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DOI 10.1002/jmri.29796

Медицинская библиотека · Journal of magnetic resonance imaging : JMRI · 2025

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.

Chen Siyi, Zhang Yue, Su Yuqi, Tian Jie, Chen Yongxin, Tang Wenjie, Fan Yaheng, Jin Chen, He Yangcheng, Xu Yongzhou, Hu Hong, Guo Yuan, Li Junping

СтатьяМногоцентровое исследованиеПеревод пока не подготовлен

Аннотация

BACKGROUND

Axillary lymph node burden(ALNB) is a critical factor in determining treatment strategies for clinical T1-T2 (cT1-T2) stage breast cancer. However, as ALNB assessment relies on invasive procedures, exploring non-invasive methods is essential.

PURPOSE: To develop and validate a habitat radiomics model for assessing ALNB in cT1-T2 breast cancer, incorporating radiogenomic data to improve interpretability.

STUDY TYPE: Retrospective.

POPULATION: 468 patients with cT1-T2 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. 0.558-0.673). The SHAP analysis was used to rank feature importance, with subregion 3 showing the highest average SHAP value. Radiogenomic analysis indicated upregulation of the KEGG ribosome pathway in the HNB group and identified differential drug sensitivity profiles among risk groups.

DATA

CONCLUSION

The Habitat model has the potential to assess ALNB in cT1-T2 breast cancer and assist radiologists in axillary diagnosis, which may help reduce the need for unnecessary ALN dissection.

EVIDENCE LEVEL: 3. Technical Efficacy: Stage 2.

Для цитирования: Chen Siyi, Zhang Yue, Su Yuqi, Tian Jie, Chen Yongxin, Tang Wenjie, Fan Yaheng, Jin Chen, He Yangcheng, Xu Yongzhou, Hu Hong, Guo Yuan, Li Junping. 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.. Journal of magnetic resonance imaging : JMRI. 2025. DOI: 10.1002/jmri.29796.

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