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Combining Molecular and Radiomic Features for Risk Assessment in Breast Cancer.
Nguyen, Alex A; McCarthy, Anne Marie; Kontos, Despina.
Affiliation
  • Nguyen AA; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • McCarthy AM; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Kontos D; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA; email: despina.kontos@pennmedicine.upenn.edu.
Annu Rev Biomed Data Sci ; 6: 299-311, 2023 08 10.
Article in En | MEDLINE | ID: mdl-37159874
ABSTRACT
Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual woman's risk, we can reduce the risk of over/undertreatment by preventing unnecessary procedures or by elevating screening procedures. Breast density measured from conventional mammography has been established as one of the most dominant risk factors for breast cancer; however, it is currently limited by its ability to characterize more complex breast parenchymal patterns that have been shown to provide additional information to strengthen cancer risk models. Molecular factors ranging from high penetrance, or high likelihood that a mutation will show signs and symptoms of the disease, to combinations of gene mutations with low penetrance have shown promise for augmenting risk assessment. Although imaging biomarkers and molecular biomarkers have both individually demonstrated improved performance in risk assessment, few studies have evaluated them together. This review aims to highlight the current state of the art in breast cancer risk assessment using imaging and genetic biomarkers.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Annu Rev Biomed Data Sci Year: 2023 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Annu Rev Biomed Data Sci Year: 2023 Document type: Article Affiliation country: United States
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