VALIDATION OF A SIMULATION PROCEDURE FOR GENERATING BREAST TOMOSYNTHESIS PROJECTION IMAGES.

In order to achieve optimal diagnostic performance in breast tomosynthesis (BT) imaging, the parameters of the imaging chain should be evaluated. For the purpose of such evaluations, a simulation procedure based on the Monte Carlo code system Penelope and the geometry of a Siemens BT system has been developed to generate BT projection images. In this work, the simulation procedure is validated by comparing contrast and sharpness in simulated images with contrast and sharpness in real images acquired with the BT system. The results of the study showed a good agreement of sharpness in real and simulated reconstructed image planes, but the contrast was shown to be higher in the simulated compared with the real projection images. The developed simulation procedure could be used to generate BT images, but it is of interest to further investigate how the procedure could be modified to generate more realistic image noise and contrast.

[1]  John M. Boone.  Spectral modeling and compilation of quantum fluence in radiography and mammography , 1998, Medical Imaging.

[2]  D R Dance,et al.  Validation of simulation of calcifications for observer studies in digital mammography , 2013, Physics in medicine and biology.

[3]  J. Sempau,et al.  PENELOPE-2006: A Code System for Monte Carlo Simulation of Electron and Photon Transport , 2009 .

[4]  Hilde Bosmans,et al.  Simulation of image detectors in radiology for determination of scatter-to-primary ratios using Monte Carlo radiation transport code MCNP/MCNPX. , 2010, Medical physics.

[5]  Kenneth C. Young,et al.  Predicting contrast detail performance from objective measurements in digital mammography , 2009, Medical Imaging.

[6]  J. Sempau,et al.  Experimental benchmarks of the Monte Carlo code penelope , 2003 .

[7]  Nassir Navab,et al.  Out-of-Plane Artifact Reduction in Tomosynthesis Based on Regression Modeling and Outlier Detection , 2012, Digital Mammography / IWDM.

[8]  Magnus Båth,et al.  Simulation of dose reduction in tomosynthesis. , 2009, Medical physics.

[9]  Francesc Salvat,et al.  Monte Carlo simulation of x-ray spectra generated by kilo-electron-volt electrons , 2003 .

[10]  Thomas Mertelmeier,et al.  Adaptation of Image Quality Using Various Filter Setups in the Filtered Backprojection Approach for Digital Breast Tomosynthesis , 2006, Digital Mammography / IWDM.

[11]  J. Sempau,et al.  A PENELOPE-based system for the automated Monte Carlo simulation of clinacs and voxelized geometries-application to far-from-axis fields. , 2011, Medical physics.

[12]  Anders Tingberg,et al.  Digital mammography and tomosynthesis for breast cancer diagnosis. , 2011, Expert opinion on medical diagnostics.

[13]  Thomas Mertelmeier,et al.  Optimizing High Resolution Reconstruction in Digital Breast Tomosynthesis Using Filtered Back Projection , 2014, Digital Mammography / IWDM.

[14]  Hilde Bosmans,et al.  Development and validation of a modelling framework for simulating 2D-mammography and breast tomosynthesis images , 2014, Physics in medicine and biology.

[15]  Thomas Mertelmeier,et al.  Optimizing filtered backprojection reconstruction for a breast tomosynthesis prototype device , 2006, SPIE Medical Imaging.

[16]  Vera Sídlová,et al.  Testing Monte Carlo computer codes for simulations of electron transport in matter. , 2010, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

[17]  Günter Lauritsch,et al.  Theoretical framework for filtered back projection in tomosynthesis , 1998, Medical Imaging.