Related Experiment Video
Updated: Jan 21, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
MRI does not predict pathologic complete response after neoadjuvant chemotherapy for breast cancer
Stephen F Sener1,2, Rachel E Sargent1,2, Connie Lee1,2
1Los Angeles County+University of Southern California (LAC+USC) Medical Center, Los Angeles, California.
Background:
This study assessed whether magnetic resonance imaging (MRI) could accurately predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) for patients receiving standardized treatment, pre- and post-NAC MRI on the same instrumentation using a consistent imaging protocol, interpreted by a single breast fellowship-trained radiologist.
Methods:
A single-institution retrospective analysis was performed including clinical, radiographic, and pathologic parameters for all patients with breast cancer treated with NAC from 2015 to 2018. Radiographic complete response (rCR) was defined as absence of suspicious MRI findings in the ipsilateral breast or lymph nodes. pCR was defined as the absence of invasive cancer or ductal carcinoma in-situ in breast or lymph nodes after operation (ypT0N0M0).
Results:
Data for 102 consecutive patients demonstrated that 44 (43.1%) had rCR and 41 (40.1%) had pCR. pCR occurred in 12 (25.0%) of 48 estrogen receptor positive (ER+) patients, 29 (53.7%) of 54 ER- patients, and 25 (52.1%) of 48 human epidermal growth factor receptor 2 positive patients. The positive predictive value for MRI after NAC was 84.5% and the negative predictive value was 72.7%. The accuracy rate for MRI was 78.6%. Of the 44 patients with rCR, 12 (27.3%) had residual cancer on the pathologic specimen after surgical excision.
Conclusion:
rCR is not accurate enough to serve as a surrogate marker for pCR on MRI after NAC.
Related Concept Videos
Predicting Molecular Geometry
Chemotherapy-Induced Nausea and Vomiting: Cannabinoids
Two synthetic agonists of THC,...
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
End Point Prediction: Gran Plot
For potentiometric titration, the Gran plot is created by plotting...
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Predicting Reaction Outcomes

