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Objective: Microscopic identification of monosodium urate (MSU) crystals is the gold standard for gout diagnosis. However, joint aspiration is not always practical, and imaging is increasingly used in clinical practice. This study aimed to assess the diagnostic accuracy of imaging features for gout compared with microscopy, using network meta-analysis methodology.
Methods: MEDLINE, EMBASE, PubMed and Cochrane databases were searched for studies reporting on the use of imaging modalities to diagnose gout in patients with an unclear diagnosis or suspected gout, which was later confirmed by microscopy. A combination of direct and indirect comparisons were performed by network meta-analysis to evaluate the combined odds ratios for sensitivity, specificity, and accuracy. To assist interpretation, the surface under the cumulative ranking curve (SUCRA) scores were calculated to provide a ranking of the imaging features.
Results: Fifteen eligible studies were included. Compared to the gold standard microscopic identification of MSU crystals, dual energy computed tomography (DECT) MSU crystal deposition and ultrasound double contour had greater sensitivity than ultrasound tophus. DECT, ultrasound double contour sign and ultrasound tophus all had greater specificity than ultrasound aggregates. The SUCRA scores ranked DECT as highest for overall accuracy, followed by ultrasound double contour, aggregates, and tophus, while ultrasound snowstorm was ranked the lowest. However, there were no significant differences in the odds ratios for overall accuracy between these imaging features.
Conclusion: DECT and ultrasound are both useful modalities for the detection of imaging features of MSU crystal deposition, and have a similar overall diagnostic accuracy for gout diagnoses.
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http://dx.doi.org/10.1016/j.semarthrit.2021.10.005 | DOI Listing |
Eur J Radiol
September 2025
Department of Radiology, Affiliated Hospital of Hebei University, Baoding 071000, China. Electronic address:
Purpose: The present study aimed to develop a noninvasive predictive framework that integrates clinical data, conventional radiomics, habitat imaging, and deep learning for the preoperative stratification of MGMT gene promoter methylation in glioma.
Materials And Methods: This retrospective study included 410 patients from the University of California, San Francisco, USA, and 102 patients from our hospital. Seven models were constructed using preoperative contrast-enhanced T1-weighted MRI with gadobenate dimeglumine as the contrast agent.
Pathol Res Pract
September 2025
Department of Pathology, Xijing Hospital and School of Basic Medicine, Fourth Military Medical University, Xi'an, China. Electronic address:
Background: Dermal clear cell sarcoma (DCCS) is a rare malignant mesenchymal neoplasm. Owing to the overlaps in its morphological and immunophenotypic profiles with a broad spectrum of tumors exhibiting melanocytic differentiation, it is frequently misdiagnosed as other tumor entities in clinical practice. By systematically analyzing the clinicopathological characteristics, immunophenotypic features, and molecular biological properties of DCCS, this study intends to further enhance pathologists' understanding of this disease and provide a valuable reference for its accurate diagnosis.
View Article and Find Full Text PDFJMIR 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.
J Cataract Refract Surg
July 2025
Department of Ophthalmology, West China Hospital of Sichuan University, Chengdu City, Sichuan Province, China.
Purpose: To develop and validate a multimodal deep-learning model for predicting postoperative vault height and selecting implantable collamer lens (ICL) sizes using Anterior Segment Optical Coherence Tomography (AS-OCT) and Ultrasound Biomicroscope (UBM) images combined with clinical features.
Setting: West China Hospital of Sichuan University, China.
Design: Deep-learning study.
Pol Merkur Lekarski
September 2025
Kharkiv Clinical Hospital on Railway Transport No. 1 ≪Health Care Center≫ of Joint-Stock Company «Ukrainian Railways», Kharkiv, Ukraine.
Objective: Aim: The purpose was to identify the morphological features of the great saphenous vein in patients with chronic venous disease of the lower extremities undergoing treatment with endovenous high-frequency electric welding in automatic mode, endovenous laser ablation, and ultrasound-guided microfoam sclerotherapy.
Patients And Methods: Materials and Methods: The material for the comprehensive morphological study consisted of fragments of the great saphenous vein obtained from 32 patients with chronic venous disease of the lower extremities. The material was divided into three groups according to the endovenous treatment techniques applied.