Cited by 282Radiomics and Machine Learning in Medical ImagingMRI in cancer diagnosisBreast Cancer Treatment Studies

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Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment

Pinker, Katja, Chin, Joanne, Melsaether, Amy N., Morris, Elizabeth A., Moy, Linda·2018·Radiology

DOI 10.1148/radiol.2018172171

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Abstract

Precision medicine is medicine optimized to the genotypic and phenotypic characteristics of an individual and, when present, his or her disease. It has a host of targets, including genes and their transcripts, proteins, and metabolites. Studying precision medicine involves a systems biology approach that integrates mathematical modeling and biology genomics, transcriptomics, proteomics, and metabolomics. Moreover, precision medicine must consider not only the relatively static genetic codes of individuals, but also the dynamic and heterogeneous genetic codes of cancers. Thus, precision medicine relies not only on discovering identifiable targets for treatment and surveillance modification, but also on reliable, noninvasive methods of identifying changes in these targets over time. Imaging via radiomics and radiogenomics is poised for a central role. Radiomics, which extracts large volumes of quantitative data from digital images and amalgamates these together with clinical and patient data into searchable shared databases, potentiates radiogenomics, which is the combination of genetic and radiomic data. Radiogenomics may provide voxel-by-voxel genetic information for a complete, heterogeneous tumor or, in the setting of metastatic disease, set of tumors and thereby guide tailored therapy. Radiogenomics may also quantify lesion characteristics, to better differentiate between benign and malignant entities, and patient characteristics, to better stratify patients according to risk for disease, thereby allowing for more precise imaging and screening. This report provides an overview of precision medicine and discusses radiogenomics specifically in breast cancer. © RSNA, 2018

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Authors: Pinker, K., Chin, J., Melsaether, A. N., Morris, E. A., & Moy, L.
Affiliations: Memorial Sloan Kettering Cancer Center (US)
ORCID: Pinker, Katja
Morris, Elizabeth A.
Moy, Linda
Venue: Radiology
Publisher: Radiological Society of North America (RSNA)
Published: 2018-06
Volume: 287
Issue: 3
Pages: 732-747
ISSN: 0033-8419 (ISSN-L)
1527-1315
DOI: 10.1148/radiol.2018172171
OpenAlex: W2803669118
Cited by: 275
References: 140
Citations by year: 2026: 18 · 2025: 27 · 2024: 31 · 2023: 44 · 2022: 43 · 2021: 42 · 2020: 35 · 2019: 24 · 2018: 11
FWCI: 4.46
Type: journal article
Language: en
Open access: closed
Locations: Radiology (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › MRI in cancer diagnosis
Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
Keywords: precision medicine, radiogenomics, radiomics, breast cancer, tumor heterogeneity, metastatic breast cancer, benign versus malignant differentiation, risk stratification, cancer screening, multimodal data integration, systems biology
MeSH terms: Breast Neoplasms, Female, Humans, Image Interpretation, Computer-Assisted, Mammography, Radiology, Biomarkers, Tumor, Genetic Predisposition to Disease, Genomics, Precision Medicine

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Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment

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