Rationale and Objectives
There are limited data on pretreatment imaging features that can predict response
to neoadjuvant chemotherapy (NAC). To extract volumetric pretreatment MRI radiomics
features and assess corresponding associations with breast cancer molecular subtypes,
pathological complete response (pCR), and residual cancer burden (RCB) in patients
treated with NAC.
Materials and Methods
In this IRB-approved study, clinical and pretreatment MRI data from patients with
biopsy-proven breast cancer who received NAC between September 2009 and July 2016
were retrospectively analyzed. Tumors were manually identified and semi-automatically
segmented on first postcontrast images. Morphological and three-dimensional textural
features were computed, including unfiltered and filtered image data, with spatial
scaling factors (SSF) of 2, 4, and 6 mm. Wilcoxon rank-sum tests and area under the
receiver operating characteristic curve were used for statistical analysis.
Results
Two hundred and fifty nine patients with unilateral breast cancer, including 73 (28.2%) HER2+, 112 (43.2%) luminal,
and 74 (28.6%) triple negative breast cancers (TNBC), were included. There was a significant
difference in the median volume (p = 0.008), median longest axial tumor diameter (p = 0.009), and median longest volumetric diameter (p = 0.01) among tumor subtypes. There was also a significant difference in minimum
signal intensity and entropy among the tumor subtypes with SSF = 4 mm (p = 0.009 and p = 0.02 respectively) and SSF = 6 mm (p = 0.007 and p < 0.001 respectively). Additionally, sphericity (p = 0.04) in HER2+ tumors and entropy with SSF = 2, 4, 6 mm (p = 0.004, 0.02, 0.047 respectively) in luminal tumors were significantly associated
with pCR. Multiple features demonstrated significant association (p < 0.05) with pCR in TNBC and with RCB in luminal tumors and TNBC, with standard deviation
of intensity with SSF = 6 mm achieving the highest AUC (AUC = 0.734) for pCR in TNBC.
Conclusion
MRI radiomics features are associated with different molecular subtypes of breast
cancer, pCR, and RCB. These features may be noninvasive imaging biomarkers to identify
cancer subtype and predict response to NAC.
Key Words
Abbreviations:
MRI (Magnetic Resonance Imaging), NAC (Neoadjuvant Chemotherapy), HER2+ (Human Epidermal Growth Factor Receptor 2 Positive), TNBC (Triple Negative Breast Cancer), ER+ (Estrogen Receptor Positive), SSF (Spatial Scaling Factor), pCR (Pathological Complete Response), RCB (Residual Cancer Burden), AUC (Area Under the Curve), ROC (Receiver Operating Characteristic)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: November 04, 2020
Accepted:
October 16,
2020
Received in revised form:
October 11,
2020
Received:
September 20,
2020
Footnotes
Research reported in this article was supported by the National Cancer Institute of the National Institutes of Health under Award Number P50 CA116201 (Mayo Clinic Breast Cancer Specialized Program of Research Excellence) awarded to SC and MG.
Identification
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© 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
