MCGPU-PET: An Open-Source Real-Time Monte Carlo PET Simulator.

Monte Carlo (MC) simulations are commonly used to model the emission, transmission, and/or detection of radiation in Positron Emission Tomography (PET). In this work, we introduce a new open-source MC software for PET simulation, MCGPU-PET, which has been designed to fully exploit the computing capabilities of modern GPUs to simulate the acquisition of more than 100 million coincidences per second from voxelized sources and material distributions. The new simulator is an extension of the PENELOPE-based MCGPU code previously used in cone-beam CT and mammography applications. We validated the accuracy of the accelerated code by comparing it to GATE and PeneloPET simulations achieving an agreement within 10 percent approximately. As an example application of the code for fast estimation of PET coincidences, a scan of the NEMA IQ phantom was simulated. A fully 3D sinogram with 6382 million true coincidences and 731 million scatter coincidences was generated in 54 seconds in one GPU. MCGPU-PET provides an estimation of true and scatter coincidences and spurious background (for positron-gamma emitters such as 124I) at a rate 3 orders of magnitude faster than CPU-based MC simulators. This significant speed-up enables the use of the code for accurate scatter and prompt-gamma background estimations within an iterative image reconstruction process.

Simultaneous quantitative imaging of two PET radiotracers via the detection of positron-electron annihilation and prompt gamma emissions.

In conventional positron emission tomography (PET), only one radiotracer can be imaged at a time, because all PET isotopes produce the same two 511 keV annihilation photons. Here we describe an image reconstruction method for the simultaneous in vivo imaging of two PET tracers and thereby the independent quantification of two molecular signals. This method of multiplexed PET imaging leverages the 350-700 keV range to maximize the capture of 511 keV annihilation photons and prompt γ-ray emission in the same energy window, hence eliminating the need for energy discrimination during reconstruction or for signal separation beforehand. We used multiplexed PET to track, in mice with subcutaneous tumours, the biodistributions of intravenously injected [124I]I-trametinib and 2-deoxy-2-[18F]fluoro-D-glucose, [124I]I-trametinib and its nanoparticle carrier [89Zr]Zr-ferumoxytol, and the prostate-specific membrane antigen (PSMA) and infused PSMA-targeted chimaeric antigen receptor T cells after the systemic administration of [68Ga]Ga-PSMA-11 and [124I]I. Multiplexed PET provides more information depth, gives new uses to prompt γ-ray-emitting isotopes, reduces radiation burden by omitting the need for an additional computed-tomography scan and can be implemented on preclinical and clinical systems without any modifications in hardware or image acquisition software.

A detector block-pairwise dead time correction method for improved quantitation with a dedicated BrainPET scanner.

'Objective. Dead time correction (DTC) is an important factor in ensuring accurate quantification in PET measurements. This is currently often achieved using a global DTC method, i.e., an average DTC factor is computed. For PET scanners designed to image dedicated organs, e.g., those used in brain imaging or positron emission mammography (PEM), a substantial amount of the administered radioactivity is located outside of the PET field-of-view (FOV). This activity contributes to the dead time (DT) of the scintillation detectors. Moreover, the count rates of the individual scintillation detectors are potentially very inhomogeneous due to the specific irradiation of each detector, especially for combined MR/PET systems, where radiation shields cannot be applied. Approach: We have developed a block-pairwise DTC method for our Siemens 3T MR BrainPET insert by extending a previously published method that uses the delayed random coincidence count rate to estimate the DT in the individual scans and planes (i.e., scintillation pixel rings). The method was validated in decay experiments using phantoms with a homogenous activity concentration and with and without out-of-FOV activity. Based on a three-compartment phantom, we compared the accuracy and noise properties of the block-pairwise DTC and the global DTC method.Main results. The currently used global DTC led to a substantial positive bias in regions with high activity; the block-pairwise DTC resulted in substantially less bias. The noise level for the block-pairwise DTC was comparable to the global DTC and image reconstructions without any DTC. Finally, we tested the block-pairwise DTC with a data set obtained from volunteer measurements using the mGluR5 (metabotropic glutamate receptor subtype 5) antagonist [11C]ABP688. When the relative differences in activity concentrations obtained with global DTC and block-pairwise DTC for the ACC and the cerebellum GM were compared, the ratios differed by a factor of up to 1.4 at the beginning-when the first injection is administered as a bolus with high radioactivity.Significance. In this work, global DTC was shown to have the potential to introduce quantification bias, while better quantitation accuracy was achieved with the presented block-pairwise DTC method. The method can be implemented in all systems that use the delayed window technique and is particulary expected to improve the quantiation accuracy of dedicated brain PET scanners due to their geometry.'

Positron range in combination with point-spread-function correction: an evaluation of different implementations for [124I]-PET imaging.

AIM: To evaluate the effect of combining positron range correction (PRC) with point-spread-function (PSF) correction and to compare different methods of implementation into iterative image reconstruction for 124I-PET imaging. MATERIALS AND METHODS: Uniform PR blurring kernels of 124I were generated using the GATE (GEANT4) framework in various material environments (lung, water, and bone) and matched to a 3D matrix. The kernels size was set to 11 × 11 × 11 based on the maximum PR in water and the voxel size of the PET system. PET image reconstruction was performed using the standard OSEM algorithm, OSEM with PRC implemented before the forward projection (OSEM+PRC simplified) and OSEM with PRC implemented in both forward- and back-projection steps (full implementation) (OSEM+PRC). Reconstructions were repeated with resolution recovery, point-spread function (PSF) included. The methods and kernel variation were validated using different phantoms filled with 124I acquired on a Siemens mCT PET/CT system. The data was evaluated for contrast recovery and image noise. RESULTS: Contrast recovery improved by 2-10% and 4-37% with OSEM+PRC simplified and OSEM+PRC, respectively, depending on the sphere size of the NEMA IQ phantom. Including PSF in the reconstructions further improved contrast by 4-19% and 3-16% with the PSF+PRC simplified and PSF+PRC, respectively. The benefit of PRC was more pronounced within low-density material. OSEM-PRC and OSEM-PSF as well as OSEM-PSF+PRC in its full- and simplified implementation showed comparable noise and convergence. OSEM-PRC simplified showed comparably faster convergence but at the cost of increased image noise. CONCLUSIONS: The combination of the PSF and PRC leads to increased contrast recovery with reduced image noise compared to stand-alone PSF or PRC reconstruction. For OSEM-PRC reconstructions, a full implementation in the reconstruction is necessary to handle image noise. For the combination of PRC with PSF, a simplified PRC implementation can be used to reduce reconstruction times.