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Extending gPET for Multi-Layer PET Simulation

Satzhan Sitmukhambetov, Junwei Du, Mingwu Jin, Yujie Chi

TL;DR

The GPU-accelerated Monte Carlo toolkit gPET is extended to support flexible multi-layer PET detectors and supports efficient optimization of DOI-enabled PET system designs.

Abstract

Depth-of-interaction (DOI) encoding is an effective strategy for reducing parallax error and preserving spatial resolution in positron emission tomography (PET), particularly in compact small-animal scanners. To enable efficient simulation-driven design of DOI-capable systems, we extend the GPU-accelerated Monte Carlo toolkit gPET to support flexible multi-layer detector geometries. The original three-level hierarchical detector model in gPET (panel-module-crystal) was expanded by introducing an intermediate "layer" level, enabling parameterized modeling of stacked scintillator architectures. The photon transport algorithm was correspondingly updated to sample interactions across multiple layers and detector panels while preserving GPU-efficient memory usage. The framework was validated using three scanner configurations: a conventional single-layer ring (H2RSPET-1CL), an aligned split-layer design (H2RSPET-1CL-split), and an offset dual-layer design (H2RSPET-2CL). System performance was evaluated following NEMA NU4-2008 protocols using sensitivity, spatial resolution, and Derenzo phantom simulations with CASToR-based maximum likelihood expectation maximization reconstruction. The H2RSPET-1CL and H2RSPET-1CL-split configurations produced statistically identical hit distributions, while H2RSPET-2CL exhibited the expected offset interaction patterns. Sensitivity of H2RSPET-2CL remained comparable to H2RSPET-1CL, generally within about 2-5 percent, while radial spatial resolution improved substantially (0.8-1.6 mm vs. 1.0-4.2 mm from the center to a 50 mm radial offset). Runtime performance remained essentially unchanged between configurations. The extended gPET framework therefore enables fast and flexible simulation of multi-layer PET detectors and supports efficient optimization of DOI-enabled PET system designs.

Extending gPET for Multi-Layer PET Simulation

TL;DR

The GPU-accelerated Monte Carlo toolkit gPET is extended to support flexible multi-layer PET detectors and supports efficient optimization of DOI-enabled PET system designs.

Abstract

Depth-of-interaction (DOI) encoding is an effective strategy for reducing parallax error and preserving spatial resolution in positron emission tomography (PET), particularly in compact small-animal scanners. To enable efficient simulation-driven design of DOI-capable systems, we extend the GPU-accelerated Monte Carlo toolkit gPET to support flexible multi-layer detector geometries. The original three-level hierarchical detector model in gPET (panel-module-crystal) was expanded by introducing an intermediate "layer" level, enabling parameterized modeling of stacked scintillator architectures. The photon transport algorithm was correspondingly updated to sample interactions across multiple layers and detector panels while preserving GPU-efficient memory usage. The framework was validated using three scanner configurations: a conventional single-layer ring (H2RSPET-1CL), an aligned split-layer design (H2RSPET-1CL-split), and an offset dual-layer design (H2RSPET-2CL). System performance was evaluated following NEMA NU4-2008 protocols using sensitivity, spatial resolution, and Derenzo phantom simulations with CASToR-based maximum likelihood expectation maximization reconstruction. The H2RSPET-1CL and H2RSPET-1CL-split configurations produced statistically identical hit distributions, while H2RSPET-2CL exhibited the expected offset interaction patterns. Sensitivity of H2RSPET-2CL remained comparable to H2RSPET-1CL, generally within about 2-5 percent, while radial spatial resolution improved substantially (0.8-1.6 mm vs. 1.0-4.2 mm from the center to a 50 mm radial offset). Runtime performance remained essentially unchanged between configurations. The extended gPET framework therefore enables fast and flexible simulation of multi-layer PET detectors and supports efficient optimization of DOI-enabled PET system designs.
Paper Structure (12 sections, 8 figures, 1 table)

This paper contains 12 sections, 8 figures, 1 table.

Table of Contents

  1. Introduction
  2. Methods
  3. Extension of gPET for multi-layer PET detector simulation
  4. Configurations to validate gPET extension
  5. Performance evaluation for single-layer and two-layer configurations
  6. Computational Performance
  7. Results
  8. Validation of gPET multi-layer extension
  9. Performance evaluation for single-layer and two-layer configurations
  10. Computational Performance
  11. Discussion
  12. Conclusion

Figures (8)

  • Figure 1: Illustration of the extended hierarchical description of a PET detector. Compared with the original three-level geometry used in gPET (panel, module, crystal)Lai2019gPET, the extended framework introduces a new layer level between the module and crystal for a four-level hierarchy: panel (level 0, highest), module (level 1), layer (level 2), and individual crystal (level 3, lowest).
  • Figure 2: Geometry illustration of (a) H2RSPET-1CL PET and (b) H2RSPET-2CL PET. The two scanners have the same diameter, axial length, and pitch size, except H2RSPET-2CL PET is a two-layer design with a half-pitch offset between the two layers.
  • Figure 3: Histogram of hit depth events in the H2RSPET detectors: (left) H2RSPET-1CL versus H2RSPET-1CL-split, and (right) H2RSPET-1CL versus H2RSPET-2CL. The $x$-axis (cm) denotes the depth of interaction (DOI) in the panel's local coordinate frame.
  • Figure 4: Scatter plot within panel's $x$ and $y$ view for a1) the H2RSPET-1CL split-layer configuration and a2) the H2RSPET-2CL scanner. b) Axial distributions of hit events along the global $z$ direction for H2RSPET-1CL and H2RSPET-2CL with a central point source.
  • Figure 5: Sensitivity profiles and percent differences for H2RSPET-1CL and H2RSPET-2CL scanner configurations along (a) axial and (b) radial directions.
  • ...and 3 more figures