Click here to

Session: Imaging General ePoster Viewing [Return to Session]

TOPAS for Imaging: A Monte Carlo Simulation Tool for PET/SPECT/CBCT Imaging

J Feld1*, C Zhang2, G Cojocaru3, S Longawa4, H Paganetti5, J Schuemann6, (1) Mass General Hospital and Massachusetts Institute of Technology, ,,(2) Mass General Hospital And Boston University, ,,(3) Mass General Hospital And Massachusetts Institute Of Technology, ,,(4) Mass General Hospital And Massachusetts Institute Of Technology, ,,(5) Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA, Boston, MA, (6) Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA, Boston, MA

Presentations

PO-GePV-I-20 (Sunday, 7/25/2021)   [Eastern Time (GMT-4)]

Purpose: To develop an extension of medical imaging devices for the TOPAS Monte Carlo (MC) system

Methods: MC methods have been extensively used to simulate imaging systems, but there have so far been no examples for the TOPAS MC. We designed easily modifiable classes for the detector geometries, sources, and scorers in PET, SPECT, and CBCT systems. The output file is scored in CASToR (Customizable and Advanced Software for Tomographic Reconstruction) format that can directly be processed for image reconstruction using CASToR.

Results: We developed TOPAS for Imaging, an extension of TOPAS designed to generate the geometries of PET, SPECT, and CBCT and record their measurements of simulated radioactive sources for reconstruction in CASToR. First comparisons to experimental data for validating the PET system will be presented.

Conclusion: TOPAS for Imaging promises to advance our understanding of imaging systems by enabling researchers to have more platforms for simulating their systems.

Funding Support, Disclosures, and Conflict of Interest: This project was funded by the AAPM, MIT, and NIH.

ePosters

    Keywords

    Monte Carlo, Tomography, Simulation

    Taxonomy

    IM- PET : Monte Carlo Modeling

    Contact Email

    Share: