바로가기  >

Abstract
Objective. The TOol for PArticle Simulation (TOPAS) is a Geant4-based Monte Carlo software application that has been used for both research and clinical studies in medical physics. So far, most users of TOPAS have focused on radiotherapy-related studies, such as modeling radiation therapy delivery systems or patient dose calculation. Here, we present the first set of TOPAS extensions to make it easier for TOPAS users to model medical imaging systems.Approach. We used the extension system of TOPAS to implement pre-built, user-configurable geometry components such as detectors (e.g. flat-panel and multi-planar detectors) for various imaging modalities and pre-built, user-configurable scorers for medical imaging systems (e.g. digitizer chain).Main results. We developed a flexible set of extensions that can be adapted to solve research questions for a variety of imaging modalities. We then utilized these extensions to model specific examples of cone-beam CT (CBCT), positron emission tomography (PET), and prompt gamma (PG) systems. The first of these new geometry components, the FlatImager, was used to model example CBCT and PG systems. Detected signals were accumulated in each detector pixel to obtain the intensity of x-rays penetrating objects or prompt gammas from proton-nuclear interaction. The second of these new geometry components, the RingImager, was used to model an example PET system. Positron-electron annihilation signals were recorded in crystals of the RingImager and coincidences were detected. The simulated data were processed using corresponding post-processing algorithms for each modality and obtained results in good agreement with the expected true signals or experimental measurement.Significance. The newly developed extension is a first step to making it easier for TOPAS users to build and simulate medical imaging systems. Together with existing TOPAS tools, this extension can help integrate medical imaging systems with radiotherapy simulations for image-guided radiotherapy.

Affiliations

Hoyeon Lee 1, Bo-Wi Cheon 2, Joseph W Feld 3, Kira Grogg 4, Joseph Perl 5, José A Ramos-Méndez 6, Bruce Faddegon 6, Chul Hee Min 2, Harald Paganetti 1, Jan Schuemann 1
1Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States of America.
2Department of Radiation Convergence Engineering, Yonsei University, Wonju, Gangwon-do 26493, Republic of Korea.
3Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America.
4The Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States of America.
5SLAC National Accelerator Laboratory, Menlo Park, CA 94025 United States of America.
6Department of Radiation Oncology, University of California San Francisco, San Francisco, CA 94115 United States of America.