Application Of Positron Emission Tomography Research Articles

Positron Emission Tomography Molecular Imaging for Phenotyping and Management of Lymphoma.

Positron emission tomography (PET) represents molecular imaging for non-invasive phenotyping of physiological and biochemical processes in various oncological diseases. PET imaging with 18F-fluorodeoxyglucose (18F-FDG) for glucose metabolism evaluation is the standard imaging modality for the clinical management of lymphoma. One of the 18F-FDG PET applications is the detection and pre-treatment staging of lymphoma, which is highly sensitive. 18F-FDG PET is also applied during treatment to evaluate the individual chemo-sensitivity and accordingly guide the response-adapted therapy. At the end of the therapy regiment, a negative PET scan is indicative of a good prognosis in patients with advanced Hodgkin's lymphoma and diffuse large B-cell lymphoma. Thus, adjuvant radiotherapy may be alleviated. Future PET studies using non-18F-FDG radiotracers, such as 68Ga-labeled pentixafor (a cyclic pentapeptide that enables sensitive and high-contrast imaging of C-X-C motif chemokine receptor 4), 68Ga-labeled fibroblast activation protein inhibitor (FAPI) that reflects the tumor microenvironment, and 89Zr-labeled atezolizumab that targets the programmed cell death-ligand 1 (PD-L1), may complement 18F-FDG and offer essential tools to decode lymphoma phenotypes further and identify the mechanisms of lymphoma therapy.

Microglia Loss and Astrocyte Activation Cause Dynamic Changes in Hippocampal [18F]DPA-714 Uptake in Mouse Models of Depression.

Major depression is a serious and chronic mental illness. However, its etiology is poorly understood. Although glial cells have been increasingly implicated in the pathogenesis of depression, the specific role of microglia and astrocytes in stress-induced depression remains unclear. Translocator protein (TSPO) has long been considered a marker of neuroinflammation and microglial activation. However, this protein is also present on astrocytes. Thus, it is necessary to explore the relationships between TSPO, microglia, and astrocytes in the context of depression. In this study, C57BL/6J male mice were subjected to chronic unpredictable stress (CUS) for 5 weeks. Subsequently, sucrose preference and tail suspension tests (TSTs) were performed to assess anhedonia and despair in these mice. [18F]DPA-714 positron emission tomography (PET) was adopted to dynamically assess the changes in glial cells before and 2, 4, or 5 weeks after CUS exposure. The numbers of TSPO+ cells, ionized calcium-binding adaptor molecule (Iba)-1+ microglial cells, TSPO+/Iba-1+ cells, glial fibrillary acidic protein (GFAP)+ astrocytes, TSPO+/GFAP+ cells, and TUNEL-stained microglia were quantified using immunofluorescence staining. Real-time PCR was used to evaluate interleukin (IL)-1β, IL-4, and IL-18 expression in the hippocampus. We observed that hippocampal [18F]DPA-714 uptake significantly increased after 2 weeks of CUS. However, the signal significantly decreased after 5 weeks of CUS. CUS significantly reduced the number of Iba-1+, TSPO+, and TSPO+/Iba-1+ cells in the hippocampus, especially in the CA1 and dentate gyrus (DG) subregions. However, this intervention increased the number of GFAP+ astrocytes in the CA2/CA3 subregions of the hippocampus. In addition, microglial apoptosis in the early stage of CUS appeared to be involved in microglia loss. Further, the expression of pro-inflammatory cytokines (IL-1β and IL-18) was significantly decreased after CUS. In contrast, the expression of the anti-inflammatory cytokine IL-4 was significantly increased after 2 weeks of CUS. These results suggested that the CUS-induced dynamic changes in hippocampal [18F]DPA-714 uptake and several cytokines may be due to combined microglial and astrocyte action. These findings provide a theoretical reference for the future clinical applications of TSPO PET.

Progress in Fast and Red Plastic Scintillators

Radiological detection where Cherenkov residual background can be prominent requires scintillators with increased emission wavelength. Cherenkov residual background precludes the use of UV-emitting sensors such as plastic scintillators. However, the literature is scarce in red-emitting plastic scintillators and only one commercial scintillator is currently available (BC-430, from Saint-Gobain Crystals and Detectors). In addition, X-ray imaging or time-of-flight positron emission tomography (ToF-PET) applications are also demanding on this type (color) of scintillators, but such applications also require that the material displays a fast response, which is not particularly the case for BC-430. We present herein our latest developments in the preparation and characterization of fast and red plastic scintillators for this application. Here, ‘fast’ means nanosecond range decay time and ‘red’ is an emission wavelength shifted towards more than 550 nm. At first, the strategy to the preparation of such material is explained by decomposing the scintillator to fundamental elements. Each stage is then optimized in terms of decay time response, then the elemental bricks are arranged to give plastic scintillator formulations that are compatible with the abovementioned characteristics. The results are compared with the red-emissive BC-430 commercial plastic, and the ultra-fast, violet-emitting BC-422Q 1% plastic. In particular, the first-time use of trans-4-dimethylamino-4′-nitrostilbene in the scintillation field as a red wavelength shifter allowed preparing plastic scintillators with the following properties: λemmax 554 nm, photoluminescence decay time 4.2 ns, and light output ≈ 6100 ph/MeV. This means a scintillator almost as bright as BC-430 but at least three times faster. This new sensor might provide useful properties for nuclear instrumentation.

Updates in the Impact of Chronic Systemic Inflammation on Vascular Inflammation by Positron Emission Tomography (PET).

In this review, we focus on the clinical and epidemiological studies pertaining to systemic and vascular inflammation by positron emission tomography (PET) in patients with chronic inflammatory conditions such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), human immunodeficiency virus (HIV), and psoriasis to highlight the importance of chronic systemic inflammation on vascular inflammation by PET in these disease states. Recent clinical and translation advancements have demonstrated the durable relationship between chronic systemic inflammation and cardiovascular disease (CVD). In chronic inflammatory states, this relationship is robustly evident in the form of increased vascular inflammation, yet traditional risk estimates often underestimate the subclinical cardiovascular risk conferred by chronic inflammation. PET has emerged as a novel, non-invasive imaging modality capable of both quantifying the degree of systemic and vascular inflammation and detecting residual inflammation prior to cardiovascular events. We begin by demonstrating the role of inflammation in the pathogenesis of atherosclerosis, discussing how PET has been utilized to measure systemic and vascular inflammation and their effect on subclinical atherosclerosis, and finally reviewing recent applications of PET in constructing improved risk stratification for patients at high risk for stroke and CVD.

Deep-learning-based fast TOF-PET image reconstruction using direction information.

Although deep learning for application in positron emission tomography (PET) image reconstruction has attracted the attention of researchers, the image quality must be further improved. In this study, we propose a novel convolutional neural network (CNN)-based fast time-of-flight PET (TOF-PET) image reconstruction method to fully utilize the direction information of coincidence events. The proposed method inputs view-grouped histo-images into a 3D CNN as a multi-channel image to use the direction information of such events. We evaluated the proposed method using Monte Carlo simulation data obtained from a digital brain phantom. Compared with a case without direction information, the peak signal-to-noise ratio and structural similarity were improved by 1.2dB and 0.02, respectively, at a coincidence time resolution of 300ps. The calculation times of the proposed method were significantly lower than those of a conventional iterative reconstruction. These results indicate that the proposed method improves both the speed and image quality of a TOF-PET image reconstruction.

Charting the Chemical and Mechanistic Scope of Light-Triggered Protein Ligation.

The creation of discrete, covalent bonds between a protein and a functional molecule like a drug, fluorophore, or radiolabeled complex is essential for making state-of-the-art tools that find applications in basic science and clinical medicine. Photochemistry offers a unique set of reactive groups that hold potential for the synthesis of protein conjugates. Previous studies have demonstrated that photoactivatable desferrioxamine B (DFO) derivatives featuring a para-substituted aryl azide (ArN3) can be used to produce viable zirconium-89-radiolabeled monoclonal antibodies (89Zr-mAbs) for applications in noninvasive diagnostic positron emission tomography (PET) imaging of cancers. Here, we report on the synthesis, 89Zr-radiochemistry, and light-triggered photoradiosynthesis of 89Zr-labeled human serum albumin (HSA) using a series of 14 different photoactivatable DFO derivatives. The photoactive groups explore a range of substituted, and isomeric ArN3 reagents, as well as derivatives of benzophenone, a para-substituted trifluoromethyl phenyl diazirine, and a tetrazole species. For the compounds studied, efficient photochemical activation occurs inside the UVA-to-visible region of the electromagnetic spectrum (∼365–450 nm) and the photochemical reactions with HSA in water were complete within 15 min under ambient conditions. Under standardized experimental conditions, photoradiosynthesis with compounds 1–14 produced the corresponding 89ZrDFO-PEG3-HSA conjugates with decay-corrected isolated radiochemical yields between 18.1 ± 1.8% and 62.3 ± 3.6%. Extensive density functional theory (DFT) calculations were used to explore the reaction mechanisms and chemoselectivity of the light-induced bimolecular conjugation of compounds 1–14 to protein. The photoactivatable DFO-derivatives operate by at least five distinct mechanisms, each producing a different type of bioconjugate bond. Overall, the experimental and computational work presented here confirms that photochemistry is a viable option for making diverse, functionalized protein conjugates.

An iterative image-based inter-frame motion compensation method for dynamic brain PET imaging

As a non-invasive imaging tool, positron emission tomography (PET) plays an important role in brain science and disease research. Dynamic acquisition is one way of brain PET imaging. Its wide application in clinical research has often been hindered by practical challenges, such as patient involuntary movement, which could degrade both image quality and the accuracy of the quantification. This is even more obvious in scans of patients with neurodegeneration or mental disorders. Conventional motion compensation methods were either based on images or raw measured data, were shown to be able to reduce the effect of motion on the image quality. As for a dynamic PET scan, motion compensation can be challenging as tracer kinetics and relatively high noise can be present in dynamic frames. In this work, we propose an image-based inter-frame motion compensation approach specifically designed for dynamic brain PET imaging. Our method has an iterative implementation that only requires reconstructed images, based on which the inter-frame subject movement can be estimated and compensated. The method utilized tracer-specific kinetic modelling and can deal with simple and complex movement patterns. The synthesized phantom study showed that the proposed method can compensate for the simulated motion in scans with 18F-FDG, 18F-Fallypride and 18F-AV45. Fifteen dynamic 18F-FDG patient scans with motion artifacts were also processed. The quality of the recovered image was superior to the one of the non-corrected images and the corrected images with other image-based methods. The proposed method enables retrospective image quality control for dynamic brain PET imaging, hence facilitating the applications of dynamic PET in clinics and research.

PET-based artificial intelligence applications in cardiac nuclear medicine.

In the recent years, artificial intelligence (AI) applications have gained interest in the field of cardiovascular medical imaging, including positron emission tomography (PET). The use of AI in cardiac PET imaging is to date limited, although first, important results have been shown, overcoming technical issues, improving diagnostic accuracy and providing prognostic information. In this review we aimed to summarize the state-of-the-art regarding AI applications in cardiovascular PET.

Photoactivatable Fluorescent Tags for Dual-Modality Positron Emission Tomography Optical Imaging.

Fluorescent protein conjugates are vital tools in a wide range of scientific disciplines from basic biochemical research to applications in clinical pathology and intraoperative surgery. We report the synthesis and characterization of photoactivatable fluorophores (PhotoTags) based on the functionalization of coumarin, fluorescein, BODIPY, rhodamine B, and cyanine dyes with a photochemically active aryl azide group. Photochemical labeling experiments using human serum albumin produced fluorescent proteins in high yields under irradiation with ultraviolet light for <15 min. We also synthesized DFO-RhodB-PEG3-ArN3─a photoactivatable compound that can be radiolabeled with 89Zr for applications in optical imaging and positron emission tomography. One-pot 89Zr-radiolabeling and light-induced protein conjugation produced [89Zr]ZrDFO-RhodB-PEG3-azepin-trastuzumab. Proof-of-concept studies in vitro and in vivo confirmed that [89Zr]ZrDFO-RhodB-PEG3-azepin-trastuzumab is a potential dual-modality agent for detecting human epidermal growth factor receptor 2 (HER2/neu) expression. Overall, the PhotoTag technology represents a rapid, synthetically versatile, and user-friendly approach for generating novel protein conjugates.

The physical basis of application of positron emission tomography and modern radiopharms

This article provides a review of the literature on the history, physical and technical foundations and features of the application of positron emission tomography (PET), which came into practice in the 1970s. PET is a method of visualizing the space-time distribution of a positron-emitting radiopharmaceutical (RP) in the patient’s body by annihilation radiation. The classification of radiopharmaceuticals that are used in clinical and diagnostic practice is considered.

Design, Synthesis and Binding Affinity Evaluation of Cytochrome P450 1B1 Targeted Chelators

Cytochrome P450 1B1 (CYP1B1) is specifically expressed in a variety of tumors which makes it a promising imaging target of tumor. We aimed to design and synthesize CYP1B1 targeted chelators for the potential application in positron emission tomography (PET) imaging of tumor. 1,4,7-triazacyclononane-1,4-diiacetic acid (NODA) was connected to the CYP1B1 selective inhibitor we developed before through polyethylene glycol (PEG) linkers with different lengths. The inhibitory activities of chelators 6a-c against CYP1 family were evaluated by 7-ethoxyresorufin o-deethylation (EROD) assay. The manual docking between the chelators and the CYP1B1 was conducted subsequently. To determine the binding affinities of 6a-c to CYP1B1 in cells, we further performed a competition study at the cellular level. Among three chelators, 6a with the shortest linker showed the best inhibitory activity against CYP1B1. In the following molecular simulation study, protein-inhibitor complex of 6a showed the nearest F-heme distance which is consistent with the results of enzymatic assay. Finally, the cell based competitive assay proved the binding affinity of 6a-c to CYP1B1 enzyme. We designed and synthesized a series of chelators which can bind to CYP1B1 enzyme in cancer cells.To our knowledge, this work is the first attempt to construct CYP1B1 targeted chelators for radiolabeling and we hope it will prompt the application of CYP1B1 imaging in tumor detection.

Prostate-Specific Membrane Antigen as Target for Neuroimaging of Central Nervous System Tumors

Introduction Positron emission tomography (PET) imaging with prostate-specific membrane antigen- (PSMA-) binding tracers has been found incidentally to demonstrate uptake in CNS tumors. Following the encouraging findings of several such case reports, there is a growing interest in the potential application of PSMA-targeted PET imaging for diagnostics, theranostics, and monitoring of CNS tumors. This is a systematic literature review on PSMA-binding tracers in CNS tumors. Methods A PubMed search was conducted, including preclinical and clinical reports. One hundred and twelve records were identified, and after screening, 56 were included in the final report. Results Tissue studies demonstrated PSMA expression in tumor vascular endothelial cells, without expression in normal brain tissue, though the extent and intensity of staining varied by anti-PSMA antibody and methodology. Most included studies reported on gliomas, which showed strong PSMA ligand uptake and more favorable tumor to background ratios than other PET tracers. There are also case reports demonstrating PSMA ligand uptake in prostate cancer brain metastases, nonprostate cancer brain metastases, and meningiomas. We also review the properties of the various PSMA-binding radiotracers available. Therapeutic and theranostic applications of PSMA-binding tracers have been studied, including labeled alpha- and beta-ray emitting isotopes, as well as PSMA targeting in directing MRI-guided focused ultrasound. Conclusions There is a potential application for PSMA-targeted PET in neuro-oncology as a combination of diagnostic and therapeutic use, as a theranostic modality for managing CNS tumors. Further research is needed regarding the mechanism(s) of PSMA expression in CNS tumors and its differential performance by tumor type.

Brown Adipose Tissue: A Short Historical Perspective.

Brown adipose tissue (BAT) was first identified by Conrad Gessner in 1551, but it was only in 1961 that it was firmly identified as a thermogenic organ. Key developments in the subsequent two decades demonstrated that: (1) BAT is quantitatively important to non-shivering thermogenesis in rodents, (2) uncoupling of oxidative phosphorylation through a mitochondrial proton conductance pathway is the central mechanism by which heat is generated, (3) uncoupling protein-1 is the critical factor regulating proton leakage in BAT mitochondria. Following pivotal studies on cafeteria-fed rats and obese ob/ob mice, BAT was then shown to have a central role in the regulation of energy balance and the etiology of obesity. The application of fluorodeoxyglucose positron emission tomography in the late 2000s confirmed that BAT is present and active in adults, resulting in renewed interest in the tissue in human energetics and obesity. Subsequent studies have demonstrated a broad metabolic role for BAT, the tissue being an important site of glucose disposal and triglyceride clearance, as well as of insulin action. BAT continues to be a potential target for the treatment of obesity and related metabolic disorders.

Role of PET-CT (Positron Emission Tomography-Computed Tomography) in Cancer Evaluation and Treatment

Context: Positron emission tomography is a nuclear medicine imaging that deals with physiological function using radioisotopes. With the most PET (Positron Emission Tomography) scanners in integration with the CT scanners of late, this technology has registered phenomenal growth. The small amount of radioactive material is called Radiotracers. Objective: Like 18F- Fluro-deoxy-2-glucose has widely used. In this article, the author introduced clinical applications of PET out of 25 patients who studied hypermetabolic lesions in lymph nodes. Methods: PET imaging is coincidence imaging which is different from the other imaging technique PET image formed from multiple rings of detector crystals. Each decay positron travel in tissue annihilation reaction is going on. FDG is the most commonly used radiotracer to detect and stage various types of malignancies. Result: The field of PET/CT imaging cares for many oncology patients. PET improved localization of malignant lesions. It improved staging biopsy and therapy. Conclusion: Finally, studies to data showed 4% to 10% improvement in the overall accuracy of staging/restaging in lesions. If we use Monte Carlo simulation, OLINDA/EXM software may improve further with widely used.

Clone Selection Artificial Intelligence Algorithm-Based Positron Emission Tomography-Computed Tomography Image Information Data Analysis for the Qualitative Diagnosis of Serous Cavity Effusion in Patients with Malignant Tumors.

This study aimed to investigate the application of positron emission tomography- (PET-) computed tomography (CT) image information data combined with serous cavity effusion based on clone selection artificial intelligence algorithm in the diagnosis of patients with malignant tumors. A total of 97 patients with PET-CT scanning and empirically confirmed as serous cavity effusion were retrospectively analyzed in this study. The clone selection artificial intelligence algorithm was applied to register the PET-CT images, and the patients were rolled into a benign effusion group and a malignant effusion group according to the benign and malignant conditions of the serous cavity effusion. Besides, the causes of patients from the two groups were analyzed, and there was a comparison of their physiological conditions. Subsequently, CT values of different KeV, lipid/water, water/iodine, and water/calcium concentrations were measured, and the differences of the above quantitative parameters between benign and malignant serous cavity effusion were compared, as well as the registration results of the clone algorithm. The results showed that the registration time and misalignment times of clonal selection algorithm (13.88, 0) were lower than those of genetic algorithm (18.72, 8). There were marked differences in CT values of 40–60 keV and 130–140 keV between the two groups. The concentrations of lipid/water, water/iodine, and water/calcium in basal substances of the malignant effusion group were obviously higher than the concentrations of the benign effusion group (P < 0.05). Benign and malignant effusions presented different manifestations in PET-CT, which was conducive to the further diagnosis of malignant tumors. Based on clone selection artificial intelligence algorithm, PET-CT could provide a new multiparameter method for the identification of benign and malignant serous cavity effusions and benign and malignant tumors.

Overview of positron emission tomography in functional imaging of the lungs for diffuse lung diseases.

Positron emission tomography (PET) is a quantitative molecular imaging modality increasingly used to study pulmonary disease processes and drug effects on those processes. The wide range of drugs and other entities that can be radiolabeled to study molecularly targeted processes is a major strength of PET, thus providing a noninvasive approach for obtaining molecular phenotyping information. The use of PET to monitor disease progression and treatment outcomes in DLD has been limited in clinical practice, with most of such applications occurring in the context of research investigations under clinical trials. Given the high costs and failure rates for lung drug development efforts, molecular imaging lung biomarkers are needed not only to aid these efforts but also to improve clinical characterization of these diseases beyond canonical anatomic classifications based on computed tomography. The purpose of this review article is to provide an overview of PET applications in characterizing lung disease, focusing on novel tracers that are in clinical development for DLD molecular phenotyping, and briefly address considerations for accurately quantifying lung PET signals.

PET-CT for the diagnosis and treatment of primary musculoskeletal tumors in Chinese patients - experience from 255 patients in a single center.

The current study was carried out to assess the value of positron emission tomography (PET)/CT on the diagnosis and staging of primary musculoskeletal tumors. PET-CT test results and histopathological study reports of all the patients with primary musculoskeletal tumors in our department from January 2006 to July 2015 were retrospectively reviewed. Maximum standardized uptake value (SUVmax) in these PET-CT reports were recorded and analyzed respectively for each type of sarcoma. A total of 255 patients were included in the final analysis. Sensitivity of SUVmax based diagnosis was 96.6% for primary malignant osseous sarcomas and 91.2% for soft tissue sarcomas. SUVmax of high-grade osseous sarcomas (average 8.4 ± 5.5) was significantly higher (p < 0.001) than low-grade osseous sarcomas (average 3.9 ± 1.8); based on current case series, SUVmax of high-grade soft tissue sarcomas (7.5 ± 5.1) was not significantly different (p = 0.229) from that of low-grade soft tissue sarcomas (5.3 ± 3.7). Significant decrease of SUVmax value after chemotherapy was associated with favorable prognosis in patients with osteosarcoma. Results of the current study indicate that, the SUVmax based application of PET-CT can be a valuable supplementary method to histopathological tests regarding the diagnosis and staging of primary musculoskeletal sarcomas. SUVmax based application of PET-CT is a highly sensitive method in diagnosis of primary osseous and soft tissue sarcomas in Chinese patients.

Deep Learning-Based Positron Emission Tomography Molecular Imaging in the Assessment of Cognitive Dysfunction in Patients with Epilepsy

This work aimed to investigate the application of positron emission tomography (PET) molecular imaging based on the deep learning algorithm in the assessment of cognitive dysfunction in patients with epilepsy. In this study, 52 hospitalized patients with epilepsy were selected as the epilepsy group and treated with different kinds of antiepileptic drugs, and 52 volunteers were selected as the control group. A U-net optimized network structure algorithm based on deep learning was proposed in this study and compared with a fully convolutional neural network (FCNN). Besides, it was applied in the PET molecular imaging of patients with epilepsy, and the segmentation effect of the U-net optimized network structure was good. According to event-related potential examinations, the proportion of patients with cognitive dysfunction in the epilepsy group (74.19%) was higher than the proportion of the control group (7.46%) ( P &lt; 0.05 ). The patients with cognitive dysfunction (57.89%) who took one antiepileptic drug were lower than those with two antiepileptic drugs (84.61%) ( P &lt; 0.05 ). The difference was statistically obvious in the overall quality of life of patients with epilepsy ( P &lt; 0.05 ). The occurrence of cognitive dysfunction in patients with epilepsy was related to the type of seizures. In addition, the quality of life of patients who suffered from cognitive dysfunction was low.

The role of neuroimaging in Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Two hallmarks of PD are the accumulation of alpha‐synuclein and the loss of dopaminergic neurons in the brain. There is no cure for PD, and all existing treatments focus on alleviating the symptoms. PD diagnosis is also based on the symptoms, such as abnormalities of movement, mood, and cognition observed in the patients. Molecular imaging methods such as magnetic resonance imaging (MRI), single‐photon emission computed tomography (SPECT), and positron emission tomography (PET) can detect objective alterations in the neurochemical machinery of the brain and help diagnose and study neurodegenerative diseases. This review addresses the application of functional MRI, PET, and SPECT in PD patients. We provide an overview of the imaging targets, discuss the rationale behind target selection, the agents (tracers) with which the imaging can be performed, and the main findings regarding each target's state in PD. Molecular imaging has proven itself effective in supporting clinical diagnosis of PD and has helped reveal that PD is a heterogeneous disorder, which has important implications for the development of future therapies. However, the application of molecular imaging for early diagnosis of PD or for differentiation between PD and atypical parkinsonisms has remained challenging. The final section of the review is dedicated to new imaging targets with which one can detect the PD‐related pathological changes upstream from dopaminergic degeneration. The foremost of those targets is alpha‐synuclein. We discuss the progress of tracer development achieved so far and challenges on the path toward alpha‐synuclein imaging in humans.

High-throughput, accurate Monte Carlo simulation on CPU hardware for PET applications

Monte Carlo simulations (MCS) represent a fundamental approach to modelling the photon interactions in positron emission tomography (PET). A variety of PET-dedicated MCS tools are available to assist and improve PET imaging applications. Of these, GATE has evolved into one of the most popular software for PET MCS because of its accuracy and flexibility. However, simulations are extremely time-consuming. The use of graphics processing units (GPU) has been proposed as a solution to this, with reported acceleration factors about 400–800. These factors refer to GATE benchmarks performed on a single CPU core. Consequently, CPU-based MCS can also be easily accelerated by one order of magnitude or beyond when exploiting multi-threading on powerful CPUs. Thus, CPU-based implementations become competitive when further optimisations can be achieved. In this context, we have developed a novel, CPU-based software called the PET physics simulator (PPS), which combines several efficient methods to significantly boost the performance. PPS flexibly applies GEANT4 cross-sections as a pre-calculated database, thus obtaining results equivalent to GATE. This is demonstrated for an elaborated PET scanner with 3-layer block detectors. All code optimisations yield an acceleration factor of ≈20 (single core). Multi-threading on a high-end CPU workstation (96 cores) further accelerates the PPS by a factor of 80. This results in a total speed-up factor of ≈1600, which outperforms comparable GPU-based MCS by a factor of ≳2. Optionally, the proposed method of coincidence multiplexing can further enhance the throughput by an additional factor of ≈15. The combination of all optimisations corresponds to an acceleration factor of ≈24 000. In this way, the PPS can simulate complex PET detector systems with an effective throughput of 106 photon pairs in less than 10 milliseconds.