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This article discusses a study that compared the effectiveness of ultrasound-guided pulsed radiofrequency ablation (PRF) of the suprascapular nerve to local anesthetics with steroids for chronic shoulder pain. The study found that both treatments provided significant pain relief and improved scores for shoulder pain and disability. However, the group that received the local anesthetic and steroid injection had lower pain levels during the 2-week follow-up period. The study suggests that both treatments can be effective options for managing chronic shoulder pain. [Extracted from the article]

Knee disorders are common among the human population. Knee osteoarthritis (OA) is the most widespread knee joint disorder, which may require surgical treatment. The detection and diagnosis of knee joint disorders from medical images demand enormous human effort and time. The development of a computer‐aided diagnosis (CAD) system can notably minimise the burden of medical experts and remove the intra‐observer and inter‐observer variations. To achieve the goal, the highly challenging research problem of knee image segmentation has been frequently paid attention in past years, which can be efficiently applied in the development of the CAD system. Knee image segmentation is a challenging task owing to the image contrasts, intensity variations, shape irregularities, and the presence of thin cartilage structures. Therefore, this paper presents a literature review of automated segmentation approaches mainly focused on the segmentation of knee cartilage and bone, with respect to the underlying technical aspects, datasets used, and the performance reported. The paper also presents the growth from classical segmentation approaches towards the deep learning approaches in the knee image segmentation. Owing to the varying quality and complexity of different knee image datasets, this paper abstains from doing a rigorous comparative evaluation of image segmentation approaches. [ABSTRACT FROM AUTHOR]

Background: Synovitis is the underlying pathology in various arthritis, and sometimes, it is difficult to differentiate various arthritis clinically or even by imaging. The purpose of our study was to use shear wave elastography (SWE) to evaluate rheumatoid arthritis (RA) and tubercular (TB) arthritis and to differentiate them using synovial stiffness., Methods: The prospective study was performed on Supersonic Imagine Aixplorer Ultrasound (USG) machine using a linear array probe SL10-2 (2-10 MHz). A total of 29 participants, 15 of RA (ACR/EULAR criteria) and 14 of proven TB arthritis were included. Region of interest of 1 mm was applied on the hypertrophied synovium and quantitative SWE data in form of elasticity (kPa) and velocity (m/s) were measured. Discrete categorical data were presented as n (%). Mean values were recorded along with standard deviation and the range of values. To find a maximal cutoff value of elasticity and velocity - receiver operating characteristic curve were plotted., Results: The mean elasticity and velocity values were 54.81 ± 10.6 kPa and 4.2 m/s ± 0.42 for RA and 37 ± 10 kPa and 3.4 ± 0.47 m/s for TB group. Significant difference ( P < 0.001) was seen in elastic modulus values between rheumatoid and TB group with cutoff of 43.6 kPa to differentiate the two groups (sensitivity - 86.7% and specificity - 80%). Similar significant ( P < 0.001) results were seen with velocity values, with cutoff of 3.76 m/s (sensitivity - 86.7% and specificity - 80%)., Conclusion: SWE shows the potential to be a useful adjunct to gray scale and color Doppler USG in differentiating various arthritis on the basis of elastic properties of the synovium. Elastic modulus and velocity are useful SWE quantitative parameters for synovial evaluation and can differentiate RA and TB arthritis., Competing Interests: There are no conflicts of interest, (Copyright: © 2021 Journal of Medical Ultrasound.)