Recovery and normalization of triple coincidences in PET

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.

Hybrid PET/Compton-camera imaging: an imager for the next generation

Compton cameras can offer advantages over gamma cameras for some applications, since they are well suited for multitracer imaging and for imaging high-energy radiotracers, such as those employed in radionuclide therapy. While in conventional clinical settings state-of-the-art Compton cameras cannot compete with well-established methods such as PET and SPECT, there are specific scenarios in which they can constitute an advantageous alternative. The combination of PET and Compton imaging can benefit from the improved resolution and sensitivity of current PET technology and, at the same time, overcome PET limitations in the use of multiple radiotracers. Such a system can provide simultaneous assessment of different radiotracers under identical conditions and reduce errors associated with physical factors that can change between acquisitions. Advances are being made both in instrumentation developments combining PET and Compton cameras for multimodal or three-gamma imaging systems, and in image reconstruction, addressing the challenges imposed by the combination of the two modalities or the new techniques. This review article summarizes the advances made in Compton cameras for medical imaging and their combination with PET.

Advances in Preclinical PET

The classical intent of PET imaging is to obtain the most accurate estimate of the amount of positron-emitting radiotracer in the smallest possible volume element located anywhere in the imaging subject at any time using the least amount of radioactivity. Reaching this goal, however, is confounded by an enormous array of interlinked technical issues that limit imaging system performance. As a result, advances in PET, human or animal, are the result of cumulative innovations across each of the component elements of PET, from data acquisition to image analysis. In the report that follows, we trace several of these advances across the imaging process with a focus on small animal PET.

Inter-crystal scattering recovery of light-sharing PET detectors using convolutional neural networks

Inter-crystal scattering (ICS) is a type of Compton scattering of photons from one crystal to adjacent crystals and causes inaccurate assignment of the annihilation photon interaction position in positron emission tomography (PET). Because ICS frequently occurs in highly light-shared PET detectors, its recovery is crucial for the spatial resolution improvement. In this study, we propose two different convolutional neural networks (CNNs) for ICS recovery, exploiting the good pattern recognition ability of CNN techniques. Using the signal distribution of a photosensor array as input, one network estimates the energy deposition in each crystal (ICS-eNet) and another network chooses the first-interacted crystal (ICS-cNet). We performed GATE Monte Carlo simulations with optical photon tracking to test PET detectors comprising different crystal arrays (8 × 8 to 21 × 21) with lengths of 20 mm and the same photosensor array (3 mm 8 × 8 array) covering an area of 25.8 × 25.8 mm². For each detector design, we trained ICS-eNet and ICS-cNet and evaluated their respective performance. ICS-eNet accurately identified whether the events were ICS (accuracy > 90%) and selected interacted crystals (accuracy > 60%) with appropriate energy estimation performance (R² > 0.7) in the 8 × 8, 12 × 12, and 16 × 16 arrays. ICS-cNet also exhibited satisfactory performance, which was less dependent on the crystal-to-sensor ratio, with an accuracy enhancement that exceeds 10% in selecting the first-interacted crystal and a reduction in error distances compared when no recovery was applied. Both ICS-eNet and ICS-cNet exhibited consistent performances under various optical property settings of the crystals. For spatial resolution measurements in PET rings, both networks achieved significant enhancements particularly for highly pixelated arrays. We also discuss approaches for training the networks in an actual experimental setup. This proof-of-concept study demonstrated the feasibility of CNNs for ICS recovery in various light-sharing designs to efficiently improve the spatial resolution of PET in various applications.

Positron annihilation localization by nanoscale magnetization

In positron emission tomography (PET), the finite range over which positrons travel before annihilating with an electron places a fundamental physical limit on the spatial resolution of PET images. After annihilation, the photon pair detected by the PET instrumentation is emitted from a location that is different from the positron-emitting source, resulting in image blurring. Here, we report on the localization of positron range, and hence annihilation quanta, by strong nanoscale magnetization of superparamagnetic iron oxide nanoparticles (SPIONs) in PET-MRI. We found that positron annihilations localize within a region of interest by up to 60% more when SPIONs are present (with [Fe] = 3 mM) compared to when they are not. The resulting full width at half maximum of the PET scans showed the spatial resolution improved by up to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\approx$$\end{document}≈ 30%. We also found evidence suggesting that the radiolabeled SPIONs produced up to a six-fold increase in ortho-positronium. These results may also have implications for emerging cancer theranostic strategies, where charged particles are used as therapeutic as well as diagnostic agents and improved dose localization within a tumor is a determinant of better treatment outcomes.

SiPM signal readout for inter-crystal scatter event identification in PET detectors

In positron emission tomography (PET) with pixelated detectors, a significant number of annihilation photons interact with scintillation crystals through single or multiple Compton scattering events. When these partial energy depositions occur across multiple crystal elements, we call them inter-crystal scatter (ICS) events. ICS events lead to incorrect localization of the annihilation photons, thereby degrading the PET image contrast, spatial resolution, and lesion detectability. The accurate identification of ICS events is the first essential step to improve the quality of PET images by rejecting ICS events or recovering ICS events without losing PET sensitivity. In this study, we propose a novel silicon photomultiplier (SiPM) readout method to identify ICS events in one-to-one coupled PET detectors with a reduced number of data acquisition channels. For concept verification, we assembled a PET detector that consists of a 16-channel SiPM array and 4 [Formula: see text] 4 lutetium oxyorthosilicate (LSO) array with a 3.2 mm crystal pitch. The proposed SiPM readout scheme serializes the 16 SiPM anode signals into four pulse train outputs encoded with four increasing time-delays in steps of 250 ns intervals. A Sum signal of the 16 SiPM anodes provides the timing information for time-of-flight measurement and a trigger signal for coincidence detection. A time-over-threshold (TOT) method was applied for obtaining the energy information followed by a subsequent TOT-to-energy calibration. We successfully identified the ICS events and determined their interacted positions and deposited energies by analyzing the digital pulses from the four pulse train output channels. The occurrence rate of ICS events was 10.85% for the 4 × 4 PET detector module with 3.2 mm-pitch LSO crystals. The PET detector yielded an energy resolution of 10.9 [Formula: see text] 0.6% and coincidence timing resolution of 285 [Formula: see text] 12 ps FWHM. We expect that the proposed method can be a useful solution for alleviating the readout burden of SiPM-based PET scanners with ICS event identification capability.

Recovery of inter-detector and inter-crystal scattering in brain PET based on LSO and GAGG crystals

Gadolinium aluminum gallium garnet (GAGG) is a promising scintillator crystal for positron emission tomography (PET) detectors owing to its advantages of energy resolution, light yield, and absence of intrinsic radiation. However, a large portion of the incident photons undergoes Compton scattering within GAGG crystal because of its low stopping power compared to that of lutetium-based crystals such as Lu₂SiO₅ (LSO). Inter-detector scattering (IDS) and inter-crystal scattering (ICS) result in loss of sensitivity and image quality of PET, respectively. We performed a Monte Carlo simulation study to evaluate IDS recovery in our currently developing brain-dedicated PET, and extended the idea to ICS recovery. We also compared the impact of the recoveries on LSO- and GAGG-based PET scanners. We measured the sensitivity and spatial resolution of the brain PET, and analyzed the image quality using a lesion phantom, a hot-rod phantom, and a 2D Hoffman phantom with applying IDS or ICS recovery. IDS recovery increased the PET sensitivity and improved the noise level of the reconstructed images. ICS recovery enhanced the spatial resolution and the contrast of the images was improved. As the occurrence rates of IDS and ICS were higher in GAGG than in LSO, the overall impact of IDS or ICS recovery was significant in GAGG. In conclusion, we showed that the proportional method would be suitable for IDS and ICS recoveries of PET, and emphasized the importance of ICS and IDS recoveries for PET using crystals with low stopping power.

Non-invasive Reporter Gene Imaging of Cell Therapies, including T Cells and Stem Cells

Cell therapies represent a rapidly emerging class of new therapeutics. They are intended and developed for the treatment of some of the most prevalent human diseases, including cancer, diabetes, and for regenerative medicine. Currently, they are largely developed without precise assessment of their in vivo distribution, efficacy, or survival either clinically or preclinically. However, it would be highly beneficial for both preclinical cell therapy development and subsequent clinical use to assess these parameters in situ to enable enhancements in efficacy, applicability, and safety. Molecular imaging can be exploited to track cells non-invasively on the whole-body level and can enable monitoring for prolonged periods in a manner compatible with rapidly expanding cell types. In this review, we explain how in vivo imaging can aid the development and clinical translation of cell-based therapeutics. We describe the underlying principles governing non-invasive in vivo long-term cell tracking in the preclinical and clinical settings, including available imaging technologies, reporter genes, and imaging agents as well as pitfalls related to experimental design. Our emphasis is on adoptively transferred T cell and stem cell therapies.

How Non-invasive in vivo Cell Tracking Supports the Development and Translation of Cancer Immunotherapies

Immunotherapy is a relatively new treatment regimen for cancer, and it is based on the modulation of the immune system to battle cancer. Immunotherapies can be classified as either molecular or cell-based immunotherapies, and both types have demonstrated promising results in a growing number of cancers. Indeed, several immunotherapies representing both classes are already approved for clinical use in oncology. While spectacular treatment successes have been reported, particularly for so-called immune checkpoint inhibitors and certain cell-based immunotherapies, they have also been accompanied by a variety of severe, sometimes life-threatening side effects. Furthermore, not all patients respond to immunotherapy. Hence, there is the need for more research to render these promising therapeutics more efficacious, more widely applicable, and safer to use. Whole-body in vivo imaging technologies that can interrogate cancers and/or immunotherapies are highly beneficial tools for immunotherapy development and translation to the clinic. In this review, we explain how in vivo imaging can aid the development of molecular and cell-based anti-cancer immunotherapies. We describe the principles of imaging host T-cells and adoptively transferred therapeutic T-cells as well as the value of traceable cancer cell models in immunotherapy development. Our emphasis is on in vivo cell tracking methodology, including important aspects and caveats specific to immunotherapies. We discuss a variety of associated experimental design aspects including parameters such as cell type, observation times/intervals, and detection sensitivity. The focus is on non-invasive 3D cell tracking on the whole-body level including aspects relevant for both preclinical experimentation and clinical translatability of the underlying methodologies.

Systematic study on factors influencing the performance of interdetector scatter recovery in small-animal PET

PURPOSE

Interdetector scatter (IDS) is a triple coincidence caused by the Compton scatter of an annihilation photon from one detector block to another which frequently occurs in small-animal positron emission tomography (PET). By finding the true lines-of-response (LORs) of annihilation photon pairs among three possible LORs in IDS events, we can utilize these recovered events to improve the sensitivity of PET systems. IDS recovery should be accurate to yield reliable images with relatively short scan times. We systemically investigated physical factors affecting IDS recovery performance, focusing on the reconstructed image quality of small-animal PET. We evaluated sensitivity increase, recovery accuracy, and image quality by applying different combinations of energy window, recovery scheme, and scanner properties.

METHODS

We used GATE Monte Carlo simulation to acquire coincidence events from a NEMA NU 4-2008 image quality phantom using small-animal PET scanner with axial field of view of 55 mm and diameter of 64 mm. We first defined energy window criteria to obtain valid IDS events. Their role was to assign triple coincidences as IDS events and to restrict the number of LOR candidates to two. We tested three different energy windows around 511 keV. Second, we applied four different recovery schemes (maximum energy, Compton kinematics, neural network, and proportional) to assigned IDS events. To measure the effects of scanner properties, energy resolutions of 0-20% and one to four depth-of-interaction (DOI) layers were simulated. For every combination of the factors, we measured sensitivity increase and recovery accuracy. We also analyzed the reconstructed images for each IDS recovery method in terms of mean pixel intensity, noise, signal-to-noise ratio (SNR), contrast, and recovery coefficients.

RESULTS

Sensitivity increase depended on the energy window and energy resolution. The maximum increase in sensitivity was 33% when energy window of [250, 750] keV was applied. Higher energy resolution yielded larger sensitivity increase, especially for narrow windows. Recovery accuracy was affected by all the factors tested in this study. Accuracy increased with narrower energy window, and a neural network scheme was the most accurate. The better energy resolution and DOI capability improved accuracy by providing precise measurement of energies and interaction positions. In image quality analysis, noise and SNR were highly dependent on the sensitivity increase and energy window. When the same energy window was applied, SNR, contrast, and recovery coefficients were higher with higher accuracy of the scheme. Meanwhile, the proportional scheme yielded the best image quality among the schemes and reduced 20% of scan time to achieve the same SNR as that of double coincidence images.

CONCLUSIONS

As a fundamental research for real implementation of IDS recovery, we conducted a simulation study to evaluate the factors affecting sensitivity increase, recovery accuracy, and image quality. Sensitivity increase was dependent on the energy window and energy resolution, while the recovery accuracy was affected by energy window, recovery scheme, energy resolution, and DOI capability. In image quality analysis, sensitivity increase and recovery accuracy dominantly affected the noise and quantitative accuracy, respectively. Among the recovery schemes, the proportional scheme obtained the best image quality.

Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems

Positron emission tomography (PET) imaging is based on detecting two time-coincident high-energy photons from the emission of a positron-emitting radioisotope. The physics of the emission, and the detection of the coincident photons, give PET imaging unique capabilities for both very high sensitivity and accurate estimation of the in vivo concentration of the radiotracer. PET imaging has been widely adopted as an important clinical modality for oncological, cardiovascular, and neurological applications. PET imaging has also become an important tool in preclinical studies, particularly for investigating murine models of disease and other small-animal models. However, there are several challenges to using PET imaging systems. These include the fundamental trade-offs between resolution and noise, the quantitative accuracy of the measurements, and integration with X-ray computed tomography and magnetic resonance imaging. In this article, we review how researchers and industry are addressing these challenges.