Radiomic signatures with contrast-enhanced magnetic resonance imaging for the assessment of breast cancer receptor status and molecular subtypes: initial results
- Background: To evaluate the diagnostic performance of radiomic signatures extracted from contrast-enhanced magnetic resonance imaging (CE-MRI) for the assessment of breast cancer receptor status and molecular subtypes. Methods: One hundred and forty-three patients with biopsy-proven breast cancer who underwent CE-MRI at 3 T were included in this IRB-approved HIPAA-compliant retrospective study. The training dataset comprised 91 patients (luminal A, n = 49; luminal B, n = 8; HER2-enriched, n = 11; triple negative, n = 23), while the validation dataset comprised 52 patients from a second institution (luminal A, n = 17; luminal B, n = 17; triple negative, n = 18). Radiomic analysis of manually segmented tumors included calculation of features derived from the first-order histogram (HIS), co-occurrence matrix (COM), run-length matrix (RLM), absolute gradient (GRA), autoregressive model (ARM), discrete Haar wavelet transform (WAV), and lesion geometry (GEO). Fisher, probability of error and average correlation (POE + ACC), and mutual information coefficients were used for feature selection. Linear discriminant analysis followed by k-nearest neighbor classification (with leave-one-out cross-validation) was used for pairwise radiomic-based separation of receptor status and molecular subtypes. Histopathology served as the standard of reference. Results: In the training dataset, radiomic signatures yielded the following accuracies > 80%: luminal B vs. luminal A, 84.2% (mainly based on COM features); luminal B vs. triple negative, 83.9% (mainly based on GEO features); luminal B vs. all others, 89% (mainly based on COM features); and HER2-enriched vs. all others, 81.3% (mainly based on COM features). Radiomic signatures were successfully validated in the separate validation dataset for luminal A vs. luminal B (79.4%) and luminal B vs. triple negative (77.1%). Conclusions: In this preliminary study, radiomic signatures with CE-MRI enable the assessment of breast cancer receptor status and molecular subtypes with high diagnostic accuracy. These results need to be confirmed in future larger studies.
Author: | Doris Leithner, Joao V. Horvat, Maria Adele Marino, Blanca Bernard-Davila, Maxine S. Jochelson, R. Elena Ochoa-Albiztegui, Danny F. Martinez, Elizabeth A. Morris, Sunitha Thakur, Katja Pinker |
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URN: | urn:nbn:de:hebis:30:3-530808 |
DOI: | https://doi.org/10.1186/s13058-019-1187-z |
ISSN: | 1465-542X |
ISSN: | 1465-5411 |
Pubmed Id: | https://pubmed.ncbi.nlm.nih.gov/31514736 |
Parent Title (English): | Breast cancer research |
Publisher: | BioMed Central |
Place of publication: | London |
Contributor(s): | Joanne Chin |
Document Type: | Article |
Language: | English |
Year of Completion: | 2019 |
Date of first Publication: | 2019/09/12 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2020/03/11 |
Tag: | Breast cancer; Contrast-enhanced; Magnetic resonance imaging; Molecular subtype; Radiomics |
Volume: | 21 |
Issue: | 1, Art. 106 |
Page Number: | 11 |
First Page: | 1 |
Last Page: | 11 |
Note: | Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
HeBIS-PPN: | 464654882 |
Institutes: | Medizin / Medizin |
Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
Sammlungen: | Universitätspublikationen |
Licence (German): | Creative Commons - Namensnennung 4.0 |