已发表论文

基于自动乳腺超声系统的优化放射组学列线图:乳腺癌转移性淋巴结负荷术前预测的潜在工具

 

Authors Li N, Song C , Huang X, Zhang H, Su J, Yang L, He J, Cui G

Received 5 December 2022

Accepted for publication 27 January 2023

Published 5 February 2023 Volume 2023:15 Pages 121—132

DOI https://doi.org/10.2147/BCTT.S398300

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Pranela Rameshwar

Background: Axillary lymph node dissection (ALND) can be safely avoided in women with T1 or T2 primary invasive breast cancer (BC) and one to two metastatic sentinel lymph nodes (SLNs). However, cancellation of ALND based solely on SLN biopsy (SLNB) may lead to adverse outcomes. Therefore, preoperative assessment of LN tumor burden becomes a new focus for ALN status.
Objective: This study aimed to develop and validate a nomogram incorporating the radiomics score (rad-score) based on automated breast ultrasound system (ABUS) and other clinicopathological features for evaluating the ALN status in patients with early-stage BC preoperatively.
Methods: Totally 354 and 163 patients constituted the training and validation cohorts. They were divided into ALN low burden (< 3 metastatic LNs) and high burden (≥ 3 metastatic LNs) based on the histopathological diagnosis. The radiomics features of the segmented breast tumor in ABUS images were extracted and selected to generate the rad-score of each patient. These rad-scores, along with the ALN burden predictors identified from the clinicopathologic characteristics, were included in the multivariate analysis to establish a nomogram. It was further evaluated in the training and validation cohorts.
Results: High ALN burdens accounted for 11.2% and 10.8% in the training and validation cohorts. The rad-score for each patient was developed based on 7 radiomics features extracted from the ABUS images. The radiomics nomogram was built with the rad-score, tumor size, US-reported LN status, and ABUS retraction phenomenon. It achieved better predictive efficacy than the nomogram without the rad-score and exhibited favorable discrimination, calibration and clinical utility in both cohorts.
Conclusion: We developed an ABUS-based radiomics nomogram for the preoperative prediction of ALN burden in BC patients. It would be utilized for the identification of patients with low ALN burden if further validated, which contributed to appropriate axillary treatment and might avoid unnecessary ALND.
Keywords: axillary lymph node, sentinel lymph node biopsy, invasive breast cancer, radiomics, nomogram, automated breast ultrasound system, tumor burden