Predicting survival and early clinical response to primary chemotherapy for patients with locally advanced breast cancer using DCE-MRI

J Magn Reson Imaging. 2009 Jun;29(6):1300-7. doi: 10.1002/jmri.21778.


Purpose: To evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a tool for early prediction of response to neoadjuvant chemotherapy (NAC) and 5-year survival in patients with locally advanced breast cancer.

Materials and methods: DCE-MRI was performed in patients scheduled for NAC (n = 24) before and after the first treatment cycle. Clinical response was evaluated after completed NAC. Relative signal intensity (RSI) and area under the curve (AUC) were calculated from the DCE-curves and compared to clinical treatment response. Kohonen and probabilistic neural network (KNN and PNN) analysis were used to predict 5-year survival.

Results: RSI and AUC were reduced after only one cycle of NAC in patients with clinical treatment response (P = 0.02 and P = 0.08). The mean and 10th percentile RSI values before NAC were significantly lower in patients surviving more than 5 years compared to nonsurvivors (P = 0.05 and 0.02). This relationship was confirmed using KNN, which demonstrated that patients who remained alive clustered in separate regions from those that died. Calibration of contrast enhancement curves by PNN for patient survival at 5 years yielded sensitivity and specificity for training and testing ranging from 80%-92%.

Conclusion: DCE-MRI in locally advanced breast cancer has the potential to predict 5-year survival in a small patient cohort. In addition, changes in tumor vascularization after one cycle of NAC can be assessed.

Publication types

  • Randomized Controlled Trial

MeSH terms

  • Adult
  • Aged
  • Antineoplastic Combined Chemotherapy Protocols / therapeutic use*
  • Area Under Curve
  • Breast Neoplasms / drug therapy*
  • Breast Neoplasms / pathology
  • Contrast Media
  • Cross-Over Studies
  • Female
  • Gadolinium DTPA
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Middle Aged
  • Neoadjuvant Therapy
  • Neural Networks, Computer
  • Predictive Value of Tests
  • Sensitivity and Specificity
  • Survival Rate


  • Contrast Media
  • gadodiamide
  • Gadolinium DTPA