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Characterisation of Screen Detected and Simulated Calcification Clusters in Digital Mammograms

  • Lucy M. Warren
  • Louise Dummott
  • Matthew G. Wallis
  • Rosalind M. Given-Wilson
  • Julie Cooke
  • David R. Dance
  • Kenneth C. Young
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8539)

Abstract

Simulated microcalcifciation clusters have been used in studies performed to investigate the effect of different imaging conditions on cancer detection in breast screening. This work compares the characteristics of the simulated clusters to screen-detected calcification clusters. Using a database of 271 screen-detected cancers it was found that 67 (25%) presented radiographically as calcification clusters. The characteristics of 1215 microcalcifications from all 67 clusters and 304 microcalcifications from 30 simulated clusters were quantitatively analysed. The diameter of simulated calcifications were within the range of 99% of real calcifications. The cluster diameters of the simulated clusters were within the range of 70% of the real clusters. Our simulated calcifications had similar characteristics to real calcifications but were representative of smaller clusters which represent 17% of screen-detected cancers. Consequently, a significant change in detection of our simulated clusters due to change in imaging condition has a predictable impact on cancer detection in screening.

Keywords

Calcification digital mammography simulation virtual clinical trials 

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References

  1. 1.
    Warren, L.M., Mackenzie, A., Cooke, J., Given-Wilson, R.M., Wallis, M.G., Chakraborty, D.P., Dance, D.R., Bosmans, H., Young, K.C.: Effect of image quality on calcification detection in digital mammography. Med. Phys. 39, 3202–3213 (2012)CrossRefGoogle Scholar
  2. 2.
    Warren, L.M., Cooke, J., Given-Wilson, R.M., Wallis, M.G., Halling-Brown, M., Mackenzie, A., Chakraborty, D.P., Bosmans, H., Dance, D.R., Young, K.C.: The effect of image processing on detection of cancers in digital mammography. AJR (in press, 2014)Google Scholar
  3. 3.
    Mackenzie, A., Warren, L.M., Dance, D.R., Chakraborty, D.P., Cooke, J., Halling-Brown, M.D., Looney, P.T., Wallis, M.G., Given-Wilson, R.M., Alexander, G.G., Young, K.C.: Using image simulation to test the effect of detector type on breast cancer detection. In: Proc. SPIE, vol. 9037 (in press, 2014)Google Scholar
  4. 4.
    Warren, L.M., Green, F.H., Shrestha, L., Mackenzie, A., Dance, D.R., Young, K.C.: Validation of simulation of calcifications for observer studies in digital mammography. Phys. Med. Biol. 58, N217-N228 (2013)Google Scholar
  5. 5.
    NHS Breast Screening Programme and Association of Breast Surgery, An audit of screen detected breast cancers for the year of screening April 2010 to March 2011, NHS Cancer Screening Programmes (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Lucy M. Warren
    • 1
    • 2
  • Louise Dummott
    • 1
    • 2
  • Matthew G. Wallis
    • 3
    • 4
  • Rosalind M. Given-Wilson
    • 5
  • Julie Cooke
    • 6
  • David R. Dance
    • 1
    • 2
  • Kenneth C. Young
    • 1
    • 2
  1. 1.National Coordinating Centre for the Physics of MammographyRoyal Surrey County Hospital NHS Foundation TrustGuildfordUK
  2. 2.Department of PhysicsUniversity of SurreyGuildfordUK
  3. 3.Cambridge Breast UnitCambridge University Hospitals NHS Foundation TrustCambridgeUK
  4. 4.NIHR Cambridge Biomedical Research CentreCambridgeUK
  5. 5.Department of RadiologySt. George’s Healthcare NHS TrustLondonUK
  6. 6.Jarvis Breast Screening and Diagnostic CentreGuildford

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