Predictive value of quantitative analysis of contrast-enhanced ultrasound gradient features of perfusion-deficient areas in early-stage breast cancer in sentinel lymph node metastasis
10.3760/cma.j.cn131148-20230517-00276
- VernacularTitle:早期乳腺癌灌注缺损区超声造影梯度特征的定量分析在前哨淋巴结转移中的预测价值
- Author:
Rui DU
1
;
Weiwei SHU
;
Xincai WU
;
Xin ZHANG
;
Yuefeng LI
Author Information
1. 江苏大学附属医院超声医学科，镇江 212001
- Keywords:
Contrast-enhanced ultrasound;
Perfusion defect;
Gradient feature;
Early breast cancer;
Sentinel lymph node
- From:
Chinese Journal of Ultrasonography
2023;32(10):880-885
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the predictive value of perfusion defect gradient features of early breast cancer using contrast-enhanced ultrasound (CEUS) in sentinel lymph node (SLN) metastasis.Methods:A retrospective analysis was performed on 147 patients with single early breast cancer confirmed by surgery and pathology in the Affiliated Hospital of Jiangsu University from January 2017 to December 2022, which were divided into SLN positive group (78 cases) and SLN negative group (69 cases) according to whether there are positive lesions in the biopsy SLN. The quantitative characteristics of CEUS in the perfusion defect and marginal high perfusion area of breast cancer in the two groups were analyzed. The differential gradient features between them were analyzed by multivariate Logistic regression and ROC curves.Results:The univariate analysis revealed statistically significant differences between the two groups for peak-arrival time gradient (ΔTTP), peak intensity gradient (ΔPI), ascending branch slope gradient (ΔRS) and area gradient under the curve (ΔAUC) (all P<0.05). Multivariate Logistic regression analysis showed that ΔTTP, ΔPI and ΔAUC were independent predictors of SLN status in early breast cancer (all P<0.05). The sensitivity (74.57%), specificity (84.42%) and area under the curve (0.789) of that combination of the three indexes for predicting SLN status were higher than the prediction efficiency of a single index.In addition, ΔTTP ( r=-0.578, P<0.05) was negatively correlated with average positive rate of SLN, and ΔPI ( r=0.629, P<0.05) and ΔAUC ( r=0.703, P<0.05) were positively correlated with average positive rate of SLN. Conclusions:The perfusion defect gradient features of early breast cancer are closely related to the SLN status and can effectively predict whether SLN metastasis occurrs.
