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DOI 10.1016/j.crad.2019.11.016

Медицинская библиотека · Clinical radiology · 2019

Role of sonoelastography in assessment of axillary lymph nodes in breast cancer: a systematic review and meta-analysis.

Wang R Y, Zhang Y W, Gao Z M, Wang X M

СтатьяМетаанализСистематический обзорПеревод пока не подготовлен

Аннотация

AIM: To evaluate the effectiveness of shear-wave elastography (SWE) and strain elastography (SE) for axillary lymph nodes (ALNs).

MATERIALS AND

METHODS

PubMed, Embase, and Cochrane Library databases were searched until September 2018. Weighted mean difference was calculated for continuous variables. The accuracy of sonoelastography was assessed by calculating pooled sensitivity, specificity, area under the curve (AUC), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). All data were analysed using Stata 12.0.

RESULTS

Ten studies with 1,038 ALNs were included in the meta-analysis. Five studies evaluated the use of SE, and the other five evaluated the SWE. The SWE stiffness values of malignant ALNs were significantly higher than those of benign nodes. Both SE and SWE have relatively high specificity and sensitivity. The max stiffness in SWE showed the highest specificity (0.94; 95% confidence interval [CI], 0.81-0.98), PLR (12.1; 95% CI, 4-36.5), NLR (0.29; 95% CI, 0.12-0.69), AUC (0.94; 95% CI, 0.91-0.96), and DOR (42; 95% CI, 12-154); in contrast, the mean stiffness showed the highest sensitivity (0.80; 95% CI, 0.61-0.91).

CONCLUSION

Sonoelastography demonstrated high sensitivity and specificity for differentiating between malignant and benign ALNs. The max and mean stiffness on SWE appeared to exhibit the highest accuracy. Thus, SWE is an effective accompaniment to sentinel node biopsy, and is appropriate for preoperative assessment of ALNs in the post-Z0011 era.

Для цитирования: Wang R Y, Zhang Y W, Gao Z M, Wang X M. Role of sonoelastography in assessment of axillary lymph nodes in breast cancer: a systematic review and meta-analysis.. Clinical radiology. 2019. DOI: 10.1016/j.crad.2019.11.016.

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