Implementation and validation of time-of-flight PET image reconstruction module for listmode and sinogram projection data in the STIR library

Nikos Efthimiou,Palak Wadhwa,Kris Thielemans,Christopher Cawthorne,Charalampos Tsoumpas,Elise Emond

doi:10.1088/1361-6560/aaf9b9

Abstract

In this paper, we describe the implementation of support for time-of-flight (TOF) positron emission tomography (PET) for both listmode and sinogram data in the open source software for tomographic image reconstruction (STIR). We provide validation and performance characterization using simulated data from the open source GATE Monte Carlo toolbox, with TOF configurations spanning from 81.2 to 209.6 ps. The coincidence detector resolution was corrected for the timing resolution deterioration due to the contribution of the crystal length. Comparison between the reconstruction of listmode and sinogram data demonstrated good agreement in both TOF and non-TOF cases in terms of relative absolute error. To reduce the reconstruction time, we assessed the truncation of the TOF kernel along lines-of-response (LOR). Rejection of LOR elements beyond four times the TOF standard deviation provides significant acceleration of without compromising the image quality. Further narrowing of the kernel can provide extra time reduction but with the gradual introduction of error in the reconstructed images. As expected, TOF reconstruction performs better than non-TOF in terms of both contrast-recovery-coefficient (CRC) and signal-to-noise ratio (SNR). CRC achieves convergence faster with TOF, at lower noise levels. SNR with TOF was superior for early iterations, but with quick deterioration. Higher timing resolution further improved reconstruction performance, while TOF bin mashing was shown to have only a small impact on reconstructed images.

Highlights

Until relatively recently, positron emission tomography (PET) detectors on commercially available PET scanners had a timing resolution of a few nanoseconds
In this paper we present the introduction of TOF reconstruction in the software for tomographic image reconstruction (STIR) library and the corresponding validation and performance evaluation through GATE Monte Carlo (MC) simulations (Jan et al 2004)
Aside from convergence issues, a potential cause is the slight mismatch between the actual the photon detection time spread function and the Gaussian model used in the reconstruction (Efthimiou et al 2018)

Summary

Introduction

PET detectors on commercially available PET scanners had a timing resolution of a few nanoseconds. Early experimental PET scanners had TOF capabilities by using barium fluoride (BaF) scintillators (Laval et al 1983), these crystals had low stopping-power and the photo-detector technology and speed of the acquisition electronics were not developed sufficiently for stable operation. In the early 2000s, the introduction of lutetium oxyorthosilicate (LSO) and lutetium-yttrium oxyorthosilicate (LYSO) scintillation crystals with high light output, good stopping power and fast responses revitalized TOF as an area of interest (Melcher and Schweitzer 1992, Moses and Derenzo 1999, Popescu et al 2004). The first generation TOF-capable clinical scanners had a coincidence timing resolution of around 600 ps (Moses 2003), with recent systems using silicon photomulipliers (SiPM) detectors achieving 250–350 ps (Surti et al 2007, Grant et al 2016) Time-of-flight (TOF) capable scanners measure the temporal difference in the γ-photon detection with sufficient accuracy to provide an indirect measurement of the most likely location of the annihilation, thereby increasing the signal-to-noise ratio (SNR) (Nemallapudi et al 2015, Dujardin et al 2018).

Methods

Results

Conclusion