Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics

列线图 无线电技术 医学 乳腺癌 接收机工作特性 阶段(地层学) 逻辑回归 队列 淋巴结 放射科 肿瘤科 癌症 内科学 古生物学 生物
作者
Weiyue Chen,Guihan Lin,Chunli Kong,Xulu Wu,Yumin Hu,Minjiang Chen,Shuiwei Xia,Chenying Lu,Min Xu,Jiansong Ji
出处
期刊:British Journal of Radiology [Wiley]
卷期号:97 (1154): 439-450 被引量:8
标识
DOI:10.1093/bjr/tqad034
摘要

Abstract Objectives Accurate axillary evaluation plays an important role in prognosis and treatment planning for breast cancer. This study aimed to develop and validate a dynamic contrast-enhanced (DCE)-MRI-based radiomics model for preoperative evaluation of axillary lymph node (ALN) status in early-stage breast cancer. Methods A total of 410 patients with pathologically confirmed early-stage invasive breast cancer (training cohort, N = 286; validation cohort, N = 124) from June 2018 to August 2022 were retrospectively recruited. Radiomics features were derived from the second phase of DCE-MRI images for each patient. ALN status-related features were obtained, and a radiomics signature was constructed using SelectKBest and least absolute shrinkage and selection operator regression. Logistic regression was applied to build a combined model and corresponding nomogram incorporating the radiomics score (Rad-score) with clinical predictors. The predictive performance of the nomogram was evaluated using receiver operator characteristic (ROC) curve analysis and calibration curves. Results Fourteen radiomic features were selected to construct the radiomics signature. The Rad-score, MRI-reported ALN status, BI-RADS category, and tumour size were independent predictors of ALN status and were incorporated into the combined model. The nomogram showed good calibration and favourable performance for discriminating metastatic ALNs (N + (≥1)) from non-metastatic ALNs (N0) and metastatic ALNs with heavy burden (N + (≥3)) from low burden (N + (1-2)), with the area under the ROC curve values of 0.877 and 0.879 in the training cohort and 0.859 and 0.881 in the validation cohort, respectively. Conclusions The DCE-MRI-based radiomics nomogram could serve as a potential non-invasive technique for accurate preoperative evaluation of ALN burden, thereby assisting physicians in the personalized axillary treatment for early-stage breast cancer patients. Advances in knowledge This study developed a potential surrogate of preoperative accurate evaluation of ALN status, which is non-invasive and easy-to-use.
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