Relationship between neuroimaging and cognition in frontotemporal dementia: An FDG-PET and structural MRI study

BACKGROUND AND PURPOSE

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative condition with a prevalence comparable to Alzheimer's disease for patients under 65 years of age. Limited studies have examined the association between cognition and neuroimaging in FTD using different imaging modalities.

METHODS

We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both gray matter (GM) volume and glucose metabolism using magnetic resonance imaging and fluorodeoxyglucose (FDG)-PET in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for FDG-PET. Partial volume correction was applied to PET data to account for disease-related atrophy.

RESULTS

Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.46, p = .04). The association between whole-cortex FDG SUVR and MoCA scores was not significant (r = 0.37, p = .09). GM volumes of the frontal cortex (r = 0.54, p = .01), caudate (r = 0.62, p<.01), and insula (r = 0.57, p<.01) were also significantly correlated with MoCA, as were SUVR values of the insula (r = 0.51, p = .02), thalamus (r = 0.48, p = .03), and posterior cingulate cortex (PCC) (r = 0.47, p = .03).

CONCLUSIONS

Whole-cortex atrophy is associated with cognitive dysfunction, and this association is larger than for whole-cortex hypometabolism as measured with FDG-PET. At the regional level, focal atrophy and/or hypometabolism in the frontal cortex, insula, PCC, thalamus, and caudate seem to be important for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways.

The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [11C]UCB-J

PURPOSE

Aging is a major societal concern due to age-related functional losses. Synapses are crucial components of neural circuits, and synaptic density could be a sensitive biomarker to evaluate brain function. [11C]UCB-J is a positron emission tomography (PET) ligand targeting synaptic vesicle glycoprotein 2A (SV2A), which can be used to evaluate brain synaptic density in vivo.

METHODS

We evaluated age-related changes in gray matter synaptic density, volume, and blood flow using [11C]UCB-J PET and magnetic resonance imaging (MRI) in a wide age range of 80 cognitive normal subjects (21-83 years old). Partial volume correction was applied to the PET data.

RESULTS

Significant age-related decreases were found in 13, two, and nine brain regions for volume, synaptic density, and blood flow, respectively. The prefrontal cortex showed the largest volume decline (4.9% reduction per decade: RPD), while the synaptic density loss was largest in the caudate (3.6% RPD) and medial occipital cortex (3.4% RPD). The reductions in caudate are consistent with previous SV2A PET studies and likely reflect that caudate is the site of nerve terminals for multiple major tracts that undergo substantial age-related neurodegeneration. There was a non-significant negative relationship between volume and synaptic density reductions in 16 gray matter regions.

CONCLUSION

MRI and [11]C-UCB-J PET showed age-related decreases of gray matter volume, synaptic density, and blood flow; however, the regional patterns of the reductions in volume and SV2A binding were different. Those patterns suggest that MR-based measures of GM volume may not be directly representative of synaptic density.

Identifying G6PC3 as a Potential Key Molecule in Hypoxic Glucose Metabolism of Glioblastoma Derived from the Depiction of 18F-Fluoromisonidazole and 18F-Fluorodeoxyglucose Positron Emission Tomography

Purpose

Glioblastoma is the most aggressive primary brain tumor, characterized by its distinctive intratumoral hypoxia. Sequential preoperative examinations using fluorine-18-fluoromisonidazole (18F-FMISO) and fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) could depict the degree of glucose metabolism with hypoxic condition. However, molecular mechanism of glucose metabolism under hypoxia in glioblastoma has been unclear. The aim of this study was to identify the key molecules of hypoxic glucose metabolism.

Methods

Using surgically obtained specimens, gene expressions associated with glucose metabolism were analyzed in patients with glioblastoma (n = 33) who underwent preoperative 18F-FMISO and 18F-FDG PET to identify affected molecules according to hypoxic condition. Tumor in vivo metabolic activities were semiquantitatively evaluated by lesion-normal tissue ratio (LNR). Protein expression was confirmed by immunofluorescence staining. To evaluate prognostic value, relationship between gene expression and overall survival was explored in another independent nonoverlapping clinical cohort (n = 17) and validated by The Cancer Genome Atlas (TCGA) database (n = 167).

Results

Among the genes involving glucose metabolic pathway, mRNA expression of glucose-6-phosphatase 3 (G6PC3) correlated with 18F-FDG LNR (P = 0.03). In addition, G6PC3 mRNA expression in 18F-FMISO high-accumulated glioblastomas was significantly higher than that in 18F-FMISO low-accumulated glioblastomas (P < 0.01). Protein expression of G6PC3 was consistent with mRNA expression, which was confirmed by immunofluorescence analysis. These findings indicated that the G6PC3 expression might be facilitated by hypoxic condition in glioblastomas. Next, we investigated the clinical relevance of G6PC3 in terms of prognosis. Among the glioblastoma patients who received gross total resection, mRNA expressions of G6PC3 in the patients with poor prognosis (less than 1-year survival) were significantly higher than that in the patients who survive more than 3 years. Moreover, high mRNA expression of G6PC3 was associated with poor overall survival in glioblastoma, as validated by TCGA database.

Conclusion

G6PC3 was affluently expressed in glioblastoma tissues with coincidentally high 18F-FDG and 18F-FMISO accumulation. Further, it might work as a prognostic biomarker of glioblastoma. Therefore, G6PC3 is a potential key molecule of glucose metabolism under hypoxia in glioblastoma.

Synaptic loss and its association with symptom severity in Parkinson's disease

Parkinson's disease (PD) is the fastest growing neurodegenerative disease, but at present there is no cure, nor any disease-modifying treatments. Synaptic biomarkers from in vivo imaging have shown promise in imaging loss of synapses in PD and other neurodegenerative disorders. Here, we provide new clinical insights from a cross-sectional, high-resolution positron emission tomography (PET) study of 30 PD individuals and 30 age- and sex-matched healthy controls (HC) with the radiotracer [11C]UCB-J, which binds to synaptic vesicle glycoprotein 2A (SV2A), and is therefore, a biomarker of synaptic density in the living brain. We also examined a measure of relative brain perfusion from the early part of the same PET scan. Our results provide evidence for synaptic density loss in the substantia nigra that had been previously reported, but also extend this to other early-Braak stage regions known to be affected in PD (brainstem, caudate, olfactory cortex). Importantly, we also found a direct association between synaptic density loss in the nigra and severity of symptoms in patients. A greater extent and wider distribution of synaptic density loss in PD patients with longer illness duration suggests that [11C]UCB-J PET can be used to measure synapse loss with disease progression. We also demonstrate lower brain perfusion in PD vs. HC groups, with a greater extent of abnormalities in those with longer duration of illness, suggesting that [11C]UCB-J PET can simultaneously provide information on changes in brain perfusion. These results implicate synaptic imaging as a useful PD biomarker for future disease-modifying interventions.

Relationship between Neuroimaging and Cognition in Frontotemporal Dementia: A [18 F]FDG PET and Structural MRI Study

Background

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous condition with a prevalence comparable to Alzheimer's Disease for patients under sixty-five years of age. Gray matter (GM) atrophy and glucose hypometabolism are important biomarkers for the diagnosis and evaluation of disease progression in FTD. However, limited studies have systematically examined the association between cognition and neuroimaging in FTD using different imaging modalities in the same patient group.

Methods

We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both GM volume and glucose metabolism using structural magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography scanning ([18F]FDG PET) in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for [18F]FDG PET. Partial volume correction was applied to PET data to account for disease-related atrophy.

Results

Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.461, p = 0.035). The association between whole-cortex [18F]FDG SUVR and MoCA scores was not Significant (r = 0.374, p = 0.094). GM volumes of the frontal cortex (r = 0.540, p = 0.011), caudate (r = 0.616, p = 0.002), and insula (r = 0.568, p = 0.007) were also Significantly correlated with MoCA, as were SUVR values of the insula (r = 0.508, p = 0.018), thalamus (r = 0.478, p = 0.028), and posterior cingulate cortex (PCC) (r = 0.472, p = 0.030).

Discussion

Whole-cortex atrophy is associated with cognitive dysfunction, and this effect is larger than for cortical hypometabolism as measured with [18F]FDG PET. At the regional level, focal atrophy and/or hypometabolism in the frontal lobe, insula, PCC, thalamus, and caudate seem to imply the importance of these regions for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways. Our findings provide insight into the relationships between structural, metabolic, and cognitive changes due to FTD.

Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET

OBJECTIVE

Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density.

METHODS

DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups.

RESULTS

Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r = -0.55, p <0.001, df = 31) but not CN (r = 0.13, p = 0.62, df = 15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group.

CONCLUSION

In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.

Markerless head motion tracking and event-by-event correction in brain PET

Objective.Head motion correction (MC) is an essential process in brain positron emission tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based motion tracking (HMT) device, for PET head MC. However, this requires attachment of a marker to the subject's head. Markerless HMT (MLMT) methods are more convenient for clinical translation than HMT with external markers. In this study, we validated the United Imaging Healthcare motion tracking (UMT) MLMT system using phantom and human point source studies, and tested its effectiveness on eight18F-FPEB and four11C-LSN3172176 human studies, with frame-based region of interest (ROI) analysis. We also proposed an evaluation metric, registration quality (RQ), and compared it to a data-driven evaluation method, motion-corrected centroid-of-distribution (MCCOD).Approach.UMT utilized a stereovision camera with infrared structured light to capture the subject's real-time 3D facial surface. Each point cloud, acquired at up to 30 Hz, was registered to the reference cloud using a rigid-body iterative closest point registration algorithm.Main results.In the phantom point source study, UMT exhibited superior reconstruction results than the Vicra with higher spatial resolution (0.35 ± 0.27 mm) and smaller residual displacements (0.12 ± 0.10 mm). In the human point source study, UMT achieved comparable performance as Vicra on spatial resolution with lower noise. Moreover, UMT achieved comparable ROI values as Vicra for all the human studies, with negligible mean standard uptake value differences, while no MC results showed significant negative bias. TheRQevaluation metric demonstrated the effectiveness of UMT and yielded comparable results to MCCOD.Significance.We performed an initial validation of a commercial MLMT system against the Vicra. Generally, UMT achieved comparable motion-tracking results in all studies and the effectiveness of UMT-based MC was demonstrated.

Dose reduction in dynamic synaptic vesicle glycoprotein 2A PET imaging using artificial neural networks

Objective. Reducing dose in positron emission tomography (PET) imaging increases noise in reconstructed dynamic frames, which inevitably results in higher noise and possible bias in subsequently estimated images of kinetic parameters than those estimated in the standard dose case. We report the development of a spatiotemporal denoising technique for reduced-count dynamic frames through integrating a cascade artificial neural network (ANN) with the highly constrained back-projection (HYPR) scheme to improve low-dose parametric imaging.Approach. We implemented and assessed the proposed method using imaging data acquired with11C-UCB-J, a PET radioligand bound to synaptic vesicle glycoprotein 2A (SV2A) in the human brain. The patch-based ANN was trained with a reduced-count frame and its full-count correspondence of a subject and was used in cascade to process dynamic frames of other subjects to further take advantage of its denoising capability. The HYPR strategy was then applied to the spatial ANN processed image frames to make use of the temporal information from the entire dynamic scan.Main results. In all the testing subjects including healthy volunteers and Parkinson's disease patients, the proposed method reduced more noise while introducing minimal bias in dynamic frames and the resulting parametric images, as compared with conventional denoising methods.Significance. Achieving 80% noise reduction with a bias of -2% in dynamic frames, which translates into 75% and 70% of noise reduction in the tracer uptake (bias, -2%) and distribution volume (bias, -5%) images, the proposed ANN+HYPR technique demonstrates the denoising capability equivalent to a 11-fold dose increase for dynamic SV2A PET imaging with11C-UCB-J.

Neuronal transcriptome, tau and synapse loss in Alzheimer's knock-in mice require prion protein

BACKGROUND

Progression of Alzheimer's disease leads to synapse loss, neural network dysfunction and cognitive failure. Accumulation of protein aggregates and brain immune activation have triggering roles in synaptic failure but the neuronal mechanisms underlying synapse loss are unclear. On the neuronal surface, cellular prion protein (PrPC) is known to be a high-affinity binding site for Amyloid-β oligomers (Aβo). However, PrPC's dependence in knock-in AD models for tau accumulation, transcriptomic alterations and imaging biomarkers is unknown.

METHODS

The necessity of PrPC was examined as a function of age in homozygous AppNL-G-F/hMapt double knock-in mice (DKI). Phenotypes of AppNL-G-F/hMapt mice with a deletion of Prnp expression (DKI; Prnp-/-) were compared with DKI mice with intact Prnp, mice with a targeted deletion of Prnp (Prnp-/-), and mice with intact Prnp (WT). Phenotypes examined included behavioral deficits, synapse loss by PET imaging, synapse loss by immunohistology, tau pathology, gliosis, inflammatory markers, and snRNA-seq transcriptomic profiling.

RESULTS

By 9 months age, DKI mice showed learning and memory impairment, but DKI; Prnp-/- and Prnp-/- groups were indistinguishable from WT. Synapse loss in DKI brain, measured by [18F]SynVesT-1 SV2A PET or anti-SV2A immunohistology, was prevented by Prnp deletion. Accumulation of Tau phosphorylated at aa 217 and 202/205, C1q tagging of synapses, and dystrophic neurites were all increased in DKI mice but each decreased to WT levels with Prnp deletion. In contrast, astrogliosis, microgliosis and Aβ levels were unchanged between DKI and DKI; Prnp-/- groups. Single-nuclei transcriptomics revealed differential expression in neurons and glia of DKI mice relative to WT. For DKI; Prnp-/- mice, the majority of neuronal genes differentially expressed in DKI mice were no longer significantly altered relative to WT, but most glial DKI-dependent gene expression changes persisted. The DKI-dependent neuronal genes corrected by Prnp deletion associated bioinformatically with synaptic function. Additional genes were uniquely altered only in the Prnp-/- or the DKI; Prnp-/- groups.

CONCLUSIONS

Thus, PrPC-dependent synapse loss, phospho-tau accumulation and neuronal gene expression in AD mice can be reversed without clearing Aβ plaque or preventing gliotic reaction. This supports targeting the Aβo-PrPC interaction to prevent Aβo-neurotoxicity and pathologic tau accumulation in AD.

Cross-Attention for Improved Motion Correction in Brain PET

Head movement during long scan sessions degrades the quality of reconstruction in positron emission tomography (PET) and introduces artifacts, which limits clinical diagnosis and treatment. Recent deep learning-based motion correction work utilized raw PET list-mode data and hardware motion tracking (HMT) to learn head motion in a supervised manner. However, motion prediction results were not robust to testing subjects outside the training data domain. In this paper, we integrate a cross-attention mechanism into the supervised deep learning network to improve motion correction across test subjects. Specifically, cross-attention learns the spatial correspondence between the reference images and moving images to explicitly focus the model on the most correlative inherent information - the head region the motion correction. We validate our approach on brain PET data from two different scanners: HRRT without time of flight (ToF) and mCT with ToF. Compared with traditional and deep learning benchmarks, our network improved the performance of motion correction by 58% and 26% in translation and rotation, respectively, in multi-subject testing in HRRT studies. In mCT studies, our approach improved performance by 66% and 64% for translation and rotation, respectively. Our results demonstrate that cross-attention has the potential to improve the quality of brain PET image reconstruction without the dependence on HMT. All code will be released on GitHub: https://github.com/OnofreyLab/dl_hmc_attention_mlcn2023.

Principal component analysis of synaptic density measured with [11C]UCB-J PET in early Alzheimer's disease

BACKGROUND

Synaptic loss is considered an early pathological event and major structural correlate of cognitive impairment in Alzheimer's disease (AD). We used principal component analysis (PCA) to identify regional patterns of covariance in synaptic density using [11C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance.

METHODS

[11C]UCB-J binding was measured in 45 amyloid + participants with AD and 19 amyloid- cognitively normal participants aged 55-85. A validated neuropsychological battery assessed performance across five cognitive domains. PCA was applied to the pooled sample using distribution volume ratios (DVR) standardized (z-scored) by region from 42 bilateral regions of interest (ROI).

RESULTS

Parallel analysis determined three significant PCs explaining 70.2% of the total variance. PC1 was characterized by positive loadings with similar contributions across the majority of ROIs. PC2 was characterized by positive and negative loadings with strongest contributions from subcortical and parietooccipital cortical regions, respectively, while PC3 was characterized by positive and negative loadings with strongest contributions from rostral and caudal cortical regions, respectively. Within the AD group, PC1 subject scores were positively correlated with performance across all cognitive domains (Pearson r = 0.24-0.40, P = 0.06-0.006), PC2 subject scores were inversely correlated with age (Pearson r = -0.45, P = 0.002) and PC3 subject scores were significantly correlated with CDR-sb (Pearson r = 0.46, P = 0.04). No significant correlations were observed between cognitive performance and PC subject scores in CN participants.

CONCLUSIONS

This data-driven approach defined specific spatial patterns of synaptic density correlated with unique participant characteristics within the AD group. Our findings reinforce synaptic density as a robust biomarker of disease presence and severity in the early stages of AD.

Preclinical evaluation of a brain penetrant PARP PET imaging probe in rat glioblastoma and nonhuman primates

PURPOSE

Currently, there are multiple active clinical trials involving poly(ADP-ribose) polymerase (PARP) inhibitors in the treatment of glioblastoma. The noninvasive quantification of baseline PARP expression using positron emission tomography (PET) may provide prognostic information and lead to more precise treatment. Due to the lack of brain-penetrant PARP imaging agents, the reliable and accurate in vivo quantification of PARP in the brain remains elusive. Herein, we report the synthesis of a brain-penetrant PARP PET tracer, (R)-2-(2-methyl-1-(methyl-11C)pyrrolidin-2-yl)-1H-benzo[d]imidazole-4-carboxamide ([11C]PyBic), and its preclinical evaluations in a syngeneic RG2 rat glioblastoma model and healthy nonhuman primates.

METHODS

We synthesized [11C]PyBic using veliparib as the labeling precursor, performed dynamic PET scans on RG2 tumor-bearing rats and calculated the distribution volume ratio (DVR) using simplified reference region method 2 (SRTM2) with the contralateral nontumor brain region as the reference region. We performed biodistribution studies, western blot, and immunostaining studies to validate the in vivo PET quantification results. We characterized the brain kinetics and binding specificity of [11C]PyBic in nonhuman primates on FOCUS220 scanner and calculated the volume of distribution (VT), nondisplaceable volume of distribution (VND), and nondisplaceable binding potential (BPND) in selected brain regions.

RESULTS

[11C]PyBic was synthesized efficiently in one step, with greater than 97% radiochemical and chemical purity and molar activity of 148 ± 85 MBq/nmol (n = 6). [11C]PyBic demonstrated PARP-specific binding in RG2 tumors, with 74% of tracer binding in tumors blocked by preinjected veliparib (i.v., 5 mg/kg). The in vivo PET imaging results were corroborated by ex vivo biodistribution, PARP1 immunohistochemistry and immunoblotting data. Furthermore, brain penetration of [11C]PyBic was confirmed by quantitative monkey brain PET, which showed high specific uptake (BPND > 3) and low nonspecific uptake (VND < 3 mL/cm3) in the monkey brain.

CONCLUSION

[11C]PyBic is the first brain-penetrant PARP PET tracer validated in a rat glioblastoma model and healthy nonhuman primates. The brain kinetics of [11C]PyBic are suitable for noninvasive quantification of available PARP binding in the brain, which posits [11C]PyBic to have broad applications in oncology and neuroimaging.

Decreased synaptic vesicle glycoprotein 2A binding in a rodent model of familial Alzheimer's disease detected by [18F]SDM-16

Introduction

Synapse loss is one of the hallmarks of Alzheimer's disease (AD) and is associated with cognitive decline. In this study, we tested [18F]SDM-16, a novel metabolically stable SV2A PET imaging probe, in the transgenic APPswe/PS1dE9 (APP/PS1) mouse model of AD and age-matched wild-type (WT) mice at 12 months of age.

Methods

Based on previous preclinical PET imaging studies using [11C]UCB-J and [18F]SynVesT-1 in the same strain animals, we used the simplified reference tissue model (SRTM), with brain stem as the pseudo reference region to calculate distribution volume ratios (DVRs).

Results

To simplify and streamline the quantitative analysis, we compared the standardized uptake value ratios (SUVRs) from different imaging windows to DVRs and found that the averaged SUVRs from 60-90 min post-injection (p.i.) are most consistent with the DVRs. Thus, we used averaged SUVRs from 60-90 min for group comparisons and found statistically significant differences in the tracer uptake in different brain regions, e.g., hippocampus (p = 0.001), striatum (p = 0.002), thalamus (p = 0.003), and cingulate cortex (p = 0.0003).

Conclusions

In conclusion, [18F]SDM-16 was used to detect decreased SV2A levels in the brain of APP/PS1 AD mouse model at one year old. Our data suggest that [18F]SDM-16 has similar statistical power in detecting the synapse loss in APP/PS1 mice as [11C]UCB-J and [18F]SynVesT-1, albeit later imaging window (60-90 min p.i.) is needed when SUVR is used as a surrogate for DVR for [18F]SDM-16 due to its slower brain kinetics.

Examining sex differences in responses to footshock stress and the role of the metabotropic glutamate receptor 5: an [18F]FPEB and positron emission tomography study in rats

Clinical investigations suggest involvement of the metabotropic glutamate receptor 5 (mGluR5) in the pathophysiology of fear learning that underlies trauma-related disorders. Here, we utilized a 4-day fear learning paradigm combined with positron emission tomography (PET) to examine the relationship between mGluR5 availability and differences in the response of rats to repeated footshock exposure (FE). Specifically, on day 1, male (n = 16) and female (n = 12) rats received 15 footshocks and were compared with control rats who did not receive footshocks (n = 7 male; n = 4 female). FE rats were classified as low responders (LR) or high responders (HR) based on freezing to the context the following day (day 2). PET with [18F]FPEB was used to calculate regional mGluR5 binding potential (BPND) at two timepoints: prior to FE (i.e., baseline), and post-behavioral testing. Additionally, we used an unbiased proteomics approach to assess group and sex differences in prefrontal cortex (PFC) protein expression. Post-behavioral testing we observed decreased BPND in LR females, but increased BPND in HR males relative to baseline. Further, individuals displaying the greatest freezing during the FE context memory test had the largest increases in PFC BPND. Males and females displayed unique post-test molecular profiles: in males, the greatest differences were between FE and CON, including upregulation of mGluR5 and related molecular networks in FE, whereas the greatest differences among females were between the LR and HR groups. These findings suggest greater mGluR5 availability increases following footshock exposure may be related to greater contextual fear memory. Results additionally reveal sex differences in the molecular response to footshock, including differential involvement of mGluR5-related molecular networks.

Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application

Objective. In PET/CT imaging, CT is used for positron emission tomography (PET) attenuation correction (AC). CT artifacts or misalignment between PET and CT can cause AC artifacts and quantification errors in PET. Simultaneous reconstruction (MLAA) of PET activity (λ-MLAA) and attenuation (μ-MLAA) maps was proposed to solve those issues using the time-of-flight PET raw data only. However,λ-MLAA still suffers from quantification error as compared to reconstruction using the gold-standard CT-based attenuation map (μ-CT). Recently, a deep learning (DL)-based framework was proposed to improve MLAA by predictingμ-DL fromλ-MLAA andμ-MLAA using an image domain loss function (IM-loss). However, IM-loss does not directly measure the AC errors according to the PET attenuation physics. Our preliminary studies showed that an additional physics-based loss function can lead to more accurate PET AC. The main objective of this study is to optimize the attenuation map generation framework for clinical full-dose¹⁸F-FDG studies. We also investigate the effectiveness of the optimized network on predicting attenuation maps for synthetic low-dose oncological PET studies.Approach. We optimized the proposed DL framework by applying different preprocessing steps and hyperparameter optimization, including patch size, weights of the loss terms and number of angles in the projection-domain loss term. The optimization was performed based on 100 skull-to-toe¹⁸F-FDG PET/CT scans with minimal misalignment. The optimized framework was further evaluated on 85 clinical full-dose neck-to-thigh¹⁸F-FDG cancer datasets as well as synthetic low-dose studies with only 10% of the full-dose raw data.Main results. Clinical evaluation of tumor quantification as well as physics-based figure-of-merit metric evaluation validated the promising performance of our proposed method. For both full-dose and low-dose studies, the proposed framework achieved <1% error in tumor standardized uptake value measures.Significance. It is of great clinical interest to achieve CT-less PET reconstruction, especially for low-dose PET studies.

Synaptic density and cognitive performance in Alzheimer's disease: A PET imaging study with [11 C]UCB-J

INTRODUCTION

For 30 years synapse loss has been referred to as the major pathological correlate of cognitive impairment in Alzheimer's disease (AD). However, this statement is based on remarkably few patients studied by autopsy or biopsy. With the recent advent of synaptic vesicle glycoprotein 2A (SV2A) positron emission tomography (PET) imaging, we have begun to evaluate the consequences of synaptic alterations in vivo.

METHODS

We examined the relationship between synaptic density measured by [11 C]UCB-J PET and neuropsychological test performance in 45 participants with early AD.

RESULTS

Global synaptic density showed a significant positive association with global cognition and performance on five individual cognitive domains in participants with early AD. Synaptic density was a stronger predictor of cognitive performance than gray matter volume.

CONCLUSION

These results confirm neuropathologic studies demonstrating a significant association between synaptic density and cognitive performance, and suggest that this correlation extends to the early stages of AD.

An objective evaluation method for head motion estimation in PET-Motion corrected centroid-of-distribution

Head motion presents a continuing problem in brain PET studies. A wealth of motion correction (MC) algorithms had been proposed in the past, including both hardware-based methods and data-driven methods. However, in most real brain PET studies, in the absence of ground truth or gold standard of motion information, it is challenging to objectively evaluate MC quality. For MC evaluation, image-domain metrics, e.g., standardized uptake value (SUV) change before and after MC are commonly used, but this measure lacks objectivity because 1) other factors, e.g., attenuation correction, scatter correction and parameters used in the reconstruction, will confound MC effectiveness; 2) SUV only reflects final image quality, and it cannot precisely inform when an MC method performed well or poorly during the scan time period; 3) SUV is tracer-dependent and head motion may cause increases or decreases in SUV for different tracers, so evaluating MC effectiveness is complicated. Here, we present a new algorithm, i.e., motion corrected centroid-of-distribution (MCCOD) to perform objective quality control for measured or estimated rigid motion information. MCCOD is a three-dimensional surrogate trace of the center of tracer distribution after performing rigid MC using the existing motion information. MCCOD is used to inform whether the motion information is accurate, using the PET raw data only, i.e., without PET image reconstruction, where inaccurate motion information typically leads to abrupt changes in the MCCOD trace. MCCOD was validated using simulation studies and was tested on real studies acquired from both time-of-flight (TOF) and non-TOF scanners. A deep learning-based brain mask segmentation was implemented, which is shown to be necessary for non-TOF MCCOD generation. MCCOD is shown to be effective in detecting abrupt translation motion errors in slowly varying tracer distribution caused by the motion tracking hardware and can be used to compare different motion estimation methods as well as to improve existing motion information.

Imaging the fetal nonhuman primate brain with SV2A positron emission tomography (PET)

PURPOSE

Exploring synaptic density changes during brain growth is crucial to understanding brain development. Previous studies in nonhuman primates report a rapid increase in synapse number between the late gestational period and the early neonatal period, such that synaptic density approaches adult levels by birth. Prenatal synaptic development may have an enduring impact on postnatal brain development, but precisely how synaptic density changes in utero are unknown because current methods to quantify synaptic density are invasive and require post-mortem brain tissue.

METHODS

We used synaptic vesicle glycoprotein 2A (SV2A) positron emission tomography (PET) radioligands [¹¹C]UCB-J and [¹⁸F]Syn-VesT-1 to conduct the first assessment of synaptic density in the developing fetal brain in gravid rhesus monkeys. Eight pregnant monkeys were scanned twice during the third trimester at two imaging sites. Fetal post-mortem samples were collected near term in a subset of subjects to quantify SV2A density by Western blot.

RESULTS

Image-derived fetal brain SV2A measures increased during the third trimester. SV2A concentrations were greater in subcortical regions than in cortical regions at both gestational ages. Near term, SV2A density was higher in primary motor and visual areas than respective associative regions. Post-mortem quantification of SV2A density was significantly correlated with regional SV2A PET measures.

CONCLUSION

While further study is needed to determine the exact relationship of SV2A and synaptic density, the imaging paradigm developed in the current study allows for the effective in vivo study of SV2A development in the fetal brain.

Identification of patients with Graves' disease who benefit from high-dose radioactive iodine therapy

OBJECTIVE

Radioactive iodine (RAI) therapy is a useful treatment for Graves' disease (GD). Most RAI sessions administer ≤ 500 MBq of iodine (I)-131. Sometimes patients require repeated RAI, often for longer periods of remission. We investigated the characteristics of patients for whom high dose (mostly 1110 MBq of I-131) RAI was effective as RAI therapy for GD.

METHODS

We retrospectively analyzed the cases of 79 patients who underwent RAI for GD in a multicenter setting. We divided the patients into two groups based on the I-131 dose administered: the low dose (LD) group who received ≤ 500 MBq (n = 44) and the high dose (HD) group who received > 500 MBq (n = 35). The therapeutic effect was defined as achieving remission and reaching the point of participating in thyroid hormone replacement therapy within 1 year after RAI. We compared the LD and HD groups' remission rates and conducted a multivariate logistic regression analysis of predictive factors for remission. In a simulation, using the formula for predicting the probability of remission obtained from the analysis results, we estimated how much the remission rate would change if the I-131 dose is increased from 500 to 1110 MBq.

RESULTS

The mean ± standard deviation I-131 dose administered in the LD group was 480 ± 6 MBq, and that of the HD group was 1054 ± 265 MBq. Thirty-five patients (80%) in the LD group and 26 patients (74%) in the HD group achieved remission; this difference in the remission rate was not significant. The multivariate analysis results demonstrated that the absorbed dose and thyroid-stimulating antibody (TSAb) were independent predictors of remission. Seven patients (8.9%) showed an increased probability of remission from < 50% to > 50% when the higher RAI dose was applied (1110 MBq instead of 500 MBq). The thyroid volume and TSAb values in these patients were relatively large at 54.7 ± 34.2 mL and 1378.4 ± 586.3%, respectively.

CONCLUSION

Although the overall remission rate was not significantly different between the patients who received high- or low-dose I-131, treatment with high-dose RAI may improve the probability of remission in patients with a massive thyroid volume and/or high-TSAb Graves' disease.

Deep learning-based attenuation correction for whole-body PET - a multi-tracer study with 18F-FDG, 68 Ga-DOTATATE, and 18F-Fluciclovine

A novel deep learning (DL)-based attenuation correction (AC) framework was applied to clinical whole-body oncology studies using 18F-FDG, 68 Ga-DOTATATE, and 18F-Fluciclovine. The framework used activity (λ-MLAA) and attenuation (µ-MLAA) maps estimated by the maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm as inputs to a modified U-net neural network with a novel imaging physics-based loss function to learn a CT-derived attenuation map (µ-CT).

METHODS

Clinical whole-body PET/CT datasets of 18F-FDG (N = 113), 68 Ga-DOTATATE (N = 76), and 18F-Fluciclovine (N = 90) were used to train and test tracer-specific neural networks. For each tracer, forty subjects were used to train the neural network to predict attenuation maps (µ-DL). µ-DL and µ-MLAA were compared to the gold-standard µ-CT. PET images reconstructed using the OSEM algorithm with µ-DL (OSEMDL) and µ-MLAA (OSEMMLAA) were compared to the CT-based reconstruction (OSEMCT). Tumor regions of interest were segmented by two radiologists and tumor SUV and volume measures were reported, as well as evaluation using conventional image analysis metrics.

RESULTS

µ-DL yielded high resolution and fine detail recovery of the attenuation map, which was superior in quality as compared to µ-MLAA in all metrics for all tracers. Using OSEMCT as the gold-standard, OSEMDL provided more accurate tumor quantification than OSEMMLAA for all three tracers, e.g., error in SUVmax for OSEMMLAA vs. OSEMDL: - 3.6 ± 4.4% vs. - 1.7 ± 4.5% for 18F-FDG (N = 152), - 4.3 ± 5.1% vs. 0.4 ± 2.8% for 68 Ga-DOTATATE (N = 70), and - 7.3 ± 2.9% vs. - 2.8 ± 2.3% for 18F-Fluciclovine (N = 44). OSEMDL also yielded more accurate tumor volume measures than OSEMMLAA, i.e., - 8.4 ± 14.5% (OSEMMLAA) vs. - 3.0 ± 15.0% for 18F-FDG, - 14.1 ± 19.7% vs. 1.8 ± 11.6% for 68 Ga-DOTATATE, and - 15.9 ± 9.1% vs. - 6.4 ± 6.4% for 18F-Fluciclovine.

CONCLUSIONS

The proposed framework provides accurate and robust attenuation correction for whole-body 18F-FDG, 68 Ga-DOTATATE and 18F-Fluciclovine in tumor SUV measures as well as tumor volume estimation. The proposed method provides clinically equivalent quality as compared to CT in attenuation correction for the three tracers.

Reversal of synapse loss in Alzheimer mouse models by targeting mGluR5 to prevent synaptic tagging by C1Q

Microglia-mediated synaptic loss contributes to the development of cognitive impairments in Alzheimer's disease (AD). However, the basis for this immune-mediated attack on synapses remains to be elucidated. Treatment with the metabotropic glutamate receptor 5 (mGluR5) silent allosteric modulator (SAM), BMS-984923, prevents β-amyloid oligomer-induced aberrant synaptic signaling while preserving physiological glutamate response. Here, we show that oral BMS-984923 effectively occupies brain mGluR5 sites visualized by [¹⁸F]FPEB positron emission tomography (PET) at doses shown to be safe in rodents and nonhuman primates. In aged mouse models of AD (APPswe/PS1ΔE9 overexpressing transgenic and App^NL-G-F/hMapt double knock-in), SAM treatment fully restored synaptic density as measured by [¹⁸F]SynVesT-1 PET for SV2A and by histology, and the therapeutic benefit persisted after drug washout. Phospho-TAU accumulation in double knock-in mice was also reduced by SAM treatment. Single-nuclei transcriptomics demonstrated that SAM treatment in both models normalized expression patterns to a far greater extent in neurons than glia. Last, treatment prevented synaptic localization of the complement component C1Q and synaptic engulfment in AD mice. Thus, selective modulation of mGluR5 reversed neuronal gene expression changes to protect synapses from damage by microglial mediators in rodents.

Imaging of Synaptic Density in Neurodegenerative Disorders

PET technology has produced many radiopharmaceuticals that target specific brain proteins and other measures of brain function. Recently, a new approach has emerged to image synaptic density by targeting the synaptic vesicle protein 2A (SV2A), an integral glycoprotein in the membrane of synaptic vesicles and widely distributed throughout the brain. Multiple SV2A ligands have been developed and translated to human use. The most successful of these to date is 11C-UCB-J, because of its high uptake, moderate metabolism, and effective quantification with a 1-tissue-compartment model. Further, since SV2A is the target of the antiepileptic drug levetiracetam, human blocking studies have characterized specific binding and potential reference regions. Regional brain SV2A levels were shown to correlate with those of synaptophysin, another commonly used marker of synaptic density, providing the basis for SV2A PET imaging to have broad utility across neuropathologic diseases. In this review, we highlight the development of SV2A tracers and the evaluation of quantification methods, including compartment modeling and simple tissue ratios. Mouse and rat models of neurodegenerative diseases have been studied with small-animal PET, providing validation by comparison to direct tissue measures. Next, we review human PET imaging results in multiple neurodegenerative disorders. Studies on Parkinson disease and Alzheimer disease have progressed most rapidly at multiple centers, with generally consistent results of patterns of SV2A or synaptic loss. In Alzheimer disease, the synaptic loss patterns differ from those of amyloid, tau, and 18F-FDG, although intertracer and interregional correlations have been found. Smaller studies have been reported in other disorders, including Lewy body dementia, frontotemporal dementia, Huntington disease, progressive supranuclear palsy, and corticobasal degeneration. In conclusion, PET imaging of SV2A has rapidly developed, and qualified radioligands are available. PET studies on humans indicate that SV2A loss might be specific to disease-associated brain regions and consistent with synaptic density loss. The recent availability of new 18F tracers, 18F-SynVesT-1 and 18F-SynVesT-2, will substantially broaden the application of SV2A PET. Future studies are needed in larger patient cohorts to establish the clinical value of SV2A PET and its potential for diagnosis and progression monitoring of neurodegenerative diseases, as well as efficacy assessment of disease-modifying therapies.

PET Imaging in Animal Models of Alzheimer’s Disease

The successful development and translation of PET imaging agents targeting β-amyloid plaques and hyperphosphorylated tau tangles have allowed for in vivo detection of these hallmarks of Alzheimer’s disease (AD) antemortem. Amyloid and tau PET have been incorporated into the A/T/N scheme for AD characterization and have become an integral part of ongoing clinical trials to screen patients for enrollment, prove drug action mechanisms, and monitor therapeutic effects. Meanwhile, preclinical PET imaging in animal models of AD can provide supportive information for mechanistic studies. With the recent advancement of gene editing technologies and AD animal model development, preclinical PET imaging in AD models will further facilitate our understanding of AD pathogenesis/progression and the development of novel treatments. In this study, we review the current state-of-the-art in preclinical PET imaging using animal models of AD and suggest future research directions.

Adaptive data-driven motion detection and optimized correction for brain PET

Head motion during PET scans causes image quality degradation, decreased concentration in regions with high uptake and incorrect outcome measures from kinetic analysis of dynamic datasets. Previously, we proposed a data-driven method, center of tracer distribution (COD), to detect head motion without an external motion tracking device. There, motion was detected using one dimension of the COD trace with a semiautomatic detection algorithm, requiring multiple user defined parameters and manual intervention. In this study, we developed a new data-driven motion detection algorithm, which is automatic, self-adaptive to noise level, does not require user-defined parameters and uses all three dimensions of the COD trace (3DCOD). 3DCOD was first validated and tested using 30 simulation studies (¹⁸F-FDG, N = 15; ¹¹C-raclopride (RAC), N = 15) with large motion. The proposed motion correction method was tested on 22 real human datasets, with 20 acquired from a high resolution research tomograph (HRRT) scanner (¹⁸F-FDG, N = 10; ¹¹C-RAC, N = 10) and 2 acquired from the Siemens Biograph mCT scanner. Real-time hardware-based motion tracking information (Vicra) was available for all real studies and was used as the gold standard. 3DCOD was compared to Vicra, no motion correction (NMC), one-direction COD (our previous method called 1DCOD) and two conventional frame-based image registration (FIR) algorithms, i.e., FIR1 (based on predefined frames reconstructed with attenuation correction) and FIR2 (without attenuation correction) for both simulation and real studies. For the simulation studies, 3DCOD yielded -2.3 ± 1.4% (mean ± standard deviation across all subjects and 11 brain regions) error in region of interest (ROI) uptake for ¹⁸F-FDG (-3.4 ± 1.7% for ¹¹C-RAC across all subjects and 2 regions) as compared to Vicra (perfect correction) while NMC, FIR1, FIR2 and 1DCOD yielded -25.4 ± 11.1% (-34.5 ± 16.1% for ¹¹C- RAC), -13.4 ± 3.5% (-16.1 ± 4.6%), -5.7 ± 3.6% (-8.0 ± 4.5%) and -2.6 ± 1.5% (-5.1 ± 2.7%), respectively. For real HRRT studies, 3DCOD yielded -0.3 ± 2.8% difference for ¹⁸F-FDG (-0.4 ± 3.2% for ¹¹C-RAC) as compared to Vicra while NMC, FIR1, FIR2 and 1DCOD yielded -14.9 ± 9.0% (-24.5 ± 14.6%), -3.6 ± 4.9% (-13.4 ± 14.3%), -0.6 ± 3.4% (-6.7 ± 5.3%) and -1.5 ± 4.2% (-2.2 ± 4.1%), respectively. In summary, the proposed motion correction method yielded comparable performance to the hardware-based motion tracking method for multiple tracers, including very challenging cases with large frequent head motion, in studies performed on a non-TOF scanner.

Feasibility of imaging synaptic density in the human spinal cord using [11C]UCB-J PET

PURPOSE

Neuronal damage and synapse loss in the spinal cord (SC) have been implicated in spinal cord injury (SCI) and neurodegenerative disorders such as Amyotrophic Lateral Sclerosis (ALS). Current standards of diagnosis for SCI include CT or MRI imaging to evaluate injury severity. The current study explores the use of PET imaging with [11C]UCB-J, which targets the synaptic vesicle protein 2A (SV2A), in the human spinal cord, as a way to visualize synaptic density and integrity in vivo.

RESULTS

First, simulations of baseline and blocking [11C]UCB-J HRRT scans were performed, based on SC dimensions and SV2A distribution to predict VT, VND, and VS values. Next, human baseline and blocking [11C]UCB-J HRRT images were used to estimate these values in the cervical SC (cSC). Simulation results had excellent agreement with observed values of VT, VND, and VS from the real human data, with baseline VT, VND, and VS of 3.07, 2.15, and 0.92 mL/cm3, respectively, with a BPND of 0.43. Lastly, we explored full SC imaging with whole-body images. Using automated SC regions of interest (ROIs) for the full SC, cSC, and thoracic SC (tSC), the distribution volume ratio (DVR) was estimated using the brain gray matter as a reference region to evaluate SC SV2A density relative to the brain. In full body imaging, DVR values of full SC, cSC, and tSC were 0.115, 0.145, and 0.112, respectively. Therefore, measured [11C]UCB-J uptake, and thus SV2A density, is much lower in the SC than in the brain.

CONCLUSIONS

The results presented here provide evidence for the feasibility of SV2A PET imaging in the human SC, however, specific binding of [11C]UCB-J is low. Ongoing and future work include further classification of SV2A distribution in the SC as well as exploring higher-affinity PET radioligands for SC imaging.

Harmonization of [11C]raclopride brain PET images from the HR+ and HRRT: method development and validation in human subjects

BACKGROUND

There has been an ongoing need to compare and combine the results of new PET imaging studies conducted with [¹¹C]raclopride with older data. This typically means harmonizing data across different scanners. Previous harmonization studies have utilized either phantoms or human subjects, but the use of both phantoms and humans in one harmonization study is not common. The purpose herein was (1) to use phantom images to develop an inter-scanner harmonization technique and (2) to test the harmonization technique in human subjects.

METHODS

To develop the harmonization technique (Experiment 1), the Iida brain phantom was filled with F-18 solution and scanned on the two scanners in question (HRRT, HR+, Siemens/CTI). Phantom images were used to determine the optimal isotropic Gaussian filter to harmonize HRRT and HR+ images. To evaluate the harmonization on human images (Experiment 2), inter-scanner variability was calculated using [¹¹C]raclopride scans of 3 human subjects on both the HRRT and HR+ using percent difference (PD) in striatal non-displaceable binding potential (BP_ND) between HR+ and HRRT (with and without Gaussian smoothing). Finally, (Experiment 3), PD_T/RT was calculated for test-retest (T/RT) variability of striatal BP_ND for 8 human subjects scanned twice on the HR+.

RESULTS

Experiment 1 identified the optimal filter as a Gaussian with a 4.5 mm FWHM. Experiment 2 resulted in 13.9% PD for unfiltered HRRT and 3.71% for HRRT filtered with 4.5 mm. Experiment 3 yielded 5.24% PD_T/RT for HR+.

CONCLUSIONS

The PD results show that the variability of harmonized HRRT is less than the T/RT variability of the HR+. The harmonization technique makes it possible for BP_ND estimates from the HRRT to be compared to (and/or combined with) those from the HR+ without adding to overall variability. Our approach is applicable to all pairs of scanners still in service.

PET Imaging of Synaptic Density: Challenges and Opportunities of Synaptic Vesicle Glycoprotein 2A PET in Small Animal Imaging

The development of novel PET imaging agents for synaptic vesicle glycoprotein 2A (SV2A) allowed for the in vivo detection of synaptic density changes, which are correlated with the progression and severity of a variety of neuropsychiatric diseases. While multiple ongoing clinical investigations using SV2A PET are expanding its applications rapidly, preclinical SV2A PET imaging in animal models is an integral component of the translation research and provides supporting and complementary information. Herein, we overview preclinical SV2A PET studies in animal models of neurodegenerative disorders and discuss the opportunities and practical challenges in small animal SV2A PET imaging. At the Yale PET Center, we have conducted SV2A PET imaging studies in animal models of multiple diseases and longitudinal SV2A PET allowed us to evaluate synaptic density dynamics in the brains of disease animal models and to assess pharmacological effects of novel interventions. In this article, we discuss key considerations when designing preclinical SV2A PET imaging studies and strategies for data analysis. Specifically, we compare the brain imaging characteristics of available SV2A tracers, i.e., [¹¹C]UCB-J, [¹⁸F]SynVesT-1, [¹⁸F]SynVesT-2, and [¹⁸F]SDM-16, in rodent brains. We also discuss the limited spatial resolution of PET scanners for small brains and challenges of kinetic modeling. We then compare different injection routes and estimate the maximum throughput (i.e., number of animals) per radiotracer synthesis by taking into account the injectable volume for each injection method, injected mass, and radioactivity half-lives. In summary, this article provides a perspective for designing and analyzing SV2A PET imaging studies in small animals.

Lower prefrontal cortical synaptic vesicle binding in cocaine use disorder: An exploratory 11 C-UCB-J positron emission tomography study in humans

Preclinical studies have revealed robust and long-lasting alterations in dendritic spines in the brain following cocaine exposure. Such alterations are hypothesized to underlie enduring maladaptive behaviours observed in cocaine use disorder (CUD). The current study explored whether synaptic density is altered in CUD. Fifteen individuals with DSM-5 CUD and 15 demographically matched healthy control (HC) subjects participated in a single 11 C-UCB-J positron emission tomography scan to assess density of synaptic vesicle glycoprotein 2A (SV2A). The volume of distribution (VT ) and the plasma-free fraction-corrected form of the total volume of distribution (VT /fP ) were analysed in the anterior cingulate cortex (ACC), dorsomedial and ventromedial prefrontal cortex (PFC), lateral and medial orbitofrontal cortex (OFC) and ventral striatum. A significant diagnostic-group-by-region interaction was observed for VT and VT /fP . Post hoc analyses revealed no differences on VT , while for VT /fP showed lower values in CUD as compared with HC subjects in the ACC (-10.9%, p = 0.02), ventromedial PFC (-9.9%, p = 0.02) and medial OFC (-9.9%, p = 0.04). Regional VT /fP values in CUD, though unrelated to measures of lifetime cocaine use, were positively correlated with the frequency of recent cocaine use (p = 0.02-0.03) and negatively correlated with cocaine abstinence (p = 0.008-0.03). These findings provide initial preliminary in vivo evidence of altered (lower) synaptic density in the PFC of humans with CUD. Cross-sectional variation in SV2A availability as a function of recent cocaine use and abstinence suggests that synaptic density may be dynamically and plastically regulated by acute cocaine, an observation that merits direct testing by studies using more definitive longitudinal designs.

Artificial intelligence for nuclear medicine in oncology

As in all other medical fields, artificial intelligence (AI) is increasingly being used in nuclear medicine for oncology. There are many articles that discuss AI from the viewpoint of nuclear medicine, but few focus on nuclear medicine from the viewpoint of AI. Nuclear medicine images are characterized by their low spatial resolution and high quantitativeness. It is noted that AI has been used since before the emergence of deep learning. AI can be divided into three categories by its purpose: (1) assisted interpretation, i.e., computer-aided detection (CADe) or computer-aided diagnosis (CADx). (2) Additional insight, i.e., AI provides information beyond the radiologist's eye, such as predicting genes and prognosis from images. It is also related to the field called radiomics/radiogenomics. (3) Augmented image, i.e., image generation tasks. To apply AI to practical use, harmonization between facilities and the possibility of black box explanations need to be resolved.

Optimized Methodology for Reference Region and Image-Derived Input Function Kinetic Modeling in Preclinical PET

PET imaging of small animals is often used for assessing biodistribution of a novel radioligand and pharmacology in small animal models of disease. PET acquisition and processing settings may affect reference region or image-derived input function (IDIF) kinetic modeling estimates. We examined four different factors in comparing quantitative results: 1) effect of reconstruction algorithm, 2) number of MAP iterations, 3) strength of the MAP prior, and 4) Attenuation and scatter. The effect of these parameters has not been explored for small-animal reference region and IDIF kinetic modeling approaches. Dynamic PET/CT scans were performed in 3 species with 3 different tracers: house sparrows with [¹¹C]raclopride, rats with [¹⁸F]AS2471907 (11βHSD1) and mice with [¹¹C]UCB-J (SV2A). FBP yielded lower kinetic modeling estimates compared to 3D-OSEM-MAP reconstructions, in sparrow and rat studies. Target resolutions (MAP prior strength) of 1.5 and 3.0mm demonstrated reduced V_T in rats but only 3.0mm reduced BP _ND in sparrows. Therefore, use of the highest target resolution (0.8mm) is warranted. We demonstrated using kinetic modeling that forgoing CT-based attenuation and scatter correction may be appropriate to improve animal throughput when using short-lived radioisotopes in sparrows and mice. This work provides recommendations and a framework for future optimization of kinetic modeling for preclinical PET methodology with novel radioligands.

Preliminary In Vivo Evidence of Reduced Synaptic Density in Human Immunodeficiency Virus (HIV) Despite Antiretroviral Therapy

BACKGROUND

Synaptic injury is a pathological hallmark of neurological impairment in people living with human immunodeficiency virus (HIV, PLWH), a common complication despite viral suppression with antiretroviral therapy (ART). Measurement of synaptic density in living humans may allow better understanding of HIV neuropathogenesis and provide a dynamic biomarker for therapeutic studies. We applied novel synaptic vesical protein 2A (SV2A) positron emission tomographic (PET) imaging to investigate synaptic density in the frontostriatalthalamic region in PLWH and HIV-uninfected participants.

METHODS

In this cross-sectional pilot study,13 older male PLWH on ART underwent magnetic resonance imaging (MRI) and PET scanning with the SV2A ligand [11C]UCB-J with partial volume correction and had neurocognitive assessments. SV2A binding potential (BPND) in the frontostriatalthalamic circuit was compared to 13 age-matched HIV-uninfected participants and assessed with respect to neurocognitive performance in PLWH.

RESULTS

PLWH had 14% lower frontostriatalthalamic SV2A synaptic density compared to HIV-uninfected (PLWH: mean [SD], 3.93 [0.80]; HIV-uninfected: 4.59 [0.43]; P = .02, effect size 1.02). Differences were observed in widespread additional regions in exploratory analyses. Higher frontostriatalthalamic SV2A BPND associated with better grooved pegboard performance, a measure of motor coordination, in PLWH (r = 0.61, P = .03).

CONCLUSIONS

In a pilot study, SV2A PET imaging reveals reduced synaptic density in older male PLWH on ART compared to HIV-uninfected in the frontostriatalthalamic circuit and other cortical areas. Larger studies controlling for factors in addition to age are needed to determine whether differences are attributable to HIV or comorbidities in PLWH. SV2A imaging is a promising biomarker for studies of neuropathogenesis and therapeutic interventions in HIV.

Generation of synthetic PET images of synaptic density and amyloid from 18 F-FDG images using deep learning

PURPOSE

Positron emission tomography (PET) imaging with various tracers is increasingly used in Alzheimer's disease (AD) studies. However, access to PET scans using new or less-available tracers with sophisticated synthesis and short half-life isotopes may be very limited. Therefore, it is of great significance and interest in AD research to assess the feasibility of generating synthetic PET images of less-available tracers from the PET image of another common tracer, in particular 18 F-FDG.

METHODS

We implemented advanced deep learning methods using the U-Net model to predict 11 C-UCB-J PET images of synaptic vesicle protein 2A (SV2A), a surrogate of synaptic density, from 18 F-FDG PET data. Dynamic 18 F-FDG and 11 C-UCB-J scans were performed in 21 participants with normal cognition (CN) and 33 participants with Alzheimer's disease (AD). Cerebellum was used as the reference region for both tracers. For 11 C-UCB-J image prediction, four network models were trained and tested, which included 1) 18 F-FDG SUV ratio (SUVR) to 11 C-UCB-J SUVR, 2) 18 F-FDG Ki ratio to 11 C-UCB-J SUVR, 3) 18 F-FDG SUVR to 11 C-UCB-J distribution volume ratio (DVR), and 4) 18 F-FDG Ki ratio to 11 C-UCB-J DVR. The normalized root mean square error (NRMSE), structure similarity index (SSIM), and Pearson's correlation coefficient were calculated for evaluating the overall image prediction accuracy. Mean bias of various ROIs in the brain and correlation plots between predicted images and true images were calculated for ROI-based prediction accuracy. Following a similar training and evaluation strategy, 18 F-FDG SUVR to 11 C-PiB SUVR network was also trained and tested for 11 C-PiB static image prediction.

RESULTS

The results showed that all four network models obtained satisfactory 11 C-UCB-J static and parametric images. For 11 C-UCB-J SUVR prediction, the mean ROI bias was -0.3% ± 7.4% for the AD group and -0.5% ± 7.3% for the CN group with 18 F-FDG SUVR as the input, -0.7% ± 8.1% for the AD group, and -1.3% ± 7.0% for the CN group with 18 F-FDG Ki ratio as the input. For 11 C-UCB-J DVR prediction, the mean ROI bias was -1.3% ± 7.5% for the AD group and -2.0% ± 6.9% for the CN group with 18 F-FDG SUVR as the input, -0.7% ± 9.0% for the AD group, and -1.7% ± 7.8% for the CN group with 18 F-FDG Ki ratio as the input. For 11 C-PiB SUVR image prediction, which appears to be a more challenging task, the incorporation of additional diagnostic information into the network is needed to control the bias below 5% for most ROIs.

CONCLUSIONS

It is feasible to use 3D U-Net-based methods to generate synthetic 11 C-UCB-J PET images from 18 F-FDG images with reasonable prediction accuracy. It is also possible to predict 11 C-PiB SUVR images from 18 F-FDG images, though the incorporation of additional non-imaging information is needed.

Comparison of [11C]UCB-J and [18F]FDG PET in Alzheimer's disease: A tracer kinetic modeling study

[11C]UCB-J PET for synaptic vesicle glycoprotein 2 A (SV2A) has been proposed as a suitable marker for synaptic density in Alzheimer's disease (AD). We compared [11C]UCB-J binding for synaptic density and [18F]FDG uptake for metabolism (correlated with neuronal activity) in 14 AD and 11 cognitively normal (CN) participants. We assessed both absolute and relative outcome measures in brain regions of interest, i.e., K1 or R1 for [11C]UCB-J perfusion, VT (volume of distribution) or DVR to cerebellum for [11C]UCB-J binding to SV2A; and Ki or KiR to cerebellum for [18F]FDG metabolism. [11C]UCB-J binding and [18F]FDG metabolism showed a similar magnitude of reduction in the medial temporal lobe of AD -compared to CN participants. However, the magnitude of reduction of [11C]UCB-J binding in neocortical regions was less than that observed with [18F]FDG metabolism. Inter-tracer correlations were also higher in the medial temporal regions between synaptic density and metabolism, with lower correlations in neocortical regions. [11C]UCB-J perfusion showed a similar pattern to [18F]FDG metabolism, with high inter-tracer regional correlations. In summary, we conducted the first in vivo PET imaging of synaptic density and metabolism in the same AD participants and reported a concordant reduction in medial temporal regions but a discordant reduction in neocortical regions.

Identifying brain networks in synaptic density PET (11C-UCB-J) with independent component analysis

BACKGROUND

The human brain is inherently organized into distinct networks, as reported widely by resting-state functional magnetic resonance imaging (rs-fMRI), which are based on blood-oxygen-level-dependent (BOLD) signal fluctuations. ¹¹C-UCB-J PET maps synaptic density via synaptic vesicle protein 2A, which is a more direct structural measure underlying brain networks than BOLD rs-fMRI.

METHODS

The aim of this study was to identify maximally independent brain source networks, i.e., "spatial patterns with common covariance across subjects", in ¹¹C-UCB-J data using independent component analysis (ICA), a data-driven analysis method. Using a population of 80 healthy controls, we applied ICA to two 40-sample subsets and compared source network replication across samples. We examined the identified source networks at multiple model orders, as the ideal number of maximally independent components (IC) is unknown. In addition, we investigated the relationship between the strength of the loading weights for each source network and age and sex.

RESULTS

Thirteen source networks replicated across both samples. We determined that a model order of 18 components provided stable, replicable components, whereas estimations above 18 were not stable. Effects of sex were found in two ICs. Nine ICs showed age-related change, with 4 remaining significant after correction for multiple comparison.

CONCLUSION

This study provides the first evidence that human brain synaptic density can be characterized into organized covariance patterns. Furthermore, we demonstrated that multiple synaptic density source networks are associated with age, which supports the potential utility of ICA to identify biologically relevant synaptic density source networks.

Quantification of SV2A Binding in Rodent Brain Using [18F]SynVesT-1 and PET Imaging

PURPOSE

Synapse loss is a hallmark of Alzheimer's disease (AD) and correlates with cognitive decline. The validation of a noninvasive in vivo imaging approach to quantify synapse would greatly facilitate our understanding of AD pathogenesis and assist drug developments for AD. As animal models of neurodegenerative and neuropsychiatric disorders play a critical role in the drug discovery and development process, a robust, objective, and translational method for quantifying therapeutic drug efficacy in animal models will facilitate the drug development process. In this study, we tested the quantification reliability of the SV2A PET tracer, [¹⁸F]SynVesT-1, in a mouse model of AD (APP/PS1) and wild-type controls, and developed a simplified quantification method to facilitate large cohort preclinical imaging studies.

PROCEDURES

We generated nondisplaceable binding potential (BP_ND) and distribution volume ratio (DVR) values using the simplified reference tissue model (SRTM) on the 90-min dynamic PET imaging data, with brain stem and cerebellum as the reference region, respectively. Then, we correlated the standardized uptake value ratio (SUVR)-1 and SUVR averaged from different imaging windows with BP_ND and DVR, using brain stem and cerebellum as the reference region, respectively. We performed homologous competitive binding assay and autoradiographic saturation binding assay using [¹⁸F]SynVesT-1 to calculate the B_max and K_d.

RESULTS

Using brain stem as the reference region, the averaged SUVR-1 from 30 to 60 min postinjection correlated well with the BP_ND calculated using SRTM. Using cerebellum as the reference region, the averaged SUVR from 30 to 60 min postinjection correlated well with the SRTM DVR. From the homologous competitive binding assay and autoradiographic saturation binding assay, the calculated the B_max and K_d were 4.5-18 pmol/mg protein and 9.8-19.6 nM, respectively, for rodent brain tissue.

CONCLUSIONS

This simplified SUVR method provides reasonable SV2A measures in APP/PS1 mice and their littermate controls. Our data indicate that, in lieu of a full 90-min dynamic scan, a 30-min static PET scan (from 30 to 60 min postinjection) would be sufficient to provide quantification data on SV2A expression, equivalent to the data generated from kinetic modeling. The methods developed here are readily applicable to the evaluation of therapeutic effects of novel drugs in this rodent model using [¹⁸F]SynVesT-1 and small animal PET.

Association of Aβ deposition and regional synaptic density in early Alzheimer's disease: a PET imaging study with [11C]UCB-J

BACKGROUND

Attempts to associate amyloid-β (Aβ) pathogenesis with synaptic loss in Alzheimer's disease (AD) have thus far been limited to small numbers of postmortem studies. Aβ plaque burden is not well-correlated with indices of clinical severity or neurodegeneration-at least in the dementia stage-as deposition of Aβ reaches a ceiling. In this study, we examined in vivo the association between fibrillar Aβ deposition and synaptic density in early AD using positron emission tomography (PET). We hypothesized that global Aβ deposition would be more strongly inversely associated with hippocampal synaptic density in participants with amnestic mild cognitive impairment (aMCI; a stage of continued Aβ accumulation) compared to those with dementia (a stage of relative Aβ plateau).

METHODS

We measured SV2A binding ([11C]UCB-J) and Aβ deposition ([11C]PiB) in 14 participants with aMCI due to AD and 24 participants with mild AD dementia. Distribution volume ratios (DVR) with a cerebellar reference region were calculated for both tracers to investigate the association between global Aβ deposition and SV2A binding in hippocampus. Exploratory analyses examined correlations between both global and regional Aβ deposition and SV2A binding across a broad range of brain regions using both ROI- and surface-based approaches.

RESULTS

We observed a significant inverse association between global Aβ deposition and hippocampal SV2A binding in participants with aMCI (r = - 0.55, P = 0.04), but not mild dementia (r = 0.05, P = 0.82; difference statistically significant by Fisher z = - 1.80, P = 0.04). Exploratory analyses across other ROIs and whole brain analyses demonstrated no broad or consistent associations between global Aβ deposition and regional SV2A binding in either diagnostic group. ROI-based analyses of the association between regional Aβ deposition and SV2A binding also revealed no consistent pattern but suggested a "paradoxical" positive association between local Aβ deposition and SV2A binding in the hippocampus.

CONCLUSIONS

Our findings lend support to a model in which fibrillar Aβ is still accumulating in the early stages of clinical disease but approaching a relative plateau, a point at which Aβ may uncouple from neurodegenerative processes including synaptic loss. Future research should investigate the relationship between Aβ deposition and synaptic loss in larger cohorts beginning preclinically and followed longitudinally in conjunction with other biomarkers.

Reduced synaptic vesicle protein 2A binding in temporal lobe epilepsy: A [11 C]UCB-J positron emission tomography study

OBJECTIVE

In this positron emission tomography (PET) study with [¹¹ C]UCB-J, we evaluated synaptic vesicle glycoprotein 2A (SV2A) binding, which is decreased in resected brain tissues from epilepsy patients, in subjects with temporal lobe epilepsy (TLE) and compared the regional binding pattern to [¹⁸ F]fluorodeoxyglucose (FDG) uptake.

METHODS

Twelve TLE subjects and 12 control subjects were examined. Regional [¹¹ C]UCB-J binding potential (BP_ND ) values were estimated using the centrum semiovale as a reference region. [¹⁸ F]FDG uptake in TLE subjects was quantified using mean radioactivity values. Asymmetry in outcome measures was assessed by comparison of ipsilateral and contralateral regions. Partial volume correction (PVC) with the iterative Yang algorithm was applied based on the FreeSurfer segmentation.

RESULTS

In 11 TLE subjects with medial temporal lobe sclerosis (MTS), the hippocampal volumetric asymmetry was 25 ± 11%. After PVC, [¹¹ C]UCB-J BP_ND asymmetry indices were 37 ± 19% in the hippocampus, with very limited asymmetry in other brain regions. Reductions in [¹¹ C]UCB-J BP_ND values were restricted to the sclerotic hippocampus when compared to control subjects. The corresponding asymmetry in hippocampal [¹⁸ F]FDG uptake was 22 ± 7% and correlated with that of [¹¹ C]UCB-J BP_ND across subjects (R²  = .38). Hippocampal asymmetries in [¹¹ C]UCB-J binding were 1.7-fold larger than those of [¹⁸ F]FDG uptake.

SIGNIFICANCE

[¹¹ C]UCB-J binding is reduced in the seizure onset zone of TLE subjects with MTS. PET imaging of SV2A may be a promising biomarker approach in the presurgical selection and evaluation of TLE patients and may improve the sensitivity of molecular imaging for seizure focus detection.

Apathy in Alzheimer's Disease Correlates with the Dopamine Transporter Level in the Caudate Nuclei

Introduction

Apathy is a common neuropsychiatric symptom in patients with Alzheimer's disease (AD). The striatal binding potential (BP) of ¹²³I-FP-CIT (N-δ-fluoropropyl-2β-carbomethoxy-3β-[4-iodophenyl]tropane) single-photon emission computed tomography (SPECT) is correlated with the degree of apathy in patients with Parkinson's disease (PD) and dementia with Lewy bodies (DLB). This study aimed to determine if dopaminergic activity in the basal ganglia is associated with the development of apathy in AD.

Methods

Nineteen subjects with AD were included and underwent ¹²³I-FP-CIT-SPECT. Patients with other types of dementia as a comorbidity, those taking antidepressants, and those with overt parkinsonism were excluded. Apathy was assessed using the Apathy Evaluation Scale Informant-Japanese version (AES-I-J). SPECT images were overlaid with images in striatal regions of interest (ROIs), and the SPECT values in these regions were counted. The relationship between BP values and AES-I-J scores was investigated using Spearman's rank correlation coefficient.

Results

Significant inverse correlations were observed between BP values and AES-I-J scores in the left caudate nucleus and there was a marginally significant inverse correlation in the right caudate nucleus.

Conclusion

The pathological basis of apathy might be the impairment of the dopaminergic nervous system. Further studies on more subjects with AD, healthy controls, and patients with PD and DLB are needed.

Assessment of a white matter reference region for 11C-UCB-J PET quantification

¹¹C-UCB-J is a positron emission tomography (PET) radioligand that has been used in humans for synaptic vesicle glycoprotein 2A (SV2A) imaging and as a potential synaptic density marker. The centrum semiovale (CS) is a proposed reference region for noninvasive quantification of ¹¹C-UCB-J, due to negligible concentrations of SV2A in this region in baboon brain assessed by in vitro methods. However, in displacement scans with SV2A-specific drug levetiracetam in humans, a decrease in ¹¹C-UCB-J concentration was observed in the CS, consistent with some degree of specific binding. The current study aims to validate the CS as a reference region by (1) optimizing CS region of interest (ROI) to minimize spill-in from gray matter with high radioactivity concentrations; (2) investigating convergence of CS ROI values using ordered subset expectation maximization (OS-EM) reconstruction, and (3) comparing baseline CS volume of distribution (V_T) to nondisplaceable uptake in gray matter, V_ND. Improving ROI definition and increasing OS-EM iterations during reconstruction decreased the difference between CS V_T and V_ND. However, even with these corrections, CS V_T overestimated V_ND by ∼35-40%. These measures showed significant correlation, suggesting that, though biased, the CS may be a useful estimate of nondisplaceable uptake, allowing for noninvasive quantification for SV2A PET.