Diagnostic and clinical utility of ultrasound elastography for uterine cervical neoplasms-a comprehensive systematic review and meta-analysis.

PURPOSE

Cervical cancer remains a major burden, especially in low-resource settings, due to limited screening. Traditional diagnostic tools, like colposcopy, are operator-dependent and often lack accuracy. Ultrasound elastography, including strain elastography (SE) and shear wave elastography (SWE), is a cost-effective, non-invasive tool for assessing tissue stiffness, aiding in distinguishing benign from malignant cervical lesions, and monitoring treatment. This review evaluates elastography's diagnostic accuracy and clinical utility in cervical cancer management.

METHODS

This systematic review and meta-analysis was performed following PRISMA 2020 guidelines and was registered with PROSPERO (CRD42025639380). PubMed, Embase, Cochrane Library, Web of Science, and Scopus were searched up to January 2025 for studies utilizing elastography in cervical cancer. Study quality was assessed using the Newcastle-Ottawa Scale. Pooled sensitivity, specificity, and SROC curves were calculated using R software and Stata, with heterogeneity and publication bias evaluated.

RESULTS

A total of twenty-three studies were included, with 19 in the meta-analysis. Elastography demonstrated high diagnostic accuracy for both detecting cervical cancer (sensitivity 88.3%, specificity 92%, AUC 0.965) and cervical intraepithelial neoplasia (CIN). SE trended to a non-significantly higher diagnostic accuracy than SWE (p = 0.51). Quantitative parameters differentiated cervical cancer from controls (SMD = 2.59, p < 0.001) and CIN (SMD = 1.75, p = 0.015). Elastography can effectively assess treatment response and tumor invasion.

CONCLUSION

Elastography aids cervical cancer diagnosis with high sensitivity and specificity, ideal for resource-limited settings due to its affordability and safety. Standardized training and guidelines are needed for consistent use. Future studies should compare SE and SWE, minimize variability, benchmark against MRI, and assess prognostic value.