The Simulation System for Emission Tomography (SimSET) is one of the foundational tools for emission tomography research, used by hundreds of researchers worldwide for both positron emission tomography (PET) and single photon emission computed tomography (SPECT). It has proven to be accurate and efficient for both PET and low energy SPECT studies; because SimSET uses a geometric model for its SPECT collimation, it is less accurate for high energy isotopes. This application proposes to address this with the use of angular response functions (ARFs), a technique that has proven to accurately model SPECT collimation and detection for high-energy isotopes more efficiently than full photon-tracking simulations. In addition, we propose a novel ARF-based importance sampling method that will speed these simulations by a factor of >50. The generation of ARF tables is another consideration: it is extremely compute intensive and has caused ARF to be used only when a large number of simulations are needed using the same isotope/collimator/detector combination. For this reason, we also propose application of importance sampling to speed the generation of ARF tables by a factor 5, and the creation of a library of angular response functions for popular isotope/collimator/detector combinations. The former will lessen the computational cost of generating the tables, the latter will, for many users/uses, eliminate the need to generate ARF tables at all. This will greatly expand the potential applications of ARF-based simulations.
Our first aim i s to accelerate SimSET SPECT simulations without sacrificing accuracy. This will be accomplished by synergistically utilizing two tools: variance reduction and angular response function (ARF) tables. Variance reduction includes importance sampling and forced detection. We hypothesis that these techniques combined with information from our angular response function tables will improve SimSET simulation efficiency by >50 times of SPECT simulations of specific radioisotopes (e.g., I-123, Y-90, etc.).
Our second aim i s to accelerate ARF table generation. This will be accomplished by using importance sampling methods in the generation of ARFs. We further propose to use an adaptive stratification scheme that will simulate photons for a given table position only as long as required to determine its value to a user-specified precision.
Our third aim i s to create a library of pre-calculated ARF tables for popular vendor isotope/collimator/detector configurations. These ARF tables will then be made publically available for download through the SimSET website. With a registered user base of >500, we believe that these enhancements to SimSET will have far reaching impact on research projects throughout the world.

Public Health Relevance

The overall goal of this work is to develop methods to speed up the SimSET Monte Carlo-based simulation software for single photon computed tomography (SPECT) imaging systems by greater than 50-fold. This type of speed up with enable new research that was previously impractical due to the computation time required for simulation. In addition, all software tools and tables developed within this project will be made available via a web-based host.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Small Research Grants (R03)
Project #
Application #
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Zubal, Ihor George
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Washington
Schools of Medicine
United States
Zip Code