Related Experiment Video
Updated: Jun 28, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Early changes in functional dynamic magnetic resonance imaging predict for pathologic response to neoadjuvant
Mei-Lin W Ah-See1, Andreas Makris, N Jane Taylor
1Mount Vernon Hospital, Northwood, Middlesex, UK. meilinahsee@hotmail.com
Purpose:
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows noninvasive, in vivo measurements of tissue microvessel perfusion and permeability. We examined whether DCE-MRI done after two cycles of neoadjuvant chemotherapy could predict final clinical and pathologic response in primary breast cancers.
Experimental Design:
Thirty-seven patients with primary breast cancer, due to receive six cycles of neoadjuvant 5-fluorouracil, epirubicin and cyclophosphamide chemotherapy, were examined using DCE-MRI before neoadjuvant chemotherapy and after two cycles of treatment. Changes in DCE-MRI kinetic parameters (K(trans), k(ep), v(e), MaxGd, rBV, rBF, MTT) were correlated with the final clinical and pathologic response to neoadjuvant chemotherapy. Test-retest variability was used to determine individual patient response.
Results:
Twenty-eight patients were evaluable for response (19 clinical responders and 9 nonresponders; 11 pathologic responders and 17 nonresponders). Changes in the DCE-MRI kinetic parameters K(trans), k(ep), MaxGd, rBV, and rBF were significantly correlated with both final clinical and pathologic response (P < 0.01). Change in K(trans) was the best predictor of pathologic nonresponse (area under the receiver operating characteristic curve, 0.93; sensitivity, 94%; specificity, 82%), correctly identifying 94% of nonresponders and 73% of responders. Change in MRI-derived tumor size did not predict for pathologic response.
Conclusion:
Changes in breast tumor microvessel functionality as depicted by DCE-MRI early on after starting anthracycline-based neoadjuvant chemotherapy can predict final clinical and pathologic response. The ability to identify nonresponders early may allow the selection of patients who may benefit from a therapy change.

