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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Nucl Med. Author manuscript; available in PMC 2010 December 8.
Published in final edited form as:
PMCID: PMC2999359
NIHMSID: NIHMS100130

Modeling block detectors in SimSET

Abstract

Objectives

We have added a block detector model to the Simulation System for Emission Tomography (SimSET) software version 2.9.

Methods

The new model simulates the detector system as a collection of right rectangular boxes and allows for very flexible positioning of these boxes. This model allows users to simulate typical block-based cylindrical tomographs, pixelated positron emission mammography (PEM) detectors, and many more imaginative tomograph designs. We have tested the block detector software against analytically derived results and against SimSET simulations of dual-headed and cylindrical detector tomographs. We have also compared experimental and simulated sensitivities for a General Electric DSTE PET for 3 different phantom diameters in 2d and 3d acquisition modes.

Results

The tests against analytically derived results and against simulations were validated both statistically using the t-test and visually by comparing profiles through the sinograms. Within the limits of statistical fluctuation, the new software passed all tests. In comparisons with data from the PET scanner, the simulation showed better agreement than previous SimSET releases, but still showed substantially increased coincidence sensitivity.

Conclusions

We believe the increased sensitivity is a result of the very simple default models used for energy resolution and scintillation light collection, and the lack of any livetime correction. The new release provides a user-modifiable function where all these factors can be realistically modeled for a given tomograph. The SimSET software, including source code, remains in the public domain.

Acknowledgments

Research Support: This work was supported in part by the U.S. Public Health Service under Grants No. CA42593 and CA126593.