Rationale and Objectives: The study investigated the potential of the combined use
of dynamic contrast-enhanced MRI and diffusion-weighted imaging in predicting the
pathological complete response (pCR) of neoadjuvant chemotherapy (NAC) after two cycles
of NAC. Materials and methods: Eighty-seven patients with breast cancer who underwent
MR examination before and after two cycles of NAC were enrolled. The patients were
randomly assigned to a training cohort and a validation cohort (3:1 ratio). MRI parameters
including tumor longest diameter, time-signal intensity curve, early enhanced ratio
(E90), maximal enhanced ratio and ADC value were measured, and percentage change in MRI
parameters were calculated. Univariate analysis and multivariate logistic regression
analysis were used to evaluate independent predictors of pCR in the training cohort.
The validation cohort was used to test the prediction model, and the nomogram was
created based on the prediction model. Results: This study demonstrated that the ADC
value after two cycles of NAC (OR = 1.041, 95% CI (1.002, 1.081); p = 0.037), percentage decrease in E90 (OR = 0.927, 95% CI (0.881, 0.977); p =0.004) and percentage decrease in tumor size
(OR = 0.948, 95% CI (0.909, 0.988); p = 0.011) were significantly important for independently predicting pCR. The prediction
model yielded AUC of 0.939 and 0.944 in the training cohort and the validation cohort,
respectively. Conclusion: The combined use of dynamic contrast-enhanced MRI and diffusion-weighted
imaging could accurately predict pCR after two cycles of NAC. The prediction model
and the nomogram had strong predictive value to NAC.
Key Words
Abbreviations:
ADC (apparent diffusion coefficient), AUC (area under the receiver operating characteristic curve), CI (confidence intervals), DCE-MRI (dynamic contrast-enhanced MRI), DWI (diffusion-weighted imaging), ER (estrogen receptor), HER2 (human epidermal growth factor receptor 2), NAC (Neoadjuvant chemotherapy), OR (odds ratio), pCR (pathological complete response), PR (progesterone receptor), ROC (receiver operating characteristic curve), ROI (region of interest), TIC (time signal intensity curve)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: February 13, 2021
Accepted:
January 13,
2021
Received in revised form:
January 13,
2021
Received:
December 7,
2020
Identification
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© 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
