GEANT4 Monte Carlo simulations for virtual clinical trials in breast X-ray imaging: Proof of concept

F. di Franco, A. Sarno, G. Mettivier, A. M. Hernandez, K. Bliznakova, J. M. Boone, P. Russo

Research output: Contribution to journalArticle

Abstract

Virtual clinical trials (VCT) are in-silico reproductions of medical examinations, which adopt digital models of patients and simulated devices. They are intended to produce clinically equivalent outcome data avoiding long execution times, ethical issues related to radiation induced risks and huge costs related to real clinical trials with a patient population. In this work, we present a platform for VCT in 2D and 3D X-ray breast imaging. The VCT platform uses Monte Carlo simulations based on the Geant4 toolkit and patient breast models derived from a cohort of high resolution dedicated breast CT (BCT) volume data sets. Projection images of the breast and three-dimensional glandular dose maps are generated for a given breast model, by simulating both 2D full-field digital mammography (DM) and 3D BCT examinations. Uncompressed voxelized breast models were derived from segmented patient images. Compressed versions of the digital breast phantoms for DM were generated using a previously published digital compression algorithm. The Monte Carlo simulation framework has the capability of generating and tracking ~105 photons/s using a server equipped with 16-cores and 3.0 GHz clock speed. The VCT platform will provide a framework for scanner design optimization, comparison between different scanner designs and between different modalities or protocols on computational breast models, without the need for scanning actual patients as in conventional clinical trials.

Original languageEnglish (US)
Pages (from-to)133-142
Number of pages10
JournalPhysica Medica
Volume74
DOIs
StatePublished - Jun 2020

Keywords

  • Monte Carlo
  • Patient-derived breast phantoms
  • Virtual clinical trials
  • X-ray breast imaging

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Physics and Astronomy(all)

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