Scholay

学术搜索 · AI 审稿 · LaTeX 协作

Habitat Radiomics Based on Dynamic Contrast‐Enhanced Magnetic Resonance Imaging for Assessing Axillary Lymph Node Burden in Clinical T1 – T2 Stage Breast Cancer: A Multicenter and Interpretable Study

作者:Si‐Yi Chen, Yue Zhang, Ying Su, Jie Tian, Yongxin Chen, Wenjie Tang, Yaheng Fan, Chen Jin, Yangcheng He, Yongzhou Xu, Hong Hu, Yuan Guo, Junping Li · 发表于:Journal of Magnetic Resonance Imaging · 年份:2025 · DOI:10.1002/jmri.29796 · 被引用次数:11 · 研究领域:Radiomics and Machine Learning in Medical Imaging、MRI in cancer diagnosis、Breast Cancer Treatment Studies

BACKGROUND: ) stage breast cancer. However, as ALNB assessment relies on invasive procedures, exploring non-invasive methods is essential. PURPOSE: breast cancer, incorporating radiogenomic data to improve interpretability. STUDY TYPE: Retrospective. POPULATION: stage breast cancer from two institutions and The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA)-Breast Invasive Carcinoma (BRCA) were included. The cohort was divided into training (n = 173), internal validation (n = 58), external validation (n = 130), and TCGA-BRCA sets (n = 107). Patients were categorized into high nodal burden (HNB; > 3 positive lymph nodes) and non-HNB (≤ 3 positive lymph nodes) groups. FIELD STRENGTH/SEQUENCE: 1.5-T MRI and 3.0-T MRI, and three-dimensional dynamic contrast-enhanced T1-weighted gradient-echo sequences. ASSESSMENT: Two logistic regression models were developed using habitat-based and clinical features. Model performance was evaluated using the AUC. SHapley Additive exPlanations (SHAP) analysis was employed to identify key features. Radiogenomic analysis, including gene set enrichment and drug sensitivity assessments, was conducted using transcriptomic data from the TCGA-BRCA set. STATISTICAL TESTS: Pearson correlation, Mann-Whitney U, genetic algorithm, logistic regression, AUC analysis, delong test, and SHAP analysis. A p-value < 0.05 was considered statistically significant. RESULTS: The Habitat model outperformed the Clinical model (AUCs: 0.840-0.932 vs. 0.558...