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Objective: This study aimed to develop (1) a new ultrasound definition for aggregates and (2) a semi-quantitative ultrasound scoring system (0-3) for tophus, double contour and aggregates. Furthermore, the intra- and inter-reader reliabilities of both the re-defined aggregates and the semi-quantitative scoring system were assessed using static image exercises.
Methods: Thirty-seven rheumatologists were invited. A Delphi process was used for re-defining aggregates and for selecting a semi-quantitative scoring system with >75% agreement obligate for reaching consensus. Subsequently, a web-based exercise on static ultrasound images was conducted in order to assess the reliability of both the re-defined aggregates and the semi-quantitative scoring system.
Results: Twenty rheumatologists contributed to all rounds of the Delphi and image exercises. A consensual re-definition of aggregates was obtained after three Delphi rounds but needed an overarching principle for scoring aggregates in patients. A consensus-based semi-quantitative ultrasound scoring system for gout lesions was developed after two Delphi rounds. The re-definition of aggregates showed good intra- and inter-reader reliability (κ-values 0.71 and 0.61). The reliabilities of the scoring system were good for all lesions with slightly higher intra-reader (κ-values 0.74-0.80) than inter-reader reliabilities (κ-values 0.61-0.67).
Conclusion: A re-definition of aggregates was obtained with a good reliability when assessing static images. The first consensus-based semi-quantitative ultrasound scoring system for gout-specific lesions was developed with good inter- and intra-reader reliability for all lesions when tested in static images. The next step is to assess the reliabilities when scoring lesions in patients.
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http://dx.doi.org/10.1016/j.semarthrit.2020.11.011 | DOI Listing |
JMIR Med Inform
September 2025
Departments of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, Guangdong, 510630, China, 86 18922109279, 86 20852523108.
Background: Despite the Coronary Artery Reporting and Data System (CAD-RADS) providing a standardized approach, radiologists continue to favor free-text reports. This preference creates significant challenges for data extraction and analysis in longitudinal studies, potentially limiting large-scale research and quality assessment initiatives.
Objective: To evaluate the ability of the generative pre-trained transformer (GPT)-4o model to convert real-world coronary computed tomography angiography (CCTA) free-text reports into structured data and automatically identify CAD-RADS categories and P categories.
JMIR Res Protoc
September 2025
Department of Urology, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
Background: Circumcision is a widely practiced procedure with cultural and medical significance. However, certain penile abnormalities-such as hypospadias or webbed penis-may contraindicate the procedure and require specialized care. In low-resource settings, limited access to pediatric urologists often leads to missed or delayed diagnoses.
View Article and Find Full Text PDFJ Craniofac Surg
September 2025
Department of Oral and Maxillofacial Surgery, University of Ulsan Hospital, University of Ulsan College of Medicine.
This study aimed to develop a deep-learning model for the automatic classification of mandibular fractures using panoramic radiographs. A pretrained convolutional neural network (CNN) was used to classify fractures based on a novel, clinically relevant classification system. The dataset comprised 800 panoramic radiographs obtained from patients with facial trauma.
View Article and Find Full Text PDFJMIR Public Health Surveill
September 2025
Hospital Israelita Albert Einstein, 755 Comendador Elias Jafet Street, L1 Floor, Room 134, São Paulo, 05653-000, Brazil.
Background: The Brazilian project, launched in 2021, aims to establish a nationwide injury registry that systematically collects detailed information on incidents and individuals across the country, regardless of injury severity. The registry integrates information from prehospital and hospital care, various health systems lacking interoperability, and data from sectors such as firefighters and police. Its primary aim is to enhance health surveillance by providing timely, high-quality information that guides prevention strategies and informs policymaking.
View Article and Find Full Text PDFJ Cataract Refract Surg
September 2025
Ophthalmology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy.
Purpose: To compare the usability and training effectiveness of a 3D-printed coaxial illumination system mounted on an off-the-shelf stereo-microscope to a professional ophthalmic surgical microscope, in cataract surgery simulation.
Setting: Ophthalmology Lab, Ophthalmology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy.
Design: Prospective randomized crossover study.