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Accuracy of transvaginal sonoelastography for differential diagnosis between malignant and benign cervical lesions: A
Yi Zhu1,2, Xue-Feng Leng3, Guo-Nan Zhang4
1Department of Ultrasound, the Affiliated Cancer Hospital, School of Medicine, University of Electronic Science and Technology of China, Sichuan Cancer Hospital and Institute, Chengdu, China.
Background:
To evaluate the performance of transvaginal sonoelastography (TVSE) for differential diagnosis between malignant and benign cervical lesions using a meta-analysis.
Methods:
An independent literature search was conducted on the English medical database, including PubMed, Embase and Medline, Cochrane Library, Web of Science, and OVID. The diagnostic accuracy of TVSE was compared with that of histopathology, which is the gold reference standard for diagnosis. The accuracy of TVSE was assessed by calculating the pooled sensitivity, specificity, diagnostic odds ratio, and area under the curve (AUC). The imaging mechanisms, assessment methods, and QUADAS scores were assessed with a meta-regression analysis. A Deeks funnel plot was performed for evaluating publication bias.
Results:
Six eligible studies reported a total sample of 615 cervical lesions (415 cancers, 200 benign lesions). TVSE showed a pooled diagnostic odds ratio of 21.42 (95% CI 13.65-33.61), sensitivity of 0.87 (95% CI 0.84-0.90), specificity of 0.79 (95% CI 0.72-0.84), and an AUC of 0.892 (Q* = 0.822). The results of the meta-regression analysis showed that the imaging mechanism (P = .253), the assessment method (P = .279), or QUADAS score (P = .205) did not affect the study heterogeneity.
Conclusion:
TVSE has a relatively high and satisfactory value for differential diagnosis between malignant and benign cervical lesions. The diagnostic performance of strain elastography and shear wave elastography were similar and good. However, to accommodate heterogeneity and publication bias, high-quality studies are required to further comparative effectiveness analyses to verify the efficacy of ultrasound detection.
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