Application of Monte Carlo algorithms to cardiac imaging reconstruction

TL;DR

This paper reviews Monte Carlo algorithms for cardiac SPECT imaging, highlighting their ability to improve image quality by accurately modeling scattering effects, enabled by recent computational advancements.

Contribution

It provides a comprehensive overview of Monte Carlo methods for scattering correction in SPECT, emphasizing recent fast reconstruction techniques using high-performance computing.

Findings

Monte Carlo methods enable fast 3D cardiac SPECT reconstruction.

Recent computational advances allow scattering correction in seconds.

Monte Carlo approaches improve image quality over deterministic methods.

Abstract

Monte Carlo algorithms have a growing impact on nuclear medicine reconstruction processes. One of the main limitations of myocardial perfusion imaging (MPI) is the effective mitigation of the scattering component, which is particularly challenging in Single Photon Emission Computed Tomography (SPECT). In SPECT, no timing information can be retrieved to locate the primary source photons. Monte Carlo methods allow an event-by-event simulation of the scattering kinematics, which can be incorporated into a model of the imaging system response. This approach was adopted since the late Nineties by several authors, and recently took advantage of the increased computational power made available by high-performance CPUs and GPUs. These recent developments enable a fast image reconstruction with an improved image quality, compared to deterministic approaches. Deterministic approaches are based on energy-windowing of the detector response, and on the cumulative estimate and subtraction of the scattering component. In this paper, we review the main strategies and algorithms to correct for the scattering effect in SPECT and focus on Monte Carlo developments, which nowadays allow the three-dimensional reconstruction of SPECT cardiac images in a few seconds.