A Study of High-Resolution Ultrasound and Magnetic Resonance Imaging Findings in Shoulder Joint Pain at a Tertiary Care Hospital in Central India
Year: 2024
Type: article
Study design: Observational Study
Abstract: Objective This study aims to investigate the diagnostic efficacy of high-resolution ultrasound (USG) and magnetic resonance imaging (MRI) in patients with shoulder joint pain at a tertiary care hospital in Central India. Methods This cross-sectional study was conducted at Acharya Vinoba Bhave Rural Hospital from 2021 to 2024. The study population consisted of patients with shoulder pain, without fractures, who were evaluated using USG and MRI. Participants with infective arthritis, rheumatoid arthritis, previous shoulder surgery, or contraindications for MRI were excluded. Data were recorded and analyzed using Microsoft Excel (Microsoft Corporation, Redmond, Washington) and R 4.2.0 software (The R Foundation, Vienna, Austria). Sensitivity, specificity, and receiver operating characteristic (ROC) curves were used to compare the diagnostic performance of USG and MRI. Results A total of 80 patients were included, with 49 (61%) males and 31 (39%) females. The MRI findings showed supraspinatus partial tears in 44 (55%) cases, complete tears in 10 (12.5%), and various other shoulder pathologies. USG detected supraspinatus partial tears in 16 (19.5%) and complete tears in seven (8.8%). Kappa statistics indicated moderate to high agreement between USG and MRI for several pathologies, with near-perfect agreement for complete tears. Conclusion High-resolution USG is a valuable tool for the initial assessment of shoulder joint pain, providing reliable diagnostic information with high agreement levels with MRI for complete tears and certain shoulder conditions. MRI remains indispensable for comprehensive evaluation, particularly for partial tears and complex pathologies.
Source: Cureus
DOI: 10.7759/cureus.66518
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4401455279