable technique to detect degenerative findings and intrasubstance tears in lateral elbow tendinopathy (LET). Machine learning methods allow supporting this radiological diagnosis. Aim: To assess multilabel classification models using machine learning models to detect degenerative findings and intrasubstance tears in US images with LET diagnosis. Materials and methods: A retrospective study was performed. US images and medical records from patients with LET diagnosis from January 1st, 2017, to December 30th, 2018, were selected. Datasets were built for training and testing models. For image analysis, features extraction, texture characteristics, intensity distribution, pixel-pixel co-occurrence patterns, and scales granularity were implemented. Six different supervised learning models were implemented for binary and multilabel classification. All models were trained to classify four tendon findings (hypoechogenicity, neovascularity, enthesopathy, and intrasubstance tear). Accuracy indicators and their confidence intervals (CI) were obtained for all models following a K-fold-repeated-cross-validation method. To measure multilabel prediction, multilabel accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) with 95% CI were used. Results: A total of 30,007 US images (4,324 exams, 2,917 patients) were included in the analysis. The RF model presented the highest mean values in the area under the curve (AUC), sensitivity, and also specificity by each degenerative finding in the binary classification. The AUC and sensitivity showed the best performance in intrasubstance tear with 0.991 [95% CI, 099, 0.99], and 0.775 [95% CI, 0.77, 0.77], respectively. Instead, specificity showed upper values in hypoechogenicity with 0.821 [95% CI, 0.82, -0.82]. In the multilabel classifier, RF also presented the highest performance. The accuracy was 0.772 [95% CI, 0.771, 0.773], a great macro of 0.948 [95% CI, 0.94, 0.94], and a micro of 0.962 [95% CI, 0.96, 0.96] AUC scores were detected. Diagnostic accuracy, sensitivity, and specificity with 95% CI were calculated. Conclusion: Machine learning algorithms based on US images with LET presented high diagnosis accuracy. Mainly the random forest model shows the best performance in binary and multilabel classifiers, particularly for intrasubstance tears.

Diagnóstico de roturas del manguito rotador por ecografía y resonancia magnética: ¿la morfología acromial influye en los resultados? / Ultrasound and magnetic resonance imaging diagnosis for rotator cuff tears: does acromial morphology affect the results?

INTRODUCCIÓN Actualmente no existen estudios que evalúen la concordancia entre la ecografía (ECO) y la resonancia magnética (RM) observando parámetros como el índice acromial (IA) y el ángulo crítico (AC) para roturas del manguito rotador (MR). Se considera que la mayor cobertura de la huella por un IA o AC incrementados podría afectar la adecuada visualización del MR en estudios de ECO al interponerse entre el complejo tendíneo y el transductor ecográfico. OBJETIVO Estimar la concordancia de la ECO y la RM en el diagnóstico de pacientes con roturas del MR confirmadas por artroscopia con IA y AC mayores al promedio normal (0.7 y 35°, respectivamente). Secundariamente, determinar si la concordancia diagnóstica es comparable entre tipos de rotura (espesor completo o parciales). MATERIALES Y MÉTODOS Estudio retrospectivo de una serie consecutiva de 100 pacientes con roturas totales o parciales del MR confirmadas por artroscopia. RESULTADOS La edad media del grupo de estudio fue de 55,7 ± 10,5 años. La media del IA fue de 0,77 ± 0,08, y la del AC, de 37,42° ± 5,88°. La concordancia entre la ECO y la RM y el IA fue > 0,7 de 56,7% (K = 0,27; p = 0,01); y < 0,7 de 35,7% (K = 0,01; p = 0,46), respectivamente. Y la concordancia entre la ECO y la RM y el AC fue > 35° de 61,5% (K = 0,32; p = 0,001); y < 35° de 33,3% (K = -0,00; p = 0,52), respectivamente. CONCLUSIÓN La concordancia diagnóstica de la ECO comparada con la de la RM, en pacientes con roturas del MR confirmada por artroscopia y con IA y AC mayores al promedio normal, fue justa. La concordancia diagnóstica de la ECO comparada con la RM, en pacientes con IA y AC menores al promedio normal, fue pobre. La capacidad diagnóstica fue similar entre la ECO y la RM para roturas parciales y totales.

INTRODUCTION Currently, there are no studies that evaluate the agreement between ultrasound (US) and magnetic resonance imaging (MRI) scans in rotator cuff (RC) tears by the observation of parameters such as the acromial index (AI) and critical shoulder angle (CSA). We hypothesize that the greater coverage of the footprint by increased AI or CSA could affect the proper visualization of the RC in US scans by its interposition between the tendinous complex and the US transducer. OBJETIVE To estimate the agreement between US and MRI in the diagnosis of patients with RC tears confirmed by arthroscopy and with AI and CSA greater than the normal average values (0.7 and 35° respectively). The secondary objective is to determine if the diagnostic agreement is comparable regarding different types of tear (partial and complete). MATERIALS AND METHODS A retrospective study of a consecutive case series of 100 patients with partial or complete RC tears confirmed by arthroscopy. RESULTS The mean age of the study group was of 55.7 10.5 years. The mean AI was of 0.77 0.08, and the mean CSA was of 37.42° 5.88°. The agreement regarding the US, the MRI and the AI was > 0.7 of 56.7% (K » 0.27; p » 0.01); and < 0.7 of 35.7% (K » 0.01; p » 0.46) respectively. And the agreement regarding the US, the MRI and the CSA was > 35° of 61.5% (K » 0.32; p » 0.001); and < 35° of 33.3% (K »-0.00; p » 0.52) respectively. CONCLUSION The diagnostic agreement of the US compared with the MRI, in patients with RC tears confirmed by arthroscopy and with AI and CSA greater than the normal average values was fair. The diagnostic agreement of the US compared with the MRI, in patients with AI and CSA lower than the normal average values was poor. The diagnostic performance of the IS and MRI was similar for partial and complete tears.