Related Experiment Video
Updated: Jun 16, 2025
Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
Published on: February 6, 2020
The development and validation of a risk stratification system for assessing axillary status after neoadjuvant
Jia-Xin Huang1,2, Jing-Si Mei3, Fei Chen4
1Department of Liver Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Objective:
It is not clear which procedure is most optimal for axilla after neoadjuvant therapy (NAT) in node-positive breast cancer patients. Accurately identifying patients with axillary pathologic complete response (pCR) is crucial to minimize the overtreatment of axilla. This study was designed to develop a risk stratification model for axillary pCR.
Methods:
In this multicenter, prospective, observational study, node-positive breast cancer patients who received NAT followed by axillary lymph node dissection (ALND) were enrolled between June 2021 and April 2024. We assessed the performance of breast shear wave elastography (SWE) utilizing virtual touch imaging quantification in determining axillary status across ultrasound (US) nodal stages following NAT. A predictive model incorporating axilla US nodal stage and breast SWE was developed using multivariate logistic regression analysis. Last, a simplified risk score was developed based on the calculated prediction probability from this model and validated in the external test cohort.
Results:
The axillary pCR rates were 52.53% in the training cohort ( n = 257) and 51.79% in the external test cohorts ( n = 195). Approximately 21.67% of US N0 cases were false negatives; 42.35% of US N1 cases were false positives. With SWE, the false negative rate was 11.53% in US N0 patients and false positive rate was 22.22% in US N1 patients. The model based on dual-modality US demonstrated strong discriminatory ability (AUC, 0.93), precise calibration (slope of calibration curve, 0.99), and practical clinical utility (probability threshold, 4.5-94.5%); the percentages of accuracy, sensitivity, and specificity were 87.94%, 88.52%, and 87.41%, respectively. Patients scoring 1 demonstrated a low axillary non-pCR rate (5.21%-6.97%), potentially reducing unnecessary ALND rate (17.12%-24.10%).
Conclusions:
The risk stratification model integrating axilla US and breast SWE demonstrated good performance for assessing axillary status after NAT in node-positive breast cancer and might provide guidance for less aggressive management for specific individuals.
