Comparative evaluation of scatter correction in 3D PET using different scatter-level approximations
Manjeshwar, Ravindra M.
Marsden, Paul K.
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Objective: In 3D PET, scatter of the gamma photons is one of the most significant physical factors which degrades not only image quality but also quantification. The currently most used scatter estimation method is the analytic single scatter simulation (SSS) which usually accommodates for multiple scattering by scaling the single scatter estimation. However, it has not been clear yet how accurate this approximation is for cases where multiple scatter is significant, raising the question: "How important is correction for multiple scattered photons, and how accurately do we need to simulate all scattered events by appropriate scaling?" This study answers these questions and evaluates the accuracy of SSS implementation in the open-source library STIR. Methods: Different scatter orders approximations are evaluated including different levels of scattering and different scaling approaches using Monte Carlo (i.e. SimSET) data. SimSET simulations of a large anthropomorphic phantom were reconstructed with iterative reconstruction algorithms. Images reconstructed with 3D filtered back-projection reprojection algorithm have been compared quantitatively in order to clarify the errors due to different scatter order approximations. Results: Quantification in regions has improved by scatter correction. For example, in the heart the ideal value was 3, whereas before scatter correction the standard uptake value (SUV) was 4.0, after single scatter correction was 3.3 and after single and double scatter correction was 3.0. After correction by scaling single scatter with tail-fit, the SUV was 3.1, whereas with total-fit it was 3.0. Similarly, for the SSS correction methodology implemented in STIR using tail-fit the heart SUV was 3.1 whereas using total-fit it was 3.0. Conclusions: The results demonstrate that correction for double scatter improves image contrast and therefore it is required for the accurate estimation of activity distribution in PET imaging. However, it has been also shown that scaling the single scatter distribution is a reasonable approximation to compensate for total scatter. Finally, scatter correction with STIR has shown excellent agreement with Monte Carlo simulations.