Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe

A Quantitative Evaluation of Joint Activity and Attenuation Reconstruction in TOF PET/MR Brain Imaging

Time-of-flight (TOF) PET data provide an effective means for attenuation correction (AC) when no (or incomplete or inaccurate) attenuation information is available. Since MR scanners provide little information on photon attenuation of different tissue types, AC in hybrid PET/MR scanners has always been challenging. In this contribution, we aim at validating the activity reconstructions of the maximum-likelihood ordered-subsets activity and attenuation (OSAA) reconstruction algorithm on a patient brain data set. We present a quantitative comparison of joint reconstructions with the current clinical gold standard-ordered-subsets expectation maximization-using CT-based AC in PET/CT, as well as the current state of the art in PET/MR, that is, zero time echo (ZTE)-based AC. Methods: The TOF PET emission data were initially used in a preprocessing stage to estimate crystal maps of efficiencies, timing offsets, and timing resolutions. Applying these additional corrections during reconstructions, OSAA, ZTE-based, and the vendor-provided atlas-based AC techniques were analyzed and compared with CT-based AC. In our initial study, we used the CT-based estimate of the expected scatter and later used the ZTE-based and OSAA attenuation estimates to compute the expected scatter contribution of the data during reconstructions. In all reconstructions, a maximum-likelihood scaling of the single-scatter simulation estimate to the emission data was used for scatter correction. The reconstruction results were analyzed in the 86 segmented regions of interest of the Hammers atlas. Results: Our quantitative analysis showed that, in practice, a tracer activity difference of +0.5% (±2.1%) and +0.1% (±2.3%) could be expected for the state-of-the-art ZTE-based and OSAA AC methods, respectively, in PET/MR compared with the clinical gold standard in PET/CT. Conclusion: Joint activity and attenuation estimation methods can provide an effective solution to the challenging AC problem for brain studies in hybrid TOF PET/MR scanners. With an accurate TOF-based (timing offsets and timing resolutions) calibration, and similar to the results of the state-of-the-art method in PET/MR, regional errors of joint TOF PET reconstructions are within a few percentage points.

Differential regional decline in dopamine receptor availability across adulthood: Linear and nonlinear effects of age

Theories of adult brain development, based on neuropsychological test results and structural neuroimaging, suggest differential rates of age-related change in function across cortical and subcortical sub-regions. However, it remains unclear if these trends also extend to the aging dopamine system. Here we examined cross-sectional adult age differences in estimates of D2-like receptor binding potential across several cortical and subcortical brain regions using PET imaging and the radiotracer [¹⁸ F]Fallypride in two samples of healthy human adults (combined N = 132). After accounting for regional differences in overall radioligand binding, estimated percent difference in receptor binding potential by decade (linear effects) were highest in most temporal and frontal cortical regions (~6-16% per decade), moderate in parahippocampal gyrus, pregenual frontal cortex, fusiform gyrus, caudate, putamen, thalamus, and amygdala (~3-5%), and weakest in subcallosal frontal cortex, ventral striatum, pallidum, and hippocampus (~0-2%). Some regions showed linear effects of age while many showed curvilinear effects such that binding potential declined from young adulthood to middle age and then was relatively stable until old age. Overall, these data indicate that the rate and pattern of decline in D2 receptor availability is regionally heterogeneous. However, the differences across regions were challenging to organize within existing theories of brain development and did not show the same pattern of regional change that has been observed in gray matter volume, white matter integrity, or cognitive performance. This variation suggests that existing theories of adult brain development may need to be modified to better account for the spatial dynamics of dopaminergic system aging.

GABA and glutamate moderate beta-amyloid related functional connectivity in cognitively unimpaired old-aged adults

Background

Effects of beta-amyloid accumulation on neuronal function precede the clinical manifestation of Alzheimer's disease (AD) by years and affect distinct cognitive brain networks. As previous studies suggest a link between beta-amyloid and dysregulation of excitatory and inhibitory neurotransmitters, we aimed to investigate the impact of GABA and glutamate on beta-amyloid related functional connectivity.

Methods

29 cognitively unimpaired old-aged adults (age = 70.03 ± 5.77 years) were administered 11C-Pittsburgh Compound B (PiB) positron-emission tomography (PET), and MRI at 7 Tesla (7T) including blood oxygen level dependent (BOLD) functional MRI (fMRI) at rest for measuring static and dynamic functional connectivity. An advanced 7T MR spectroscopic imaging (MRSI) sequence based on the free induction decay acquisition localized by outer volume suppression’ (FIDLOVS) technology was used for gray matter specific measures of GABA and glutamate in the posterior cingulate and precuneus (PCP) region.

Results

GABA and glutamate MR-spectra indicated significantly higher levels in gray matter than in white matter. A global effect of beta-amyloid on functional connectivity in the frontal, occipital and inferior temporal lobes was observable. Interactive effects of beta-amyloid with gray matter GABA displayed positive PCP connectivity to the frontomedial regions, and the interaction of beta-amyloid with gray matter glutamate indicated positive PCP connectivity to frontal and cerebellar regions. Furthermore, decreased whole-brain but increased fronto-occipital and temporo-parietal dynamic connectivity was found, when GABA interacted with regional beta-amyloid deposits in the amygdala, frontal lobe, hippocampus, insula and striatum.

Conclusions

GABA, and less so glutamate, may moderate beta-amyloid related functional connectivity. Additional research is needed to better characterize their interaction and potential impact on AD.

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Combined ultra-high fieldstrength FIDLOVS MRSI at 7 Tesla with 11C-PIB PET.

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Assessment of gray matter specific levels of GABA and glutamate.

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Identification of interactive effects of GABA, glutamate and beta-Amyloid.

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GABA may moderate dysfunctional beta-Amyloid effects on pre-clinical brain pathology.

Exploring quantitative group-wise differentiation of Alzheimer's disease and behavioural variant frontotemporal dementia using tract-specific microstructural white matter and functional connectivity measures at multiple time points

Objectives

This study explored group-wise quantitative measures of tract-specific white matter (WM) microstructure and functional default mode network (DMN) connectivity to establish an initial indication of their clinical applicability for early-stage and follow-up differential diagnosis of Alzheimer’s disease (AD) and behavioural variant frontotemporal dementia (bvFTD).

Methods

Eleven AD and 12 bvFTD early-stage patients and 18 controls underwent diffusion tensor imaging and resting state functional magnetic resonance imaging at 3 T. All AD and 6 bvFTD patients underwent the same protocol at 1-year follow-up. Functional connectivity measures of DMN and WM tract-specific diffusivity measures were determined for all groups. Exploratory analyses were performed to compare all measures between the three groups at baseline and between patients at follow-up. Additionally, the difference between baseline and follow-up diffusivity measures in AD and bvFTD patients was compared.

Results

Functional connectivity of the DMN was not different between groups at baseline and at follow-up. Diffusion abnormalities were observed widely in bvFTD and regionally in the hippocampal cingulum in AD. The extent of the differences between bvFTD and AD was diminished at follow-up, yet abnormalities were still more pronounced in bvFTD. The rate of change was similar in bvFTD and AD.

Conclusions

This study provides a tentative indication that quantitative tract-specific microstructural WM abnormalities, but not quantitative functional connectivity of the DMN, may aid early-stage and follow-up differential diagnosis of bvFTD and AD. Specifically, pronounced microstructural changes in anterior WM tracts may characterise bvFTD, whereas microstructural abnormalities of the hippocampal cingulum may characterise AD.

Key Points

• The clinical applicability of quantitative brain imaging measures for early-stage and follow-up differential diagnosis of dementia subtypes was explored using a group-wise approach.

• Quantitative tract-specific microstructural white matter abnormalities, but not quantitative functional connectivity of the default mode network, may aid early-stage and follow-up differential diagnosis of behavioural variant frontotemporal dementia and Alzheimer’s disease.

• Pronounced microstructural white matter (WM) changes in anterior WM tracts characterise behavioural variant frontotemporal dementia, whereas microstructural WM abnormalities of the hippocampal cingulum in the absence of other WM changes characterise Alzheimer’s disease.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06061-7) contains supplementary material, which is available to authorized users.

Amyloid PET and cognitive decline in cognitively normal individuals: the SCIENCe project

We examined the relationships between amyloid-β PET and concurrent and longitudinal cognitive performance in 107 cognitively normal individuals with subjective cognitive decline (age: 64 ± 8 years, 44% female, Mini-Mental State Examination score 29 ± 1). All underwent 90-minute dynamic [¹⁸F]florbetapir PET scanning and longitudinal neuropsychological tests with a mean follow-up of 3.4 ± 3.0 years. Receptor parametric mapping was used to calculate [¹⁸F]florbetapir binding potential (BP_ND), and we performed linear mixed models to assess the relationships between global [¹⁸F]florbetapir BP_ND and neuropsychological performance. Higher [¹⁸F]florbetapir BP_ND was related to lower concurrent Mini-Mental State Examination (β ± SE: -1.69 ± 0.63 p < 0.01) and to steeper rate of decline on tasks capturing memory (Rey Auditory Verbal Learning Task immediate [β ± SE -1.81 ± 0.81, p < 0.05] and delayed recall [β ± SE -1.19 ± 0.34, p < 0.01]), attention/executive functions (Stroop II [color] [β ± SE -0.02 ± 0.01, p < 0.05], Stroop III [word-color] [β ± SE -0.03 ± 0.02, p < 0.05]), and language (category fluency [β ± SE -0.04 ± 0.01, p < 0.01]). These findings suggest that higher amyloid-β load in cognitively normal individuals with subjective cognitive decline from a memory clinic is associated with lower concurrent global cognition and with faster rate of decline in a variety of cognitive domains.

MIST: A multi-resolution parcellation of functional brain networks

The functional architecture of the brain is organized across multiple levels of spatial resolutions, from distributed networks to the localized areas they are made of. A brain parcellation that defines functional nodes at multiple resolutions is required to investigate the functional connectome across these scales. Here we present the Multiresolution Intrinsic Segmentation Template (MIST), a multi-resolution group level parcellation of the cortical, subcortical and cerebellar gray matter. The individual MIST parcellations match other published group parcellations in internal homogeneity and reproducibility and perform very well in real-world application benchmarks. In addition, the MIST parcellations are fully annotated and provide a hierarchical decomposition of functional brain networks across nine resolutions (7 to 444 functional parcels). We hope that the MIST parcellation will accelerate research in brain connectivity across resolutions. Because visualizing multiresolution parcellations is challenging, we provide an interactive web interface to explore the MIST. The MIST is also available through the popular nilearn toolbox.

Long-term effects of stimulant exposure on cerebral blood flow response to methylphenidate and behavior in attention-deficit hyperactivity disorder

Stimulant prescription rates for attention deficit hyperactivity disorder (ADHD) are increasing, even though potential long-term effects on the developing brain have not been well-studied. A previous randomized clinical trial showed short-term age-dependent effects of stimulants on the DA system. We here assessed the long-term modifying effects of age-of-first-stimulant treatment on the human brain and behavior. 81 male adult ADHD patients were stratified into three groups: 1) early stimulant treatment (EST; <16 years of age) 2) late stimulant treatment (LST: ≥23 years of age) and 3) stimulant treatment naive (STN; no history of stimulant treatment). We used pharmacological magnetic resonance imaging (phMRI) to assess the cerebral blood flow (CBF) response to an oral methylphenidate challenge (MPH, 0.5 mg/kg), as an indirect measure of dopamine function in fronto-striatal areas. In addition, mood and anxiety scores, and recreational drug use were assessed. Baseline ACC CBF was lower in the EST than the STN group (p = 0.03), although CBF response to MPH was similar between the three groups (p = 0.23). ADHD symptom severity was higher in the STN group compared to the other groups (p < 0.01). In addition, the EST group reported more depressive symptoms (p = 0.04), but not anxiety (p = 0.26), and less recreational drug use (p = 0.04). In line with extensive pre-clinical data, our data suggest that early, but not late, stimulant treatment long-lastingly affects the human brain and behavior, possibly indicating fundamental changes in the dopamine system.

Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification

Accurate parcellation and labeling of primary cortical sulci in the human fetal brain is useful for regional analysis of brain development. However, human fetal brains show large spatio-temporal changes in brain size, cortical folding patterns, and relative position/size of cortical regions, making accurate automatic sulcal labeling challenging. Here, we introduce a novel sulcal labeling method for the fetal brain using spatio-temporal gyrification information from multiple fetal templates. First, spatial probability maps of primary sulci are generated on the templates from 23 to 33 gestational weeks and registered to an individual brain. Second, temporal weights, which determine the level of contribution to the labeling for each template, are defined by similarity of gyrification between the individual and the template brains. We combine the weighted sulcal probability maps from the multiple templates and adopt sulcal basin-wise approach to assign sulcal labels to each basin. Our labeling method was applied to 25 fetuses (22.9-29.6 gestational weeks), and the labeling accuracy was compared to manually assigned sulcal labels using the Dice coefficient. Moreover, our multi-template basin-wise approach was compared to a single-template approach, which does not consider the temporal dynamics of gyrification, and a fully-vertex-wise approach. The mean accuracy of our approach was 0.958 across subjects, significantly higher than the accuracies of the other approaches. This novel approach shows highly accurate sulcal labeling and provides a reliable means to examine characteristics of cortical regions in the fetal brain.

Covariance statistics and network analysis of brain PET imaging studies

The analysis of structural and functional neuroimaging data using graph theory has increasingly become a popular approach for visualising and understanding anatomical and functional relationships between different cerebral areas. In this work we applied a network-based approach for brain PET studies using population-based covariance matrices, with the aim to explore topological tracer kinetic differences in cross-sectional investigations. Simulations, test-retest studies and applications to cross-sectional datasets from three different tracers ([18F]FDG, [18F]FDOPA and [11C]SB217045) and more than 400 PET scans were investigated to assess the applicability of the methodology in healthy controls and patients. A validation of statistics, including the assessment of false positive differences in parametric versus permutation testing, was also performed. Results showed good reproducibility and general applicability of the method within the range of experimental settings typical of PET neuroimaging studies, with permutation being the method of choice for the statistical analysis. The use of graph theory for the quantification of [18F]FDG brain PET covariance, including the definition of an entropy metric, proved to be particularly relevant for Alzheimer's disease, showing an association with the progression of the pathology. This study shows that covariance statistics can be applied to PET neuroimaging data to investigate the topological characteristics of the tracer kinetics and its related targets, although sensitivity to experimental variables, group inhomogeneities and image resolution need to be considered when the method is applied to cross-sectional studies.

Reduced resilience of brain gray matter networks in idiopathic generalized epilepsy: A graph-theoretical analysis

Purpose

The pathophysiology of idiopathic generalized epilepsy (IGE) is still unclear, but graph theory may help to understand it. Here, we examined the graph-theoretical findings of the gray matter network in IGE using anatomical covariance methods.

Materials and methods

We recruited 33 patients with IGE and 35 age- and sex-matched healthy controls. Gray matter images were obtained by 3.0-T 3D T1-weighted MRI and were normalized using the voxel-based morphometry tools of Statistical Parametric Mapping 12. The normalized images were subjected to graph-theoretical group comparison using the Graph Analysis Toolbox with two different parcellation schemes. Initially, we used the Automated Anatomical Labeling template, whereas the Hammers Adult atlas was used for the second analysis.

Results

The resilience analyses revealed significantly reduced resilience of the IGE gray matter networks to both random failure and targeted attack. No significant between-group differences were found in global network measures, including the clustering coefficient and characteristic path length. The IGE group showed several changes in regional clustering, including an increase mainly in wide areas of the bilateral frontal lobes. The second analysis with another region of interest (ROI) parcellation generated the same results in resilience and global network measures, but the regional clustering results differed between the two parcellation schemes.

Conclusion

These results may reflect the potentially weak network organization in IGE. Our findings contribute to the accumulation of knowledge on IGE.

The Shape of Things to Come in Speech Production: A Functional Magnetic Resonance Imaging Study of Visual Form Interference during Lexical Access

Studies of context effects in speech production have shown that semantic feature overlap produces interference in naming of categorically related objects. In neuroimaging studies, this semantic interference effect is consistently associated with involvement of left superior and middle temporal gyri. However, at least part of this effect has recently been shown to be attributable to visual form similarity, as categorically related objects typically share visual features. This fMRI study examined interference produced by visual form overlap in the absence of a category relation in a picture-word interference paradigm. Both visually similar and visually dissimilar distractors led to increased BOLD responses in the left inferior frontal gyrus compared with the congruent condition. Naming pictures in context with a distractor word denoting an object visually similar in form slowed RTs compared with unrelated words and was associated with reduced activity in the left posterior middle temporal gyrus. This area is reliably observed in lexical level processing during language production tasks. No significant differential activity was observed in areas typically engaged by early perceptual or conceptual feature level processing or in areas proposed to be engaged by postlexical language processes, suggesting that visual form interference does not arise from uncertainty or confusion during perceptual or conceptual identification or after lexical processing. We conclude that visual form interference has a lexical locus, consistent with the predictions of competitive lexical selection models.

Widespread microglial activation in multiple system atrophy

Background

The pattern and role of microglial activation in multiple system atrophy is largely unclear. The objective of this study was to use [¹¹C](R)‐PK11195 PET to determine the extent and correlation of activated microglia with clinical parameters in MSA patients.

Methods

Fourteen patients with the parkinsonian phenotype of MSA (MSA‐P) with a mean disease duration of 2.9 years (range 2‐5 years) were examined with [¹¹C](R)‐PK11195 PET and compared with 10 healthy controls.

Results

Patients with the parkinsonian phenotype of MSA showed a significant (P ≤ 0.01) mean increase in binding potentials compared with healthy controls in the caudate nucleus, putamen, pallidum, precentral gyrus, orbitofrontal cortex, presubgenual anterior cingulate cortex, and the superior parietal gyrus. No correlations between binding potentials and clinical parameters were found.

Conclusions

In early clinical stages of the parkinsonian phenotype of MSA, there is widespread microglial activation as a marker of neuroinflammatory changes without correlation to clinical parameters in our patient population. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Hypercapnic BOLD MRI compared to H215O PET/CT for the hemodynamic evaluation of patients with Moyamoya Disease

Background and purpose

Patients with Moyamoya Disease (MMD) need hemodynamic evaluation of vascular territories at risk of stroke. Today's investigative standards include H₂¹⁵O PET/CT with pharmacological challenges with acetazolamide (ACZ). Recent developments suggest that CO₂-triggered blood‑oxygen-level-dependent (BOLD) functional MRI might provide comparable results to current standard methods for evaluation of territorial hemodynamics, while being a more widely available and easily implementable method. This study examines results of a newly developed quantifiable analysis algorithm for CO₂-triggered BOLD MRI in Moyamoya patients and correlates the results with H₂¹⁵O PET/CT with ACZ challenge to assess comparability between both modalities.

Methods

CO₂-triggered BOLD MRI was performed and compared to H₂¹⁵O PET/CT with ACZ challenge in patients with angiographically proven MMD. Images of both modalities were analyzed retrospectively in a blinded, standardized fashion by visual inspection, as well as with a semi-quantitative analysis using stimuli-induced approximated regional perfusion-weighted data and BOLD-signal changes with reference to cerebellum.

Results

20 consecutive patients fulfilled the inclusion criteria, a total of 160 vascular territories were analyzed retrospectively. Visual analysis (4-step visual rating system) of standardized, color-coded cerebrovascular reserve/reactivity maps showed a very strong correlation (Spearman's rho = 0.9, P < 0.001) between both modalities. Likewise, comparison of approximated regional perfusion changes across vascular territories (normalized to cerebellar change) reveal a highly significant correlation between both methods (Pearson's r = 0.71, P < 0.001).

Conclusions

The present analysis indicates that CO₂-triggered BOLD MRI is a very promising tool for the hemodynamic evaluation of MMD patients with results comparable to those seen in H₂¹⁵O PET/CT with ACZ challenge. It therefore holds future potential in becoming a routine examination in the pre- and postoperative evaluation of MMD patients after further prospective evaluation.

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Non-invasive cerebrovascular reactivity measurement with BOLD MRI.

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CO₂-triggered BOLD MRI correlates strongly with H₂¹⁵O PET/CT with ACZ challenge

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Widely-available tool for the hemodynamic evaluation of Moyamoya patients.

Dual-phase [18F]florbetapir in frontotemporal dementia

PURPOSE

The PET tracer [18F]florbetapir is a specific fibrillar amyloid-beta (Aβ) biomarker. During the late scan phase (> 40 min), it provides pathological information about Aβ status. Early scan phase (0-10 min) can provide FDG-'like' information. The current investigation tested the feasibility of using florbetapir as a dual-phase biomarker in behavioural variant frontotemporal dementia (bvFTD).

METHODS

Eight bvFTD patients underwent [18F]florbetapir and [18]FDG-PET scans. Additionally, ten healthy controls and ten AD patients underwent florbetapir-PET only. PET data were acquired dynamically for 60-min post-injection. The bvFTD PET data were used to define an optimal time window, representing blood flow-related pseudo-metabolism ('pseudo-FDG'), of florbetapir data that maximally correlated with the corresponding real FDG SUVR (40-60 min) in a composite neocortical FTD region.

RESULTS

A 2 to 5-min time window post-injection of the florbetapir-PET data provided the largest correlation (Pearson's r = 0.79, p = 0.02) to the FDG data. The pseudo-FDG images demonstrated strong internal consistency with actual FDG data and were also visually consistent with the bvFTD patients' hypometabolic profiles. The ability to identify bvFTD from blind visual rating of pseudo-FDG images was consistent with previous reports using FDG data (sensitivity = 75%, specificity = 85%).

CONCLUSIONS

This investigation demonstrates that early phase florbetapir uptake shows a reduction of frontal lobe perfusion in bvFTD, similar to metabolic findings with FDG. Thus, dynamic florbetapir scans can serve as a dual-phase biomarker in dementia patients to distinguish FTD from AD and cognitively normal elderly, removing the need for a separate FDG-PET scan in challenging dementia cases.

Amyloid-β Load Is Related to Worries, but Not to Severity of Cognitive Complaints in Individuals With Subjective Cognitive Decline: The SCIENCe Project

Objective: Subjective cognitive decline (SCD) is associated with an increased risk of Alzheimer's Disease (AD). Early disease processes, such as amyloid-β aggregation measured with quantitative PET, may help to explain the phenotype of SCD. The aim of this study was to investigate whether quantitative amyloid-β load is associated with both self- and informant-reported cognitive complaints and memory deficit awareness in individuals with SCD. Methods: We included 106 SCD patients (mean ± SD age: 64 ± 8, 45%F) with 90 min dynamic [¹⁸F]florbetapir PET scans. We used the following questionnaires to assess SCD severity: cognitive change index (CCI, self and informant reports; 2 × 20 items), subjective cognitive functioning (SCF, four items), and five questions "Do you have complaints?" (yes/no) for memory, attention, organization and language), and "Does this worry you? (yes/no)." The Rivermead Behavioral Memory Test (RBMT)-Stories (immediate and delayed recall) was used to assess objective episodic memory. To investigate the level of self-awareness, we calculated a memory deficit awareness index (Z-transformed (inverted self-reported CCI minus episodic memory); higher index, heightened self-awareness) and a self-proxy index (Z-transformed self- minus informant-reported CCI). Mean cortical [¹⁸F]florbetapir binding potential (BP_ND) was derived from the PET data. Logistic and linear regression analyses, adjusted for age, sex, education, and depressive symptoms, were used to investigate associations between BP_ND and measures of SCD. Results: Higher mean cortical [¹⁸F]florbetapir BP_ND was associated with SCD-related worries (odds ratio = 1.76 [95%CI = 1.07 ± 2.90]), but not with other SCD questionnaires (informant and self-report CCI or SCF, total scores or individual items, all p > 0.05). In addition, higher mean cortical [¹⁸F]florbetapir BP_ND was associated with a higher memory deficit awareness index (Beta = 0.55), with an interaction between BP_ND and education (p = 0.002). There were no associations between [¹⁸F]florbetapir BP_ND and self-proxy index (Beta = 0.11). Conclusion: Amyloid-β deposition was associated with SCD-related worries and heightened memory deficit awareness (i.e., hypernosognosia), but not with severity of cognitive complaints. Our findings indicate that worries about self-perceived decline may reflect an early symptom of amyloid-β related pathology rather than subjective cognitive functioning.

Relative cerebral flow from dynamic PIB scans as an alternative for FDG scans in Alzheimer's disease PET studies

In Alzheimer's Disease (AD) dual-tracer positron emission tomography (PET) studies with 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) and 11C-labelled Pittsburgh Compound B (PIB) are used to assess metabolism and cerebral amyloid-β deposition, respectively. Regional cerebral metabolism and blood flow (rCBF) are closely coupled, both providing an index for neuronal function. The present study compared PIB-derived rCBF, estimated by the ratio of tracer influx in target regions relative to reference region (R1) and early-stage PIB uptake (ePIB), to FDG scans. Fifteen PIB positive (+) patients and fifteen PIB negative (-) subjects underwent both FDG and PIB PET scans to assess the use of R1 and ePIB as a surrogate for FDG. First, subjects were classified based on visual inspection of the PIB PET images. Then, discriminative performance (PIB+ versus PIB-) of rCBF methods were compared to normalized regional FDG uptake. Strong positive correlations were found between analyses, suggesting that PIB-derived rCBF provides information that is closely related to what can be seen on FDG scans. Yet group related differences between method's distributions were seen as well. Also, a better correlation with FDG was found for R1 than for ePIB. Further studies are needed to validate the use of R1 as an alternative for FDG studies in clinical applications.

A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease

Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's disease (AD), while other MCI types tend to remain stable over-time and do not progress to AD. To identify and choose effective and personalized strategies to prevent or slow the progression of AD, we need to develop objective measures that are able to discriminate the MCI patients who are at risk of AD from those MCI patients who have less risk to develop AD. Here, we present a novel deep learning architecture, based on dual learning and an ad hoc layer for 3D separable convolutions, which aims at identifying MCI patients who have a high likelihood of developing AD within 3 years. Our deep learning procedures combine structural magnetic resonance imaging (MRI), demographic, neuropsychological, and APOe4 genetic data as input measures. The most novel characteristics of our machine learning model compared to previous ones are the following: 1) our deep learning model is multi-tasking, in the sense that it jointly learns to simultaneously predict both MCI to AD conversion as well as AD vs. healthy controls classification, which facilitates relevant feature extraction for AD prognostication; 2) the neural network classifier employs fewer parameters than other deep learning architectures which significantly limits data-overfitting (we use ∼550,000 network parameters, which is orders of magnitude lower than other network designs); 3) both structural MRI images and their warp field characteristics, which quantify local volumetric changes in relation to the MRI template, were used as separate input streams to extract as much information as possible from the MRI data. All analyses were performed on a subset of the database made publicly available via the Alzheimer's Disease Neuroimaging Initiative (ADNI), (n = 785 participants, n = 192 AD patients, n = 409 MCI patients (including both MCI patients who convert to AD and MCI patients who do not covert to AD), and n = 184 healthy controls). The most predictive combination of inputs were the structural MRI images and the demographic, neuropsychological, and APOe4 data. In contrast, the warp field metrics were of little added predictive value. The algorithm was able to distinguish the MCI patients developing AD within 3 years from those patients with stable MCI over the same time-period with an area under the curve (AUC) of 0.925 and a 10-fold cross-validated accuracy of 86%, a sensitivity of 87.5%, and specificity of 85%. To our knowledge, this is the highest performance achieved so far using similar datasets. The same network provided an AUC of 1 and 100% accuracy, sensitivity, and specificity when classifying patients with AD from healthy controls. Our classification framework was also robust to the use of different co-registration templates and potentially irrelevant features/image portions. Our approach is flexible and can in principle integrate other imaging modalities, such as PET, and diverse other sets of clinical data. The convolutional framework is potentially applicable to any 3D image dataset and gives the flexibility to design a computer-aided diagnosis system targeting the prediction of several medical conditions and neuropsychiatric disorders via multi-modal imaging and tabular clinical data.

Impact of P-Glycoprotein Function on the Brain Kinetics of the Weak Substrate 11C-Metoclopramide Assessed with PET Imaging in Humans

PET with avid substrates of P-glycoprotein (ABCB1) provided evidence of the role of this efflux transporter in effectively restricting the brain penetration of its substrates across the human blood-brain barrier (BBB). This may not reflect the situation for weak ABCB1 substrates including several antidepressants, antiepileptic drugs, and neuroleptics, which exert central nervous system effects despite being transported by ABCB1. We performed PET with the weak ABCB1 substrate ¹¹C-metoclopramide in humans to elucidate the impact of ABCB1 function on its brain kinetics. Methods: Ten healthy male subjects underwent 2 consecutive ¹¹C-metoclopramide PET scans without and with ABCB1 inhibition using cyclosporine A (CsA). Pharmacokinetic modeling was performed to estimate the total volume of distribution (V _T) and the influx (K ₁) and efflux (k ₂) rate constants between plasma and selected brain regions. Furthermore, ¹¹C-metoclopramide washout from the brain was estimated by determining the elimination slope (k _E,brain) of the brain time-activity curves. Results: In baseline scans, ¹¹C-metoclopramide showed appreciable brain distribution (V _T = 2.11 ± 0.33 mL/cm³). During CsA infusion, whole-brain gray matter V _T and K ₁ were increased by 29% ± 17% and 9% ± 12%, respectively. K ₂ was decreased by 15% ± 5%, consistent with a decrease in k _E,brain (-32% ± 18%). The impact of CsA on outcome parameters was significant and similar across brain regions except for the pituitary gland, which is not protected by the BBB. Conclusion: Our results show for the first time that ABCB1 does not solely account for the "barrier" property of the BBB but also acts as a detoxifying system to limit the overall brain exposure to its substrates at the human blood-brain interface.

Structural Thalamofrontal Hypoconnectivity Is Related to Oculomotor Corollary Discharge Dysfunction in Schizophrenia

By predicting sensory consequences of actions, humans can distinguish self-generated sensory inputs from those that are elicited externally. This is one mechanism by which we achieve a subjective sense of agency over our actions. Corollary discharge (CD) signals-"copies" of motor signals sent to sensory areas-permit such predictions, and CD abnormalities are a hypothesized mechanism for the agency disruptions in schizophrenia that characterize a subset of symptoms. Indeed, behavioral evidence of altered CD, including in the oculomotor system, has been observed in schizophrenia patients. A pathway projecting from the superior colliculus to the frontal eye fields (FEFs) via the mediodorsal thalamus (MD) conveys oculomotor CD associated with saccadic eye movements in nonhuman primates. This animal work provides a promising translational framework in which to investigate CD abnormalities in clinical populations. In the current study, we examined whether structural connectivity of this MD-FEF pathway relates to oculomotor CD functioning in schizophrenia. Twenty-two schizophrenia patients and 24 healthy control participants of both sexes underwent diffusion tensor imaging, and a large subset performed a trans-saccadic perceptual task that yields measures of CD. Using probabilistic tractography, we identified anatomical connections between FEF and MD and extracted indices of microstructural integrity. Patients exhibited compromised microstructural integrity in the MD-FEF pathway, which was correlated with greater oculomotor CD abnormalities and more severe psychotic symptoms. These data reinforce the role of the MD-FEF pathway in transmitting oculomotor CD signals and suggest that disturbances in this pathway may relate to psychotic symptom manifestation in patients.SIGNIFICANCE STATEMENT People with schizophrenia sometimes experience abnormalities in a sense of agency, which may stem from abnormal sensory predictions about their own actions. Consistent with this notion, the current study found reduced structural connectivity in patients with schizophrenia in a specific brain pathway found to transmit such sensorimotor prediction signals in nonhuman primates. Reduced structural connectivity was correlated with behavioral evidence for impaired sensorimotor predictions and psychotic symptoms.

Brain atlas for assessing the impact of tumor location on perioperative quality of life in patients with high-grade glioma: A prospective population-based cohort study

Background

Tumor location is important for surgical decision making. Particular attention is paid to regions that contain sensorimotor and language functions, but it is unknown if these are the most important regions from the patients' perspective.

Objective

To develop an atlas for depicting and assessing the potential importance of tumor location for perioperative health-related quality of life (HRQoL) in patients with newly diagnosed high-grade glioma.

Methods

Patient-reported HRQoL data and semi-automatically segmented preoperative 3D MRI-images were combined in 170 patients. The images were registered to a standardized space where the individual tumors were given the values and color intensity of the corresponding HRQoL. Descriptive brain maps of HRQoL, defined quantitative analyses, and voxel-based lesion symptom mapping comparing patients with tumors in different locations were made.

Results

There was no statistical difference in overall perioperative HRQoL between patients with tumors located in left or right hemisphere, between patients with tumors in different lobes, or between patients with tumors located in non-eloquent, near eloquent, or eloquent areas. Patients with tumors involving the internal capsule, and patients with preoperative motor symptoms and postoperative motor deficits, reported significantly worse overall HRQoL-scores.

Conclusions

The impact of anatomical tumor location on overall perioperative HRQoL seems less than frequently believed, and the distinction between critical and less critical brain regions seems more unclear according to the patients than perhaps when judged by physicians. However, worse HRQoL was found in patients with tumors in motor-related regions, indicating that these areas are crucial also from the patients' perspective.

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The impact of tumor location on patient-reported overall quality of life is low.

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There is no “dominant hemisphere” from the patients' perspective.

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Motor related regions seem to be most crucial for the patients.

Longitudinal tau and metabolic PET imaging in relation to novel CSF tau measures in Alzheimer's disease

Purpose

Studies comparing CSF and PET tau biomarkers have included only commercial CSF assays examining specific phosphorylation sites (e.g. threonine 181, P-tau_181p) and mid-domain tau (i.e. total tau, T-tau). Moreover, these studies did not examine CSF tau levels in relation to cerebral glucose metabolism. We thus aimed to examine CSF tau measures, using both commercial and novel assays, in relation to [¹⁸F]THK5317 (tau) and [¹⁸F]FDG PET (glucose metabolism).

Methods

Fourteen Alzheimer’s disease (AD) patients (seven prodromal, seven dementia) underwent [¹⁸F]THK5317 and [¹⁸F]FDG PET studies, with follow-up performed in ten subjects (six prodromal, four dementia) after 17 months. In addition to commercial assays, novel measures capturing N-terminus+mid-domain (tau N-Mid) and C-terminally truncated (tau-368) fragments were included.

Results

While the levels of all forms of CSF tau were found to be inversely associated with baseline [¹⁸F]FDG uptake, associations with baseline [¹⁸F]THK5317 uptake varied in relation to the degree of isocortical hypometabolism ([¹⁸F]FDG SUVR). Changes in the levels of the novel CSF markers tracked longitudinal changes in tracer uptake better than changes in P-tau_181p and T-tau levels, and improved concordance with dichotomized regional [¹⁸F]THK5317 measures.

Conclusion

Our findings suggest that neurodegeneration may modulate the relationship between CSF and PET tau biomarkers, and that, by comparison to P-tau_181p and T-tau, tau-368 and tau N-Mid may better capture tau pathology and synaptic impairment.

Electronic supplementary material

The online version of this article (10.1007/s00259-018-4242-6) contains supplementary material, which is available to authorized users.

Neural Responsivity to Food Cues in Patients With Unmedicated First-Episode Psychosis

IMPORTANCE

Schizophrenia is associated with a reduced life expectancy of 15 to 20 years owing to a high prevalence of cardiometabolic disorders. Obesity, a key risk factor for the development of cardiometabolic alterations, is more prevalent in individuals with schizophrenia. Although obesity is linked to the altered reward processing of food cues, no studies have investigated this link in schizophrenia without the confounds of antipsychotics and illness chronicity.

OBJECTIVE

To investigate neural responsivity to food cues in first-episode psychosis without the confounds of antipsychotic medication or illness chronicity.

DESIGN, SETTING, AND PARTICIPANTS

A case-control study was conducted from January 31, 2015, to September 30, 2018, in London, United Kingdom, of 29 patients with first-episode psychosis who were not taking antipsychotic medication and 28 matched controls.

MAIN OUTCOMES AND MEASURES

Participants completed a food cue paradigm while undergoing a functional magnetic resonance imaging scan. Neural activation was indexed using the blood oxygen level-dependent hemodynamic response. The Dietary Instrument for Nutrition Education was used to measure diet, and the International Physical Activity Questionnaire was used to measure exercise.

RESULTS

There were no significant differences in age, sex, or body mass index between the 29 patients (25 men and 4 women; mean [SD] age, 26.1 [4.8] years) and 28 controls (22 men and 6 women; mean [SD] age, 26.4 [5.5] years). Relative to controls, patients consumed more saturated fat (t46 = -3.046; P = .004) and undertook less high-intensity (U = 304.0; P = .01) and low-intensity (U = 299.5; P = .005) weekly exercise. There were no group differences in neural responses to food vs nonfood cues in whole-brain or region-of-interest analyses of the nucleus accumbens, insula, or hypothalamus. Body mass index was inversely correlated with the mean blood oxygen level-dependent signal in the nucleus accumbens in response to food vs nonfood cues in controls (R = -0.499; P = .01) but not patients (R = 0.082; P = .70).

CONCLUSIONS AND RELEVANCE

Relative to controls, patients with first-episode psychosis who were not taking antipsychotic medication consumed more saturated fat and showed an altered association between body mass index and neural response to food cues in the absence of differences in neural responses to food cues. These findings highlight how maladaptive eating patterns and alterations in the association between body mass index and neural responses to food cues are established early in the course of schizophrenia.

Semi-quantitative cerebral blood flow parameters derived from non-invasive [15O]H2O PET studies

Quantification of regional cerebral blood flow (CBF) using [¹⁵O]H₂O positron emission tomography (PET) requires the use of an arterial input function. Arterial sampling, however, is not always possible, for example in ill-conditioned or paediatric patients. Therefore, it is of interest to explore the use of non-invasive methods for the quantification of CBF. For validation of non-invasive methods, test-retest normal and hypercapnia data from 15 healthy volunteers were used. For each subject, the data consisted of up to five dynamic [¹⁵O]H₂O brain PET studies of 10 min and including arterial sampling. A measure of CBF was estimated using several non-invasive methods earlier reported in literature. In addition, various parameters were derived from the time-activity curve (TAC). Performance of these methods was assessed by comparison with full kinetic analysis using correlation and agreement analysis. The analysis was repeated with normalization to the whole brain grey matter value, providing relative CBF distributions. A reliable, absolute quantitative estimate of CBF could not be obtained with the reported non-invasive methods. Relative (normalized) CBF was best estimated using the double integration method.

The Effects of Antipsychotic Treatment on Presynaptic Dopamine Synthesis Capacity in First-Episode Psychosis: A Positron Emission Tomography Study

BACKGROUND

Elevated striatal dopamine synthesis capacity has been implicated in the etiology and antipsychotic response in psychotic illness. The effects of antipsychotic medication on dopamine synthesis capacity are poorly understood, and no prospective studies have examined this question in a solely first-episode psychosis sample. Furthermore, it is unknown whether antipsychotic efficacy is linked to reductions in dopamine synthesis capacity. We conducted a prospective [¹⁸F]-dihydroxyphenyl-L-alanine positron emission tomography study in antipsychotic naïve/free people with first-episode psychosis commencing antipsychotic treatment.

METHODS

Dopamine synthesis capacity (indexed as influx rate constant) and clinical symptoms (measured using Positive and Negative Syndrome Scale) were measured before and after at least 5 weeks of antipsychotic treatment in people with first-episode psychosis. Data from a prior study indicated that a sample size of 13 would have >80% power to detect a statistically significant change in dopamine synthesis capacity at alpha = .05 (two tailed).

RESULTS

A total of 20 people took part in the study, 17 of whom were concordant with antipsychotic medication at therapeutic doses. There was no significant effect of treatment on dopamine synthesis capacity in the whole striatum (p = .47), thalamus, or midbrain, nor was there any significant relationship between change in dopamine synthesis capacity and change in positive (ρ = .35, p = .13), negative, or total psychotic symptoms.

CONCLUSIONS

Dopamine synthesis capacity is unaltered by antipsychotic treatment, and therapeutic effects are not mediated by changes in this aspect of dopaminergic function.

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging

Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the preprocessing method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

Mesolimbic connectivity signatures of impulsivity and BMI in early adolescence

Across age groups, differences in connectivity of the mesolimbic and the prefrontal cortex co-vary with trait impulsivity and sensation-seeking. Impulsivity and sensation-seeking are also known to increase during early adolescence as maturation of subcortical structures outpaces that of the prefrontal cortex. While an imbalance between the striatum and prefrontal cortex is considered a normal developmental process, higher levels of adolescent impulsivity and sensation-seeking are associated with an increased risk for diverse problems, including obesity. To determine how the relationship between sensation-seeking, impulsivity and body mass index (BMI) is related to shared neural correlates we measured their relationships with the connectivity of nuclei in the striatum and dopaminergic midbrain in young adolescents. Data were collected from 116 children between the ages of 12 and 14, and included resting state functional magnetic resonance imaging, personality measures from the Substance Use Risk Profile Scale, and BMI Z-score for age. The shared variance for the connectivity of regions of interest in the substantia nigra, ventral tegmental area, ventral striatum and sub-thalamic nucleus, personality measures and BMI Z-score for age, were analyzed using partial least squares correlation. This analysis identified a single significant striato-limbic network that was connected with the substantia nigra, ventral tegmental area and sub-thalamic nuclei (p = 0.002). Connectivity within this network which included the hippocampi, amygdalae, parahippocampal gyri and the regions of interest, correlated positively with impulsivity and BMI Z-score for age and negatively with sensation-seeking. Together, these findings emphasize that, in addition to the well-established role that frontostriatal circuits play in the development of adolescent personality traits, connectivity of limbic regions with the striatum and midbrain also impact impulsivity, sensation-seeking and BMI Z-score in adolescents.

Longitudinal association between astrocyte function and glucose metabolism in autosomal dominant Alzheimer's disease

PURPOSE

The spatial resolution of ¹⁸F-fluorodeoxyglucose PET does not allow the specific cellular origin of its signal to be determined, but it is commonly accepted that transport and trapping of ¹⁸F-fluorodeoxyglucose reflects neuronal glucose metabolism. The main frameworks for the diagnosis of Alzheimer's disease suggest that hypometabolism measured with ¹⁸F-fluorodeoxyglucose PET is a biomarker of neuronal injury and neurodegeneration. There is preclinical evidence to suggest that astrocytes contribute, at least partially, to the in vivo ¹⁸F-fluorodeoxyglucose PET signal. However, due to a paucity of PET tracers for imaging astrocytic processes, the relationship between astrocyte function and glucose metabolism in human brain is not fully understood. The aim of this study was to investigate the longitudinal association between astrocyte function and glucose metabolism in Alzheimer's disease.

METHODS

The current investigation combined longitudinal PET data from patients with autosomal dominant Alzheimer's disease, including data on astrocyte function (¹¹C-deuterium-L-deprenyl binding) and glucose metabolism (¹⁸F-fluorodeoxyglucose uptake). Research participants included 7 presymptomatic and 4 symptomatic mutation carriers (age 44.9 ± 9.8 years and 58.0 ± 3.7 years, respectively) and 16 noncarriers (age 51.1 ± 14.2 years). Eight carriers and eight noncarriers underwent longitudinal follow-up PET imaging at an average of 2.8 ± 0.2 and 3.0 ± 0.5 years from baseline, respectively.

RESULTS

Longitudinal decline in astrocyte function as measured using ¹¹C-deuterium-L-deprenyl PET was significantly associated with progressive hypometabolism (¹⁸F-fluorodeoxyglucose uptake) in mutation carriers; no significant association was observed in noncarriers.

CONCLUSION

The emerging data shift the accepted wisdom that decreases in cerebral metabolism measured with ¹⁸F-fluorodeoxyglucose solely reflect neuronal injury, and places astrocytes more centrally in the development of Alzheimer's disease.

Inflammation in the hippocampus affects IGF1 receptor signaling and contributes to neurological sequelae in rheumatoid arthritis

Aberrant insulin-like growth factor 1 receptor (IGF1R)/insulin receptor signaling in brain has recently been linked to neurodegeneration in diabetes mellitus and in Alzheimer’s disease. In this study, we demonstrate that functional disability and pain in patients with rheumatoid arthritis (RA) and in experimental RA are associated with hippocampal inflammation and inhibition of IGF1R/insulin receptor substrate 1 (IRS1) signal, reproducing an IGF1/insulin-resistant state. This restricts formation of new neurons in the hippocampus, reduces hippocampal volume, and predisposes RA patients to develop neurological symptoms. Improving IRS1 function through down-regulation of IGF1R disinhibits neurogenesis and can potentially ameliorate neurological symptoms. This opens perspectives for drugs that revert IGF1/insulin resistance as an essential complement to the antirheumatic and antiinflammatory arsenal.

Rheumatoid arthritis (RA) is an inflammatory joint disease with a neurological component including depression, cognitive deficits, and pain, which substantially affect patients’ quality of daily life. Insulin-like growth factor 1 receptor (IGF1R) signaling is one of the factors in RA pathogenesis as well as a known regulator of adult neurogenesis. The purpose of this study was to investigate the association between IGF1R signaling and the neurological symptoms in RA. In experimental RA, we demonstrated that arthritis induced enrichment of IBA1⁺ microglia in the hippocampus. This coincided with inhibitory phosphorylation of insulin receptor substrate 1 (IRS1) and up-regulation of IGF1R in the pyramidal cell layer of the cornus ammoni and in the dentate gyrus, reproducing the molecular features of the IGF1/insulin resistance. The aberrant IGF1R signaling was associated with reduced hippocampal neurogenesis, smaller hippocampus, and increased immobility of RA mice. Inhibition of IGF1R in experimental RA led to a reduction of IRS1 inhibition and partial improvement of neurogenesis. Evaluation of physical functioning and brain imaging in RA patients revealed that enhanced functional disability is linked with smaller hippocampus volume and aberrant IGF1R/IRS1 signaling. These results point to abnormal IGF1R signaling in the brain as a mediator of neurological sequelae in RA and provide support for the potentially reversible nature of hippocampal changes.

Brain imaging correlates of mild cognitive impairment and early dementia in patients with type 2 diabetes mellitus

BACKGROUND AND AIMS

The risk of mild cognitive impairment and dementia is increased in type 2 diabetes mellitus (T2DM). We aimed to identify the neuroanatomical correlates of mild cognitive impairment (MCI) and early dementia in patients with T2DM, using advanced multimodal MRI.

METHODS AND RESULTS

Twenty-five patients (≥70 years) with T2DM and MCI (n = 22) or early dementia (n = 3) were included. The reference group consisted of 23 patients with T2DM with intact cognition. All patients underwent a 3 T MRI. Brain volumes and white matter hyperintensity volumes were obtained with automated segmentation methods. White matter connectivity was assessed with diffusion tensor imaging and fiber tractography. Infarcts and microbleeds were rated visually. Compared to patients without cognitive impairment, those with impairment had a lower grey matter volume (effect size: -0.58, p=0.042), especially in the right temporal lobe and subcortical brain regions (effect sizes: -0.45 to -0.91, false discovery rate corrected p < 0.05). White matter volume (effect size: -0.47, p = 0.11) and white matter connectivity (effect size: 0.55, p = 0.054) were also reduced in patients with versus without cognitive impairment, albeit not statistically significant. White matter hyperintensity volumes and occurrence of other vascular lesions did not differ between the two patient groups.

CONCLUSION

In patients with T2DM, grey matter atrophy rather than vascular brain injury appears to be the primary imaging correlate of MCI and early dementia.

Disease progression timeline estimation for Alzheimer's disease using discriminative event based modeling

Alzheimer's Disease (AD) is characterized by a cascade of biomarkers becoming abnormal, the pathophysiology of which is very complex and largely unknown. Event-based modeling (EBM) is a data-driven technique to estimate the sequence in which biomarkers for a disease become abnormal based on cross-sectional data. It can help in understanding the dynamics of disease progression and facilitate early diagnosis and prognosis by staging patients. In this work we propose a novel discriminative approach to EBM, which is shown to be more accurate than existing state-of-the-art EBM methods. The method first estimates for each subject an approximate ordering of events. Subsequently, the central ordering over all subjects is estimated by fitting a generalized Mallows model to these approximate subject-specific orderings based on a novel probabilistic Kendall's Tau distance. We also introduce the concept of relative distance between events which helps in creating a disease progression timeline. Subsequently, we propose a method to stage subjects by placing them on the estimated disease progression timeline. We evaluated the proposed method on Alzheimer's Disease Neuroimaging Initiative (ADNI) data and compared the results with existing state-of-the-art EBM methods. We also performed extensive experiments on synthetic data simulating the progression of Alzheimer's disease. The event orderings obtained on ADNI data seem plausible and are in agreement with the current understanding of progression of AD. The proposed patient staging algorithm performed consistently better than that of state-of-the-art EBM methods. Event orderings obtained in simulation experiments were more accurate than those of other EBM methods and the estimated disease progression timeline was observed to correlate with the timeline of actual disease progression. The results of these experiments are encouraging and suggest that discriminative EBM is a promising approach to disease progression modeling.

Early Phase PIB-PET as a Surrogate for Global and Regional Cerebral Blood Flow Measures

BACKGROUND AND PURPOSE

To explore the potential for simplified measures of [¹¹ C]PIB uptake to serve as a surrogate for cerebral blood flow (CBF) measures, thereby, providing both pathological and functional information in the same scan.

METHODS

Participants (N = 24, 16 M, 8 F, 57-87 years) underwent quantitative [¹⁵ O]water imaging and dynamic [¹¹ C]PIB imaging. Time-activity curves were created for each participant's regional [¹¹ C]PIB data scaled in standardized uptake values (SUVs). The frame in which maximal uptake occurred was defined for each subject (ie, "peak"). The concentration (SUV) for each region at the individual's peak, during the 3.5-4 minute time interval and for the initial 6 minute sum, was determined. R1 (ie, relative delivery using cerebellum as reference tissue) from the simplified reference tissue model 2 was determined for each region. PIB SUVs were compared to the absolute CBF global and regional values (in mL/minute/100 mL) and the R1 values were compared to the cerebellar-normalized rCBF.

RESULTS

Significant linear relationships were found for all SUV measures with measures of absolute global and regional CBF that were comparable to the relationship between normalized CBF and R1. The individual SUV_peak exhibited the strongest relationship both regionally and globally. All individuals and all regions had highly significant regression slopes. Age, gender, or amyloid burden did not influence the relationship.

CONCLUSION

Early PIB uptake has the potential to effectively serve as a surrogate for global and regional CBF measures. The simple and readily obtainable individual's SUV_peak value was the strongest predictor regionally and globally of CBF.

In vivo assessment of neuroinflammation in progressive multiple sclerosis: a proof of concept study with [18F]DPA714 PET

Background

Over the past decades, positron emission tomography (PET) imaging has become an increasingly useful research modality in the field of multiple sclerosis (MS) research, as PET can visualise molecular processes, such as neuroinflammation, in vivo. The second generation PET radioligand [¹⁸F]DPA714 binds with high affinity to the 18-kDa translocator-protein (TSPO), which is mainly expressed on activated microglia. The aim of this proof of concept study was to evaluate this in vivo marker of neuroinflammation in primary and secondary progressive MS.

Methods

All subjects were genotyped for the rs6971 polymorphism within the TSPO gene, and low-affinity binders were excluded from participation in this study. Eight patients with progressive MS and seven age and genetic binding status matched healthy controls underwent a 60 min dynamic PET scan using [¹⁸F]DPA714, including both continuous on-line and manual arterial blood sampling to obtain metabolite-corrected arterial plasma input functions.

Results

The optimal model for quantification of [¹⁸F]DPA714 kinetics was a reversible two-tissue compartment model with additional blood volume parameter. For genetic high-affinity binders, a clear increase in binding potential was observed in patients with MS compared with age-matched controls. For both high and medium affinity binders, a further increase in binding potential was observed in T2 white matter lesions compared with non-lesional white matter. Volume of distribution, however, did not differentiate patients from healthy controls, as the large non-displaceable compartment of [¹⁸F]DPA714 masks its relatively small specific signal.

Conclusion

The TSPO radioligand [¹⁸F]DPA714 can reliably identify increased focal and diffuse neuroinflammation in progressive MS when using plasma input-derived binding potential, but observed differences were predominantly visible in high-affinity binders.

Electronic supplementary material

The online version of this article (10.1186/s12974-018-1352-9) contains supplementary material, which is available to authorized users.

A challenge of predicting seizure frequency in temporal lobe epilepsy using neuroanatomical features

The pathological and clinical characteristics of temporal lobe epilepsy (TLE) tend to be affected by epileptic seizures, specifically represented by seizure lateralization and frequency. Although the lateralization of the epileptogenic zone can be clarified in terms of neuroanatomical damage, there have been conflicting findings on the relationship between seizure frequency and neuroanatomical damage. In this study we sought to examine the relationship in the framework of machine learning-based predictive modeling. We acquired 60 grey matter (GM) anatomical features from structural MRI data and 46 white matter (WM) anatomical features from diffusion-weighted MRI data for 42 TLE patients and 45 healthy controls and applied the random forests method to the neuroanatomical features. We demonstrated that, whereas the neuroanatomical features were promising markers for the discrimination of the TLE patients from the healthy controls, the separation between the TLE patients with low and high seizure frequency on the basis of the neuroanatomical features was challenging. When we applied feature selection techniques for the construction of the predictive models, a greater number of features were selected as being relevant to the distinction of the TLE patients from the healthy controls than to the classification of the TLE patients according to seizure frequency. Furthermore, we adopted model-based clustering analysis and showed that seizure frequency-based subgroups were not matched well with neuroanatomy-based subgroups in the TLE patients. We propose that the challenge of predicting seizure frequency using neuroanatomical features could be attributable to considerable inter-individual variability in neuroanatomical damage among seizure frequency-based subgroups.

The relationship between amplitude of low frequency fluctuations and gray matter volume of the mirror neuron system: Differences between low disability multiple sclerosis patients and healthy controls

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The study of the relationship between function and structure of the brain is interesting in multiple sclerosis patients.

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Different relationship between amplitude of low frequency fluctuations (ALFF) and gray matter volume has been detected.

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This difference may be associated with the presence of white matter lesions involving specific tracts.

The study of the relationship between function and structure of the brain could be particularly interesting in neurodegenerative diseases like multiple sclerosis (MS).

The aim of the present work is to identify differences of the amplitude of low frequency fluctuations (ALFF) in the mirror neuron system (MNS) between MS patients and healthy controls and to study the relationship between ALFF and the gray matter volume (GMV) of the regions that belong to the MNS.

Relapsing-remitting MS patients with minor disability were compared to healthy controls (HC) using resting-state functional magnetic resonance imaging (fMRI), anatomic T1 weighted images and diffusion tensor imaging (DTI). Region of interest (ROI) analyses was performed in the MNS regions.

A decrease of ALFF in MS patients was observed in the left inferior frontal gyrus (IFG). Furthermore, a correlation between ALFF in the IFG and the GMV of the left inferior parietal lobule (IPL) was identified. This relationship was different for MS patients than for HC, which may be associated with changes in diffusivity measures which were impaired in MS patients.

MS patients with low disability may show ALFF differences in the MNS without clinical correspondence. This functional difference may be associated with cortical and subcortical changes related to the disease.

Assessing Amyloid Pathology in Cognitively Normal Subjects Using 18F-Flutemetamol PET: Comparing Visual Reads and Quantitative Methods

Our objective was to determine the optimal approach for assessing amyloid disease in a cognitively normal elderly population. Methods: Dynamic ¹⁸F-flutemetamol PET scans were acquired using a coffee-break protocol (a 0- to 30-min scan and a 90- to 110-min scan) on 190 cognitively normal elderly individuals (mean age, 70.4 y; 60% female). Parametric images were generated from SUV ratio (SUVr) and nondisplaceable binding potential (BP_ND) methods, with cerebellar gray matter as a reference region, and were visually assessed by 3 trained readers. Interreader agreement was calculated using κ-statistics, and semiquantitative values were obtained. Global cutoffs were calculated for both SUVr and BP_ND using a receiver-operating-characteristic analysis and the Youden index. Visual assessment was related to semiquantitative classifications. Results: Interreader agreement in visual assessment was moderate for SUVr (κ = 0.57) and good for BP_ND images (κ = 0.77). There was discordance between readers for 35 cases (18%) using SUVr and for 15 cases (8%) using BP_ND, with 9 overlapping cases. For the total cohort, the mean (±SD) SUVr and BP_ND were 1.33 (±0.21) and 0.16 (±0.12), respectively. Most of the 35 cases (91%) for which SUVr image assessment was discordant between readers were classified as negative based on semiquantitative measurements. Conclusion: The use of parametric BP_ND images for visual assessment of ¹⁸F-flutemetamol in a population with low amyloid burden improves interreader agreement. Implementing semiquantification in addition to visual assessment of SUVr images can reduce false-positive classification in this population.

Alterations in the connection topology of brain structural networks in Internet gaming addiction

Internet gaming addiction (IGA), as the most popular subtype of Internet addiction, is becoming a common and widespread mental health concern, but there are still debates on whether IGA constitutes a psychiatric disorder. The view on the brain as a complex network has developed network analysis of neuroimaging data, revealing that abnormalities of brain functional and structural systems are related to alterations in brain network configuration, such as small-world topology, in neuropsychiatric disorders. Here we applied network analysis to diffusion-weighted MRI data of 102 gaming individuals and 41 non-gaming healthy individuals to seek changes in the small-world topology of brain structural networks in IGA. The connection topology of brain structural networks shifted to the direction of random topology in the gaming individuals, irrespective of whether they were diagnosed with Internet gaming disorder. Furthermore, when we simulated targeted or untargeted attacks on nodes, the connection topology of the gaming individuals' brain structural networks under no attacks was comparable to that of the non-gaming healthy individuals' brain structural networks under targeted attacks. Alterations in connection topology provide a clue that Internet gaming addicted brains could be as abnormal as brains suffering from targeted damage.

PET imaging of noradrenaline transporters in Parkinson's disease: focus on scan time

OBJECTIVE

In subjects with idiopathic Parkinson's disease (PD) the functional state of the locus coeruleus and the subtle derangements in the finely tuned dopamine-noradrenaline interplay are largely unknown. The PET ligand (S,S)-[¹¹C]-O-methylreboxetine (C-11 MRB) has been described to reliably bind noradrenaline transporters but long scanning protocols might hamper its use, especially in patients with PD. We aimed to assess the feasibility of reducing C-11 MRB scans to 30 min.

METHODS

Ten patients with idiopathic PD underwent dynamic C-11 MRB PET (120 min duration) and brain magnetic resonance imaging. Model-based (i.e., simplified and multilinear reference tissue model 2) non-displaceable binding potentials (BP) of selected brain regions were analyzed for a 90 min scan protocol and compared with BP derived from static 30-min data with different starting times (30, 40, 50 and 60 min) after C-11 MRB injection. Intraclass correlation coefficient and linear regression analysis were used to explore the association between BP of different scan durations. Spearman's ρ served to describe the correlation of BP with demographic and clinical parameters.

RESULTS

With respect to kinetic models, BP_50-80 and BP_60-90 showed the best correlation in several brain areas (R² range 0.95-98; p < 0.001). The thalamus showed the highest BP on average. No correlation between BP, clinical and demographic characteristics was observed.

CONCLUSIONS

An acquisition time of 30 min, starting 50 or 60 min after C-11 MRB injection, allows a reliable estimation of noradrenaline transporter binding values in Parkinsonian people. A short acquisition time can significantly reduce the discomfort of Parkinsonian patients and facilitate PET studies, especially in the medication-off-state.

Involvement of the Precuneus/Posterior Cingulate Cortex Is Significant for the Development of Alzheimer's Disease: A PET (THK5351, PiB) and Resting fMRI Study

Background: Imaging studies in Alzheimer’s disease (AD) have yet to answer the underlying questions concerning the relationship among tau retention, neuroinflammation, network disruption and cognitive decline. We compared the spatial retention patterns of ¹⁸F-THK5351 and resting state network (RSN) disruption in patients with early AD and healthy controls.

Methods: We enrolled 23 ¹¹C-Pittsburgh compound B (PiB)-positive patients with early AD and 24 ¹¹C-PiB-negative participants as healthy controls. All participants underwent resting state functional MRI and ¹⁸F-THK5351 PET scans. We used scaled subprofile modeling/principal component analysis (SSM/PCA) to reduce the complexity of multivariate data and to identify patterns that exhibited the largest statistical effects (variances) in THK5351 concentration in AD and healthy controls.

Findings: SSM/PCA identified a significant spatial THK5351 pattern composed by mainly three clusters including precuneus/posterior cingulate cortex (PCC), right and left dorsolateral prefrontal cortex (DLPFC) which accounted for 23.6% of the total subject voxel variance of the data and had 82.6% sensitivity and 79.1% specificity in discriminating AD from healthy controls. There was a significant relationship between the intensity of the ¹⁸F-THK5351 covariation pattern and cognitive scores in AD. The spatial patterns of ¹⁸F-THK5351 uptake showed significant similarity with intrinsic functional connectivity, especially in the PCC network. Seed-based connectivity analysis from the PCC showed significant decrease in connectivity over widespread brain regions in AD patients. An evaluation of an autopsied AD patient with Braak V showed that ¹⁸F-THK5351 retention corresponded to tau deposition, monoamine oxidase-B (MAO-B) and astrogliosis in the precuneus/PCC.

Interpretation: We identified an AD-specific spatial pattern of ¹⁸F-THK5351 retention in the precuneus/PCC, an important connectivity hub region in the brain. Disruption of the functional connections of this important network hub may play an important role in developing dementia in AD.

Disrupted Coupling Between the Spontaneous Fluctuation and Functional Connectivity in Idiopathic Generalized Epilepsy

Purpose: The purpose of this study was to comprehensively evaluate alterations of resting-state spontaneous brain activity in patients with idiopathic generalized epilepsy (IGE) and its subgroups [juvenile myoclonic epilepsy (JME) and generalized tonic-clonic seizures (GTCS)]. Methods: Resting state functional magnetic resonance imaging (fMRI) data were acquired from 60 patients with IGE and 60 healthy controls (HCs). Amplitude of low frequency fluctuation (ALFF), global functional connectivity density (gFCD), local FCD (lFCD), and long range FCD (lrFCD) were used to evaluate spontaneous brain activity in the whole brain. Moreover, the coupling between ALFF and FCDs (gFCD, lFCD, and lrFCD) was analyzed on both voxel-wise and subject-wise levels. Two-sample t-tests were used to analyze the difference in ALFF, FCDs and coupling on a subject-wise level between the two groups. Nonparametric permutation tests were used to evaluate differences in coupling on a voxel-wise level. Key findings: Patients with IGE and its subgroups showed reduced ALFF, gFCD and lrFCD in posterior regions of the default mode network (DMN). In addition, decreased ALFF and increased coupling with FCD were found in the cerebellum, while decreased coupling was observed in the bilateral pre- and postcentral gyrus in IGE compared with the coupling in HCs. Similar findings were found in the analysis between each of the two subgroups of IGE (JME and GTCS) and HCs, and JME patients had increased coupling in the cerebellum and bilateral middle occipital gyrus compared with coupling in the GTCS patients. Significance: This study demonstrated a multifactor abnormality of the DMN in IGE and emphasized that the abnormality in the cerebellum was associated with dysfunctional motor symptoms during seizures and might participate in the regulation of GSWDs in IGE.

A Proof-of-Concept Study to Inhibit ABCG2- and ABCB1-Mediated Efflux Transport at the Human Blood-Brain Barrier

The adenosine triphosphate-binding cassette transporters P-glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2) are 2 efflux transporters at the blood-brain barrier (BBB) that effectively restrict brain distribution of dual ABCB1/ABCG2 substrate drugs, such as tyrosine kinase inhibitors. Pharmacologic inhibition of ABCB1/ABCG2 may improve the efficacy of dual-substrate drugs for treatment of brain tumors, but no marketed ABCB1/ABCG2 inhibitors are currently available. In the present study, we examined the potential of supratherapeutic-dose oral erlotinib to inhibit ABCB1/ABCG2 activity at the human BBB. Methods: Healthy men underwent 2 consecutive PET scans with ¹¹C-erlotinib: a baseline scan and a second scan either with concurrent intravenous infusion of the ABCB1 inhibitor tariquidar (3.75 mg/min, n = 5) or after oral intake of single ascending doses of erlotinib (300 mg, n = 7; 650 mg, n = 8; or 1,000 mg, n = 2). Results: Although tariquidar administration had no effect on ¹¹C-erlotinib brain distribution, oral erlotinib led, at the 650-mg dose, to significant increases in volume of distribution (23% ± 13%, P = 0.008), influx rate constant of radioactivity from plasma into brain (58% ± 26%, P = 0.008), and area under the brain time-activity curve (78% ± 17%, P = 0.008), presumably because of combined partial saturation of ABCG2 and ABCB1 activity. Inclusion of further subjects into the 1,000-mg dose group was precluded by adverse skin events (rash). Conclusion: Supratherapeutic-dose erlotinib may be used to enhance brain delivery of ABCB1/ABCG2 substrate anticancer drugs, but its clinical applicability for continuous ABCB1/ABCG2 inhibition at the BBB may be limited by safety concerns.

Performance Level and Cortical Atrophy Modulate the Neural Response to Increasing Working Memory Load in Younger and Older Adults

There is evidence that the neural response to increasing working memory (WM) load is modulated by age and performance level. For a valid interpretation of these effects, however, it is important to understand, whether and how they are related to gray matter atrophy. In the current work, we therefore used functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM) to examine the association between age, performance level, spatial WM load-related brain activation and gray matter volume in 18 younger high-performers (YHP), 17 younger low-performers (YLP), 17 older high-performers (OHP), and 18 older low-performers (OLP). In multiple sub regions of the prefrontal cortex (PFC), load-related activation followed a linear trend with increasing activation at increasing load in all experimental groups. Results did not reveal differences between the sub groups. Older adults additionally showed a pattern of increasing activation from low to medium load but stable or even decreasing activation from medium to high load in other sub regions of the PFC (quadratic trend). Quadratic trend related brain activation was higher in older than in younger adults and in OLP compared to OHP. In OLP, quadratic trend related brain activation was negatively correlated with both performance accuracy and prefrontal gray matter volume. The results suggest an efficient upregulation of multiple PFC areas as response to increasing WM load in younger and older adults. Older adults and particularly OLP additionally show dysfunctional response patterns (i.e., enhanced quadratic trend related brain activation compared to younger adults and OHP, respectively) in other PFC clusters being associated with gray matter atrophy.

Robustness of post-reconstruction and direct kinetic parameter estimates under rigid head motion in dynamic brain PET imaging

OBJECTIVE

Dynamic PET imaging is extensively used in brain imaging to estimate parametric maps. Inter-frame motion can substantially disrupt the voxel-wise time-activity curves (TACs), leading to erroneous maps during kinetic modelling. Therefore, it is important to characterize the robustness of kinetic parameters under various motion and kinetic model related factors.

METHODS

Fully 4D brain simulations ([¹⁵O]H₂O and [¹⁸F]FDG dynamic datasets) were performed using a variety of clinically observed motion patterns. Increasing levels of head motion were investigated as well as varying temporal frames of motion initiation. Kinetic parameter estimation was performed using both post-reconstruction kinetic analysis and direct 4D image reconstruction to assess bias from inter-frame emission blurring and emission/attenuation mismatch.

RESULTS

Kinetic parameter bias heavily depends on the time point of motion initiation. Motion initiated towards the end of the scan results in the most biased parameters. For the [¹⁸F]FDG data, k₄ is the more sensitive parameter to positional changes, while K₁ and blood volume were proven to be relatively robust to motion. Direct 4D image reconstruction appeared more sensitive to changes in TACs due to motion, with parameter bias spatially propagating and depending on the level of motion.

CONCLUSION

Kinetic parameter bias highly depends upon the time frame at which motion occurred, with late frame motion-induced TAC discontinuities resulting in the least accurate parameters. This is of importance during prolonged data acquisition as is often the case in neuro-receptor imaging studies. In the absence of a motion correction, use of TOF information within 4D image reconstruction could limit the error propagation.

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data

A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of Alzheimer's disease (AD). However, while the vast majority of these works use the public dataset ADNI for evaluation, they are difficult to reproduce because different key components of the validation are often not readily available. These components include selected participants and input data, image preprocessing and cross-validation procedures. The performance of the different approaches is also difficult to compare objectively. In particular, it is often difficult to assess which part of the method (e.g. preprocessing, feature extraction or classification algorithms) provides a real improvement, if any. In the present paper, we propose a framework for reproducible and objective classification experiments in AD using three publicly available datasets (ADNI, AIBL and OASIS). The framework comprises: i) automatic conversion of the three datasets into a standard format (BIDS); ii) a modular set of preprocessing pipelines, feature extraction and classification methods, together with an evaluation framework, that provide a baseline for benchmarking the different components. We demonstrate the use of the framework for a large-scale evaluation on 1960 participants using T1 MRI and FDG PET data. In this evaluation, we assess the influence of different modalities, preprocessing, feature types (regional or voxel-based features), classifiers, training set sizes and datasets. Performances were in line with the state-of-the-art. FDG PET outperformed T1 MRI for all classification tasks. No difference in performance was found for the use of different atlases, image smoothing, partial volume correction of FDG PET images, or feature type. Linear SVM and L2-logistic regression resulted in similar performance and both outperformed random forests. The classification performance increased along with the number of subjects used for training. Classifiers trained on ADNI generalized well to AIBL and OASIS. All the code of the framework and the experiments is publicly available: general-purpose tools have been integrated into the Clinica software (www.clinica.run) and the paper-specific code is available at: https://gitlab.icm-institute.org/aramislab/AD-ML.

A novel partial volume correction method for accurate quantification of [18F] flortaucipir in the hippocampus

Background

Off-target binding in the choroid plexus (CP) may cause spill-in of the tau PET tracer [¹⁸F] flortaucipir into the adjacent hippocampus region. The impact of this spill-in on hippocampal uptake was assessed using a novel partial volume correction method (PVC).

Methods

PVC was performed on 20 [¹⁸F] flortaucipir dynamic PET scans (10 probable AD and 10 controls). Volumes of interest (VOIs) were defined for both hippocampus and CP. The correlation between hippocampal and CP distribution volume (V_T), with and without PVC, was determined. Both anatomically defined and eroded VOIs were used.

Results

For controls, the correlation between hippocampal and CP V_T was significantly reduced after using PVC along with an eroded VOI (r² = 0.59, slope = 0.80 versus r² = 0.15, slope = 0.15; difference: p < 0.05). The same was true for AD patients (p < 0.05).

Conclusion

PVC together with an optimized hippocampal VOI resulted in effective reduction of CP spill-in and improved accuracy of hippocampal V_T.

Electronic supplementary material

The online version of this article (10.1186/s13550-018-0432-2) contains supplementary material, which is available to authorized users.

Treatment with Growth Hormone (GH) Increased the Metabolic Activity of the Brain in an Elder Patient, Not GH-Deficient, Who Suffered Mild Cognitive Alterations and Had an ApoE 4/3 Genotype

(1) Background: We analyzed, using PET-SCAN and cognitive tests, how growth hormone (GH) could act in the brain of an older woman, not deficient in GH, who showed mild cognitive alterations (MCI) and had a genotype of ApoE 4/3 and familial dyslipidemia. (2) Methods: After performing a first psychometric study (TAVEC verbal learning test), the metabolic activity of brain structures related to knowledge, memory, and behavior was analyzed using 18-F fluorodeoxyglucose PET-SCAN. The patient was then treated with GH (0.4 mg/day, subcutaneous) for three weeks and on the last day under this treatment, a new PET-SCAN was performed. One month after beginning treatment with GH, a new TAVEC test was performed. (3) Results: GH administration normalized the cognitive deficits observed in the first psychometric test and significantly (p < 0.025) increased the metabolic activity in practically all brain cortical areas, specifically in the left hippocampus and left amygdala, although not in the left parahippocampus. (4) Conclusions: This study demonstrates for the first time the positive effects of GH on cerebral metabolism in a patient without GH deficiency, recovering the function of affected areas related to knowledge, memory, and behavior in an elderly patient with MCI.

The Effect of 40-Hz Light Therapy on Amyloid Load in Patients with Prodromal and Clinical Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. AD pathology is characterized by abnormal aggregation of the proteins amyloid-β (Aβ) and hyperphosphorylated tau. No effective disease modifying therapies are currently available. A short-duration intervention with 40 Hz light flicker has been shown to reduce brain Aβ load in transgenic mice. We aimed to test the effect of a similar short-duration 40 Hz light flicker regime in human AD patients. We utilized a Light Emitting Diode (LED) light bulb with a 40 Hz flicker. Six Aβ positive patients received 10 days of light therapy, had 2 hours of daily exposure, and underwent a postintervention PiB PET on day 11. After 10 days of light therapy, no significant decrease of PiB SUVR values was detected in any volumes of interest tested (primary visual cortex, visual association cortex, lateral parietal cortex, precuneus, and posterior cingulate) or in the total motor cortex, and longer treatments may be necessary to induce amyloid removal in humans.