Work

Exploration of acute gout diagnosis based on ultrasound viscoelastic imaging: quantitative parameter analysis and clinical validation

Year: 2025

Type: article

Abstract: Objectives To explore the optimal quantitative parameters and clinical application value of ultrasound viscoelastic imaging in the differential diagnosis of acute gout (AG) and non-AG. Methods This study enrolled 102 patients presenting with acute joint swelling and pain, and divided them into the AG group and non-AG group. Differences in viscoelastic quantitative parameters, including the shear wave velocity (C), viscosity coefficient (V) and dispersion coefficient (D), between the two groups were compared. Parameters with significant differences were included in generalized estimating equations (GEE) analysis to screen out the optimal parameters for predicting AG, and receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic efficacy of each parameter alone and in combination. Results The AG group included 45 patients, and the non-AG group included 57 patients. There were statistically significant differences in C mean , C max , C min , C SD , V mean , V max , V SD , D mean , D max , and D SD between the two groups (all P < 0.05). GEE analysis showed that the parameters finally included in the equation were C mean and D max , and the equation was Logit(P) = (−11.186) + (3.456 × C mean ) + (0.191 × D max ). ROC curve analysis revealed that among single parameters, C mean had the highest AUC of 0.836 (95% CI 0.774∼0.897), with an optimal cutoff value of 2.36 m/s. The AUC of the GEE model was 0.885 (95% CI 0.833∼0.938), with an optimal cutoff value of 0.41. The AUC of the GEE model combining multiple parameters was superior to that of single-parameter diagnosis ( P = 0.033). Conclusion Among ultrasound viscoelastic parameters, C mean and D max are effective non-invasive quantitative indicators for diagnosing AG, and the diagnostic efficacy of combined multi-parameter diagnosis is superior to that of single-parameter diagnosis.

Source: Frontiers in Medicine

DOI: 10.3389/fmed.2025.1729517

Authors: Jiesi Zhang, Xiao Chen, Peipei Li, Mei Zhao, Li Li, Yuquan Ye

Institutions: Hebei Medical University, Hebei General Hospital

Language: English

Topic: Ultrasound Imaging and Elastography

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801