Repetitive mild closed-head injury induced synapse loss and increased local BOLD-fMRI signal homogeneity.

Repeated mild head injuries due to sports, or domestic violence and military service are increasingly linked to debilitating symptoms in the long term. Although symptoms may take decades to manifest, potentially treatable neurobiological alterations must begin shortly after injury. Better means to diagnose and treat traumatic brain injuries, requires an improved understanding of the mechanisms underlying progression and means through which they can be measured. Here, we employ a repetitive mild closed-head injury (rmTBI) and chronic variable stress (CVS) mouse model to investigate emergent structural and functional brain abnormalities. Brain imaging is achieved with [ 18 F]SynVesT-1 positron emission tomography, with the synaptic vesicle glycoprotein 2A ligand marking synapse density and BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI). Animals were scanned six weeks after concluding rmTBI/Stress procedures. Injured mice showed widespread decreases in synaptic density coupled with an i ncrease in local BOLD-fMRI synchrony detected as regional homogeneity. Injury-affected regions with higher synapse density showed a greater increase in fMRI regional homogeneity. Taken together, these observations may reflect compensatory mechanisms following injury. Multimodal studies are needed to provide deeper insights into these observations.

Medial amygdalar tau is associated with anxiety symptoms in preclinical Alzheimer's disease.

BACKGROUND: While the amygdala receives early tau deposition in Alzheimer's disease (AD) and is involved in social and emotional processing, the relationship between amygdalar tau and early neuropsychiatric symptoms in AD is unknown. We sought to determine whether focal tau binding in the amygdala and abnormal amygdalar connectivity were detectable in a preclinical AD cohort and identify relationships between these and self-reported mood symptoms. METHODS: We examined n=598 individuals (n=347 amyloid-positive (58% female), n=251 amyloid-negative (62% female); subset into tau PET and fMRI cohorts) from the A4 Study. In our tau PET cohort, we used amygdalar segmentations to examine representative nuclei from three functional divisions of the amygdala. We analyzed between-group differences in division-specific tau binding in the amygdala in preclinical AD. We conducted seed-based functional connectivity analyses from each division in the fMRI cohort. Finally, we conducted exploratory post-hoc correlation analyses between neuroimaging biomarkers of interest and anxiety and depression scores. RESULTS: Amyloid-positive individuals demonstrated increased tau binding in medial and lateral amygdala (F(4,442)=14.61, p=0.00045; F(4,442)=5.83, p=0.024, respectively). Across amygdalar divisions, amyloid-positive individuals had relatively increased regional connectivity from amygdala to other temporal regions, insula, and orbitofrontal cortex. There was an interaction by amyloid group between tau binding in the medial and lateral amygdala and anxiety. Medial amygdala to retrosplenial connectivity negatively correlated with anxiety symptoms (rs=-0.103, p=0.015). CONCLUSIONS: Our findings suggest that preclinical tau deposition in the amygdala may result in meaningful changes in functional connectivity which may predispose patients to mood symptoms.

Performance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager.

The collaboration of Yale, the University of California, Davis, and United Imaging Healthcare has successfully developed the NeuroEXPLORER, a dedicated human brain PET imager with high spatial resolution, high sensitivity, and a built-in 3-dimensional camera for markerless continuous motion tracking. It has high depth-of-interaction and time-of-flight resolutions, along with a 52.4-cm transverse field of view (FOV) and an extended axial FOV (49.5 cm) to enhance sensitivity. Here, we present the physical characterization, performance evaluation, and first human images of the NeuroEXPLORER. Methods: Measurements of spatial resolution, sensitivity, count rate performance, energy and timing resolution, and image quality were performed adhering to the National Electrical Manufacturers Association (NEMA) NU 2-2018 standard. The system's performance was demonstrated through imaging studies of the Hoffman 3-dimensional brain phantom and the mini-Derenzo phantom. Initial 18F-FDG images from a healthy volunteer are presented. Results: With filtered backprojection reconstruction, the radial and tangential spatial resolutions (full width at half maximum) averaged 1.64, 2.06, and 2.51 mm, with axial resolutions of 2.73, 2.89, and 2.93 mm for radial offsets of 1, 10, and 20 cm, respectively. The average time-of-flight resolution was 236 ps, and the energy resolution was 10.5%. NEMA sensitivities were 46.0 and 47.6 kcps/MBq at the center and 10-cm offset, respectively. A sensitivity of 11.8% was achieved at the FOV center. The peak noise-equivalent count rate was 1.31 Mcps at 58.0 kBq/mL, and the scatter fraction at 5.3 kBq/mL was 36.5%. The maximum count rate error at the peak noise-equivalent count rate was less than 5%. At 3 iterations, the NEMA image-quality contrast recovery coefficients varied from 74.5% (10-mm sphere) to 92.6% (37-mm sphere), and background variability ranged from 3.1% to 1.4% at a contrast of 4.0:1. An example human brain 18F-FDG image exhibited very high resolution, capturing intricate details in the cortex and subcortical structures. Conclusion: The NeuroEXPLORER offers high sensitivity and high spatial resolution. With its long axial length, it also enables high-quality spinal cord imaging and image-derived input functions from the carotid arteries. These performance enhancements will substantially broaden the range of human brain PET paradigms, protocols, and thereby clinical research applications.

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.

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.

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.

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.

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.

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.

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-ß oligomers (Aßo). 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 Aß 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 Aß plaque or preventing gliotic reaction. This supports targeting the Aßo-PrPC interaction to prevent Aßo-neurotoxicity and pathologic tau accumulation in AD.

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.

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.

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.

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.

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.

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.

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.

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.