Rationale and Objectives
We aimed to investigate the value of magnetic resonance image (MRI)-based radiomics
in predicting Ki-67 expression of breast cancer.
Methods
In this retrospective study, 159 lesions from 154 patients were included. Radiomic
features were extracted from contrast-enhanced T1-weighted MRI (C+MRI) and apparent
diffusion coefficient (ADC) maps, with open-source software. Dimension reduction was
done with reliability analysis, collinearity analysis, and feature selection. Two
different Ki-67 expression cut-off values (14% vs 20%) were studied as reference standard
for the classifications. Input for the models were radiomic features from individual
MRI sequences or their combination. Classifications were performed using a generalized
linear model.
Results
Considering Ki-67 cut-off value of 14%, training and testing AUC values were 0.785
(standard deviation [SD], 0.193) and 0.849 for ADC; 0.696 (SD, 0.150) and 0.695 for
C+MRI; 0.755 (SD, 0.171) and 0.635 for the combination of both sequences, respectively.
Regarding Ki-67 cut-off value of 20%, training and testing AUC values were 0.744 (SD,
0.197) and 0.617 for ADC; 0.629 (SD, 0.251) and 0.741 for C+MRI; 0.761 (SD, 0.207)
and 0.618 for the combination of both sequences, respectively.
Conclusion
ADC map-based selected radiomic features coupled with generalized linear modeling
might be a promising non-invasive method to determine the Ki-67 expression level of
breast cancer.
KEY WORDS
Abbreviations:
ADC (Apparent diffusion coefficient), AUC (Area under the receiver operating characteristic curve), BC (Breast cancer), C+MRI (Contrast-enhanced T1-weighted MRI), D (Dimensional), DCE-MRI (Dynamic contrast-enhanced magnetic resonance imaging), DWI (Diffusion-weighted echo-planar images), FLASH (Fast low angle shot), GLM (Generalized linear model), HER-2 (Human epithelial receptor-2), ICC (Intra-class correlation coefficient), LASSO (The least absolute shrinkage and selection operator), LoG (Laplacian of Gaussian), MCC (Matthews correlation coefficient), mi RNA (micro RNA), MRI (Magnetic resonance imaging), NAC (Neoadjuvant chemotherapy), TNBC (Triple negative breast cancer), PACS (Picture Archiving and Communication System), RNA (Ribonucleic acid), ROI (Region of interest), SD (Standard deviation), SUBT (Subtraction)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: March 17, 2021
Accepted:
February 2,
2021
Received in revised form:
January 28,
2021
Received:
December 14,
2020
Identification
Copyright
© 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
