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Positron emission tomography is a highly sensitive molecular imaging modality, based on the coincident detection of annihilation photons after positron decay. The most used detector is based on dense, fast, and luminous scintillators read out by light sensors. This review covers the various detector concepts for clinical and preclinical systems.

[Abstract] Purpose: Although some dementia with Lewy bodies (DLB) patients have Alzheimer disease (AD) pathology, there are no reports comparing AD and DLB by amyloid PET and tau PET in the same patient. The aim of this study was to investigate the regional difference of metabolic reduction, amyloid deposition and tau deposition between DLB and AD brain.Methods: Five consecutive subjects with DLB and five age and Mini-mental state examination score matched AD patients, who underwent both fluoro-2-deoxyglucose (FDG)-PET, Pittsburgh compound B (PiB)-amyloid PET and THK5351 (THK)-tau PET, were included in this study. Voxel-based statistical analysis was performed with Statistical Parametric Mapping for comparison with FDG, amyloid and tau accumulation between the DLB and AD brains.Results: FDG PET demonstrated that occipital metabolism in DLB group was significantly lower than that in AD group. PiB PET demonstrated that in the AD group the anterior to posterior cingulate cortices, supplementary motor area, and thalamic amyloid depositions were significantly higher than those in the DLB group. THK PET demonstrated that in the AD group the posterior cingulate cortices, posterior internal capsules, thalamic and peri-brainstem regions tau depositions were significantly higher than those in the DLB group.Conclusions: In the DLB brain, it is suggested that decreased regional glucose metabolism is unrelated to amyloid and tau depositions, and the amyloid and tau depositions in the cingulate gyri and thalamic regions in the AD brain are higher than those in DLB brain.

In tissue engineering, miniature Electrical Impedance Tomography (mEIT) (or bioimpedance tomography), is an emerging tomographic modality that contributes to non-destructive and label-free imaging and monitoring of 3-D cellular dynamics. The main challenge of mEIT comes from the nonlinear and ill-posed image reconstruction problem, leading to the increased sensitivity to imperfect measurement signals. Physical model-based image reconstruction methods have been successfully applied to conventional setups, but are less satisfying for the mEIT setup regarding image quality, conductivity retrieval and computational efficiency. Data-driven or learning-based methods have recently become a new frontier for tomographic image reconstruction, particularly for medical imaging modalities, e.g., Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI). However, the study of learning-based image reconstruction methods in challenging micro-scale sensor setups and the seamless integration of such algorithms with the tomography instrument remains a gap. This thesis aims to develop 2-D and 3-D imaging platforms integrating multi-frequency EIT and machine learning-based image reconstruction algorithms to extract spectroscopic electrical properties of 3-D cultivated cells under in vitro conditions, in a non-destructive, robust, and computation-efficient manner. Recent advances in deep learning have pointed out a promising alternative for EIT image reconstruction. However, it is still challenging to image multiple objects with varying conductivity levels with a single neural network. A deep learning and group sparsity regularization-based hybrid image reconstruction framework was proposed to enable high-quality cell culture imaging with mEIT. A deep neural network was proposed to estimate the structural information in binary masks, given the limited number of data sets. Then the structural information is encoded in group sparsity regularization to obtain the final conductivity estimation. We validated our approach by imaging 3D cancer cell spheroids (MCF-7). Our method can be readily translated to spheroids, organoids, and cell culture in scaffolds of biomaterials. As the measured conductivity is a proxy for cell viability, mEIT has excellent potential to enable non-invasive, real-time, long-term monitoring of 3D cell growth, opening new avenues in regenerative medicine and drug testing. Deep learning provides binary structural information in the above-mentioned hybrid learning approach, whereas the regularization algorithm determines conductivity contrasts. Despite the advancement of structure distribution, the exact conductivity values of different objects are less accurately estimated by the regularization-based framework, which essentially prevents EIT’s transition from generating qualitative images to quantitative images. A structure-aware dual-branch deep learning method was proposed to further tackle this issue to predict structure distribution and conductivity values. The proposed network comprises two independent branches to encode the structure and conductivity features, respectively, and the two branches are joined later to make final predictions of conductivity distributions. Numerical and experimental evaluation results on MCF-7 human breast cancer cell spheroids demonstrate the superior performance of the proposed method in dealing with the multi-level, continuous conductivity reconstruction problem. Multi-frequency Electrical Impedance Tomography (mfEIT) is an emerging biomedical imaging modality to reveal frequency-dependent conductivity distributions in biomedical applications. Conventional model-based image reconstruction methods suffer from low spatial resolution, unconstrained frequency correlation and high computational cost. Most existing learning-based approaches deal with the single-frequency setup, which is inefficient and ineffective when extended to the multi-frequency setup. A Multiple Measurement Vector (MMV) model-based learning algorithm named MMV-Net was proposed to solve the mfEIT image reconstruction problem. MMV-Net considers the correlations between mfEIT images and unfolds the update steps of the Alternating Direction Method of Multipliers for the MMV problem (MMV-ADMM). The nonlinear shrinkage operator associated with the weighted l_{1,2} regularization term of MMV-ADMM is generalized in MMV-Net with a cascade of a Spatial Self-Attention module and a Convolutional Long Short-Term Memory (ConvLSTM) module to capture intra- and inter-frequency dependencies better. The proposed MMV-Net was validated on our Edinburgh mfEIT Dataset and a series of comprehensive experiments. The results show superior image quality, convergence performance, noise robustness and computational efficiency against the conventional MMV-ADMM and the state-of-the-art deep learning methods. Finally, few work on image reconstruction for Electrical Impedance Tomography (EIT) focuses on 3D geometries. Existing reconstruction algorithms adopt voxel grids for representation, which typically results in low image quality and considerable computational cost, and limits their applicability to real-time applications. In contrast, point clouds are a more efficient format for 3D surfaces, and such representation can naturally handle 3D shapes of arbitrary topologies with fine-grained details. Therefore, a learning-based 3D EIT reconstruction algorithm with efficient 3D representations (i.e., point cloud) was proposed to achieve higher image accuracy, spatial resolution and computational efficiency. A transformer-like point cloud network is adopted for 3D image reconstruction. This network simultaneously recovers the 3D coordinates of points to adaptively portray the objects' surface and predicts each point's conductivity. The results show that point cloud provides more efficient fine-shape descriptions and effectively alleviates computational costs. In summary, the work demonstrated in this thesis addressed the research void in tissue imaging with bioimpedance tomography by developing learning-based imaging approaches. The results achieved in this thesis could promote bioimpedance tomography as a robust, intelligent imaging technique for tissue engineering applications.

The overconsumption of palatable energy-dense foods drives obesity, but few human studies have investigated dopamine (DA) release in response to the consumption of a palatable meal, a putative mediator of excess intake in obesity. We imaged [11C]raclopride in the brain with positron emission tomography (PET) to assess striatal dopamine (DA) receptor binding pre- and post-consumption of a highly palatable milkshake (250 mL, 420 kcal) in 11 females, 6 of whom had severe obesity, and 5 of whom had healthy-weight. Those with severe obesity underwent assessments pre- and 3 months post-vertical sleeve gastrectomy (VSG). Our results demonstrated decreased post- vs. pre-meal DA receptor binding in the ventral striatum (p = 0.032), posterior putamen (p = 0.012), and anterior caudate (p = 0.018), consistent with meal-stimulated DA release. Analysis of each group separately suggested that results in the caudate and putamen were disproportionately driven by meal-associated changes in the healthy-weight group. Baseline (pre-meal) DA receptor binding was lower in severe obesity than in the healthy-weight group. Baseline DA receptor binding and DA release did not change from pre- to post-surgery. The results of this small pilot study suggest that milkshake acutely stimulates DA release in the ventral and dorsal striatum. This phenomenon likely contributes to the overconsumption of highly palatable foods in the modern environment.

International audience; Background: The resistance of glioblastoma stem cells (GSCs) to treatment is one of the causes of glioblastoma (GBM) recurrence. Endothelin A receptor (ETA) overexpression in GSCs constitutes an attractive biomarker for targeting this cell subpopulation, as illustrated by several clinical trials evaluating the therapeutic efficacy of endothelin receptor antagonists against GBM. In this context, we have designed an immunoPET radioligand combining the chimeric antibody targeting ETA, chimeric-Rendomab A63 (xiRA63), with 89Zr isotope and evaluated the abilities of xiRA63 and its Fab (ThioFab-xiRA63) to detect ETA+ tumors in a mouse model xenografted orthotopically with patient-derived Gli7 GSCs.Results: Radioligands were intravenously injected and imaged over time by µPET-CT imaging. Tissue biodistribution and pharmacokinetic parameters were analyzed, highlighting the ability of [89Zr]Zr-xiRA63 to pass across the brain tumor barrier and achieve better tumor uptake than [89Zr]Zr-ThioFab-xiRA63.Conclusions: This study shows the high potential of [89Zr]Zr-xiRA63 in specifically targeting ETA+ tumors, thus raising the possibility of detecting and treating ETA+ GSCs, which could improve the management of GBM patients.

Peer reviewed: True, Simple Summary: There is an unmet clinical need for imaging agents capable of detecting the presence, extent, and distribution of tumor cell death following treatment. We describe here a gallium-68-labeled derivative of the C2A domain of Synaptotagmin-I (68Ga-C2Am), which binds to the phosphatidylserine exposed by dying cells, for imaging tumor cell death in vivo using positron emission tomography (PET). Since PET is a highly sensitive tomographic imaging technique that is widely used in clinical oncology and gallium-68 has emerged as a cost-effective radiotracer that can be eluted on site from a benchtop generator, 68Ga-C2Am could find clinical application for the rapid assessment of tumor responses to treatment. Abstract: There is an unmet clinical need for imaging agents capable of detecting early evidence of tumor cell death, since the timing, extent, and distribution of cell death in tumors following treatment can give an indication of treatment outcome. We describe here 68Ga-labeled C2Am, which is a phosphatidylserine-binding protein, for imaging tumor cell death in vivo using positron emission tomography (PET). A one-pot synthesis of 68Ga-C2Am (20 min, 25 °C, >95% radiochemical purity) has been developed, using a NODAGA-maleimide chelator. The binding of 68Ga-C2Am to apoptotic and necrotic tumor cells was assessed in vitro using human breast and colorectal cancer cell lines, and in vivo, using dynamic PET measurements in mice implanted subcutaneously with the colorectal tumor cells and treated with a TRAIL-R2 agonist. 68Ga-C2Am showed predominantly renal clearance and low retention in the liver, spleen, small intestine, and bone and generated a tumor-to-muscle (T/m) ratio of 2.3 ± 0.4, at 2 h post probe administration and at 24 h following treatment. 68Ga-C2Am has the potential to be used in the clinic as a PET tracer for assessing early treatment response in tumors.

Background Myocardial perfusion imaging by positron emission tomography (PET-MPI) is the current gold standard for quantification of myocardial blood flow. F-18-flurpiridaz was recently introduced as a valid alternative to currently used PET-MPI probes. Nonetheless, optimum scan duration and time interval for image analysis are currently unknown. Further, it is unclear whether rest/stress PET-MPI with F-18-flurpiridaz is feasible in mice. Methods Rest/stress PET-MPI was performed with F-18-flurpiridaz (0.6-3.0 MBq) in 27 mice aged 7-8 months. Regadenoson (0.1 mu g/g) was used for induction of vasodilator stress. Kinetic modeling was performed using a metabolite-corrected arterial input function. Image-derived myocardial F-18-flurpiridaz uptake was assessed for different time intervals by placing a volume of interest in the left ventricular myocardium. Results Tracer kinetics were best described by a two-tissue compartment model. K-1 ranged from 6.7 to 20.0 mL center dot cm(-3)center dot min(-1), while myocardial volumes of distribution (V-T) were between 34.6 and 83.6 mL center dot cm(-3). Of note, myocardial F-18-flurpiridaz uptake (%ID/g) was significantly correlated with K-1 at rest and following pharmacological vasodilation for all time intervals assessed. However, while Spearman's coefficients (r(s)) ranged between 0.478 and 0.681, R-2 values were generally low. In contrast, an excellent correlation of myocardial F-18-flurpiridaz uptake with V-T was obtained, particularly when employing the averaged myocardial uptake from 20 to 40 min post tracer injection (R-2 >= 0.98). Notably, K-1 and V-T were similarly sensitive to pharmacological vasodilation induction. Further, mean stress-to-rest ratios of K-1, V-T, and %ID/g F-18-flurpiridaz were virtually identical, suggesting that %ID/g F-18-flurpiridaz can be used to estimate coronary flow reserve (CFR) in mice. Conclusion Our findings suggest that a simplified assessment of relative myocardial perfusion and CFR, based on image-derived tracer uptake, is feasible with F-18-flurpiridaz in mice, enabling high-throughput mechanistic CFR studies in rodents., Journal of Nuclear Cardiology, 30 (1), ISSN:1071-3581, ISSN:1532-6551

Purpose Resveratrol has shown promising anti-inflammatory effects in in vitro and animal studies. We aimed to investigate this effect on arterial inflammation in vivo. Methods This was an additional analysis of a double-blind randomized crossover trial which included eight male subjects with decreased insulin sensitivity who underwent an 18F-fluoroxyglucose (18F-FDG) PET/CT after 34 days of placebo and resveratrol treatment (150 mg/day). 18F-FDG uptake was analyzed in the carotid arteries and the aorta, adipose tissue regions, spleen, and bone marrow as measures for arterial and systemic inflammation. Maximum target-to-background ratios (TBRmax) were compared between resveratrol and placebo treatment with the non-parametric Wilcoxon signed-rank test. Median values are shown with their interquartile range. Results Arterial 18F-FDG uptake was non-significantly higher after resveratrol treatment (TBRmax all vessels 1.7 (1.6–1.7)) in comparison to placebo treatment (1.5 (1.4–1.6); p=0.050). Only in visceral adipose tissue, the increase in 18F-FDG uptake after resveratrol reached statistical significance (p=0.024). Furthermore, CRP-levels were not significantly affected by resveratrol treatment (p=0.091). Conclusions Resveratrol failed to attenuate arterial or systemic inflammation as measured with 18F-FDG PET in subjects at risk of developing type 2 diabetes. However, validation of these findings in larger human studies is needed.

Purpose Positron emission tomography (PET) with the first and only tau targeting radiotracer of 18F-flortaucipir approved by FDA has been increasingly used in depicting tau pathology deposition and distribution in patients with cognitive impairment. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform 18F-flortaucipir PET imaging. Method A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for 18F-flortaucipir PET imaging in Alzheimer’s disease (AD), focusing on clinical scenarios, patient preparation, and administered activities, as well as image acquisition, processing, interpretation, and reporting. Conclusion This international consensus and practice guideline will help to promote the standardized use of 18F-flortaucipir PET in patients with AD. It will become an international standard for this purpose in clinical practice.

Background Universally maximum standardized uptake value (SUVmax) and lactate dehydrogenase (LDH) are used as tools for response assessment in Hodgkin Lymphoma (HL) patients. Our objectives are to evaluate the predictive potential and response assessment of total lesion glycolysis (TLG) and metabolic tumor volume (MTV)—maximum three target lesions—as another alternatives and to investigate the correlation between TLG and MTV with LDH. Results Both initial SUVmax and TLG were significantly associated with early patient response (p value 0.03, 0.047, respectively). An optimal threshold for SUVmax and TLG less than or equal 19.52, and 158.6, respectively, correlated with better therapeutic response. Initial LDH was moderately correlated with initial values of TLG (rs = 0.4, p value 0.01), MTV (rs = 0.44, p value 0.01) and SUVmax (rs = 0.42, p value 0.01). Conclusion TLG in correlation with LDH can be significant prognostic factors of therapeutic response in HL. They can be used for the identification of a subset of HL patients with a better outcome.

PURPOSE: Further diagnostic testing may be required after a coronary computed tomography angiography (CTA) showing suspected coronary stenosis. Whether myocardial perfusion imaging (MPI) provides further prognostic information post-CTA remains debated. We evaluated the prognosis for patients completing CTA stratified for post-CTA diagnostic work-up using real-world data.METHODS: We identified all patients in our uptake area with angina symptoms undergoing first-time CTA over a 10-year period. Follow-up time was a median of 3.7 years [1.9-5.8]. The primary endpoint was a composite of myocardial infarction or death. The secondary endpoint was late revascularization.RESULTS: During the study period 53,351 patients underwent CTA. Of these, 24% were referred for further down-stream testing, 3,547 (7%) to MPI and 9,135 (17%) to invasive coronary angiography (ICA). The primary and secondary endpoints occurred in 2,026 (3.8%) and 954 (1.8%) patients. Patient-characteristic-adjusted hazard ratios for the primary and secondary endpoint using patients with a normal CTA as reference were 1.37 (1.21-1.55) and 2.50 (1.93-3.23) for patient treated medically, 1.68 (1.39-2.03) and 6.13 (4.58-8.21) for patients referred to MPI and 1.94 (1.69-2.23) and 9.18 (7.16-11.78) for patients referred for ICA, respectively. Adjusted analysis with stratification for disease severity at CTA showed similar hazard ratios for patients treated medically after CTA and patients referred for MPI and treated medically after the MPI.CONCLUSION: In patients completing coronary CTA, second-line MPI testing seems to identify patients at low risk of future events. MPI seems to have the potential to act as gatekeeper for ICA after coronary CTA.

Background: Amyloid-β (Aβ) accumulation is considered the earliest pathological change in Alzheimer’s disease (AD). The Amyloid Imaging to Prevent Alzheimer’s Disease (AMYPAD) consortium is a collaborative European framework across European Federation of Pharmaceutical Industries Associations (EFPIA), academic, and ‘Small and Medium-sized enterprises’ (SME) partners aiming to provide evidence on the clinical utility and cost-effectiveness of Positron Emission Tomography (PET) imaging in diagnostic work-up of AD and to support clinical trial design by developing optimal quantitative methodology in an early AD population. The AMYPAD studies: In the Diagnostic and Patient Management Study (DPMS), 844 participants from eight centres across three clinical subgroups (245 subjective cognitive decline, 342 mild cognitive impairment, and 258 dementia) were included. The Prognostic and Natural History Study (PNHS) recruited pre-dementia subjects across 11 European parent cohorts (PCs). Approximately 1600 unique subjects with historical and prospective data were collected within this study. PET acquisition with [18F]flutemetamol or [18F]florbetaben radiotracers was performed and quantified using the Centiloid (CL) method. Results: AMYPAD has significantly contributed to the AD field by furthering our understanding of amyloid deposition in the brain and the optimal methodology to measure this process. Main contributions so far include the validation of the dual-time window acquisition protocol to derive the fully quantitative non-displaceable binding potential (BPND), assess the value of this metric in the context of clinical trials, improve PET-sensitivity to emerging Aβ burden and utilize its available regional information, establish the quantitative accuracy of the Centiloid method across tracers and support implementation of quantitative amyloid-PET measures in the clinical routine. Future steps: The AMYPAD consortium has succeeded in recruiting and following a large number of prospective subjects and setting up a collaborative framework to integrate data across European PCs. Efforts are currently ongoing in collaboration with ARIDHIA and ADDI to harmonize, integrate, and curate all available clinical data from the PNHS PCs, which will become openly accessible to the wider scientific community.

Comparisons of late-onset Alzheimer's disease (LOAD) and autosomal dominant AD (ADAD) are confounded by age.We compared biomarkers from cerebrospinal fluid (CSF), magnetic resonance imaging, and amyloid imaging with Pittsburgh Compound-B (PiB) across four groups of 387 cognitively normal participants, 42 to 65 years of age, in the Dominantly Inherited Alzheimer Network (DIAN) and the Adult Children Study (ACS) of LOAD: DIAN mutation carriers (MCs) and non-carriers (NON-MCs), and ACS participants with a positive (FH+) and negative (FH-) family history of LOAD.At baseline, MCs had the lowest age-adjusted level of CSF Aβ42 and the highest levels of total and phosphorylated tau-181, and PiB uptake. Longitudinally, MC had similar increase in PiB uptake to FH+, but drastically faster decline in hippocampal volume than others, and was the only group showing cognitive decline.Preclinical ADAD and LOAD share many biomarker signatures, but cross-sectional and longitudinal differences may exist.

Refereed/Peer-reviewed Cancer stem cells are known to play a key role in tumour development, proliferation, and metastases. Their unique properties confer resistance to therapy, often leading to treatment failure. It is believed that research into the identification, targeting, and eradication of these cells can revolutionise oncological treatment. Based on the principle that what cannot be seen, cannot be targeted, a primary step in cancer management is the identification of these cells. The current review aims to encompass the state-of-the-art functional imaging techniques that enable the identification of cancer stem cells via various pathways and mechanisms. The paper presents in vivo molecular techniques that are currently available or await clinical implementation. Challenges and future prospects are highlighted to open new research avenues in cancer stem cell imaging.

With an ageing population, the number of people suffering from Alzheimer’s disease (AD) and Parkinson’s disease (PD) escalates yearly. Pathological hallmarks of AD and PD include aggregated proteins and synaptic dysfunction. Developing imaging probes targeting specific pathological hallmarks is highly valuable in aiding early diagnosis and treatment assessment. The thesis focused on evaluating positron emission tomography (PET) imaging probes that can visualise different pathological changes in preclinical models of neurodegeneration. Ligands targeting synaptic vesicle protein 2A (SV2A), alpha-synuclein (αSyn), and amyloid-beta (Aβ) are investigated. In paper I, we compared synaptic density in transgenic AD and PD mouse models to their wild-type age-matched controls using SV2A PET. In the hippocampus, lower synaptic density was found in the PD mice compared to the control. In paper II, we continued using SV2A PET and studied synaptic density in ageing mice. Synaptic density remained steady for most of the lifespan but slightly decreased in old age. In paper III, we developed and evaluated five antibody-based PET radioligands targeting αSyn aggregates. By conjugating anti-αSyn antibodies with the transferrin receptor (TfR) binder 8D3, we increased antibody brain entry significantly. These bispecific antibodies displayed high specificity and selectivity to αSyn aggregates. The most promising candidate successfully imaged brain-deposited αSyn but was unable to detect endogenously expressed αSyn in PD mouse models. In light of this, further investigation of antibody brain entry, distribution, and elimination is needed. Thus, in paper IV, we used microdialysis to compare the brain pharmacokinetics of a bispecific antibody targeting TfR and Aβ and its regular monospecific version that only binds to Aβ. The bispecific antibody showed distinct pharmacokinetics and entered the brain more efficiently than the regular antibody. Lastly, in paper V, we studied the impact of anti-Aβ antibody treatment on amyloid PET. AD mice were short-term treated with anti-Aβ antibody mAb158 and underwent [11C]PiB ex vivo autoradiography. We found a trend indicating that the treatment reduced the [11C]PiB signal despite no reduction in total Aβ levels. Our results contribute to an increased understanding of PET radioligands imaging neurodegeneration. Furthermore, it provides valuable information for designing and developing new PET radioligands.

Journal of labelled compounds and radiopharmaceuticals 66(3), 116-125 (2023). doi:10.1002/jlcr.4018, Published by Wiley, New York, NY [u.a.]

Shichao Wu,1– 4,* Di Liao,3– 5,* Xi Li,3– 5 Zeyu Liu,3– 5 Lin Zhang,3– 5 Fong Ming Mo,1,2,4 Shuo Hu,1,2,4 Jian Xia,3– 5 Xiangrui Yang1– 4 1Department of Nuclear Medicine (PET Center), Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People’s Republic of China; 2Key Laboratory of Nanobiological Technology of National Health Commission, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People’s Republic of China; 3Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People’s Republic of China; 4National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People’s Republic of China; 5Clinical Research Center for Cerebrovascular Disease of Hunan Province, Central South University, Changsha, Hunan, 410008, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiangrui Yang; Jian Xia Email yangxr@csu.edu.cn; xjian1216@csu.edu.cnIntroduction: Although the preparation of lipid nanoparticles (LNPs) achieves great success, their retention of highly hydrophobic drugs is still problematic.Methods: Herein, we report a novel strategy for efficiently loading hydrophobic drugs to LNPs for stroke therapy. Oleoylethanolamide (OEA), an endogenous highly hydrophobic molecule with outstanding neuroprotective effect, was successfully loaded to OEA-SPC&DSPE-PEG lipid nanoparticles (OSDP LNPs) with a drug loading of 15.9 ± 1.2 wt%. Efficient retention in OSDP LNPs greatly improved the pharmaceutical property and enhanced the neuroprotective effect of OEA.Results: Through the data of positron emission tomography (PET) and TTC-stained brain slices, it could be clearly visualized that the acute ischemic brain tissues were preserved as penumbral tissues and bounced back with reperfusion. The in vivo experiments stated that OSDP LNPs could significantly improve the survival rate, the behavioral score, the cerebral infarct volume, the edema degree, the spatial learning and memory ability of the MCAO (middle cerebral artery occlusion) rats.Discussion: These results suggest that the OSDP LNPs have a great chance to develop hydrophobic OEA into a potential anti-stroke formulation.Keywords: stroke, oleoylethanolamide, OEA, lipid nanoparticles, neuroprotective, positron emission tomography, PET

Despite the development of therapeutic interventions to prevent mortality following myocardial infarction (MI), there is a significant long-term risk of developing heart failure (HF). Injectable collagen hydrogels have demonstrated considerable promise as a therapeutic solution to reduce adverse ventricle remodeling associated with the development of HF post-MI. Matrix metalloproteinases (MMPs) are proteolytic enzymes involved in the degradation of the structural components of the extracellular matrix (ECM). The activation of MMPs following MI is an essential step in the cardiac repair process. However, uncontrolled enzymatic activity during this time has been associated with the formation of adverse fibrosis. Given the role of the proteases in tissue remodeling, MMPs may be a potential biomarker to predict the development of HF. This thesis work seeks to examine the effect of a novel hydrogel matrix therapy on cardiac tissue post-MI using broad-spectrum MMP-targeted radiotracer, [18F]BR3531. In Study 1, serial positron emission tomography (PET) imaging was performed to elucidate the spatial and temporal binding of [18F]BR351 post-MI using a murine model. Imaging was performed by administering [18F]BR351 at time points corresponding with periods of peak MMP activation post-MI. In vivo PET imaging and in vitro autoradiography demonstrated decreased [18F]BR351 binding in the infarct region. In Study 2, the model was used to evaluate the efficacy of a therapeutic collagen hydrogel to attenuate tissue remodeling. The groups that received the matrix treatment exhibited improved [18F]BR351 uptake in the infarct region. However, conflicting results between in vivo imaging and in vitro autoradiography, and immunohistochemistry using MMP2 and MMP9 indicate that [18F]BR351 may not be suited for MMP imaging in mouse models of MI.

Background We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection–Diffusion–Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues. Results Interstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal). Conclusion Our spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.

The serotonin 1B (5-HT1B) receptor has lately received considerable interest in relation to psychiatric and neurological diseases, partly due to findings based on quantification using Positron Emission Tomography (PET). Although the brainstem is an important structure in this regard, PET radioligand binding quantification in brainstem areas often shows poor reliability. This study aims to improve PET quantification of 5-HT1B receptor binding in the brainstem. Volumes of interest (VOIs) were selected based on a 3D [3H]AZ10419369 Autoradiography brainstem model, which visualized 5-HT1B receptor distribution in high resolution. Two previously developed VOI delineation methods were tested and compared to a conventional manual method. For a method based on template data, a [11C]AZ10419369 PET template was created by averaging parametric binding potential (BPND) images of 52 healthy subjects. VOIs were generated based on a predefined volume and BPND thresholding and subsequently applied to test-retest [11C]AZ10419369 parametric BPND images of 8 healthy subjects. For a method based on individual subject data, VOIs were generated directly on each individual parametric image. Both methods showed improved reliability compared to a conventional manual VOI. The VOIs created with [11C]AZ10419369 template data can be automatically applied to future PET studies measuring 5-HT1B receptor binding in the brainstem.

Statins are 3-hydroxy-3-methylglutaryl- coenzyme A reductase inhibitors that are widely used to prevent cardiovascular diseases. However, a series of pleiotropic mechanisms have been associated with statins, particularly with atorvastatin. Therefore, the assessment of [F-18]atorvastatin kinetics with positron emission tomography (PET) may elucidate the mechanism of action of statins and the impact of sexual dimorphism, which is one of the most debated interindividual variations influencing the therapeutic efficacy. [F-18]Atorvastatin was synthesized via a previously optimized F-18-deoxyfluorination strategy, used for preclinical PET studies in female and male Wistar rats (n = 7 for both groups), and for subsequent ex vivo biodistribution assessment. PET data were fitted to several pharmacokinetic models, which allowed for estimating relevant kinetic parameters. Both PET imaging and biodistribution studies showed negligible uptake of [F-18]atorvastatin in all tissues compared with the primary target organ (liver), excretory pathways (kidneys and small intestine), and stomach. Uptake of [F-18]atorvastatin was 38 +/- 3% higher in the female liver than in the male liver. The irreversible 2-tissue compartment model showed the best fit to describe [F-18]atorvastatin kinetics in the liver. A strong correlation (R-2 > 0.93) between quantitative Ki (the radiotracer's unidirectional net rate of influx between compartments) and semi-quantitative liver's SUV (standard uptake value), measured between 40 to 90 min, showed potential to use the latter parameter, which circumvents the need for blood sampling as a surrogate of Ki for monitoring [F-18]atorvastatin uptake. Preclinical assays showed faster uptake and clearance for female rats compared to males, seemingly related to a higher efficiency for exchanges between the arterial input and the hepatic tissue. Due to the slow [F-18]atorvastatin kinetics, equilibrium between the liver and plasma concentration was not reached during the time frame studied, making it difficult to obtain sufficient and accurate kinetic information to quantitatively characterize the radiotracer pharmacokinetics over time. Nevertheless, the reported results suggest that the SUV can potentially be used as a simplified measure, provided all scans are performed at the same time point. Preclinical PET-studies with [F-18]atorvastatin showed faster uptake and clearance in female compared to male rats, apparently related to higher efficiency for exchange between arterial blood and hepatic tissue.

Aluminum (Al) excess and hypercholesterinaemia are established risks of Alzheimer’s disease (AD). The aim of this study was to establish an AD-resembling hypercholesterinaemic animal model—with the involvement of 8 week and 48 week-old Fischer-344 rats—by Al administration for the safe and rapid verification of β-amyloid-targeted positron emission tomography (PET) radiopharmaceuticals. Measurement of lipid parameters and β-amyloid–affine [11C]C-Pittsburgh Compound B ([11C]C-PIB) PET examinations were performed. Compared with the control, the significantly elevated cholesterol and LDL levels of the rats receiving the cholesterol-rich diet support the development of hypercholesterinaemia (p ≤ 0.01). In the older cohort, a notably increased age-related radiopharmaceutical accumulation was registered compared to in the young (p ≤ 0.05; p ≤ 0.01). A monotherapy-induced slight elevation of mean standardised uptake values (SUVmean) was statistically not significant; however, adult rats administered a combined diet expressed remarkable SUVmean increment compared to the adult control (SUVmean: from 0.78 ± 0.16 to 1.99 ± 0.28). One and two months after restoration to normal diet, the cerebral [11C]C-PIB accumulation of AD-mimicking animals decreased by half and a third, respectively, to the baseline value. The proposed in vivo Al-induced AD-resembling animal system seems to be adequate for the understanding of AD neuropathology and future drug testing and radiopharmaceutical development.

The low response rates associated with immune checkpoint inhibitor (ICI) use has led to a surge in research investigating adjuvant combination strategies in an attempt to enhance efficacy. Repurposing existing drugs as adjuvants accelerates the pace of cancer immune therapy research; however, many combinations exacerbate the immunogenic response elicited by ICIs and can lead to adverse immune-related events. Metformin, a widely used type 2 diabetes drug is an ideal candidate to repurpose as it has a good safety profile and studies suggest that metformin can modulate the tumour microenvironment, promoting a favourable environment for T cell activation but has no direct action on T cell activation on its own. In the current study we used PET imaging with [18F]AlF-NOTA-KCNA3P, a radiopharmaceutical specifically targeting KV1.3 the potassium channel over-expressed on active effector memory T-cells, to determine whether combining PD1 with metformin leads to an enhanced immunological memory response in a preclinical colorectal cancer model. Flow cytometry was used to assess which immune cell populations infiltrate the tumours in response to the treatment combination. Imaging with [18F]AlF-NOTA-KCNA3P demonstrated that adjuvant metformin significantly improved anti-PD1 efficacy and led to a robust anti-tumour immunological memory response in a syngeneic colon cancer model through changes in tumour infiltrating effector memory T-cells.

Background CD4+ T cells are central inflammatory mediators in the pathogenesis of autoimmune rheumatoid arthritis (RA), as they are one of the dominating cell types in synovial inflammation. Molecular imaging of CD4+ T cells has potential role for early detection and monitoring of RA. Here, we developed a new radiotracer for in vivo immunoPET imaging of murine CD4+ T cells and tested it in the collagen-induced arthritis (CIA) mouse model of human RA. Results The tracer, [64Cu]Cu-NOTA-CD4-F(ab)’2 ([64Cu]Cu-NOTA-CD4), was generated from F(ab)’2 fragments of R-anti-mouse CD4 antibodies conjugated to the 2-S-(isothiocyanatbenzyl)-1,4,7-triazacyclononane-1,4,7-triacetic acid (p-SCN-Bn-NOTA) chelator and radiolabeled with copper-64. Accumulation of the tracer and isotype control was evaluated in the CIA model and mice receiving whole-body irradiation (WBI) (5 Gy). The potential of [64Cu]Cu-NOTA-CD4 for response assessment was evaluated in CIA induced mice treated with dexamethasone (DXM). Imaging data were compared with flow cytometry and immunohistochemistry (IHC) of inflammatory cells including CD4+ T cells. [64Cu]Cu-NOTA-CD4 showed increased accumulation in T cell-rich tissues compared with isotype control (p 64Cu]Cu-NOTA-CD4 was observed in T cell-depleted tissue (p + T cells in CIA mice. Conclusions We developed and evaluated a new radiotracer, [64Cu]Cu-NOTA-CD4, for immunoPET imaging of murine CD4+ T cells. [64Cu]Cu-NOTA-CD4 was successfully synthesized by F(ab)’2 fragments of R-anti-mouse CD4 antibodies conjugated to a chelator and radiolabeled with copper-64. We found that our novel CD4 PET tracer can be used for noninvasive visualization of murine CD4+ T cells.

Gastrin-releasing peptide receptors (GRPR) are overexpressed in prostate cancer (PCa). Since bombesin analogue aminobenzoic-acid (AMBA) binds to GRPR with high affinity, scandium-44 conjugated AMBA is a promising radiotracer in the PET diagnostics of GRPR positive tumors. Herein, the GRPR specificity of the newly synthetized [44Sc]Sc-NODAGA-AMBA was investigated in vitro and in vivo applying PCa PC-3 xenograft. After the in-vitro assessment of receptor binding, PC-3 tumor-bearing mice were injected with [44Sc]Sc/[68Ga]Ga-NODAGA-AMBA (in blocking studies with bombesin) and in-vivo PET examinations were performed to determine the radiotracer uptake in standardized uptake values (SUV). 44Sc/68Ga-labelled NODAGA-AMBA was produced with high molar activity (approx. 20 GBq/µmoL) and excellent radiochemical purity. The in-vitro accumulation of [44Sc]Sc-NODAGA-AMBA in PC-3 cells was approximately 25-fold higher than that of the control HaCaT cells. Relatively higher uptake was found in vitro, ex vivo, and in vivo in the same tumor with the 44Sc-labelled probe compared to [68Ga]Ga-NODAGA-AMBA. The GRPR specificity of [44Sc]Sc-NODAGA-AMBA was confirmed by significantly (p ≤ 0.01) decreased %ID and SUV values in PC-3 tumors after bombesin pretreatment. The outstanding binding properties of the novel [44Sc]Sc-NODAGA-AMBA to GRPR outlines its potential to be a valuable radiotracer in the imaging of GRPR-positive PCa.

Background Inflammation of patients joints with severe disease activity of rheumatoid arthritis (RA) has already been visualized and quantified by 2-[18F]fluoro-2-deoxy-D-glucose positron emission computed tomography ([18F] FDG PET/CT), but little is known about the metabolic status and its relationship with clinical and ultrasonography (US) metrology in patients with low/moderate activity or in remission. Methods Clinical assessments [based on 28-joint disease activity score (DAS28-CRP) and Clinical Disease Activity Index (CDAI)], [18F] FDG PET/CT, US and X-ray were performed on 63 RA patients classified into remission or low/moderate or severe disease activity groups. PET/CT was visually and then semi-quantitatively analysed by determining the standardized uptake value (SUV) of positive joints. Results Of the 1764 joints, 21.1% were tender only, 13.7% swollen only, 27.6% tender or swollen, 7.3% tender and swollen, 20.5% PET/CT-positive and 8.6% US-positive. PET and US measurements were correlated, albeit with poor concordance. The positive predictive value of PET/CT for clinical evaluation (tender and/or swollen) was low, whereas its negative predictive value was high. Highly significant differences were found with the number of PET/CT-positive joints and with cumulative SUV between “severe” and “non-severe” patients (including those in remission and those with low/moderate activity) and not between those classified as “remission” and “non-remission” or “remission” and “low/moderate activity”. Moreover, the correlation between PET/CT measurements and clinical activity was positive only in the CDAI severe disease group. In patients in remission or with low/moderate activity, only 20–30% of joints were PET/CT-negative. In remission, PET/CT and US were positive in different joints, and PET/CT-positive but US-negative joints mainly exhibited RA (38.1%) or normal (49.2%) and not osteoarthritic (12.7%) X-ray patterns. Conclusions [18F] FDG PET/CT was effective at distinguishing patients with severely active disease from other patients. In non-severe RA patients, including those in remission, PET/CT results are discordant from US and clinical observations. A longitudinal analysis is needed to explore the clinical relevance of such infra-clinical disease.

The importance of machine learning (ML) in the clinical environment increases constantly. Differentiation of pathological from physiological tracer-uptake in positron emission tomography/computed tomography (PET/CT) images is considered time-consuming and attention intensive, hence crucial for diagnosis and treatment planning. This study aimed at comparing and validating supervised ML algorithms to classify pathological uptake in prostate cancer (PC) patients based on prostate-specific membrane antigen (PSMA)-PET/CT. Retrospective analysis of 68Ga-PSMA-PET/CTs of 72 PC patients resulted in a total of 77 radiomics features from 2452 manually delineated hotspots for training and labeled pathological (1629) or physiological (823) as ground truth (GT). As the held-out test dataset, 331 hotspots (path.:128, phys.: 203) were delineated in 15 other patients. Three ML classifiers were trained and ranked to assess classification performance. As a result, a high overall average performance (area under the curve (AUC) of 0.98) was achieved, especially to detect pathological uptake (0.97 mean sensitivity). However, there is still room for improvement to detect physiological uptake (0.82 mean specificity), especially for glands. The ML algorithm applied to manually delineated lesions predicts hotspot labels with high accuracy on unseen data and may be an important tool to assist in clinical diagnosis.

Background The deposition of β-amyloid (Aβ) in the brain is a biomarker of Alzheimer’s disease (AD). Highly sensitive Aβ positron emission tomography (PET) imaging plays an essential role in diagnosing and evaluating the therapeutic effects of AD. Aim To synthesize a new Aβ tracer [18F]DRKXH1 (5-(4-(6-(2-[18]fluoroethoxy)ethoxy)imidazo[1,2-alpha]pyridin-2-yl)phenyl) and evaluate the tracer performance by biodistribution analysis, in vivo small-animal PET-CT dynamic scan, ex vivo and in vitro autoradiography, and PET in human subjects. Methods [18F]DRKXH1 was synthesized automatically by the GE FN module. Log D (pH 7.4) and biodistribution of [18F]DRKXH1 were investigated. Small-animal-PET was used for [18F]DRKXH1 and [18F]AV45 imaging study in AD transgenic mice (APPswe/PSEN1dE9) and age-matched normal mice. The distribution volume ratios (DVR) and standardized uptake value ratios (SUVRs) were calculated with the cerebellum as the reference region. The deposition of Aβ plaques in the brain of AD transgenic mice was determined by ex vivo autoradiography and immunohistochemistry. In vitro autoradiography was performed in the postmortem brain sections of AD patients and healthy controls. Two healthy control subjects and one AD patient was subjected to in vivo PET study using [18F]DRKXH1. Results The yield of [18F]DRKXH1 was 40%, and the specific activity was 156.64 ± 11.55 GBq/μmol. [18F]DRKXH1 was mainly excreted through the liver and kidney. The small-animal PET study showed high initial brain uptake and rapid washout of [18F]DRKXH1. The concentration of [18F]DRKXH1 was detected in the cortex and hippocampus of AD transgenic mice brain. The cortex DVR of AD transgenic mice was higher than that of WT mice (P 18F]-DRKXH1 is higher than that of [18F]-AV45 (1.29 ± 0.05 vs. 1.05 ± 0.08; t = 5.33, P = 0.0003). Autoradiography of postmortem human brain sections showed [18F]DRKXH1-labeled Aβ plaques in the AD brain. The AD patients had high retention in cortical regions, while healthy control subjects had uniformly low radioactivity uptake. Conclusions [18F]DRKXH1 is an Aβ tracer with high sensitivity in preclinical study and has the potential for in vivo detection of the human brain.

Objectives: Combined positron emission tomography/computed tomography (PET/CT) has gradually advanced with the introduction of newly developed techniques. However, the recent status of imaging techniques (e.g., scanning range, availability of correction methods, and decisions on performing delayed scan) in oncologic PET/CT with 18F-fluorodeoxyglucose (18F-FDG) in Japan is unclear. We conducted a nationwide cross-sectional survey to document 18F-FDG PET/CT protocols and clarify the recent status of imaging techniques for oncologic 18F-FDG PET/CT in Japan.Methods: We conducted a web survey hosted by the Japanese Society of Radiological Technology between October and December 2017. The questionnaire included nine items on the demographics of the respondents, their scan protocols, and additional imaging to their routine protocols.Results: We received responses from 119 Japanese technologists who performed 18F-FDG PET/CT in practice. Almost all the respondents stated that the scanning range was from the top of the head to the pelvis or mid-thigh region. Newly developed techniques were used by fewer than half of the respondents. Most respondents performed additional imaging in consultation with physicians, such as delayed imaging (83%) or an extended scanning range for early imaging (55%).Conclusions: Our survey helps in clarifying the recent state of oncologic 18F-FDG PET/CT imaging techniques in Japan. Given that 18F-FDG PET/CT practices most frequently performed additional imaging along with their routine scan protocol, the practice constitutes the most varied examination performed in Japanese nuclear medicine.

As a serine hydrolase, monoacylglycerol lipase (MAGL) is principally responsible for the metabolism of 2-arachidonoylglycerol (2-AG) in the central nervous system (CNS), leading to the formation of arachidonic acid (AA). Dysfunction of MAGL has been associated with multiple CNS disorders and symptoms, including neuroinflammation, cognitive impairment, epileptogenesis, nociception and neurodegenerative diseases. Inhibition of MAGL provides a promising therapeutic direction for the treatment of these conditions, and a MAGL positron emission tomography (PET) probe would greatly facilitate preclinical and clinical development of MAGL inhibitors. Herein, we design and synthesize a small library of fluoropyridyl-containing MAGL inhibitor candidates. Pharmacological evaluation of these candidates by activity-based protein profiling identified 14 as a lead compound, which was then radiolabeled with fluorine-18 via a facile SNAr reaction to form 2-[18F]fluoropyridine scaffold. Good blood–brain barrier permeability and high in vivo specific binding was demonstrated for radioligand [18F]14 (also named as [18F]MAGL-1902). This work may serve as a roadmap for clinical translation and further design of potent 18F-labeled MAGL PET tracers.

Background A growing body of evidence highlights sex differences in the diagnostic accuracy of cardiovascular imaging modalities. Nonetheless, the role of sex hormones in modulating myocardial perfusion and coronary flow reserve (CFR) is currently unclear. The aim of our study was to assess the impact of female and male sex hormones on myocardial perfusion and CFR. Methods Rest and stress myocardial perfusion imaging (MPI) was conducted by small animal positron emission tomography (PET) with [F-18]flurpiridaz in a total of 56 mice (7-8 months old) including gonadectomized (Gx) and sham-operated males and females, respectively. Myocardial [F-18]flurpiridaz uptake (% injected dose per mL, % ID/mL) was used as a surrogate for myocardial perfusion at rest and following intravenous regadenoson injection, as previously reported. Apparent coronary flow reserve (CFRApp) was calculated as the ratio of stress and rest myocardial perfusion. Left ventricular (LV) morphology and function were assessed by cardiac magnetic resonance (CMR) imaging. Results Orchiectomy resulted in a significant decrease of resting myocardial perfusion (Gx vs. sham, 19.4 +/- 1.0 vs. 22.2 +/- 0.7 % ID/mL, p = 0.034), while myocardial perfusion at stress remained unchanged (Gx vs. sham, 27.5 +/- 1.2 vs. 27.3 +/- 1.2 % ID/mL, p = 0.896). Accordingly, CFRApp was substantially higher in orchiectomized males (Gx vs. sham, 1.43 +/- 0.04 vs. 1.23 +/- 0.05, p = 0.004), and low serum testosterone levels were linked to a blunted resting myocardial perfusion (r = 0.438, p = 0.020) as well as an enhanced CFRApp (r = -0.500, p = 0.007). In contrast, oophorectomy did not affect myocardial perfusion in females. Of note, orchiectomized males showed a reduced LV mass, stroke volume, and left ventricular ejection fraction (LVEF) on CMR, while no such effects were observed in oophorectomized females. Conclusion Our experimental data in mice indicate that sex differences in myocardial perfusion are primarily driven by testosterone. Given the diagnostic importance of PET-MPI in clinical routine, further studies are warranted to determine whether testosterone levels affect the interpretation of myocardial perfusion findings in patients., European Journal of Nuclear Medicine and Molecular Imaging, 49, ISSN:1619-7070, ISSN:1619-7089

The N-methyl-D-aspartate receptor (NMDAR) plays a crucial role in neurodegenerative diseases such as Alzheimer’s disease and in the treatment of major depression by new fast-acting antidepressants such as ketamine. Given their broad implications, GluN2B-containing NMDARs have been of large interest as diagnostic and therapeutic targets. Recently, (R)-11C-Me-NB1 was investigated preclinically and shown to be a promising radioligand for imaging GluN2B subunits. Here, we report on the performance characteristics of this novel radioligand in a first-in-human PET study. Methods: Six healthy male subjects were scanned twice on a fully-integrated PET/MR scanner with (R)-11C-Me-NB1 for 120 min. Brain uptake and tracer distribution over time were investigated by standardized uptake values (SUV). Test-retest reliability was assessed with the absolute percentage difference (APD) and the coefficient of variation (COV). Exploratory total volumes of distribution (VT) were computed using an arterial input function and the Logan plot as well as a constrained two-tissue compartment model with K1/k2 coupled (2TCM). SUV was correlated with VT to investigate its potential as a surrogate marker of GluN2B expression. Results: High and heterogeneous radioligand uptake was observed across the entire gray matter with reversible kinetics within the scan time. SUV APD ranged from 6.8 - 8.5% and COV from 4.9 - 6.0%, indicating a high test-retest reliability. A moderate correlation was found between SUV averaged from 70-90 min and VT using Logan plot (Spearman’s rho = 0.44). Correlation between VT Logan and 2TCM was r= 0.76. Conclusion: The novel radioligand, (R)-11C-Me-NB1, was highly effective in mapping GluN2B-enriched NMDARs in the human brain. With a heterogeneous uptake and a high test-retest reliability, this radioligand offers promise to deepen our understanding of the GluN2B-containing NMDA receptor in the pathophysiology and treatment of neuropsychiatric disease such as Alzheimer’s disease and major depression. Additionally, it could help in the selection of appropriate doses of GluN2B-targeting drugs. ISSN:0097-9058 ISSN:0022-3123 ISSN:0161-5505 ISSN:2159-662X ISSN:1535-5667

Purpose Translocator protein 18-kDa (TSPO) imaging with positron emission tomography (PET) is widely used in research studies of brain diseases that have a neuro-immune component. Quantification of TSPO PET images, however, is associated with several challenges, such as the lack of a reference region, a genetic polymorphism affecting the affinity of the ligand for TSPO, and a strong TSPO signal in the endothelium of the brain vessels. These challenges have created an ongoing debate in the field about which type of quantification is most useful and whether there is an appropriate simplified model. Methods This review focuses on the quantification of TSPO radioligands in the human brain. The various methods of quantification are summarized, including the gold standard of compartmental modeling with metabolite-corrected input function as well as various alternative models and non-invasive approaches. Their advantages and drawbacks are critically assessed. Results and conclusions Researchers employing quantification methods for TSPO should understand the advantages and limitations associated with each method. Suggestions are given to help researchers choose between these viable alternative methods.

Purpose Adult granulosa cell tumors (AGCTs) of the ovary represent a rare malignancy in which timing and choice of treatment is a clinical challenge. This study investigates the value of FDG-PET/CT and FES-PET/CT in monitoring recurrent AGCTs and assessing eligibility for anti-hormonal treatment. Materials and methods We evaluated 22 PET/CTs from recurrent AGCT patients to determine tumor FDG (n = 16) and FES (n = 6) uptake by qualitative and quantitative analysis. We included all consecutive patients from two tertiary hospitals between 2003-2020. Expression of ERα and ERβ and mitoses per 2 mm2 were determined by immunohistochemistry and compared to FES and FDG uptake, respectively. Results Qualitative assessment showed low-to-moderate FDG uptake in most patients (14/16), and intense uptake in 2/16. One patient with intense tumor FDG uptake had a high mitotic rate (18 per 2 mm2) Two out of six patients showed FES uptake on PET/CT at qualitative analysis. Lesion-based quantitative assessment showed a mean SUVmax of 2.4 (± 0.9) on FDG-PET/CT and mean SUVmax of 1.7 (± 0.5) on FES-PET/CT. Within patients, expression of ERα and ERβ varied and did not seem to correspond with FES uptake. In one FES positive patient, tumor locations with FES uptake remained stable or decreased in size during anti-hormonal treatment, while all FES negative locations progressed. Conclusions This study shows that in AGCTs, FDG uptake is limited and therefore FDG-PET/CT is not advised. FES-PET/CT may be useful to non-invasively capture the estrogen receptor expression of separate tumor lesions and thus assess the potential eligibility for hormone treatment in AGCT patients.

PurposeProton therapy precisely delivers radiation to cancers to cause damaging strand breaks to cellular DNA, kill malignant cells, and stop tumor growth. Therapeutic protons also generate short-lived activated nuclei of carbon, oxygen, and nitrogen atoms in patients as a result of atomic transmutations that are imaged by positron emission tomography (PET). We hypothesized that the transition of 18O to 18F in an 18O-substituted nucleoside irradiated with therapeutic protons may result in the potential for combined diagnosis and treatment for cancer with proton therapy.Materials and MethodsReported here is a feasibility study with a therapeutic proton beam used to irradiate H218O to a dose of 10 Gy produced by an 85 MeV pristine Bragg peak. PET imaging initiated >45 minutes later showed an 18F decay signal with T1/2 of ∼111 minutes.ResultsThe 18O to 18F transmutation effect on cell survival was tested by exposing SQ20B squamous carcinoma cells to physiologic 18O-thymidine concentrations of 5 μM for 48 hours followed by 1- to 9-Gy graded doses of proton radiation given 24 hours later. Survival analyses show radiation sensitization with a dose modification factor (DMF) of 1.2.ConclusionsThese data support the idea of therapeutic transmutation in vitro as a biochemical consequence of proton activation of 18O to 18F in substituted thymidine enabling proton radiation enhancement in a cancer cell. 18O-substituted molecules that incorporate into cancer targets may hold promise for improving the therapeutic window of protons and can be evaluated further for postproton therapy PET imaging.

Duchenne muscular dystrophy (DMD) is a neuromuscular disorder caused by dystrophin loss—notably within muscles and the central neurons system. DMD presents as cognitive weakness, progressive skeletal and cardiac muscle degeneration until pre-mature death from cardiac or respiratory failure. Innovative therapies have improved life expectancy; however, this is accompanied by increased late-onset heart failure and emergent cognitive degeneration. Thus, better assessment of dystrophic heart and brain pathophysiology is needed. Chronic inflammation is strongly associated with skeletal and cardiac muscle degeneration; however, neuroinflammation’s role is largely unknown in DMD despite being prevalent in other neurodegenerative diseases. Here, we present an inflammatory marker translocator protein (TSPO) positron emission tomography (PET) protocol for in vivo concomitant assessment of immune cell response in hearts and brains of a dystrophin-deficient mouse model [mdx:utrn(+/−)]. Preliminary analysis of whole-body PET imaging using the TSPO radiotracer, [18F]FEPPA in four mdx:utrn(+/−) and six wildtype mice are presented with ex vivo TSPO-immunofluorescence tissue staining. The mdx:utrn(+/−) mice showed significant elevations in heart and brain [18F]FEPPA activity, which correlated with increased ex vivo fluorescence intensity, highlighting the potential of TSPO-PET to simultaneously assess presence of cardiac and neuroinflammation in dystrophic heart and brain, as well as in several organs within a DMD model.

Radiopharmaceuticals based on the highly potent FAP inhibitor (FAPi) UAMC-1110 have shown great potential in molecular imaging, but the short tumor retention time of the monomers do not match the physical half-lives of the important therapeutic radionuclides 177Lu and 225Ac. This was improved with the dimer DOTAGA.(SA.FAPi)2, but pharmacological and radiolabeling properties still need optimization. Therefore, the novel FAPi homodimers DO3A.Glu.(FAPi)2 and DOTAGA.Glu.(FAPi)2. were synthesized and quantitatively radiolabeled with 68Ga, 90Y, 177Lu and 225Ac. The radiolabeled complexes showed high hydrophilicity and were generally stable in human serum (HS) and phosphate-buffered saline (PBS) at 37 °C over two half-lives, except for [225Ac]Ac-DOTAGA.Glu.(FAPi)2 in PBS. In vitro affinity studies resulted in subnanomolar IC50 values for FAP and high selectivity for FAP over the related proteases PREP and DPP4 for both compounds as well as for [natLu]Lu-DOTAGA.Glu.(FAPi)2. In a first proof-of-principle patient study (medullary thyroid cancer), [177Lu]Lu-DOTAGA.Glu.(FAPi)2 was compared to [177Lu]Lu-DOTAGA.(SA.FAPi)2. High uptake and long tumor retention was observed in both cases, but [177Lu]Lu-DOTAGA.Glu.(FAPi)2 significantly reduces uptake in non-target and critical organs (liver, colon). Overall, the novel FAPi homodimer DOTAGA.Glu.(FAPi)2 showed improved radiolabeling in vitro and pharmacological properties in vivo compared to DOTAGA.(SA.FAPi)2. [177Lu]Lu-DOTAGA.Glu.(FAPi)2 and [225Ac]Ac-DOTAGA.Glu.(FAPi)2 appear promising for translational application in patients.

Purpose Epilepsy is one of the most disabling neurological disorders, which affects all age groups and often results in severe consequences. Since misdiagnoses are common, many pediatric patients fail to receive the correct treatment. Recently, 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) imaging has been used for the evaluation of pediatric epilepsy. However, the epileptic focus is very difficult to be identified by visual assessment since it may present either hypo- or hyper-metabolic abnormality with unclear boundary. This study aimed to develop a novel symmetricity-driven deep learning framework of PET imaging for the identification of epileptic foci in pediatric patients with temporal lobe epilepsy (TLE). Methods We retrospectively included 201 pediatric patients with TLE and 24 age-matched controls who underwent 18F-FDG PET-CT studies. 18F-FDG PET images were quantitatively investigated using 386 symmetricity features, and a pair-of-cube (PoC)-based Siamese convolutional neural network (CNN) was proposed for precise localization of epileptic focus, and then metabolic abnormality level of the predicted focus was calculated automatically by asymmetric index (AI). Performances of the proposed framework were compared with visual assessment, statistical parametric mapping (SPM) software, and Jensen-Shannon divergence-based logistic regression (JS-LR) analysis. Results The proposed deep learning framework could detect the epileptic foci accurately with the dice coefficient of 0.51, which was significantly higher than that of SPM (0.24, P < 0.01) and significantly (or marginally) higher than that of visual assessment (0.31–0.44, P = 0.005–0.27). The area under the curve (AUC) of the PoC classification was higher than that of the JS-LR (0.93 vs. 0.72). The metabolic level detection accuracy of the proposed method was significantly higher than that of visual assessment blinded or unblinded to clinical information (90% vs. 56% or 68%, P < 0.01). Conclusion The proposed deep learning framework for 18F-FDG PET imaging could identify epileptic foci accurately and efficiently, which might be applied as a computer-assisted approach for the future diagnosis of epilepsy patients. Trial registration NCT04169581. Registered November 13, 2019 Public site: https://clinicaltrials.gov/ct2/show/NCT04169581

Purpose Standardized uptake value ratio (SUVr) used to quantify amyloid-β burden from amyloid-PET scans can be biased by variations in the tracer’s nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we propose a novel amyloid-PET quantification approach that harnesses the intermodal image translation capability of convolutional networks to remove this undesirable source of variability. Methods Paired MR and PET images exhibiting very low specific uptake were selected from a Singaporean amyloid-PET study involving 172 participants with different severities of CeVD. Two convolutional neural networks (CNN), ScaleNet and HighRes3DNet, and one conditional generative adversarial network (cGAN) were trained to map structural MR to NS PET images. NS estimates generated for all subjects using the most promising network were then subtracted from SUVr images to determine specific amyloid load only (SAβL). Associations of SAβL with various cognitive and functional test scores were then computed and compared to results using conventional SUVr. Results Multimodal ScaleNet outperformed other networks in predicting the NS content in cortical gray matter with a mean relative error below 2%. Compared to SUVr, SAβL showed increased association with cognitive and functional test scores by up to 67%. Conclusion Removing the undesirable NS uptake from the amyloid load measurement is possible using deep learning and substantially improves its accuracy. This novel analysis approach opens a new window of opportunity for improved data modeling in Alzheimer’s disease and for other neurodegenerative diseases that utilize PET imaging.

Imaging tools are potentially able to provide valuable data regarding the development of an efficient vaccine against viral diseases. Tracking immune cells in vivo by imaging modalities can help us understand the intrinsic behaviors of immune cells in response to vaccine components. Imaging patterns at the vaccination site and draining lymph nodes might provide useful information about the vaccine potency. Besides, serial lung CT imaging has been purposed to evaluate vaccine efficiency regarding its protection against typical lung lesions of viral pneumonias. On the other hand, vaccination causes various confusing radiologic patterns that pose diagnostic challenges for clinicians and pitfalls for reading radiologists. This manuscript reviews potential applications of imaging modalities in the process of vaccine development and also goes over some of the imaging findings/pitfalls following vaccination., Highlights • Imaging tools could track the immune cell dynamics in vivo, which holds valuable research attention in the vaccination field. • Serial CT imaging might be a great indicator of vaccine efficiency in research setting. • Vaccination causes various confusing radiologic patterns that pose diagnostic challenges for clinicians and radiologists.

Yanlei Ji,1,2 Qingtao Qiu,3 Jing Fu,4 Kai Cui,5 Xia Chen,6 Ligang Xing,3 Xiaorong Sun6 1Department of Ultrasound Medicine, Shandong Cancer Hospital and Institute, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People’s Republic of China; 2Department of Ultrasound Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, People’s Republic of China; 3Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, People’s Republic of China; 4Department of Ultrasound Medicine, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong 250014, People’s Republic of China; 5Department of PET/CT, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250033, People’s Republic of China; 6Department of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, People’s Republic of ChinaCorrespondence: Xiaorong SunDepartment of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 440 Jiyan Road, Jinan, Shandong 250117, People’s Republic of ChinaTel/Fax + 86-531-67626287Email 251400067@qq.comPurpose: To investigate the impact of staging on differences in glucose metabolic heterogeneity between lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) by 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) textural analysis and to develop a stage-specific PET radiomic prediction model to distinguish lung ADC from SCC.Patients and Methods: Patients who were histologically diagnosed with lung ADC or SCC and underwent pretreatment 18F-FDG PET/CT scans were retrospectively identified. Radiomic features were extracted from a semiautomatically outlined tumor region in the Chang-Gung Image Texture Analysis (CGITA) software package. The differences in radiomic parameters between lung ADC and SCC were compared stage-by-stage in 253 consecutive NSCLC patients with stages I to III disease. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature selection. A radiomic signature for each stage was subsequently constructed and evaluated. Then, an individual nomogram incorporating the radiomic signature and clinical risk factors was established and evaluated. The performance of the constructed models was assessed by receiver operating characteristic (ROC) curve analysis, and the nomogram was further validated by calibration curve analysis.Results: The performance of the radiomic signature for distinguishing lung ADC and SCC in both the training and validation cohorts was good, with AUCs of 0.883, 0.854, and 0.895 in the training cohort and 0.932, 0.944, and 0.886 in the validation cohort for stages I, II, and III NSCLC, respectively. The radiomic-clinical nomogram integrating radiomic features with independent clinical predictors exhibited more favorable discriminative performance, with AUCs of 0.982, 0.963, and 0.979 in the training cohort and 0.989, 0.984, and 0.978 in the validation cohort for stages I, II, and III, respectively.Conclusion: Differences in PET radiomic features between lung ADC and SCC varied in different stages. Stage-specific PET radiomic prediction models provided more favorable performance for discriminating the histological subtype of NSCLC.Keywords: non-small-cell lung cancer, positron emission tomography, PET, textural analysis, heterogeneity, staging

Background: Alterations of hypothalamic–pituitary–adrenal (HPA) axis activity and serotonergic signaling are implicated in the pathogenesis of human obesity and may contribute to its metabolic and mental complications. The association of these systems has not been investigated in human obesity. Objective: To investigate the relation of HPA responsiveness and serotonin transporter (5-HTT) availability in otherwise healthy individuals with obesity class II or III (OB) compared to non-obesity controls (NO). Study participants: Twenty-eight OB (21 females; age 36.6 ± 10.6 years; body mass index (BMI) 41.2 ± 5.1 kg/m2) were compared to 12 healthy NO (8 females; age 35.8 ± 7.4 years; BMI 22.4 ± 2.3 kg/m2), matched for age and sex. Methods: HPA axis responsiveness was investigated using the combined dexamethasone/corticotropin-releasing hormone (dex/CRH) test, and curve indicators were derived for cortisol and adrenocorticotropic hormone (ACTH). The 5-HTT selective tracer [11C]DASB was applied, and parametric images of the binding potentials (BPND) were calculated using the multilinear reference tissue model and evaluated by atlas-based volume of interest (VOI) analysis. The self-questionnaires of behavioral inhibition system/behavioral activation system (BIS/BAS) with subscales drive, fun-seeking and reward were assessed. Results: OB showed significant positive correlations of ACTH curve parameters with overall 5-HTT BPND (ACTHAUC: r = 0.39, p = 0.04) and 5-HTT BPND of the caudate nucleus (ACTHAUC: r = 0.54, p = 0.003). In NO, cortisol indicators correlated significantly with BPND in the hippocampus (cortisolAUC: r = 0.59, p = 0.04). In OB, BAS reward was inversely associated with the ACTHAUC (r = −0.49, p = 0.009). Conclusion: The present study supports a serotonergic-neuroendocrine association, which regionally differs between OB and NO. In OB, areas processing emotion and reward seem to be in-volved. The finding of a serotonergic HPA correlation may have implications for other diseases with dysregulated stress axis responsiveness, and for potential pharmacologic interven-tions.

Purpose End-of-life studies have validated the binary visual reads of 18F-labeled amyloid PET tracers as an accurate tool for the presence or absence of increased neuritic amyloid plaque density. In this study, the performance of a support vector machine (SVM)-based classifier will be tested against pathological ground truths and its performance determined in cognitively healthy older adults. Methods We applied SVM with a linear kernel to an 18F-Flutemetamol end-of-life dataset to determine the regions with the highest feature weights in a data-driven manner and to compare between two different pathological ground truths: based on neuritic amyloid plaque density or on amyloid phases, respectively. We also trained and tested classifiers based on the 10% voxels with the highest amplitudes of feature weights for each of the two neuropathological ground truths. Next, we tested the classifiers’ diagnostic performance in the asymptomatic Alzheimer’s disease (AD) phase, a phase of interest for future drug development, in an independent dataset of cognitively intact older adults, the Flemish Prevent AD Cohort-KU Leuven (F-PACK). A regression analysis was conducted between the Centiloid (CL) value in a composite volume of interest (VOI), as index for amyloid load, and the distance to the hyperplane for each of the two classifiers, based on the two pathological ground truths. A receiver operating characteristic analysis was also performed to determine the CL threshold that optimally discriminates between neuritic amyloid plaque positivity versus negativity, or amyloid phase positivity versus negativity, within F-PACK. Results The classifiers yielded adequate specificity and sensitivity within the end-of-life dataset (neuritic amyloid plaque density classifier: specificity of 90.2% and sensitivity of 83.7%; amyloid phase classifier: specificity of 98.4% and sensitivity of 84.0%). The regions with the highest feature weights corresponded to precuneus, caudate, anteromedial prefrontal, and also posterior inferior temporal and inferior parietal cortex. In the cognitively normal cohort, the correlation coefficient between CL and distance to the hyperplane was −0.66 for the classifier trained with neuritic amyloid plaque density, and −0.88 for the classifier trained with amyloid phases. This difference was significant. The optimal CL cut-off for discriminating positive versus negative scans was CL = 48–51 for the different classifiers (area under the curve (AUC) = 99.9%), except for the classifier trained with amyloid phases and based on the 10% voxels with highest feature weights. There the cut-off was CL = 26 (AUC = 99.5%), which closely matched the CL threshold for discriminating phases 0–2 from 3–5 based on the end-of-life dataset and the neuropathological ground truth. Discussion Among a set of neuropathologically validated classifiers trained with end-of-life cases, transfer to a cognitively normal population works best for a classifier trained with amyloid phases and using only voxels with the highest amplitudes of feature weights.

In recent years, the field of neuroimaging dramatically moved forward by means of the expeditious development of specific radioligands of novel targets. Among these targets, the synaptic vesicle glycoprotein 2A (SV2A) is a transmembrane protein of synaptic vesicles, present in all synaptic terminals, irrespective of neurotransmitter content. It is involved in key functions of neurons, focused on the regulation of neurotransmitter release. The ubiquitous expression in gray matter regions of the brain is the basis of its candidacy as a marker of synaptic density. Following the development of molecules derived from the structure of the anti-epileptic drug levetiracetam, which selectively binds to SV2A, several radiolabeled markers have been synthetized to allow the study of SV2A distribution with positron emission tomography (PET). These radioligands permit the evaluation of in vivo changes of SV2A distribution held to be a potential measure of synaptic density in physiological and pathological conditions. The use of SV2A as a biomarker of synaptic density raises important questions. Despite numerous studies over the last decades, the biological function and the expressional properties of SV2A remain poorly understood. Some functions of SV2A were claimed, but have not been fully elucidated. While the expression of SV2A is ubiquitous, stronger associations between SV2A and Υ amino butyric acid (GABA)-ergic rather than glutamatergic synapses were observed in some brain structures. A further issue is the unclear interaction between SV2A and its tracers, which reflects a need to clarify what really is detected with neuroimaging tools. Here, we summarize the current knowledge of the SV2A protein and we discuss uncertain aspects of SV2A biology and physiology. As SV2A expression is ubiquitous, but likely more strongly related to a certain type of neurotransmission in particular circumstances, a more extensive knowledge of the protein would greatly facilitate the analysis and interpretation of neuroimaging results by allowing the evaluation not only of an increase or decrease of the protein level, but also of the type of neurotransmission involved.

Over the last decades, there has been an increasing interest in dedicated preclinical imaging modalities for research in biomedicine. Especially in the case of positron emission tomography (PET), reconstructed images provide useful information of the morphology and function of an internal organ. PET data, stored as sinograms, involve the Radon transform of the image under investigation. The analytical approach to PET image reconstruction incorporates the derivative of the Hilbert transform of the sinogram. In this direction, in the present work we present a novel numerical algorithm for the inversion of the Radon transform based on Chebyshev polynomials of the first kind. By employing these polynomials, the computation of the derivative of the Hilbert transform of the sinogram is significantly simplified. Extending the mathematical setting of previous research based on Chebyshev polynomials, we are able to efficiently apply our new Chebyshev inversion scheme for the case of analytic preclinical PET image reconstruction. We evaluated our reconstruction algorithm on projection data from a small-animal image quality (IQ) simulated phantom study, in accordance with the NEMA NU 4-2008 standards protocol. In particular, we quantified our reconstructions via the image quality metrics of percentage standard deviation, recovery coefficient, and spill-over ratio. The projection data employed were acquired for three different Poisson noise levels: 100% (NL1), 50% (NL2), and 20% (NL3) of the total counts, respectively. In the uniform region of the IQ phantom, Chebyshev reconstructions were consistently improved over filtered backprojection (FBP), in terms of percentage standard deviation (up to 29% lower, depending on the noise level). For all rods, we measured the contrast-to-noise-ratio, indicating an improvement of up to 68% depending on the noise level. In order to compare our reconstruction method with FBP, at equal noise levels, plots of recovery coefficient and spill-over ratio as functions of the percentage standard deviation were generated, after smoothing the NL3 reconstructions with three different Gaussian filters. When post-smoothing was applied, Chebyshev demonstrated recovery coefficient values up to 14% and 42% higher, for rods 1–3 mm and 4–5 mm, respectively, compared to FBP, depending on the smoothing sigma values. Our results indicate that our Chebyshev-based analytic reconstruction method may provide PET reconstructions that are comparable to FBP, thus yielding a good alternative to standard analytic preclinical PET reconstruction methods.

Umbilical cord mesenchymal stem cell-derived extracellular vesicles (UC-MSC-EVs) have become an emerging strategy for treating various autoimmune and metabolic disorders, particularly diabetes. Delivery of UC-MSC-EVs is essential to ensure optimal efficacy of UC-MSC-EVs. To develop safe and superior EVs-based delivery strategies, we explored nuclear techniques including positron emission tomography (PET) to evaluate the delivery of UC-MSC-EVs in vivo. In this study, human UC-MSC-EVs were first successfully tagged with I-124 to permit PET determination. Intravenous (I.V.) and intra-arterial (I.A.) administration routes of [124I]I-UC-MSC-EVs were compared and evaluated by in vivo PET-CT imaging and ex vivo biodistribution in a non-diabetic Lewis (LEW) rat model. For I.A. administration, [124I]I-UC-MSC-EVs were directly infused into the pancreatic parenchyma via the celiac artery. PET imaging revealed that the predominant uptake occurred in the liver for both injection routes, and further imaging characterized clearance patterns of [124I]I-UC-MSC-EVs. For biodistribution, the uptake (%ID/gram) in the spleen was significantly higher for I.V. administration compared to I.A. administration (1.95 ± 0.03 and 0.43 ± 0.07, respectively). Importantly, the pancreas displayed similar uptake levels between the two modalities (0.20 ± 0.06 for I.V. and 0.24 ± 0.03 for I.A.). Therefore, our initial data revealed that both routes had similar delivery efficiency for [124I]I-UC-MSC-EVs except in the spleen and liver, considering that higher spleen uptake could enhance immunomodulatory application of UC-MSC-EVs. These findings could guide the development of safe and efficacious delivery strategies for UC-MSC-EVs in diabetes therapies, in which a minimally invasive I.V. approach would serve as a better delivery strategy. Further confirmation studies are ongoing.

The degree of acetylation of lysine residues on histones influences the accessibility of DNA and, furthermore, the gene expression. Histone deacetylases (HDACs) are overexpressed in various tumour diseases, resulting in the interest in HDAC inhibitors for cancer therapy. The aim of this work is the development of a novel 18F-labelled HDAC1/2-specific inhibitor with a benzamide-based zinc-binding group to visualize these enzymes in brain tumours by positron emission tomography (PET). BA3, exhibiting high inhibitory potency for HDAC1 (IC50 = 4.8 nM) and HDAC2 (IC50 = 39.9 nM), and specificity towards HDAC3 and HDAC6 (specificity ratios >230 and >2080, respectively), was selected for radiofluorination. The two-step one-pot radiosynthesis of [18F]BA3 was performed in a TRACERlab FX2 N radiosynthesizer by a nucleophilic aliphatic substitution reaction. The automated radiosynthesis of [18F]BA3 resulted in a radiochemical yield of 1%, a radiochemical purity of >96% and a molar activity between 21 and 51 GBq/µmol (n = 5, EOS). For the characterization of BA3, in vitro and in vivo experiments were carried out. The results of these pharmacological and pharmacokinetic studies indicate a suitable inhibitory potency of BA3, whereas the applicability for non-invasive imaging of HDAC1/2 by PET requires further optimization of the properties of this compound.

Antibodies are attractive as radioligands due to their outstanding specificity and high affinity, but their inability to cross the blood–brain barrier (BBB) limits their use for CNS targets. To enhance brain distribution, amyloid-β (Aβ) antibodies were fused to a transferrin receptor (TfR) antibody fragment, enabling receptor mediated transport across the BBB. The aim of this study was to label these bispecific antibodies with fluorine-18 and use them for Aβ PET imaging. Bispecific antibody ligands RmAb158-scFv8D3 and Tribody A2, both targeting Aβ and TfR, were functionalized with trans-cyclooctene (TCO) groups and conjugated with 18F-labeled tetrazines through an inverse electron demand Diels–Alder reaction performed at ambient temperature. 18F-labeling did not affect antibody binding in vitro, and initial brain uptake was high. Conjugates with the first tetrazine variant ([18F]T1) displayed high uptake in bone, indicating extensive defluorination, a problem that was resolved with the second and third tetrazine variants ([18F]T2 and [18F]T3). Although the antibody ligands’ half-life in blood was too long to optimally match the physical half-life of fluorine-18 (t1/2 = 110 min), [18F]T3-Tribody A2 PET seemed to discriminate transgenic mice (tg-ArcSwe) with Aβ deposits from wild-type mice 12 h after injection. This study demonstrates that 18F-labeling of bispecific, brain penetrating antibodies is feasible and, with further optimization, could be used for CNS PET imaging.

Voxel-based morphometry (VBM) analysis of nuclear Magnetic Resonance Imaging (MRI) data allows the identification of medial temporal lobe (MTL) atrophy and is widely used to assist the diagnosis of Alzheimer’s disease (AD). However, its reliability in the clinical environment has not yet been confirmed. To determine the credibility of VBM, amyloid positron emission tomography (PET) and VBM studies were compared retrospectively. Patients who underwent Pittsburgh Compound B (PiB) PET were retrospectively recruited. Ninety-seven patients were found to be amyloid negative and 116 were amyloid positive. MTL atrophy in the PiB positive group, as quantified by thin sliced 3D MRI and VBM software, was significantly more severe (p =0.0039) than in the PiB negative group. However, data histogram showed a vast overlap between the two groups. The area under the ROC curve (AUC) was 0.646. MMSE scores of patients in the amyloid negative and positive groups were also significantly different (p = 0.0028), and the AUC was 0.672. Thus, MTL atrophy could not reliably differentiate between amyloid positive and negative patients in a clinical setting, possibly due to the wide array of dementia-type diseases that exist other than AD.

Transferrin receptor 1 (TfR1) mediated transcytosis is an attractive strategy to enhance brain uptake of protein drugs, but translation remains a challenge. Here, a single domain shark antibody VNAR fragment (TXB2) with similar affinity to murine and human TfR1 was used to shuttle protein cargo into the brain. TXB2 was fused to a human IgG1 Fc domain (hFc) or to the amyloid-β (Aβ) antibody bapineuzumab (Bapi). TXB2-hFc displayed 20-fold higher brain concentrations compared with a control VNAR-hFc at 18 hours post-injection in wt mice. At the same time point, brain concentrations of Bapi-TXB2 was threefold higher than Bapi. In transgenic mice overexpressing human Aβ, the brain-to-blood concentration ratio increased with time due to interaction with intracerebral Aβ deposits. The relatively stable threefold difference between Bapi-TXB2 and Bapi was observed for up to 6 days after injection. PET imaging and ex vivo autoradiography revealed more parenchymal distribution of Bapi-TXB2 compared with Bapi. In conclusion, the TXB2 VNAR shuttle markedly increased brain uptake of protein cargo and increased brain concentrations of the Aβ binding antibody Bapi.