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A Comparative Study of the Inter-reader Variability of Breast Percent Density Estimation in Digital Mammography: Potential Effect of Reader’s Training and Clinical Experience

  • Conference paper
Digital Mammography (IWDM 2010)

Abstract

The variability of breast percent density (PD%) estimation from digital mammography (DM) images was evaluated using measurements from readers with different training and clinical experience. Post-processed DM images (PremiumView TM, GE Healthcare)from 40 women were analyzed. Breast PD% estimation was performed using the Cumulus software (Ver. 4.0, Univ. Toronto). Two groups of readers were considered, one with clinical (i.e., radiologists) and one with non-clinical training (i.e., physicists). Consistency of PD% was analyzed using the Pearson correlation coefficient (r) and ANOVA. Inter-reader agreement was higher among clinical (r=0.91, p<0.001), than non-clinical readers (r=0.83, p<0.001). Intra-reader consistency after repeated reads was on average equally high for both groups (r=0.91, p<0.001). Our results suggest that the reader’s experience and training has an effect on the obtained PD% measures. The higher correlation among the clinically trained readers could be attributed to their extensive exposure to post-processed DM images and their knowledge of breast anatomy.

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References

  1. Boyd, N.F., Guo, H., Martin, L.J., Sun, L., Stone, J., Fishell, E., Jong, R.A., Hislop, G., Chiarelli, A., Minkin, S., Yaffe, M.J.: Mammographic density and the risk and detection of breast cancer. New England Journal of Medicine 356, 227–236 (2007)

    Article  Google Scholar 

  2. Nicholson, B.T., LoRusso, A.P., Smolkin, M., Bovbjerg, V.E., Petroni, G.R., Harvey, J.A.: Accuracy of assigned BI-RADS breast density category definitions. Academic Radiology 13, 1143–1149 (2006)

    Article  Google Scholar 

  3. Ooms, E.A., Zonderland, H.M., Eijkemans, M.J., Kriege, M., Mahdavian Delavary, B., Burger, C.W., Ansink, A.C.: Mammography: interobserver variability in breast density assessment. Breast 16, 568–576 (2007)

    Article  Google Scholar 

  4. Yaffe, M.J.: Mammographic density. Measurement of mammographic density. Breast Cancer Research 10, 209 (2008)

    Article  Google Scholar 

  5. McCormack, V.A., dos Santos Silva, I.: Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiology, Biomarkers & Prevention 15, 1159–1169 (2006)

    Article  Google Scholar 

  6. Bakic, P.R., Carton, A.-K., Kontos, D., Zhang, C., Troxel, A.B., Maidment, A.D.A.: Breast percent density estimation from mammograms and central tomosynthesis projections. Radiology 252, 40–49 (2009)

    Article  Google Scholar 

  7. Kontos, D., Ikejimba, L., Bakic, P.R., Troxel, A.B., Conant, E.F., Maidment, A.D.A.: Digital breast tomosynthesis parenchymal texture analysis for breast cancer risk estimation: Results from a screening trial. Presented at 95th Scientific Assembly and Annual Meeting of the Radiological Society of North America, Chicago, IL (2009)

    Google Scholar 

  8. Kontos, D., Bakic, P.R., Carton, A.K., Troxel, A.B., Conant, E.F., Maidment, A.D.A.: Parenchymal texture analysis in digital breast tomosynthesis for breast cancer risk estimation: A preliminary study. Academic Radiology 16, 283–298 (2009)

    Article  Google Scholar 

  9. Bakic, P.R., Carton, A.K., Kontos, D., Zhang, C., Troxel, A.B., Maidment, A.D.: Breast percent density: estimation on digital mammograms and central tomosynthesis projections. Radiology 252, 40–49 (2009)

    Article  Google Scholar 

  10. Jeffreys, M., Warren, R., Highnam, R., Smith, G.D.: Initial experiences of using an automated volumetric measure of breast density: the standard mammogram form. Br. J. Radiol. 79, 378–382 (2006)

    Article  Google Scholar 

  11. Heine, J.J., Carston, M.J., Scott, C.G., Brandt, K.R., Wu, F.F., Pankratz, V.S., Sellers, T.A., Vachon, C.M.: An automated approach for estimation of breast density. Cancer Epidemiol Biomarkers Prev. 17, 3090–3097 (2008)

    Article  Google Scholar 

  12. van Engeland, S., Snoeren, P.R., Huisman, H., Boetes, C., Karssemeijer, N.: Volumetric breast density estimation from full-field digital mammograms. IEEE Trans. Med. Imaging 25, 273–282 (2006)

    Article  Google Scholar 

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Conant, E.F. et al. (2010). A Comparative Study of the Inter-reader Variability of Breast Percent Density Estimation in Digital Mammography: Potential Effect of Reader’s Training and Clinical Experience. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds) Digital Mammography. IWDM 2010. Lecture Notes in Computer Science, vol 6136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13666-5_16

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  • DOI: https://doi.org/10.1007/978-3-642-13666-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13665-8

  • Online ISBN: 978-3-642-13666-5

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