A prospective 5-year longitudinal study detects neurocognitive and imaging correlates of seizure remission in self-limiting Rolandic epilepsy.

OBJECTIVE: Self-limiting Rolandic epilepsy (RE) is the most common epilepsy in school-age children. Seizures are generally infrequent, but cognitive, language, and motor coordination problems can significantly impact the child's life. To better understand brain structure and function changes in RE, we longitudinally assessed neurocognition, cortical thickness, and subcortical volumes. METHODS: At baseline, we recruited 30 participants diagnosed with RE and 24-healthy controls and followed up for 4.94 ± 0.8 years when the participants with RE were in seizure remission. Measures included were as follows: T1-weighted magnetic resonance brain imaging (MRI) with FreeSurfer analysis and detailed neuropsychological assessments. MRI and neuropsychological data were compared between baseline and follow-up in seizure remission. RESULTS: Longitudinal MRI revealed excess cortical thinning in the left-orbitofrontal (p = 0.0001) and pre-central gyrus (p = 0.044). There is a significant association (p = 0.003) between a reduction in cortical thickness in the left-orbitofrontal cluster and improved processing of filtered words. Longitudinal neuropsychology revealed significant improvements in the symptoms of developmental coordination disorder (DCD, p = 0.005) in seizure remission. CONCLUSIONS: There is evidence for altered development of neocortical regions between active seizure state and seizure remission in RE within two clusters maximal in the left-orbitofrontal and pre-central gyrus. There is significant evidence for improvement in motor coordination between active seizures and seizure remission and suggestive evidence for a decline in fluid intelligence and gains in auditory processing.

Motion-corrected and high-resolution anatomically assisted (MOCHA) reconstruction of arterial spin labeling MRI.

PURPOSE: A model-based reconstruction framework is proposed for motion-corrected and high-resolution anatomically assisted (MOCHA) reconstruction of arterial spin labeling (ASL) data. In this framework, all low-resolution ASL control-label pairs are used to reconstruct a single high-resolution cerebral blood flow (CBF) map, corrected for rigid-motion, point-spread-function blurring and partial volume effect. METHODS: Six volunteers were recruited for CBF imaging using pseudo-continuous ASL labeling, two-shot 3D gradient and spin-echo sequences and high-resolution T1 -weighted MRI. For 2 volunteers, high-resolution scans with double and triple resolution in the partition direction were additionally collected. Simulations were designed for evaluations against a high-resolution ground-truth CBF map, including a simulated hyperperfused lesion and hyperperfusion/hypoperfusion abnormalities. The MOCHA technique was compared with standard reconstruction and a 3D linear regression partial-volume effect correction method and was further evaluated for acquisitions with reduced control-label pairs and k-space undersampling. RESULTS: The MOCHA reconstructions of low-resolution ASL data showed enhanced image quality, particularly in the partition direction. In simulations, both MOCHA and 3D linear regression provided more accurate CBF maps than the standard reconstruction; however, MOCHA resulted in the lowest errors and well delineated the abnormalities. The MOCHA reconstruction of standard-resolution in vivo data showed good agreement with higher-resolution scans requiring 4-times and 9-times longer acquisitions. The MOCHA reconstruction was found to be robust for 4-times-accelerated ASL acquisitions, achieved by reduced control-label pairs or k-space undersampling. CONCLUSION: The MOCHA reconstruction reduces partial-volume effect by direct reconstruction of CBF maps in the high-resolution space of the corresponding anatomical image, incorporating motion correction and point spread function modeling. Following further evaluation, MOCHA should promote the clinical application of ASL.

Multi-modal synergistic PET and MR reconstruction using mutually weighted quadratic priors.

PURPOSE: To propose a framework for synergistic reconstruction of PET-MR and multi-contrast MR data to improve the image quality obtained from noisy PET data and from undersampled MR data. THEORY AND METHODS: Weighted quadratic priors were devised to preserve common boundaries between PET-MR images while reducing noise, PET Gibbs ringing, and MR undersampling artifacts. These priors are iteratively reweighted using normalized multi-modal Gaussian similarity kernels. Synergistic PET-MR reconstructions were built on the PET maximum a posteriori expectation maximization algorithm and the MR regularized sensitivity encoding method. The proposed approach was compared to conventional methods, total variation, and prior-image weighted quadratic regularization methods. Comparisons were performed on a simulated [18 F]fluorodeoxyglucose-PET and T1 /T2 -weighted MR brain phantom, 2 in vivo T1 /T2 -weighted MR brain datasets, and an in vivo [18 F]fluorodeoxyglucose-PET and fluid-attenuated inversion recovery/T1 -weighted MR brain dataset. RESULTS: Simulations showed that synergistic reconstructions achieve the lowest quantification errors for all image modalities compared to conventional, total variation, and weighted quadratic methods. Whereas total variation regularization preserved modality-unique features, this method failed to recover PET details and was not able to reduce MR artifacts compared to our proposed method. For in vivo MR data, our method maintained similar image quality for 3× and 14× accelerated data. Reconstruction of the PET-MR dataset also demonstrated improved performance of our method compared to the conventional independent methods in terms of reduced Gibbs and undersampling artifacts. CONCLUSION: The proposed methodology offers a robust multi-modal synergistic image reconstruction framework that can be readily built on existing established algorithms.

Test-retest reproducibility of quantitative binding measures of [11C]Ro15-4513, a PET ligand for GABAA receptors containing alpha5 subunits.

INTRODUCTION: Alteration of γ-aminobutyric acid "A" (GABAA) receptor-mediated neurotransmission has been associated with various neurological and psychiatric disorders. [11C]Ro15-4513 is a PET ligand with high affinity for α5-subunit-containing GABAA receptors, which are highly expressed in limbic regions of the human brain (Sur et al., 1998). We quantified the test-retest reproducibility of measures of [11C]Ro15-4513 binding derived from six different quantification methods (12 variants). METHODS: Five healthy males (median age 40 years, range 38-49 years) had a 90-min PET scan on two occasions (median interval 12 days, range 11-30 days), after injection of a median dose of 441 MegaBequerels of [11C]Ro15-4513. Metabolite-corrected arterial plasma input functions (parent plasma input functions, ppIFs) were generated for all scans. We quantified regional binding using six methods (12 variants), some of which were region-based (applied to the average time-activity curve within a region) and others were voxel-based: 1) Models requiring arterial ppIFs - regional reversible compartmental models with one and two tissue compartments (2kbv and 4kbv); 2) Regional and voxelwise Logan's graphical analyses (Logan et al., 1990), which required arterial ppIFs; 3) Model-free regional and voxelwise (exponential) spectral analyses (SA; (Cunningham and Jones, 1993)), which also required arterial ppIFs; 4) methods not requiring arterial ppIFs - voxelwise standardised uptake values (Kenney et al., 1941), and regional and voxelwise simplified reference tissue models (SRTM/SRTM2) using brainstem or alternatively cerebellum as pseudo-reference regions (Lammertsma and Hume, 1996; Gunn et al., 1997). To compare the variants, we sampled the mean values of the outcome parameters within six bilateral, non-reference grey matter regions-of-interest. Reliability was quantified in terms of median absolute percentage test-retest differences (MA-TDs; preferentially low) and between-subject coefficient of variation (BS-CV, preferentially high), both compounded by the intraclass correlation coefficient (ICC). These measures were compared between variants, with particular interest in the hippocampus. RESULTS: Two of the six methods (5/12 variants) yielded reproducible data (i.e. MA-TD <10%): regional SRTMs and voxelwise SRTM2s, both using either the brainstem or the cerebellum; and voxelwise SA. However, the SRTMs using the brainstem yielded a lower median BS-CV (7% for regional, 7% voxelwise) than the other variants (8-11%), resulting in lower ICCs. The median ICCs across six regions were 0.89 (interquartile range 0.75-0.90) for voxelwise SA, 0.71 (0.64-0.84) for regional SRTM-cerebellum and 0.83 (0.70-0.86) for voxelwise SRTM-cerebellum. The ICCs for the hippocampus were 0.89 for voxelwise SA, 0.95 for regional SRTM-cerebellum and 0.93 for voxelwise SRTM-cerebellum. CONCLUSION: Quantification of [11C]Ro15-4513 binding shows very good to excellent reproducibility with SRTM and with voxelwise SA which, however, requires an arterial ppIF. Quantification in the α5 subunit-rich hippocampus is particularly reliable. The very low expression of the α5 in the cerebellum (Fritschy and Mohler, 1995; Veronese et al., 2016) and the substantial α1 subunit density in this region may hamper the application of reference tissue methods.

Using [(11)C]Ro15 4513 PET to characterise GABA-benzodiazepine receptors in opiate addiction: Similarities and differences with alcoholism.

The importance of the GABA-benzodiazepine receptor complex and its subtypes are increasingly recognised in addiction. Using the α1/α5 benzodiazepine receptor PET radioligand [(11)C]Ro15 4513, we previously showed reduced binding in the nucleus accumbens and hippocampus in abstinent alcohol dependence. We proposed that reduced [(11)C]Ro15 4513 binding in the nucleus accumbens was a marker of addiction whilst the reduction in hippocampus and positive relationship with memory was a consequence of chronic alcohol abuse. To examine this further we assessed [(11)C]Ro15 4513 binding in another addiction, opiate dependence, and used spectral analysis to estimate contributions of α1 and α5 subtypes to [(11)C]Ro15 4513 binding in opiate and previously acquired alcohol-dependent groups. Opiate substitute maintained opiate-dependent men (n=12) underwent an [(11)C]Ro15 4513 PET scan and compared with matched healthy controls (n=13). We found a significant reduction in [(11)C]Ro15 4513 binding in the nucleus accumbens in the opiate-dependent compared with the healthy control group. There was no relationship between [(11)C]Ro15 4513 binding in the hippocampus with memory. We found that reduced [(11)C]Ro15 4513 binding was associated with reduced α5 but not α1 subtypes in the opiate-dependent group. This was also seen in an alcohol-dependent group where an association between memory performance and [(11)C]Ro15 4513 binding was primarily driven by α5 and not α1 subtype. We suggest that reduced α5 levels in the nucleus accumbens are associated with addiction since we have now shown this in dependence to two pharmacologically different substances, alcohol and opiates.

Risk factors for reading disability in families with rolandic epilepsy.

OBJECTIVE: The high prevalence and impact of neurodevelopmental comorbidities in childhood epilepsy are now well known, as are the increased risks and familial aggregation of reading disability (RD) and speech sound disorder (SSD) in rolandic epilepsy (RE). The risk factors for RD in the general population include male sex, SSD, and ADHD, but it is not known if these are the same in RE or whether there is a contributory role of seizure and treatment-related variables. METHODS: An observational study of 108 probands with RE (age range: 3.6-22 years) and their 159 siblings (age range: 1-29 years; 83 with EEG data) were singly ascertained in the US or UK through a proband affected by RE. We used a nested case-control design, multiple logistic regression, and generalized estimating equations to test the hypothesis of an association between RD and seizure variables or antiepileptic drug treatment in RE; we also assessed an association between EEG focal sharp waves and RD in siblings. RESULTS: Reading disability was reported in 42% of probands and 22% of siblings. Among probands, RD was strongly associated with a history of SSD (OR: 9.64, 95% CI: 2.45-37.21), ADHD symptoms (OR: 10.31, 95% CI: 2.15-49.44), and male sex (OR: 3.62, 95% CI: 1.11-11.75) but not with seizure or treatment variables. Among siblings, RD was independently associated only with SSD (OR: 4.30, 95% CI: 1.42-13.0) and not with the presence of interictal EEG focal sharp waves. SIGNIFICANCE: The principal risk factors for RD in RE are SSD, ADHD, and male sex, the same risk factors as for RD without epilepsy. Seizure or treatment variables do not appear to be important risk factors for RD in probands with RE, and there was no evidence to support interictal EEG focal sharp waves as a risk factor for RD in siblings. Future studies should focus on the precise neuropsychological characterization of RD in families with RE and on the effectiveness of standard oral-language and reading interventions.

Test-retest reproducibility of cannabinoid-receptor type 1 availability quantified with the PET ligand [¹¹C]MePPEP.

BACKGROUND: Endocannabinoids are involved in normal cognition, and dysfunction in cannabinoid-receptor-mediated neurotransmission has been suggested in a variety of neurological and psychiatric pathologies. The type 1 cannabinoid receptor (CB1) is widely expressed in the human central nervous system. The objective of this study was to quantify the test-retest reproducibility of measures of the PET ligand [(11)C]MePPEP in order to assess the stability of CB1-receptor quantification in humans in vivo. METHODS: Fifteen healthy subjects (eight females; median age 32 years, range 25 to 65 years) had a 90-minute PET scan on two occasions after injection of a median dose of [(11)C]MePPEP of 364 MBq. Metabolite-corrected arterial plasma input functions were obtained for all scans. Eight ROIs, reflecting different levels of receptor densities/concentrations, were defined automatically: hippocampus, anterior cingulate gyrus, inferior frontal gyrus, caudate nucleus, globus pallidus, nucleus accumbens, thalamus, and pons. We used seven quantification methods: reversible compartmental models with one and two tissue classes, two and four rate constants, and a variable blood volume term (2kbv; 4kbv); model-free (spectral) analyses with and without regularisation, including one with voxel-wise quantification; the simplified reference tissue model (SRTM) with pons as a pseudo-reference region; and modified standard uptake values (mSUVs) calculated for the period of ~30-60 min after injection. Percentage test-retest change and between-subject variability were both assessed, and test-retest reliability was quantified by the intraclass correlation coefficient (ICC). The ratio of binding estimates pallidum:pons served as an indicator of a method's ability to reflect binding heterogeneity. RESULTS: Neither the SRTM nor the 4kbv model produced reliable measures, with ICCs around zero. Very good (>0.75) or excellent (>0.80) ICCs were obtained with the other methods. The most reliable were spectral analysis parametric maps (average across regions±standard deviation 0.83±0.03), rank shaping regularised spectral analysis (0.82±0.05), and the 2kbv model (0.82±0.09), but mSUVs were also reliable for most regions (0.79±0.13). Mean test-retest changes among the five well-performing methods ranged from 12±10% for mSUVs to 16% for 2kbv. Intersubject variability was high, with mean between-subject coefficients of variation ranging from 32±13% for mSUVs to 45% for 2kbv. The highest pallidum:pons ratios of binding estimates were achieved by mSUV (4.2), spectral analysis-derived parametric maps (3.6), and 2kbv (3.6). CONCLUSION: Quantification of CB1 receptor availability using [(11)C]MePPEP shows good to excellent reproducibility with several kinetic models and model-free analyses, whether applied on a region-of-interest or voxelwise basis. Simple mSUV measures were also reliable for most regions, but do not allow fully quantitative interpretation. [(11)C]MePPEP PET is well placed as a tool to investigate CB1-receptor mediated neurotransmission in health and disease.

Quantification of opioid receptor availability following spontaneous epileptic seizures: correction of [11C]diprenorphine PET data for the partial-volume effect.

Previous positron emission tomography (PET) studies in refractory temporal lobe epilepsy (TLE) using the non-selective opioid receptor antagonist [(11)C]diprenorphine (DPN) did not detect any changes in mesial temporal structures, despite known involvement of the hippocampus in seizure generation. Normal binding in smaller hippocampi is suggestive of increased receptor concentration in the remaining grey matter. Correction for partial-volume effect (PVE) has not been used in previous DPN PET studies. Here, we present PVE-corrected DPN-PET data quantifying post-ictal and interictal opioid receptor availability in humans with mTLE. Eight paired datasets of post-ictal and interictal DPN PET scans and eleven test/retest control datasets were available from a previously published study on opioid receptor changes in TLE following seizures (Hammers et al., 2007a). Five of the eight participants with TLE had documented hippocampal sclerosis. Data were re-analyzed using regions of interest and a novel PVE correction method (structural functional synergistic-resolution recovery (SFS-RR); (Shidahara et al., 2012)). Data were denoised, followed by application of SFS-RR, with anatomical information derived via precise anatomical segmentation of the participants' MRI (MAPER; (Heckemann et al., 2010)). [(11)C]diprenorphine volume-of-distribution (VT) was quantified in six regions of interest. Post-ictal increases were observed in the ipsilateral fusiform gyri and lateral temporal pole. A novel finding was a post-ictal increase in [(11)C]DPN VT relative to the interictal state in the ipsilateral parahippocampal gyrus, not observed in uncorrected datasets. As for voxel-based (SPM) analyses, correction for global VT values was essential in order to demonstrate focal post-ictal increases in [(11)C]DPN VT. This study provides further direct human in vivo evidence for changes in opioid receptor availability in TLE following seizures, including changes that were not evident without PVE correction. Denoising, resolution recovery and precise anatomical segmentation can extract valuable information from PET studies that would be missed with conventional post-processing procedures.

Pre-training via Transfer Learning and Pretext Learning a Convolutional Neural Network for Automated Assessments of Clinical PET Image Quality.

Positron emission tomography (PET) using a fraction of the usual injected dose would reduce the amount of radioligand needed, as well as the radiation dose to patients and staff, but would compromise reconstructed image quality. For performing the same clinical tasks with such images, a clinical (rather than numerical) image quality assessment is essential. This process can be automated with convolutional neural networks (CNNs). However, the scarcity of clinical quality readings is a challenge. We hypothesise that exploiting easily available quantitative information in pretext learning tasks or using established pre-trained networks could improve CNN performance for predicting clinical assessments with limited data. CNNs were pre-trained to predict injected dose from image patches extracted from eight real patient datasets, reconstructed using between 0.5%-100% of the available data. Transfer learning with seven different patients was used to predict three clinically-scored quality metrics ranging from 0-3: global quality rating, pattern recognition and diagnostic confidence. This was compared to pre-training via a VGG16 network at varying pre-training levels. Pre-training improved test performance for this task: the mean absolute error of 0.53 (compared to 0.87 without pre-training), was within clinical scoring uncertainty. Future work may include using the CNN for novel reconstruction methods performance assessment.

PET image enhancement using artificial intelligence for better characterization of epilepsy lesions.

Introduction: [18F]fluorodeoxyglucose ([18F]FDG) brain PET is used clinically to detect small areas of decreased uptake associated with epileptogenic lesions, e.g., Focal Cortical Dysplasias (FCD) but its performance is limited due to spatial resolution and low contrast. We aimed to develop a deep learning-based PET image enhancement method using simulated PET to improve lesion visualization. Methods: We created 210 numerical brain phantoms (MRI segmented into 9 regions) and assigned 10 different plausible activity values (e.g., GM/WM ratios) resulting in 2100 ground truth high quality (GT-HQ) PET phantoms. With a validated Monte-Carlo PET simulator, we then created 2100 simulated standard quality (S-SQ) [18F]FDG scans. We trained a ResNet on 80% of this dataset (10% used for validation) to learn the mapping between S-SQ and GT-HQ PET, outputting a predicted HQ (P-HQ) PET. For the remaining 10%, we assessed Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Root Mean Squared Error (RMSE) against GT-HQ PET. For GM and WM, we computed recovery coefficients (RC) and coefficient of variation (COV). We also created lesioned GT-HQ phantoms, S-SQ PET and P-HQ PET with simulated small hypometabolic lesions characteristic of FCDs. We evaluated lesion detectability on S-SQ and P-HQ PET both visually and measuring the Relative Lesion Activity (RLA, measured activity in the reduced-activity ROI over the standard-activity ROI). Lastly, we applied our previously trained ResNet on 10 clinical epilepsy PETs to predict the corresponding HQ-PET and assessed image quality and confidence metrics. Results: Compared to S-SQ PET, P-HQ PET improved PNSR, SSIM and RMSE; significatively improved GM RCs (from 0.29 ± 0.03 to 0.79 ± 0.04) and WM RCs (from 0.49 ± 0.03 to 1 ± 0.05); mean COVs were not statistically different. Visual lesion detection improved from 38 to 75%, with average RLA decreasing from 0.83 ± 0.08 to 0.67 ± 0.14. Visual quality of P-HQ clinical PET improved as well as reader confidence. Conclusion: P-HQ PET showed improved image quality compared to S-SQ PET across several objective quantitative metrics and increased detectability of simulated lesions. In addition, the model generalized to clinical data. Further evaluation is required to study generalization of our method and to assess clinical performance in larger cohorts.

The association between N-methyl-d-aspartate receptor availability and glutamate levels: A multi-modal PET-MR brain imaging study in first-episode psychosis and healthy controls.

BACKGROUND: Evidence from post-mortem studies and in vivo imaging studies suggests there may be reduced N-methyl-d-aspartate receptor (NMDAR) levels in the hippocampus in patients with schizophrenia. Other studies have reported increased glutamate in striatum in schizophrenia patients. It has been hypothesised that NMDAR hypofunction leads to the disinhibition of glutamatergic signalling; however, this has not been tested in vivo. METHODS: In this study, we investigated the relationship between hippocampal NMDAR and striatal glutamate using simultaneous positron emission tomography-magnetic resonance (PET-MR) imaging. We recruited 40 volunteers to this cross-sectional study; 21 patients with schizophrenia, all in their first episode of illness, and 19 healthy controls. We measured hippocampal NMDAR availability using the PET ligand [18F]GE179. This was indexed relative to whole brain as the distribution volume ratio (DVR). Striatal glutamatergic indices (glutamate and Glx) were acquired simultaneously, using combined PET-MR proton magnetic resonance spectroscopy (1H-MRS). RESULTS: A total of 33 individuals (15 healthy controls, 18 patients) were included in the analyses (mean (SD) age of controls, 27.31 (4.68) years; mean (SD) age of patients, 24.75 (4.33), 27 male and 6 female). We found an inverse relationship between hippocampal DVR and striatal glutamate levels in people with first-episode psychosis (rho = -0.74, p < 0.001) but not in healthy controls (rho = -0.22, p = 0.44). CONCLUSION: This study show that lower relative NMDAR availability in the hippocampus may drive increased striatal glutamate levels in patients with schizophrenia. Further work is required to determine whether these findings may yield new targets for drug development in schizophrenia.

Mapping neurotransmitter systems to the structural and functional organization of the human neocortex.

Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from more than 1,200 healthy individuals to construct a whole-brain three-dimensional normative atlas of 19 receptors and transporters across nine different neurotransmitter systems. We found that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting-state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncovered a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we found both expected and novel associations between receptor distributions and cortical abnormality patterns across 13 disorders. We replicated all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.

A Retrospective Case Series Analysis of the Relationship Between Phenylalanine: Tyrosine Ratio and Cerebral Glucose Metabolism in Classical Phenylketonuria and Hyperphenylalaninemia.

We retrospectively examined the relationship between blood biomarkers, in particular the historical mean phenylalanine to tyrosine (Phe:Tyr) ratio, and cerebral glucose metabolism. We hypothesized that the historical mean Phe:Tyr ratio would be more predictive of cerebral glucose metabolism than the phenylalanine (Phe) level alone. We performed a retrospective case series analysis involving 11 adult classical phenylketonuria/hyperphenylalaninemia patients under the care of an Inherited Metabolic & Neuropsychiatry Clinic who had complained of memory problems, collating casenote data from blood biochemistry, and clinical [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET). The Phe:Tyr ratio was calculated for individual blood samples and summarized as historical mean Phe:Tyr ratio (Phe:Tyr) and historical standard deviation in Phe:Tyr ratio (SD-Phe:Tyr), for each patient. Visual analyses of [18F]FDG PET revealed heterogeneous patterns of glucose hypometabolism for eight patients. [18F]FDG PET standardized uptake was negatively correlated with Phe in a large cluster with peak localized to right superior parietal gyrus. Even larger clusters of negative correlation that encompassed most of the brain, with frontal peaks, were observed with Phe:Tyr, and SD-Phe:Tyr. Our case series analysis provides further evidence for the association between blood biomarkers, and cerebral glucose hypometabolism. Mean historical blood Phe:Tyr ratio, and its standard deviation over time, appear to be more indicative of global cerebral glucose metabolism in patients with memory problems than Phe.

N-methyl-D-aspartate receptor availability in first-episode psychosis: a PET-MR brain imaging study.

N-methyl-D-aspartate receptor (NMDAR) hypofunction is hypothesised to underlie psychosis but this has not been tested early in illness. To address this, we studied 40 volunteers (21 patients with first-episode psychosis and 19 matched healthy controls) using PET imaging with an NMDAR selective ligand, [18F]GE-179, that binds to the ketamine binding site to index its distribution volume ratio (DVR) and volume of distribution (VT). Hippocampal DVR, but not VT, was significantly lower in patients relative to controls (p = 0.02, Cohen's d = 0.81; p = 0.15, Cohen's d = 0.49), and negatively associated with total (rho = -0.47, p = 0.04), depressive (rho = -0.67, p = 0.002), and general symptom severity (rho = -0.74, p < 0.001). Exploratory analyses found no significant differences in other brain regions (anterior cingulate cortex, thalamus, striatum and temporal cortex). These findings are consistent with the NMDAR hypofunction hypothesis and identify the hippocampus as a key locus for relative NMDAR hypofunction, although further studies should test specificity and causality.

Αlpha 5 subunit-containing GABAA receptors in temporal lobe epilepsy with normal MRI.

GABAA receptors containing the α5 subunit mediate tonic inhibition and are widely expressed in the limbic system. In animals, activation of α5-containing receptors impairs hippocampus-dependent memory. Temporal lobe epilepsy is associated with memory impairments related to neuron loss and other changes. The less selective PET ligand [11C]flumazenil has revealed reductions in GABAA receptors. The hypothesis that α5 subunit receptor alterations are present in temporal lobe epilepsy and could contribute to impaired memory is untested. We compared α5 subunit availability between individuals with temporal lobe epilepsy and normal structural MRI ('MRI-negative') and healthy controls, and interrogated the relationship between α5 subunit availability and episodic memory performance, in a cross-sectional study. Twenty-three healthy male controls (median ± interquartile age 49 ± 13 years) and 11 individuals with MRI-negative temporal lobe epilepsy (seven males; 40 ± 8) had a 90-min PET scan after bolus injection of [11C]Ro15-4513, with arterial blood sampling and metabolite correction. All those with epilepsy and six controls completed the Adult Memory and Information Processing Battery on the scanning day. 'Bandpass' exponential spectral analyses were used to calculate volumes of distribution separately for the fast component [V F; dominated by signal from α1 (α2, α3)-containing receptors] and the slow component (V S; dominated by signal from α5-containing receptors). We made voxel-by-voxel comparisons between: the epilepsy and control groups; each individual case versus the controls. We obtained parametric maps of V F and V S measures from a single bolus injection of [11C]Ro15-4513. The epilepsy group had higher V S in anterior medial and lateral aspects of the temporal lobes, the anterior cingulate gyri, the presumed area tempestas (piriform cortex) and the insulae, in addition to increases of ∼24% and ∼26% in the ipsilateral and contralateral hippocampal areas (P < 0.004). This was associated with reduced V F:V S ratios within the same areas (P < 0.009). Comparisons of V S for each individual with epilepsy versus controls did not consistently lateralize the epileptogenic lobe. Memory scores were significantly lower in the epilepsy group than in controls (mean ± standard deviation -0.4 ± 1.0 versus 0.7 ± 0.3; P = 0.02). In individuals with epilepsy, hippocampal V S did not correlate with memory performance on the Adult Memory and Information Processing Battery. They had reduced V F in the hippocampal area, which was significant ipsilaterally (P = 0.03), as expected from [11C]flumazenil studies. We found increased tonic inhibitory neurotransmission in our cohort of MRI-negative temporal lobe epilepsy who also had co-morbid memory impairments. Our findings are consistent with a subunit shift from α1/2/3 to α5 in MRI-negative temporal lobe epilepsy.

Attenuation of proliferation in oligodendrocyte precursor cells by activated microglia.

Activated microglia can influence the survival of neural cells through the release of cytotoxic factors. Here, we investigated the interaction between Toll-like receptor 4 (TLR4)-activated microglia and oligodendrocytes or their precursor cells (OPC). Primary rat or N9 microglial cells were activated by exposure to TLR4-specifc lipopolysaccharide (LPS), resulting in mitogen-activated protein kinase activation, increased CD68 and inducible nitric oxide synthase expression, and release of the proinflammatory cytokines tumor necrosis factor (TNF) and interleukin-6 (IL-6). Microglial conditioned medium (MGCM) from LPS-activated microglia attenuated primary OPC proliferation without inducing cell death. The microglial-induced inhibition of OPC proliferation was reversed by stimulating group III metabotropic glutamate receptors in microglia with the agonist L-AP4. In contrast to OPC, LPS-activated MGCM enhanced the survival of mature oligodendrocytes. Further investigation suggested that TNF and IL-6 released from TLR4-activated microglia might contribute to the effect of MGCM on OPC proliferation, insofar as TNF depletion of LPS-activated MGCM reduced the inhibition of OPC proliferation, and direct addition of TNF or IL-6 attenuated or increased proliferation, respectively. OPC themselves were also found to express proteins involved in TLR4 signalling, including TLR4, MyD88, and MAL. Although LPS stimulation of OPC did not induce proinflammatory cytokine release or affect their survival, it did trigger JNK phosphorylation, suggesting that TLR4 signalling in these cells is active. These findings suggest that OPC survival may be influenced not only by factors released from endotoxin-activated microglia but also through a direct response to endotoxins. This may have consequences for myelination under conditions in which microglial activation and cerebral infection are both implicated. , Inc.

Error propagation analysis of seven partial volume correction algorithms for [18F]THK-5351 brain PET imaging.

BACKGROUND: Novel partial volume correction (PVC) algorithms have been validated by assuming ideal conditions of image processing; however, in real clinical PET studies, the input datasets include error sources which cause error propagation to the corrected outcome. METHODS: We aimed to evaluate error propagations of seven PVCs algorithms for brain PET imaging with [18F]THK-5351 and to discuss the reliability of those algorithms for clinical applications. In order to mimic brain PET imaging of [18F]THK-5351, pseudo-observed SUVR images for one healthy adult and one adult with Alzheimer's disease were simulated from individual PET and MR images. The partial volume effect of pseudo-observed PET images were corrected by using Müller-Gärtner (MG), the geometric transfer matrix (GTM), Labbé (LABBE), regional voxel-based (RBV), iterative Yang (IY), structural functional synergy for resolution recovery (SFS-RR), and modified SFS-RR algorithms with incorporation of error sources in the datasets for PVC processing. Assumed error sources were mismatched FWHM, inaccurate image-registration, and incorrectly segmented anatomical volume. The degree of error propagations in ROI values was evaluated by percent differences (%diff) of PV-corrected SUVR against true SUVR. RESULTS: Uncorrected SUVRs were underestimated against true SUVRs (- 15.7 and - 53.7% in hippocampus for HC and AD conditions), and application of each PVC algorithm reduced the %diff. Larger FWHM mismatch led to larger %diff of PVC-SUVRs against true SUVRs for all algorithms. Inaccurate image registration showed systematic propagation for most algorithms except for SFS-RR and modified SFS-RR. Incorrect segmentation of the anatomical volume only resulted in error propagations in limited local regions. CONCLUSIONS: We demonstrated error propagation by numerical simulation of THK-PET imaging. Error propagations of 7 PVC algorithms for brain PET imaging with [18F]THK-5351 were significant. Robust algorithms for clinical applications must be carefully selected according to the study design of clinical PET data.

On brain atlas choice and automatic segmentation methods: a comparison of MAPER & FreeSurfer using three atlas databases.

Several automatic image segmentation methods and few atlas databases exist for analysing structural T1-weighted magnetic resonance brain images. The impact of choosing a combination has not hitherto been described but may bias comparisons across studies. We evaluated two segmentation methods (MAPER and FreeSurfer), using three publicly available atlas databases (Hammers_mith, Desikan-Killiany-Tourville, and MICCAI 2012 Grand Challenge). For each combination of atlas and method, we conducted a leave-one-out cross-comparison to estimate the segmentation accuracy of FreeSurfer and MAPER. We also used each possible combination to segment two datasets of patients with known structural abnormalities (Alzheimer's disease (AD) and mesial temporal lobe epilepsy with hippocampal sclerosis (HS)) and their matched healthy controls. MAPER was better than FreeSurfer at modelling manual segmentations in the healthy control leave-one-out analyses in two of the three atlas databases, and the Hammers_mith atlas database transferred to new datasets best regardless of segmentation method. Both segmentation methods reliably identified known abnormalities in each patient group. Better separation was seen for FreeSurfer in the AD and left-HS datasets, and for MAPER in the right-HS dataset. We provide detailed quantitative comparisons for multiple anatomical regions, thus enabling researchers to make evidence-based decisions on their choice of atlas and segmentation method.

Decreased GABA-A Receptor Binding in Association With ß-Lactam Antibiotic Use.

ß-Lactam antibiotics are proconvulsive. In laboratory animals, this effect seems to be predominantly mediated through inhibition of GABA-A receptors, but it has not been demonstrated in humans in vivo. We report images of a [C]Ro15-4513 PET from a 40-year-old man who had completed a 1-week course of flucloxacillin before it. Relative to healthy controls, the participant had significantly lower mean gray matter binding. These novel data suggest that, in humans, the proconvulsive effect of ß-lactam antibiotics is mediated via either competition for the same benzodiazepine-binding site as [C]Ro15-4513 or downregulation of GABA-A receptor expression.

Intercomparison of MR-informed PET image reconstruction methods.

PURPOSE: Numerous image reconstruction methodologies for positron emission tomography (PET) have been developed that incorporate magnetic resonance (MR) imaging structural information, producing reconstructed images with improved suppression of noise and reduced partial volume effects. However, the influence of MR structural information also increases the possibility of suppression or bias of structures present only in the PET data (PET-unique regions). To address this, further developments for MR-informed methods have been proposed, for example, through inclusion of the current reconstructed PET image, alongside the MR image, in the iterative reconstruction process. In this present work, a number of kernel and maximum a posteriori (MAP) methodologies are compared, with the aim of identifying methods that enable a favorable trade-off between the suppression of noise and the retention of unique features present in the PET data. METHODS: The reconstruction methods investigated were: the MR-informed conventional and spatially compact kernel methods, referred to as KEM and KEM largest value sparsification (LVS) respectively; the MR-informed Bowsher and Gaussian MR-guided MAP methods; and the PET-MR-informed hybrid kernel and anato-functional MAP methods. The trade-off between improving the reconstruction of the whole brain region and the PET-unique regions was investigated for all methods in comparison with postsmoothed maximum likelihood expectation maximization (MLEM), evaluated in terms of structural similarity index (SSIM), normalized root mean square error (NRMSE), bias, and standard deviation. Both simulated BrainWeb (10 noise realizations) and real [18 F] fluorodeoxyglucose (FDG) three-dimensional datasets were used. The real [18 F]FDG dataset was augmented with simulated tumors to allow comparison of the reconstruction methodologies for the case of known regions of PET-MR discrepancy and evaluated at full counts (100%) and at a reduced (10%) count level. RESULTS: For the high-count simulated and real data studies, the anato-functional MAP method performed better than the other methods under investigation (MR-informed, PET-MR-informed and postsmoothed MLEM), in terms of achieving the best trade-off for the reconstruction of the whole brain and PET-unique regions, assessed in terms of the SSIM, NRMSE, and bias vs standard deviation. The inclusion of PET information in the anato-functional MAP method enables the reconstruction of PET-unique regions to attain similarly low levels of bias as unsmoothed MLEM, while moderately improving the whole brain image quality for low levels of regularization. However, for low count simulated datasets the anato-functional MAP method performs poorly, due to the inclusion of noisy PET information in the regularization term. For the low counts simulated dataset, KEM LVS and to a lesser extent, HKEM performed better than the other methods under investigation in terms of achieving the best trade-off for the reconstruction of the whole brain and PET-unique regions, assessed in terms of the SSIM, NRMSE, and bias vs standard deviation. CONCLUSION: For the reconstruction of noisy data, multiple MR-informed methods produce favorable whole brain vs PET-unique region trade-off in terms of the image quality metrics of SSIM and NRMSE, comfortably outperforming the whole image denoising of postsmoothed MLEM.