Mammographic breast density assessed with fully automated method and its risk for breast cancer

Pendem Saikiran, Ruqiya Ramzan, S. Nandish, Phani Deepika Kamineni, Priyanka, Arathy Mary John

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Objectives: We evaluated the association between breast cancer and breast density (BD) measured using fully automated software. We also evaluated the performance of cancer risk models such as only clinical risk factors, density related measures, and both clinical risk factors and density-related measures for determining cancer risk. Materials and Methods: This is a retrospective case-control study. The data were collected from August 2015 to December 2018. Two hundred fifty women with breast cancer and 400 control subjects were included in this study. We evaluated the BD qualitatively using breast imaging-reporting and data system density and quantitatively using 3D slicer. We also collected clinical factors such as age, familial history of breast cancer, menopausal status, number of births, body mass index, and hormonal replacement therapy use. We calculated the odds ratio (OR) for BD to determine the risk of breast cancer. We performed receiver operating characteristic (ROC) curve to assess the performance of cancer risk models. Results: The OR for the percentage BD for second, third, and fourth quartiles was 1.632 (95% confidence intervals [CI]: 1.102-2.416), 2.756 (95% CI: 1.704-4.458), and 3.163 (95% CI: 1.356-5.61). The area under ROC curve for clinical risk factors only, mammographic density measures, combined mammographic, and clinical risk factors was 0.578 (95% CI: 0.45, 0.64), 0.684 (95% CI: 0.58, 0.75), and 0.724 (95% CI: 0.64, 0.80), respectively. Conclusion: Mammographic BD was found to be positively associated with breast cancer. The density related measures combined clinical risk factors, and density model had good discriminatory power in identifying the cancer risk.

Original languageEnglish
Article numberA1301202000
JournalJournal of Clinical Imaging Science
Volume9
Issue number1
DOIs
Publication statusPublished - 01-01-2019
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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