Siyi Chen, Yue Zhang, Yuqi Su, Jie Tian, Yongxin Chen, Wenjie Tang, Yaheng Fan, Chen Jin, Yangcheng He, Yongzhou Xu, Hong Hu, Yuan Guo, Junping Li
{"title":"基于动态增强磁共振成像的栖息地放射组学评估临床T1-T2期乳腺癌腋窝淋巴结负担：一项多中心和可解释的研究。","authors":"Siyi Chen, Yue Zhang, Yuqi Su, Jie Tian, Yongxin Chen, Wenjie Tang, Yaheng Fan, Chen Jin, Yangcheng He, Yongzhou Xu, Hong Hu, Yuan Guo, Junping Li","doi":"10.1002/jmri.29796","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Axillary lymph node burden(ALNB) is a critical factor in determining treatment strategies for clinical T<sub>1</sub>-T<sub>2</sub> (cT<sub>1</sub>-T<sub>2</sub>) stage breast cancer. However, as ALNB assessment relies on invasive procedures, exploring non-invasive methods is essential.</p><p><strong>Purpose: </strong>To develop and validate a habitat radiomics model for assessing ALNB in cT<sub>1</sub>-T<sub>2</sub> breast cancer, incorporating radiogenomic data to improve interpretability.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>468 patients with cT<sub>1</sub>-T<sub>2</sub> 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.</p><p><strong>Field strength/sequence: </strong>1.5-T MRI and 3.0-T MRI, and three-dimensional dynamic contrast-enhanced T1-weighted gradient-echo sequences.</p><p><strong>Assessment: </strong>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.</p><p><strong>Statistical tests: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Data conclusion: </strong>The Habitat model has the potential to assess ALNB in cT<sub>1</sub>-T<sub>2</sub> breast cancer and assist radiologists in axillary diagnosis, which may help reduce the need for unnecessary ALN dissection.</p><p><strong>Evidence level: </strong>3. Technical Efficacy: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"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.\",\"authors\":\"Siyi Chen, Yue Zhang, Yuqi Su, Jie Tian, Yongxin Chen, Wenjie Tang, Yaheng Fan, Chen Jin, Yangcheng He, Yongzhou Xu, Hong Hu, Yuan Guo, Junping Li\",\"doi\":\"10.1002/jmri.29796\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Axillary lymph node burden(ALNB) is a critical factor in determining treatment strategies for clinical T<sub>1</sub>-T<sub>2</sub> (cT<sub>1</sub>-T<sub>2</sub>) stage breast cancer. However, as ALNB assessment relies on invasive procedures, exploring non-invasive methods is essential.</p><p><strong>Purpose: </strong>To develop and validate a habitat radiomics model for assessing ALNB in cT<sub>1</sub>-T<sub>2</sub> breast cancer, incorporating radiogenomic data to improve interpretability.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>468 patients with cT<sub>1</sub>-T<sub>2</sub> 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.</p><p><strong>Field strength/sequence: </strong>1.5-T MRI and 3.0-T MRI, and three-dimensional dynamic contrast-enhanced T1-weighted gradient-echo sequences.</p><p><strong>Assessment: </strong>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.</p><p><strong>Statistical tests: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Data conclusion: </strong>The Habitat model has the potential to assess ALNB in cT<sub>1</sub>-T<sub>2</sub> breast cancer and assist radiologists in axillary diagnosis, which may help reduce the need for unnecessary ALN dissection.</p><p><strong>Evidence level: </strong>3. Technical Efficacy: Stage 2.</p>\",\"PeriodicalId\":16140,\"journal\":{\"name\":\"Journal of Magnetic Resonance Imaging\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Magnetic Resonance Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/jmri.29796\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Magnetic Resonance Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/jmri.29796","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
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.
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.
期刊介绍：
The Journal of Magnetic Resonance Imaging (JMRI) is an international journal devoted to the timely publication of basic and clinical research, educational and review articles, and other information related to the diagnostic applications of magnetic resonance.
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