Efficient Monte-Carlo based system modelling for image reconstruction in preclinical pinhole SPECT

Area of Science:

• Nuclear medicine
• Medical imaging physics
• Small animal imaging

Background:

• Ultra-high-resolution imaging in small animals relies on multi-pinhole collimation for SPECT and PET.
• Accurate statistical iterative image reconstruction requires precise energy-dependent photon transport modeling through collimators and detectors.
• System matrices, representing photon detection probabilities, are crucial for high-quality image reconstruction.

Purpose of the Study:

• To introduce a novel Fast Monte Carlo (FMC)-based method for generating system matrices for pinhole imaging.
• To evaluate the FMC method's applicability to various radionuclides and collimator types.
• To compare the performance of FMC-generated matrices against traditional and ray-tracing methods.

Main Methods:

• Developed an FMC-based matrix generation method using accelerated point source simulations and model-based interpolation.
• Applied the method to a VECTor PET-SPECT system with HE-UHR-M and EXIRAD-3D collimators.
• Evaluated using experimental data (99mTc, 111In, 123I) and simulations (67Ga, 90Y), comparing with traditional and ray-tracing matrices.

Main Results:

• FMC-based matrices yielded superior image quality compared to traditional and ray-tracing matrices in several cases.
• FMC matrices demonstrated better generalization for radionuclides with energies deviating from calibration.
• FMC matrices were computationally more efficient for very-high-resolution imaging than ray-tracing matrices.

Conclusions:

• The FMC method is an efficient, accurate, and versatile tool for creating system matrices for ultra-high-resolution pinhole SPECT.
• FMC facilitates easy energy combination in matrices, beneficial for radionuclides with multiple photopeaks or continuous energy spectra.
• The proposed method enhances the quality and applicability of small animal SPECT and PET imaging.