European Journal of Radiology
Volume 54, Issue 3 , Pages 371-376 , June 2005

DOSIS: a Monte Carlo simulation program for dose related studies in mammography

  • H. Delis

      Affiliations

    • Department of Medical Physics, School of Medicine, University of Patras, 26500 Patras, Greece
    • ,
  • G. Spyrou

      Affiliations

    • Department of Medical Physics, School of Medicine, University of Patras, 26500 Patras, Greece
    • Foundation of Biomedical Research, Academy of Athens, 11527 Athens, Greece
    • ,
  • G. Panayiotakis

      Affiliations

    • Department of Medical Physics, School of Medicine, University of Patras, 26500 Patras, Greece
    • ,
  • G. Tzanakos

      Affiliations

    • Department of Physics, Division of Nuclear and Particle Physics, University of Athens, 15771 Athens, Greece
    • Corresponding Author InformationCorresponding author. Tel.: +30 2107276938; fax: +30 21072676742.

Received 3 May 2004 ,Revised 27 July 2004 ,Accepted 29 July 2004.

References 

  1. Huda W, Sajewicz AM, Ogden KM, Dance DR. Experimental investigation of the dose and image quality characteristics of a digital mammography imaging system. Med Phys. 2003;30:442–448
  2. Dance DR, Thilander Klang A, Sandborg M, Skinner CL, Castellano Smith IA, Alm Carlsson G. Influence of anode/filter material and tube potential on contrast, signal to noise ratio and average absorbed dose in mammography: a Monte Carlo study. Br J Radiol. 2000;73:1056–1067
  3. Guibelable E, Fernadez JM, Vano E, Llorca A, Ruiz MJ. Image quality and patient dose for different screen-film combinations. Br J Radiol. 1994;67:166–173
  4. In:  Moores BM,  Wall BF,  Eriskat H,  Schibilla H editor. Optimization of Image Quality and Patient Exposure in Diagnostic Radiology. London: British Institute of Radiology, BIR Report 20; 1989;
  5. Brenner DJ. Enhanced risk from low-energy screen-film mammography X-rays. Br J Radiol. 1989;62:910–914
  6. Brenner DJ, Sawant SG, Hande MP, et al. Routine screening mammography: how important is the radiation-risk side of the benefit-risk equation?. Int J Radiat Biol. 2002;78:1065–1067
  7. Klein R, Aichinger H, Dierker J, et al. Determination of average glandular dose with modern mammographic units for two large groups of patients. Phys Med Biol. 1997;42:651–671
  8. Alm Carlsson G, Dance DR, Perlsiden J, Sandborg M. Use of the concept of the energy imparted in diagnostic radiology. Appl Radiat Isot. 1999;50:39–62
  9. Gkanatsios NA, Huda W. Computation of energy imparted in diagnostic radiology. Med Phys. 1997;24:571–579
  10. Zoetelief J, Jansen JTM. Calculation of air kerma to average glandular tissue dose conversion factors for mammography. Radiat Prot Dosimetry. 1995;57:397–400
  11. Dance DR. Monte Carlo calculation of conversion factors for the estimation of mean glandular breast dose. Phys Med Biol. 1990;35:1211–1219
  12. Dance DR, Skinner CL, Alm Carlsson G. Breast dosimetry. Appl Radiat Isot. 1990;50:185–203
  13. Doi K, Chan HP. Evaluation of absorbed dose in mammography: Monte Carlo simulation studies. Radiology. 1980;135:199–208
  14. Kulkarni RN, Supe SJ. Radiation dose to the breast during mammography: a comprehensive, realistic Monte Carlo calculation. Phys Med Biol. 1984;29:1257–1264
  15. Spyrou G, Tzanakos G, Bakas A, Panayiotakis G. Monte Carlo simulated mammograms: development and validation. Phys Med Biol. 1998;43:3341–3357
  16. Spyrou G, Panayiotakis G, Tzanakos G. MASTOS: mammography simulation tool for design optimization studies. Med Inform Internet Med. 2000;25:275–293
  17. Spyrou G, Tzanakos G, Nikiforides G, Panayiotakis G. A Monte Carlo simulation model of mammographic imaging with X-ray sources of finite dimensions. Phys Med Biol. 2002;47:917–933
  18. Peplow DE, Verghese K. Digital mammography image simulation using Monte Carlo. Med Phys. 2000;27:568–579
  19. Jansen JTM, Zoetelief J. Optimisation of mammographic breast cancer screening using a computer simulation model. Eur J Radiol. 1997;24(2):137–144
  20. Delis H, Spyrou G, Tzanakos G, Panayiotakis G. The influence of mammographic X-ray spectra on absorbed energy distribution in breast: Monte Carlo simulation studies. Radiat Meas (in press).
  21. Birch R, Marshall M, Ardran GM. Catalogue of Spectral Data for Diagnostic X-rays. London: The Hospital Physicists’ Association; 1979;
  22. Fewell TR, Shuping RE . Handbook of Mammographic X-ray Spectra. Springfield: HEW Publication (FDA) 79 (8071), NTIS; 1978;
  23. Boone JM, Seibert A . An accurate method for computer-generating tungsten anode X-ray spectra from 30 to 140kV. Med Phys. 1997;24(11):1661–1670
  24. Boone JM, Thomas R, Fewell TR, Robert J, Jennings RJ. Molybdenum, rhodium, and tungsten anode spectral models using interpolating polynomials with application to mammography. Med Phys. 1997;24(12):1863–1874
  25. Wachsmann F, Drexler G. Graphs and Tables for Use in Radiology. Springer-Verlag; 1976;
  26. Jansen JTM, de Wit NJP, Zoetelief J. Comparison of measured and calculated in-phantom depth-dose distributions for mammography. Radiat Prot Dosimetry. 1992;43:245–249

PII: S0720-048X(04)00272-4

doi: 10.1016/j.ejrad.2004.07.014

European Journal of Radiology
Volume 54, Issue 3 , Pages 371-376 , June 2005

Article Tools

* Image Usage & Resolution