KEYWORDS: Breast, Monte Carlo methods, Sensors, Tissues, Digital breast tomosynthesis, Clinical trials, X-rays, 3D image processing, X-ray imaging, Breast imaging
In silico reproductions of clinical exams represent an alternative strategy in the research and development of medical devices, which permit to avoid issues and costs related to clinical trials on patient population. In this work, we present a platform for virtual clinical trials in 2D and 3D x-ray breast imaging. The platform, developed by the medical physics team at University of Naples, Italy, permits to simulate digital mammography (DM), digital breast tomosynthesis (DBT) and CT dedicated to the breast (BCT) examinations. It relies on Monte Carlo simulations based on Geant4 toolkit and adopts digital models of patients derived from high-resolution 3D clinical breast images acquired at UC Davis, USA. Uncompressed digital breast models for BCT exam simulations were produced by means of a tissue classification algorithm; the compressed digital breast models for simulating DM and DBT are derived by the uncompressed ones via a simulated tissue compression. For a selected exam, specifications and digital patient, the platform computes breast image projections and glandular dose maps within the organ. Energy integrating a well as photon counting and spectral imaging detection scheme have been simulated. The current version of the software uses the Geant4 standard physics list Option4 and simulates and tracks <105 photons/s, when run on a 16-core CPU at 3.0 GHz. The developed platform will be an invaluable tool for R and D of apparatuses, and it will permit the access to clinical-like data to a broad research community. Digital patient exposures with the available phantom dataset will be possible for the same patient-derived phantom in uncompressed or compressed format, in DM, DBT and BCT modalities.
We are developing a platform for virtual (in silico) clinical trials in x-ray breast imaging and dosimetry fully based on Monte Carlo simulations and which adopts patient-like digital phantoms. We report the initial steps and first results of this project. Our collaboration was established for producing a “user-friendly” computational platform which reproduces both 2D (full-fields digital mammography) and 3D (digital breast tomosynthesis, CT dedicated to the breast) breast imaging examinations for technique optimization and for developing protocols and computed aided diagnostic applications. Dose optimization strategies and technique performance comparisons will be explored. A dataset of anatomically realistic, 2D and 3D digital breast phantoms have been produced by means of voxel classification and digital compression of clinical breast CT scans acquired at UC Davis. Monte Carlo simulations, based on the Geant4 toolkit, have been developed for insilico FFDM, DBT and BCT examinations.
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