Radiomics in Triple Negative Breast Cancer: New Horizons in an Aggressive Subtype of the Disease

In the last decade, the analysis of the medical images has evolved significantly, applications and tools capable to extract quantitative characteristics of the images beyond the discrimination capacity of the investigator's eye being developed. The applications of this new research field, calle...

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Bibliographic Details
Published in:Journal of clinical medicine 2022-01, Vol.11 (3), p.616
Main Authors: Mireștean, Camil Ciprian, Volovăț, Constantin, Iancu, Roxana Irina, Iancu, Dragoș Petru Teodor
Format: Article
Language:English
Subjects:
Algorithms
Biomarkers
Brain cancer
Breast cancer
Clinical medicine
Magnetic resonance imaging
Mammography
Medical imaging
Medical prognosis
Precision medicine
Radiomics
Review
Software
Tomography
Tumors
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Summary:In the last decade, the analysis of the medical images has evolved significantly, applications and tools capable to extract quantitative characteristics of the images beyond the discrimination capacity of the investigator's eye being developed. The applications of this new research field, called radiomics, presented an exponential growth with direct implications in the diagnosis and prediction of response to therapy. Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype with a severe prognosis, despite the aggressive multimodal treatments applied according to the guidelines. Radiomics has already proven the ability to differentiate TNBC from fibroadenoma. Radiomics features extracted from digital mammography may also distinguish between TNBC and non-TNBC. Recent research has identified three distinct subtypes of TNBC using IRM breast images voxel-level radiomics features (size/shape related features, texture features, sharpness). The correlation of these TNBC subtypes with the clinical response to neoadjuvant therapy may lead to the identification of biomarkers in order to guide the clinical decision. Furthermore, the variation of some radiomics features in the neoadjuvant settings provides a tool for the rapid evaluation of treatment efficacy. The association of radiomics features with already identified biomarkers can generate complex predictive and prognostic models. Standardization of image acquisition and also of radiomics feature extraction is required to validate this method in clinical practice.
ISSN:2077-0383
2077-0383
DOI:10.3390/jcm11030616