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Personalised screening: is this the way forward?

F J Gilbert1, A Selamoglu1

  • 1Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.

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This summary is machine-generated.

Supplemental imaging like DBT, ABUS, CESM, and ABB-MRI can improve breast cancer detection, especially in women with dense breasts. These advanced techniques offer better cancer identification than traditional mammography alone.

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Mammography screening is common but less sensitive in women with dense breast tissue.
  • Predictive models incorporating breast density and SNPs exist for breast cancer risk.
  • Dense breast tissue poses challenges for mammographic sensitivity.

Purpose of the Study:

  • To review the current status of advanced breast cancer screening techniques.
  • To evaluate supplemental imaging options for women with dense or heterogeneously dense breasts.
  • To assess the potential of newer technologies in increasing cancer detection rates.

Main Methods:

  • Literature review of digital breast tomosynthesis (DBT), automated breast ultrasound (ABUS), contrast-enhanced mammography (CESM), and abbreviated magnetic resonance imaging (ABB-MRI).
  • Analysis of reported cancer detection rates and recall rates for each technique.
  • Evaluation of sensitivity and specificity compared to standard mammography.

Main Results:

  • DBT increases cancer detection by ~15% with fewer recalls.
  • ABUS shows modest increases in cancer detection (2-4/1,000) with initial higher recalls.
  • CESM offers high sensitivity comparable to MRI; ABB-MRI is effective for high-risk screening.

Conclusions:

  • Advanced imaging techniques like DBT, ABUS, CESM, and ABB-MRI show promise for improving breast cancer screening, particularly in women with dense breasts.
  • Further research into cost-effectiveness and detailed reporting of detected tumors is needed.
  • These supplemental methods can enhance cancer detection in at-risk populations.