A study on the prognostic assessment of triple-negative breast cancer using habitat analysis of preoperative DCE-MRI subtraction maps - Report - MDSpire

A study on the prognostic assessment of triple-negative breast cancer using habitat analysis of preoperative DCE-MRI subtraction maps

  • By

  • Yiming Yao

  • Junfeng Kong

  • Shanshan Jiang

  • Yuan Sun

  • Wanqiu Zhang

  • Jinding Wei

  • Sen Xing

  • Fangsheng Mou

  • Xinghua Liu

  • Wenbing Zeng

  • July 3, 2026

  • 0 min

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Clinical Report: Evaluating Disease-Free Survival in Triple-Negative Breast Cancer

Overview

This study assesses disease-free survival (DFS) in triple-negative breast cancer (TNBC) using habitat analysis of preoperative DCE-MRI subtraction maps.

Background

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer, representing 15-20% of cases and associated with high recurrence rates. Accurate preoperative assessment of tumor heterogeneity is crucial for predicting treatment response and stratifying prognostic risk.

Data Highlights

MeasureHigh-Risk GroupLow-Risk GroupP-value
Habitat ITH0.59 ± 0.140.42 ± 0.22< 0.001

Key Findings

  • A total of 145 TNBC patients were enrolled, with 29 experiencing recurrence.
  • Habitat ITH was significantly higher in the high-risk recurrence group compared to the low-risk group.
  • The AUC for habitat ITH in predicting TNBC recurrence was 0.71.
  • Habitat ITH was identified as an independent predictor of poorer DFS (HR 1.465, P = 0.013).

Clinical Implications

The findings indicate that habitat analysis of DCE-MRI subtraction maps may enhance the prognostic assessment of TNBC.

Conclusion

Habitat analysis of preoperative DCE-MRI subtraction maps contributes to the prognostic assessment of TNBC.

Related Resources & Content

  1. Frontiers in Medicine, 2026 -- Multi-parametric MRI habitat radiomics with interpretable machine learning for early prediction of axillary lymph node metastasis in triple-negative breast cancer
  2. Frontiers in Oncology, 2026 -- MRI-based habitat radiomics for preoperative prediction of axillary pathological complete response in breast cancer after neoadjuvant therapy: a multicenter study
  3. European Radiology, 2025 -- Radiomics Utilizing Deep Learning Fails to Enhance Prediction of Residual Cancer Burden Following Chemotherapy in the LIMA Breast MRI Study
  4. European Radiology — Dynamic Susceptibility Contrast MRI-Based Vascular Heterogeneity as a Predictor of Local Recurrence Patterns in High-Grade Gliomas Preoperatively
  5. Overall Survival with Pembrolizumab in Early-Stage Triple-Negative Breast Cancer
  6. NCCN Guidelines® Insights: Breast Cancer, Version 5.2025
  7. PARP Inhibition Shows Long-term Survival Benefits for Patients With High-risk, BRCA-positive Breast Cancer in OlympiA Trial
  8. NEJM at ESMO — Overall Survival with Pembrolizumab in Early-Stage Triple- Negative Breast Cancer | New England Journal of Medicine
  9. OlympiA Trial: Long-Term Benefits of Olaparib Confirmed in High-Risk Subgroup of Breast Cancer - The ASCO Post
  10. Adjuvant PARP Inhibitors in Patients With High-Risk Early-Stage HER2-Negative Breast Cancer and Germline BRCA Mutations: ASCO Hereditary Breast Cancer Guideline Rapid Recommendation Update | Journal of Clinical Oncology
  11. ACR PRACTICE PARAMETER FOR THE
  12. MRI Exam-Specific Parameters: Breast (Revised 3-19-2025) : Accreditation Support
  13. Breast Imaging Reporting and Data System v2025: Key Updates in MRI - PMC
  14. The QIBA Profile for Diffusion-Weighted MRI: Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker | Radiology
  15. MRI‐based radiomics models for early predicting pathological response to neoadjuvant chemotherapy in triple‐negative breast cancer: A systematic review and meta‐analysis - PMC
  16. Multiparametric MRI–based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer | Scientific Reports
  17. Xu et al. Cancer Imaging (2025) 25:108
  18. TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods - PMC
  19. IBSI – Image Biomarker Standardisation Initiative

Original Source(s)

A study on the prognostic assessment of triple-negative breast cancer using habitat analysis of preoperative DCE-MRI subtraction maps

  • by Yiming Yao, Junfeng Kong, Shanshan Jiang, Yuan Sun, Wanqiu Zhang, Jinding Wei, Sen Xing, Fangsheng Mou, Xinghua Liu, Wenbing Zeng

  • July 3, 2026

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