GPU-based SPECT Reconstruction Using Reverse Monte Carlo Simulations

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Project Summary/Abstract Interest in applications of radiopharmaceutical conjugates has notably increased in the last few years for the treatment of a variety of cancers. These conjugates are composed of chelators to target cancer cells and radionuclides to employ the cytotoxicity of ionizing radiation. Radiation dosimetry is required to determine the dosages, efficacy, and safety of these treatments, and 3D quantitative imaging of the biodistribution of activity represents the best tool to perform dosimetry. For most radionuclides employed (non-positron-emitters), SPECT imaging is needed for patient-specific dosimetry. However, multiple physical factors affect SPECT image quality, such as attenuation, scattering, or the response collimator-detector system in SPECT scans. To account for them, Monte Carlo techniques can be used due to their remarkable accuracy in representing physical processes relevant to the transport of ionizing radiation. In particular, 3D SPECT reconstruction from the acquired bidimensional projections may be obtained by transporting backward the photons detected in the gamma camera projections, although many photons to be reversely transported require specially optimized architecture and simulations. This project will develop a new reverse Monte Carlo software for SPECT reconstruction, built from scratch in the GPU to speed up simulations. First, only the relevant reverse physical processes will be selected and modeled using inverse processes of the well-characterized TOPAS Monte Carlo code for radiation transport. Then, specific properties of collimator-detector systems will be integrated into our code to determine the angular distributions for the photons detected. Finally, these developments will be integrated into a GPU-based platform and shared with the Informatics Technology for Cancer Research program at NCI for further results of specific commercial SPECT scans from the research community.