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

Microglial Activation and Progression of Nigrostriatal Dysfunction in Isolated REM Sleep Behavior Disorder

BACKGROUND

Using 11C-(R)-PK11195-PET, we found increased microglia activation in isolated REM sleep behavior disorder (iRBD) patients. Their role remains to be clarified.

OBJECTIVES

The objective is to assess relationships between activated microglia and progression of nigrostriatal dysfunction in iRBD.

METHODS

Fifteen iRBD patients previously scanned with 11C-(R)-PK11195 and 18F-DOPA-PET underwent repeat 18F-DOPA-PET after 3 years. 18F-DOPA Ki changes from baseline were evaluated with volumes-of-interest and voxel-based analyses.

RESULTS

Significant 18F-DOPA Ki reductions were found in putamen and caudate. Reductions were larger and more widespread in patients with increased nigral microglia activation at baseline. Left nigral 11C-(R)-PK11195 binding at baseline was a predictor of 18F-DOPA Ki reduction in left caudate (coef = -0.0426, P = 0.016).

CONCLUSIONS

Subjects with increased baseline 11C-(R)-PK11195 binding have greater changes in nigrostriatal function, suggesting a detrimental rather than protective effect of microglial activation. Alternatively, both phenomena occur in patients with prominent nigrostriatal dysfunction without a causative link. The clinical and therapeutic implications of these findings need further elucidation. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

DOCK-PET: database of CNS kinetic parameters in the healthy human brain for existing PET tracers

PURPOSE

Information about developed positron emission tomography (PET) tracers and obtained clinical PET images is publicly available in a database. However, findings regarding the kinetic parameters of PET tracers are yet to be summarized. Therefore, in this study, we created an open-access database of central nervous system (CNS) kinetic parameters in the healthy human brain for existing PET tracers (DOCK-PET).

METHODS

Our database includes information on the kinetic parameters and compounds of existing CNS-PET tracers. The kinetic parameter dataset comprises the analysis methods, VT, BPND, K parameters, relevant literature, and study details. The list of PET tracers and kinetic parameter information was compiled through keyword-based searches of PubMed and the Molecular Imaging and Contrast Agent Database (MICAD). The kinetic parameters obtained, including VT, BPND, and K parameters, were reorganized based on the defined brain anatomical regions. All data were rigorously double-checked before being summarized in Microsoft Excel and JavaScript Object Notation (JSON) formats.

RESULTS

Of the 247 PET tracers identified through searches using the PubMed and MICAD websites, the kinetic parameters of 120 PET tracers were available. Among the 120 PET tracers, compound structures with chemical and physical properties were obtained from the PubChem website or the ChemDraw software. Furthermore, the affinity information of the 104 PET tracers was gathered from PubChem or extensive literature surveys of the 120 PET tracers.

CONCLUSIONS

We developed a comprehensive open-access database, DOCK-PET, that includes both kinetic parameters of healthy humans and compound information for existing CNS-PET tracers.

Multiscale brain age prediction reveals region-specific accelerated brain aging in Parkinson's disease

Brain biological age, which measures the aging process in the brain using neuroimaging data, has been used to assess advanced brain aging in neurodegenerative diseases, including Parkinson disease (PD). However, assuming that whole brain degeneration is uniform may not be sufficient for assessing the complex neurodegenerative processes in PD. In this study we constructed a multiscale brain age prediction models based on structural MRI of 1240 healthy participants. To assess the brain aging patterns using the brain age prediction model, 93 PD patients and 91 healthy controls matching for sex and age were included. We found increased global and regional brain age in PD patients. The advanced aging regions were predominantly noted in the frontal and temporal cortices, limbic system, basal ganglia, thalamus, and cerebellum. Furthermore, region-level rather than global brain age in PD patients was associated with disease severity. Our multiscale brain age prediction model could aid in the development of objective image-based biomarkers to detect advanced brain aging in neurodegenerative diseases.

GNN-based structural information to improve DNN-based basal ganglia segmentation in children following early brain lesion

Analyzing the basal ganglia following an early brain lesion is crucial due to their noteworthy role in sensory-motor functions. However, the segmentation of these subcortical structures on MRI is challenging in children and is further complicated by the presence of a lesion. Although current deep neural networks (DNN) perform well in segmenting subcortical brain structures in healthy brains, they lack robustness when faced with lesion variability, leading to structural inconsistencies. Given the established spatial organization of the basal ganglia, we propose enhancing the DNN-based segmentation through post-processing with a graph neural network (GNN). The GNN conducts node classification on graphs encoding both class probabilities and spatial information regarding the regions segmented by the DNN. In this study, we focus on neonatal arterial ischemic stroke (NAIS) in children. The approach is evaluated on both healthy children and children after NAIS using three DNN backbones: U-Net, UNETr, and MSGSE-Net. The results show an improvement in segmentation performance, with an increase in the median Dice score by up to 4% and a reduction in the median Hausdorff distance (HD) by up to 93% for healthy children (from 36.45 to 2.57) and up to 91% for children suffering from NAIS (from 40.64 to 3.50). The performance of the method is compared with atlas-based methods. Severe cases of neonatal stroke result in a decline in performance in the injured hemisphere, without negatively affecting the segmentation of the contra-injured hemisphere. Furthermore, the approach demonstrates resilience to small training datasets, a widespread challenge in the medical field, particularly in pediatrics and for rare pathologies.

Chronic Hyponatremia and Brain Structure and Function Before and After Treatment

RATIONALE & OBJECTIVE

Hyponatremia is the most common electrolyte disorder and is associated with significant morbidity and mortality. This study investigated neurocognitive impairment, brain volume, and alterations in magnetic resonance imaging (MRI)-based measures of cerebral function in patients before and after treatment for hyponatremia.

STUDY DESIGN

Prospective cohort study.

SETTING & PARTICIPANTS

Patients with presumed chronic hyponatremia without signs of hypo- or hypervolemia treated in the emergency department of a German tertiary-care hospital.

EXPOSURE

Hyponatremia (ie, plasma sodium concentration [Na+]<125mmol/L) before and after treatment leading to [Na+]>130mmol/L.

OUTCOMES

Standardized neuropsychological testing (Mini-Mental State Examination, DemTect, Trail Making Test A/B, Beck Depression Inventory, Timed Up and Go) and resting-state MRI were performed before and after treatment of hyponatremia to assess total brain and white and gray matter volumes as well as neuronal activity and its synchronization.

ANALYTICAL APPROACH

Changes in outcomes after treatment for hyponatremia assessed using bootstrapped confidence intervals and Cohen d statistic. Associations between parameters were assessed using correlation analyses.

RESULTS

During a 3.7-year period, 26 patients were enrolled. Complete data were available for 21 patients. Mean [Na+]s were 118.4mmol/L before treatment and 135.5mmol/L after treatment. Most measures of cognition improved significantly. Comparison of MRI studies showed a decrease in brain tissue volumes, neuronal activity, and synchronization across all gray matter after normalization of [Na+]. Volume effects were particularly prominent in the hippocampus. During hyponatremia, synchronization of neuronal activity was negatively correlated with [Na+] (r=-0.836; 95% CI, -0.979 to-0.446) and cognitive function (Mini-Mental State Examination, r=-0.523; 95% CI, -0.805 to-0.069; DemTect, r=-0.744; 95% CI, -0.951 to-0.385; and Trail Making Test A, r=0.692; 95% CI, 0.255-0.922).

LIMITATIONS

Small sample size, insufficient quality of several MRI scans as a result of motion artifact.

CONCLUSIONS

Resolution of hyponatremia was associated with improved cognition and reductions in brain volumes and neuronal activity. Impaired cognition during hyponatremia is closely linked to increased neuronal activity rather than to tissue volumes. Furthermore, the hippocampus appears to be particularly susceptible to hyponatremia, exhibiting pronounced changes in tissue volume.

PLAIN-LANGUAGE SUMMARY

Hyponatremia is a common clinical problem, and patients often present with neurologic symptoms that are at least partially reversible. This study used neuropsychological testing and magnetic resonance imaging to examine patients during and after correction of hyponatremia. Treatment led to an improvement in patients' cognition as well as a decrease in their brain volumes, spontaneous neuronal activity, and synchronized neuronal activity between remote brain regions. Volume effects were particularly prominent in the hippocampus, an area of the brain that is important for the modulation of memory. During hyponatremia, patients with the lowest sodium concentrations had the highest levels of synchronized neuronal activity and the poorest cognitive test results.

Brain gray matter volume of reward-related structures in Inuit adolescents pre- and postnatally exposed to lead, mercury and polychlorinated biphenyls

This study aimed to assess associations between prenatal and postnatal exposure to lead (Pb), mercury (Hg) and polychlorinated biphenyls (PCBs) and gray matter volume of key regions of the brain reward circuit, namely the caudate nucleus, putamen, nucleus accumbens (nAcc), the amygdala, the orbitofrontal cortex (OFC) and the anterior cingulate cortex (ACC). Structural magnetic resonance imaging (MRI) was conducted in 77 Inuit adolescents (mean age = 18.39) from Nunavik, Canada, who also completed the Brief Sensation Seeking Scale (BSSS-4) and Sensation Seeking - 2 (SS-2), two self-report questionnaires evaluating the tendency toward sensation seeking, which is a proxy of reward-related behaviors. Exposures to Pb, Hg and PCBs were measured in cord blood at birth, in blood samples at 11 years old and at time of testing (18 years old). Multivariate linear regressions were corrected for multiple comparisons and adjusted for potential confounders, such as participants' sociodemographic characteristics and nutrient fish intake. Results showed that higher cord blood Pb levels predicted smaller gray matter volume in the bilateral nAcc, caudate nucleus, amygdala and OFC as well as in left ACC. A moderating effect of sex was identified, indicating that the Pb-related reduction in volume in the nAcc and caudate nucleus was more pronounced in female. Higher blood Hg levels at age 11 predicted smaller right amygdala independently of sex. No significant associations were found between blood PCBs levels at all three times of exposure. This study provides scientific support for the detrimental effects of prenatal Pb and childhood Hg blood concentrations on gray matter volume in key reward-related brain structures.

Investigating the discrimination ability of 3D convolutional neural networks applied to altered brain MRI parametric maps

Convolutional neural networks (CNNs) are gradually being recognized in the neuroimaging community as a powerful tool for image analysis. Despite their outstanding performances, some aspects of CNN functioning are still not fully understood by human operators. We postulated that the interpretability of CNNs applied to neuroimaging data could be improved by investigating their behavior when they are fed data with known characteristics. We analyzed the ability of 3D CNNs to discriminate between original and altered whole-brain parametric maps derived from diffusion-weighted magnetic resonance imaging. The alteration consisted in linearly changing the voxel intensity of either one (monoregion) or two (biregion) anatomical regions in each brain volume, but without mimicking any neuropathology. Performing ten-fold cross-validation and using a hold-out set for testing, we assessed the CNNs' discrimination ability according to the intensity of the altered regions, comparing the latter's size and relative position. Monoregion CNNs showed that the larger the modified region, the smaller the intensity increase needed to achieve good performances. Biregion CNNs systematically outperformed monoregion CNNs, but could only detect one of the two target regions when tested on the corresponding monoregion images. Exploiting prior information on training data allowed for a better understanding of CNN behavior, especially when altered regions were combined. This can inform about the complexity of CNN pattern retrieval and elucidate misclassified examples, particularly relevant for pathological data. The proposed analytical approach may serve to gain insights into CNN behavior and guide the design of enhanced detection systems exploiting our prior knowledge.

Endocannabinoid levels in plasma and neurotransmitters in the brain: a preliminary report on patients with a psychotic disorder and healthy individuals

BACKGROUND

Interactions between the endocannabinoid system (ECS) and neurotransmitter systems might mediate the risk of developing a schizophrenia spectrum disorder (SSD). Consequently, we investigated in patients with SSD and healthy controls (HC) the relations between (1) plasma concentrations of two prototypical endocannabinoids (N-arachidonoylethanolamine [anandamide] and 2-arachidonoylglycerol [2-AG]) and (2) striatal dopamine synthesis capacity (DSC), and glutamate and y-aminobutyric acid (GABA) levels in the anterior cingulate cortex (ACC). As anandamide and 2-AG might reduce the activity of these neurotransmitters, we hypothesized negative correlations between their plasma levels and the abovementioned neurotransmitters in both groups.

METHODS

Blood samples were obtained from 18 patients and 16 HC to measure anandamide and 2-AG plasma concentrations. For all subjects, we acquired proton magnetic resonance spectroscopy scans to assess Glx (i.e. glutamate plus glutamine) and GABA + (i.e. GABA plus macromolecules) concentrations in the ACC. Ten patients and 14 HC also underwent [18F]F-DOPA positron emission tomography for assessment of striatal DSC. Multiple linear regression analyses were used to investigate the relations between the outcome measures.

RESULTS

A negative association between 2-AG plasma concentration and ACC Glx concentration was found in patients (p = 0.008). We found no evidence of other significant relationships between 2-AG or anandamide plasma concentrations and dopaminergic, glutamatergic, or GABAergic measures in either group.

CONCLUSIONS

Our preliminary results suggest an association between peripheral 2-AG and ACC Glx levels in patients.

Sex Differences in Response Inhibition-Related Neural Predictors of Posttraumatic Stress Disorder in Civilians With Recent Trauma

BACKGROUND

Females are more likely to develop posttraumatic stress disorder (PTSD) than males. Impaired inhibition has been identified as a mechanism for PTSD development, but studies on potential sex differences in this neurobiological mechanism and how it relates to PTSD severity and progression are relatively rare. Here, we examined sex differences in neural activation during response inhibition and PTSD following recent trauma.

METHODS

Participants (n = 205, 138 female sex assigned at birth) were recruited from emergency departments within 72 hours of a traumatic event. PTSD symptoms were assessed 2 weeks and 6 months posttrauma. A Go/NoGo task was performed 2 weeks posttrauma in a 3T magnetic resonance imaging scanner to measure neural activity during response inhibition in the ventromedial prefrontal cortex, right inferior frontal gyrus, and bilateral hippocampus. General linear models were used to examine the interaction effect of sex on the relationship between our regions of interest and the whole brain, PTSD symptoms at 6 months, and symptom progression between 2 weeks and 6 months.

RESULTS

Lower response inhibition-related ventromedial prefrontal cortex activation 2 weeks posttrauma predicted more PTSD symptoms at 6 months in females but not in males, while greater response inhibition-related right inferior frontal gyrus activation predicted lower PTSD symptom progression in males but not females. Whole-brain interaction effects were observed in the medial temporal gyrus and left precentral gyrus.

CONCLUSIONS

There are sex differences in the relationship between inhibition-related brain activation and PTSD symptom severity and progression. These findings suggest that sex differences should be assessed in future PTSD studies and reveal potential targets for sex-specific interventions.

Connectome gradient dysfunction contributes to white matter hyperintensity-related cognitive decline

BACKGROUND

Although white matter hyperintensity (WMH) is closely associated with cognitive decline, the precise neurobiological mechanisms underlying this relationship are not fully elucidated. Connectome studies have identified a primary-to-transmodal gradient in functional brain networks that support the spectrum from sensation to cognition. However, whether connectome gradient structure is altered as WMH progresses and how this alteration is associated with WMH-related cognitive decline remain unknown.

METHODS

A total of 758 WMH individuals completed cognitive assessment and resting-state functional MRI (rs-fMRI). The functional connectome gradient was reconstructed based on rs-fMRI by using a gradient decomposition framework. Interrelations among the spatial distribution of WMH, functional gradient measures, and specific cognitive domains were explored.

RESULTS

As the WMH volume increased, the executive function (r = -0.135, p = 0.001) and information-processing speed (r = -0.224, p = 0.001) became poorer, the gradient range (r = -0.099, p = 0.006), and variance (r = -0.121, p < 0.001) of the primary-to-transmodal gradient reduced. A narrower gradient range (r = 0.131, p = 0.001) and a smaller gradient variance (r = 0.136, p = 0.001) corresponded to a poorer executive function. In particular, the relationship between the frontal/occipital WMH and executive function was partly mediated by gradient range/variance of the primary-to-transmodal gradient.

CONCLUSIONS

These findings indicated that WMH volume, the primary-to-transmodal gradient, and cognition were interrelated. The detrimental effect of the frontal/occipital WMH on executive function was partly mediated by the decreased differentiation of the connectivity pattern between the primary and transmodal areas.

Evaluation of [11C]UCB-A positron emission tomography in human brains

BACKGROUND

In preclinical studies, the positron emission tomography (PET) imaging with [11C]UCB-A provided promising results for imaging synaptic vesicle protein 2A (SV2A) as a proxy for synaptic density. This paper reports the first-in-human [11C]UCB-A PET study to characterise its kinetics in healthy subjects and further evaluate SV2A-specific binding.

RESULTS

Twelve healthy subjects underwent 90-min baseline [11C]UCB-A scans with PET/MRI, with two subjects participating in an additional blocking scan with the same scanning procedure after a single dose of levetiracetam (1500 mg). Our results indicated abundant [11C]UCB-A brain uptake across all cortical regions, with slow elimination. Kinetic modelling of [11C]UCB-A PET using various compartment models suggested that the irreversible two-tissue compartment model best describes the kinetics of the radioactive tracer. Accordingly, the Patlak graphical analysis was used to simplify the analysis. The estimated SV2A occupancy determined by the Lassen plot was around 66%. Significant specific binding at baseline and comparable binding reduction as grey matter precludes the use of centrum semiovale as reference tissue.

CONCLUSIONS

[11C]UCB-A PET imaging enables quantifying SV2A in vivo. However, its slow kinetics require a long scan duration, which is impractical with the short half-life of carbon-11. Consequently, the slow kinetics and complicated quantification methods may restrict its use in humans.

Predicting conversion from mild cognitive impairment to Alzheimer's disease: a multimodal approach

Successively predicting whether mild cognitive impairment patients will progress to Alzheimer's disease is of significant clinical relevance. This ability may provide information that can be leveraged by emerging intervention approaches and thus mitigate some of the negative effects of the disease. Neuroimaging biomarkers have gained some attention in recent years and may be useful in predicting the conversion of mild cognitive impairment to Alzheimer's disease. We implemented a novel multi-modal approach that allowed us to evaluate the potential of different imaging modalities, both alone and in different degrees of combinations, in predicting the conversion to Alzheimer's disease of mild cognitive impairment patients. We applied this approach to the imaging data from the Alzheimer's Disease Neuroimaging Initiative that is a multi-modal imaging dataset comprised of MRI, Fluorodeoxyglucose PET, Florbetapir PET and diffusion tensor imaging. We included a total of 480 mild cognitive impairment patients that were split into two groups: converted and stable. Imaging data were segmented into atlas-based regions of interest, from which relevant features were extracted for the different imaging modalities and used to construct machine-learning models to classify mild cognitive impairment patients into converted or stable, using each of the different imaging modalities independently. The models were then combined, using a simple weight fusion ensemble strategy, to evaluate the complementarity of different imaging modalities and their contribution to the prediction accuracy of the models. The single-modality findings revealed that the model, utilizing features extracted from Florbetapir PET, demonstrated the highest performance with a balanced accuracy of 83.51%. Concerning multi-modality models, not all combinations enhanced mild cognitive impairment conversion prediction. Notably, the combination of MRI with Fluorodeoxyglucose PET emerged as the most promising, exhibiting an overall improvement in predictive capabilities, achieving a balanced accuracy of 78.43%. This indicates synergy and complementarity between the two imaging modalities in predicting mild cognitive impairment conversion. These findings suggest that β-amyloid accumulation provides robust predictive capabilities, while the combination of multiple imaging modalities has the potential to surpass certain single-modality approaches. Exploring modality-specific biomarkers, we identified the brainstem as a sensitive biomarker for both MRI and Fluorodeoxyglucose PET modalities, implicating its involvement in early Alzheimer's pathology. Notably, the corpus callosum and adjacent cortical regions emerged as potential biomarkers, warranting further study into their role in the early stages of Alzheimer's disease.

Approaches to Measuring Language Lateralisation: An Exploratory Study Comparing Two fMRI Methods and Functional Transcranial Doppler Ultrasound

In this exploratory study we compare and contrast two methods for deriving a laterality index (LI) from functional magnetic resonance imaging (fMRI) data: the weighted bootstrapped mean from the LI Toolbox (toolbox method), and a novel method that uses subtraction of activations from homologous regions in left and right hemispheres to give an array of difference scores (mirror method). Data came from 31 individuals who had been selected to include a high proportion of people with atypical laterality when tested with functional transcranial Doppler ultrasound (fTCD). On two tasks, word generation and semantic matching, the mirror method generally gave better agreement with fTCD laterality than the toolbox method, both for individual regions of interest, and for a large region corresponding to the middle cerebral artery. LI estimates from this method had much smaller confidence intervals (CIs) than those from the toolbox method; with the mirror method, most participants were reliably lateralised to left or right, whereas with the toolbox method, a higher proportion were categorised as bilateral (i.e., the CI for the LI spanned zero). Reasons for discrepancies between fMRI methods are discussed: one issue is that the toolbox method averages the LI across a wide range of thresholds. Furthermore, examination of task-related t-statistic maps from the two hemispheres showed that language lateralisation is evident in regions characterised by deactivation, and so key information may be lost by ignoring voxel activations below zero, as is done with conventional estimates of the LI.

Disrupted individual-level morphological brain network in spinal muscular atrophy types 2 and 3

BACKGROUND AND OBJECTIVE

Spinal muscular atrophy (SMA) is one of the most common monogenic neuromuscular diseases, and the pathogenesis mechanisms, especially the brain network topological properties, remain unknown. This study aimed to use individual-level morphological brain network analysis to explore the brain neural network mechanisms in SMA.

METHODS

Individual-level gray matter (GM) networks were constructed by estimating the interregional similarity of GM volume distribution using both Kullback-Leibler divergence-based similarity (KLDs) and Jesen-Shannon divergence-based similarity (JSDs) measurements based on Automated Anatomical Labeling 116 and Hammersmith 83 atlases for 38 individuals with SMA types 2 and 3 and 38 age- and sex-matched healthy controls (HCs). The topological properties were analyzed by the graph theory approach and compared between groups by a nonparametric permutation test. Additionally, correlation analysis was used to assess the associations between altered topological metrics and clinical characteristics.

RESULTS

Compared with HCs, although global network topology remained preserved in individuals with SMA, brain regions with altered nodal properties mainly involved the right olfactory gyrus, right insula, bilateral parahippocampal gyrus, right amygdala, right thalamus, left superior temporal gyrus, left cerebellar lobule IV-V, bilateral cerebellar lobule VI, right cerebellar lobule VII, and vermis VII and IX. Further correlation analysis showed that the nodal degree of the right cerebellar lobule VII was positively correlated with the disease duration, and the right amygdala was negatively correlated with the Hammersmith Functional Motor Scale Expanded (HFMSE) scores.

CONCLUSIONS

Our findings demonstrated that topological reorganization may prioritize global properties over nodal properties, and disrupted topological properties in the cortical-limbic-cerebellum circuit in SMA may help to further understand the network pathogenesis underlying SMA.

Relationships between Serotonin Transporter Availability and the Global Efficiency of the Executive Control Brain Network

The diverse effects of serotonin on cognition may emerge from the modulation of large-scale brain networks that support distinct cognitive processes. Yet, the specific effect of serotoninergic modulation on the properties of these networks remains elusive. Here, we used a simultaneous PET-fMRI scanner combined with graph theory analyses to investigate the modulation of network properties by the Serotonin Transporter (SERT) availability measured in the dorsal raphe nucleus (DRN). We defined global efficiency as the average mean of efficiencies over all pairs of distinct nodes of specific brain networks, and determined whether SERT levels correlated with the global efficiency of each network. SERT availability in the DRN correlated negatively with the global efficiency of the executive control brain network, which is engaged in cognitive control and directed attention. No relationship was observed between SERT availability and the global efficiency of the default mode or the salience brain networks. These findings indicate a specific role of serotoninergic modulation in the executive control brain network via a change in its global efficiency.

Basal forebrain volume and metabolism in carriers of the Colombian mutation for autosomal dominant Alzheimer's disease

We aimed to study atrophy and glucose metabolism of the cholinergic basal forebrain in non-demented mutation carriers for autosomal dominant Alzheimer's disease (ADAD). We determined the level of evidence for or against atrophy and impaired metabolism of the basal forebrain in 167 non-demented carriers of the Colombian PSEN1 E280A mutation and 75 age- and sex-matched non-mutation carriers of the same kindred using a Bayesian analysis framework. We analyzed baseline MRI, amyloid PET, and FDG-PET scans of the Alzheimer's Prevention Initiative ADAD Colombia Trial. We found moderate evidence against an association of carrier status with basal forebrain volume (Bayes factor (BF10) = 0.182). We found moderate evidence against a difference of basal forebrain metabolism (BF10 = 0.167). There was only inconclusive evidence for an association between basal forebrain volume and delayed memory and attention (BF10 = 0.884 and 0.184, respectively), and between basal forebrain volume and global amyloid load (BF10 = 2.1). Our results distinguish PSEN1 E280A mutation carriers from sporadic AD cases in which cholinergic involvement of the basal forebrain is already detectable in the preclinical and prodromal stages. This indicates an important difference between ADAD and sporadic AD in terms of pathogenesis and potential treatment targets.

MRI atlas of the pituitary gland in young female adults

The probabilistic topography and inter-individual variability of the pituitary gland (PG) remain undetermined. The absence of a standardized reference atlas hinders research on PG volumetrics. In this study, we aimed at creating maximum probability maps for the anterior and posterior PG in young female adults. We manually delineated the anterior and posterior parts of the pituitary glands in 26 healthy subjects using high-resolution MRI T1 images. A three-step procedure and a cost function-masking approach were employed to optimize spatial normalization for the PG. We generated probabilistic atlases and maximum probability maps, which were subsequently coregistered back to the subjects' space and compared to manual delineations. Manual measurements led to a total pituitary volume of 705 ± 88 mm³, with the anterior and posterior volumes measuring 614 ± 82 mm³ and 91 ± 20 mm³, respectively. The mean relative volume difference between manual and atlas-based estimations was 1.3%. The global pituitary atlas exhibited an 80% (± 9%) overlap for the DICE index and 67% (± 11%) for the Jaccard index. Similarly, these values were 77% (± 13%) and 64% (± 14%) for the anterior pituitary atlas and 62% (± 21%) and 47% (± 17%) for the posterior PG atlas, respectively. We observed a substantial concordance and a significant correlation between the volume estimations of the manual and atlas-based methods for the global pituitary and anterior volumes. The maximum probability maps of the anterior and posterior PG lay the groundwork for automatic atlas-based segmentation methods and the standardized analysis of large PG datasets.

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients

INTRODUCTION

Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, the gold standard TSPO PET quantification method includes a 90 min scan and continuous arterial blood sampling, which is challenging to perform on a routine basis. In this work, we determine what information is required for a simplified quantification approach using a machine learning algorithm.

MATERIALS AND METHODS

We analyzed data from 18 patients with ischemic stroke who received 0-90 min [18F]GE-180 PET as well as T1-weigted (T1w), FLAIR, and arterial spin labeling (ASL) MRI scans. During PET scans, five manual venous blood samples at 5, 15, 30, 60, and 85 min post injection (p.i.) were drawn, and plasma activity concentration was measured. Total distribution volume (VT) was calculated using Logan plot with the full dynamic PET and an image-derived input function (IDIF) from the carotid arteries. IDIF was scaled by a calibration factor derived from all the measured plasma activity concentrations. The calculated VT values were used for training a random forest regressor. As input features for the model, we used three late PET frames (60-70, 70-80, and 80-90 min p.i.), the ASL image reflecting perfusion, the voxel coordinates, the lesion mask, and the five plasma activity concentrations. The algorithm was validated with the leave-one-out approach. To estimate the impact of the individual features on the algorithm's performance, we used Shapley Additive Explanations (SHAP). Having determined that the three late PET frames and the plasma activity concentrations were the most important features, we tested a simplified quantification approach consisting of dividing a late PET frame by a plasma activity concentration. All the combinations of frames/samples were compared by means of concordance correlation coefficient and Bland-Altman plots.

RESULTS

When using all the input features, the algorithm predicted VT values with high accuracy (87.8 ± 8.3%) for both lesion and non-lesion voxels. The SHAP values demonstrated high impact of the late PET frames (60-70, 70-80, and 80-90 min p.i.) and plasma activity concentrations on the VT prediction, while the influence of the ASL-derived perfusion, voxel coordinates, and the lesion mask was low. Among all the combinations of the late PET frames and plasma activity concentrations, the 70-80 min p.i. frame divided by the 30 min p.i. plasma sample produced the closest VT estimate in the ischemic lesion.

CONCLUSION

Reliable TSPO PET quantification is achievable by using a single late PET frame divided by a late blood sample activity concentration.

Cortical Tau Aggregation Patterns associated with Apraxia in Alzheimer's Disease

Objectives

Apraxia is a core feature of Alzheimer's disease, but the pathomechanism of this characteristic symptom is not well understood. Here, we systematically investigated apraxia profiles in a well-defined group of patients with Alzheimer's disease (AD; N=32) who additionally underwent PET imaging with the second-generation tau PET tracer [18F]PI-2620. We hypothesized that specific patterns of tau pathology might be related to apraxic deficits.

Methods

Patients (N=32) with a biomarker-confirmed diagnosis of Alzheimer's disease were recruited in addition to a sample cognitively unimpaired controls (CU 1 ; N=41). Both groups underwent in-depth neuropsychological assessment of apraxia (Dementia Apraxia Screening Test; DATE and the Cologne Apraxia Screening; KAS). In addition, static PET imaging with [18F]PI-2620 was performed to assess tau pathology in the AD patients. To specifically investigate the association of apraxia with regional tau-pathology, we compared the PET-data from this group with an independent sample of amyloid-negative cognitively intact participants (CU 2; N=54) by generation of z-score-deviation maps as well as voxel- based multiple regression analyses.

Results

We identified significant clusters of tau-aggregation in praxis-related regions (e.g., supramarginal gyrus, angular gyrus, temporal, parietal and occipital regions) that were associated with apraxia. These regions were similar between the two apraxia assessments. No correlations between tau-tracer uptake in primary motor cortical or subcortical brain regions and apraxia were observed.

Conclusions

These results suggest that tau deposition in specific cortical brain regions may induce local neuronal dysfunction leading to a dose-dependent functional decline in praxis performance.

Impact of improved dead time correction on the quantification accuracy of a dedicated BrainPET scanner

OBJECTIVE

Quantitative values derived from PET brain images are of high interest for neuroscientific applications. Insufficient DT correction (DTC) can lead to a systematic bias of the output parameters obtained by a detailed analysis of the time activity curves (TACs). The DTC method currently used for the Siemens 3T MR BrainPET insert is global, i.e., differences in DT losses between detector blocks are not considered, leading to inaccurate DTC and, consequently, to inaccurate measurements masked by a bias. However, following careful evaluation with phantom measurements, a new block-pairwise DTC method has demonstrated a higher degree of accuracy compared to the global DTC method.

APPROACH

Differences between the global and the block-pairwise DTC method were studied in this work by applying several radioactive tracers. We evaluated the impact on [11C]ABP688, O-(2-[18F]fluoroethyl)-L-tyrosine (FET), and [15O]H2O TACs.

RESULTS

For [11C]ABP688, a relevant bias of between -0.0034 and -0.0053 ml/ (cm3 • min) was found in all studied brain regions for the volume of distribution (VT) when using the current global DTC method. For [18F]FET-PET, differences of up to 10% were observed in the tumor-to-brain ratio (TBRmax), these differences depend on the radial distance of the maximum from the PET isocenter. For [15O]H2O, differences between +4% and -7% were observed in the GM region. Average biases of -4.58%, -3.2%, and -1.2% for the regional cerebral blood flow (CBF (K1)), the rate constant k2, and the volume of distribution VT were observed, respectively. Conversely, in the white matter region, average biases of -4.9%, -7.0%, and 3.8% were observed for CBF (K1), k2, and VT, respectively.

CONCLUSION

The bias introduced by the global DTC method leads to an overestimation in the studied quantitative parameters for all applications compared to the block-pairwise method.

SIGNIFICANCE

The observed differences between the two DTC methods are particularly relevant for research applications in neuroscientific studies as they affect the accuracy of quantitative Brain PET images.

Noradrenergic alterations in Parkinson's disease: a combined 11C-yohimbine PET/neuromelanin MRI study

Degeneration of the noradrenergic system is now considered a pathological hallmark of Parkinson's disease, but little is known about its consequences in terms of parkinsonian manifestations. Here, we evaluated two aspects of the noradrenergic system using multimodal in vivo imaging in patients with Parkinson's disease and healthy controls: the pigmented cell bodies of the locus coeruleus with neuromelanin sensitive MRI; and the density of α2-adrenergic receptors (ARs) with PET using 11C-yohimbine. Thirty patients with Parkinson's disease and 30 age- and sex-matched healthy control subjects were included. The characteristics of the patients' symptoms were assessed using the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Patients showed reduced neuromelanin signal intensity in the locus coeruleus compared with controls and diminished 11C-yohimbine binding in widespread cortical regions, including the motor cortex, as well as in the insula, thalamus and putamen. Clinically, locus coeruleus neuronal loss was correlated with motor (bradykinesia, motor fluctuations, tremor) and non-motor (fatigue, apathy, constipation) symptoms. A reduction of α2-AR availability in the thalamus was associated with tremor, while a reduction in the putamen, the insula and the superior temporal gyrus was associated with anxiety. These results highlight a multifaceted alteration of the noradrenergic system in Parkinson's disease since locus coeruleus and α2-AR degeneration were found to be partly uncoupled. These findings raise important issues about noradrenergic dysfunction that may encourage the search for new drugs targeting this system, including α2-ARs, for the treatment of Parkinson's disease.

Gray matter gamma-hydroxy-butyric acid and glutamate reflect beta-amyloid burden at old age

Gamma-hydroxy-butyric acid (GABA) and glutamate are neurotransmitters with essential importance for cognitive processing. Here, we investigate relationships between GABA, glutamate, and brain ß-amyloid (Aß) burden before clinical manifestation of Alzheimer's disease (AD). Thirty cognitively healthy adults (age 69.9 ± 6 years) received high-resolution atlas-based 1H-magnetic resonance spectroscopic imaging (MRSI) at ultra-high magnetic field strength of 7 Tesla for gray matter-specific assessment of GABA and glutamate. We assessed Aß burden with positron emission tomography and risk factors for AD. Higher gray matter GABA and glutamate related to higher Aß-burden (ß = 0.60, p < 0.05; ß = 0.64, p < 0.02), with positive effect modification by apolipoprotein-E-epsilon-4-allele (APOE4) (p = 0.01-0.03). GABA and glutamate negatively related to longitudinal change in verbal episodic memory performance (ß = -0.48; p = 0.02; ß = -0.50; p = 0.01). In vivo measures of GABA and glutamate reflect early AD pathology at old age, in an APOE4-dependent manner. GABA and glutamate may represent promising biomarkers and potential targets for early therapeutic intervention and prevention.

Highlights

Gray matter-specific metabolic imaging with high-resolution atlas-based MRSI at 7 Tesla.Higher GABA and glutamate relate to ß-amyloid burden, in an APOE4-dependent manner.Gray matter GABA and glutamate identify older adults with high risk of future AD.GABA and glutamate might reflect altered synaptic and neuronal activity at early AD.

Pharmacokinetic Analysis of [18F]FES PET in the Human Brain and Pituitary Gland

PURPOSE

Estrogen receptors (ER) are implicated in psychiatric disorders. We assessed if ER availability in the human brain could be quantified using 16α-[18F]-fluoro-17β-estradiol ([18F]FES) positron emission tomography (PET).

PROCEDURES

Seven post‑menopausal women underwent a dynamic [18F]FES PET scan with arterial blood sampling. A T1-weighted MRI was acquired for anatomical information. After one week, four subjects received a selective ER degrader (SERD), four hours before the PET scan. Pharmacokinetic analysis was performed using a metabolite-corrected plasma curve as the input function. The optimal kinetic model was selected based on the Akaike information criterion and standard error of estimated parameters. Accuracy of Logan graphical analysis and standardized uptake value (SUV) was determined via correlational analyses.

RESULTS

The reversible two-tissue compartment model (2T4k) model with fixed K1/k2 was preferred. The total volume of distribution (VT) could be more reliably estimated than the binding potential (BPND). A high correlation of VT with Logan graphical analysis was observed, but only a moderate correlation with SUV. SERD administration resulted in a reduced VT in the pituitary gland, but not in other regions.

CONCLUSIONS

The optimal quantification method for [18F]FES was the 2T4k with fixed K1/k2 or Logan graphical analysis, but specific binding was only observed in the pituitary gland.

Microglia measured by TSPO PET are associated with Alzheimer's disease pathology and mediate key steps in a disease progression model

INTRODUCTION

Evidence suggests microglial activation precedes regional tau and neurodegeneration in Alzheimer's disease (AD). We characterized microglia with translocator protein (TSPO) positron emission tomography (PET) within an AD progression model where global amyloid beta (Aβ) precedes local tau and neurodegeneration, resulting in cognitive impairment.

METHODS

Florbetaben, PBR28, and MK-6240 PET, T1 magnetic resonance imaging, and cognitive measures were performed in 19 cognitively unimpaired older adults and 22 patients with mild cognitive impairment or mild AD to examine associations among microglia activation, Aβ, tau, and cognition, adjusting for neurodegeneration. Mediation analyses evaluated the possible role of microglial activation along the AD progression model.

RESULTS

Higher PBR28 uptake was associated with higher Aβ, higher tau, and lower MMSE score, independent of neurodegeneration. PBR28 mediated associations between tau in early and middle Braak stages, between tau and neurodegeneration, and between neurodegeneration and cognition.

DISCUSSION

Microglia are associated with AD pathology and cognition and may mediate relationships between subsequent steps in AD progression.

Hierarchical Principal Components for Data-Driven Multiresolution fMRI Analyses

Understanding the organization of neural processing is a fundamental goal of neuroscience. Recent work suggests that these systems are organized as a multiscale hierarchy, with increasingly specialized subsystems nested inside general processing systems. Current neuroimaging methods, such as independent component analysis (ICA), cannot fully capture this hierarchy since they are limited to a single spatial scale. In this manuscript, we introduce multiresolution hierarchical principal components analysis (hPCA) and compare it to ICA using simulated fMRI datasets. Furthermore, we describe a parametric statistical filtering method developed to focus analyses on biologically relevant features. Lastly, we apply hPCA to the Human Connectome Project (HCP) to demonstrate its ability to estimate a hierarchy from real fMRI data. hPCA accurately estimated spatial maps and time series from networks with diverse hierarchical structures. Simulated hierarchies varied in the degree of branching, such as two-way or three-way subdivisions, and the total number of levels, with varying equal or unequal subdivision sizes at each branch. In each case, as well as in the HCP, hPCA was able to reconstruct a known hierarchy of networks. Our results suggest that hPCA can facilitate more detailed and comprehensive analyses of the brain's network of networks and the multiscale regional specializations underlying neural processing and cognition.

Mindfulness meditation modulates stress-eating and its neural correlates

Stress-related overeating can lead to excessive weight gain, increasing the risk of metabolic and cardiovascular disease. Mindfulness meditation has been demonstrated to reduce stress and increase interoceptive awareness and could, therefore, be an effective intervention for stress-related overeating behavior. To investigate the effects of mindfulness meditation on stress-eating behavior, meditation-naïve individuals with a tendency to stress-eat (N = 66) participated in either a 31-day, web-based mindfulness meditation training or a health training condition. Behavioral and resting-state fMRI data were acquired before and after the intervention. Mindfulness meditation training, in comparison to health training, was found to significantly increase mindfulness while simultaneously reducing stress- and emotional-eating tendencies as well as food cravings. These behavioral results were accompanied by functional connectivity changes between the hypothalamus, reward regions, and several areas of the default mode network in addition to changes observed between the insula and somatosensory areas. Additional changes between seed regions (i.e., hypothalamus and insula) and brain areas attributed to emotion regulation, awareness, attention, and sensory integration were observed. Notably, these changes in functional connectivity correlated with behavioral changes, thereby providing insight into the underlying neural mechanisms of the effects of mindfulness on stress-eating.Clinical trial on the ISRCTN registry: trial ID ISRCTN12901054.

Relationship between neuroimaging and emotion recognition in mild cognitive impairment patients

OBJECTIVE

Dementia is a major public health problem with high needs for early detection, efficient treatment, and prognosis evaluation. Social cognition impairment could be an early dementia indicator and can be assessed with emotion recognition evaluation tests. The purpose of this study is to investigate the link between different brain imaging modalities and cognitive status in Mild Cognitive Impairment (MCI) patients, with the goal of uncovering potential physiopathological mechanisms based on social cognition performance.

METHODS

The relationship between the Reading the Mind in the Eyes Test (RMET) and some clinical and biochemical variables ([18 F]FDG PET-CT and anatomical MR parameters, neuropsychological evaluation, and CSF biomarkers) was studied in 166 patients with MCI by using a correlational approach.

RESULTS

The RMET correlated with neuropsychological variables, as well as with structural and functional brain parameters obtained from the MR and FDG-PET imaging evaluation. However, significant correlations between the RMET and CSF biomarkers were not found.

DISCUSSION

Different neuroimaging parameters were found to be related to an emotion recognition task in MCI. This analysis identified potential minimally-invasive biomarkers providing some knowledge about the physiopathological mechanisms in MCI.

Developing a novel dual-injection FDG-PET imaging methodology to study the functional neuroanatomy of gait

Gait is an excellent indicator of physical, emotional, and mental health. Previous studies have shown that gait impairments in ageing are common, but the neural basis of these impairments are unclear. Existing methodologies are suboptimal and novel paradigms capable of capturing neural activation related to real walking are needed. In this study, we used a hybrid PET/MR system and measured glucose metabolism related to both walking and standing with a dual-injection paradigm in a single study session. For this study, 15 healthy older adults (10 females, age range: 60.5-70.7 years) with normal cognition were recruited from the community. Each participant received an intravenous injection of [18F]-2-fluoro-2-deoxyglucose (FDG) before engaging in two distinct tasks, a static postural control task (standing) and a walking task. After each task, participants were imaged. To discern independent neural functions related to walking compared to standing, we applied a bespoke dose correction to remove the residual 18F signal of the first scan (PETSTAND) from the second scan (PETWALK) and proportional scaling to the global mean, cerebellum, or white matter (WM). Whole-brain differences in walking-elicited neural activity measured with FDG-PET were assessed using a one-sample t-test. In this study, we show that a dual-injection paradigm in healthy older adults is feasible with biologically valid findings. Our results with a dose correction and scaling to the global mean showed that walking, compared to standing, increased glucose consumption in the cuneus (Z = 7.03), the temporal gyrus (Z = 6.91) and the orbital frontal cortex (Z = 6.71). Subcortically, we observed increased glucose metabolism in the supraspinal locomotor network including the thalamus (Z = 6.55), cerebellar vermis and the brainstem (pedunculopontine/mesencephalic locomotor region). Exploratory analyses using proportional scaling to the cerebellum and WM returned similar findings. Here, we have established the feasibility and tolerability of a novel method capable of capturing neural activations related to actual walking and extended previous knowledge including the recruitment of brain regions involved in sensory processing. Our paradigm could be used to explore pathological alterations in various gait disorders.

Performance on complex memory tests is associated with β-amyloid in individuals at risk of developing Alzheimer's disease

The pathophysiological development of Alzheimer's disease (AD) begins in the brain years before the onset of clinical symptoms. The accumulation of beta-amyloid (Aβ) is thought to be the first cortical pathology to occur. Carrying one apolipoprotein E (APOE) ε4 allele increases the risk of developing AD at least 2-3 times and is associated with earlier Aβ accumulation. Although it is difficult to identify Aβ-related cognitive impairment in early AD with standard cognitive tests, more sensitive memory tests may be able to do this. We sought to examine associations between Aβ and performance on three tests within three subdomains of memory, verbal, visual, and associative memory, to elucidate which of these tests were sensitive to Aβ-related cognitive impairment in at-risk subjects. 55 APOE ε4 carriers underwent MRI, 11 C-Pittsburgh Compound B (PiB) PET, and cognitive testing. A composite cortical PiB SUVR cut-off score of 1.5 was used to categorise subjects as either APOE ε4 Aβ+ or APOE ε4 Aβ-. Correlations were carried out using cortical surface analysis. In the whole APOE ε4 group, we found significant correlations between Aβ load and performance on verbal, visual, and associative memory tests in widespread cortical areas, the strongest association being with performance on associative memory tests. In the APOE ε4 Aβ+ group, we found significant correlations between Aβ load and performance of verbal and associative, but not visual, memory in localised cortical areas. Performance on verbal and associative memory tests provides sensitive markers of early Aβ-related cognitive impairment in at-risk subjects.

Atypical language organization following perinatal infarctions of the left hemisphere is associated with structural changes in right-hemispheric grey matter

AIM

To assess how atypical language organization after early left-hemispheric brain lesions affects grey matter in the contralesional hemisphere.

METHOD

This was a cross-sectional study with between-group comparisons of 14 patients (six female, 8-26 years) with perinatal left-hemispheric brain lesions (two arterial ischemic strokes, 11 periventricular haemorrhagic infarctions, one without classification) and 14 typically developing age-matched controls (TDC) with functional magnetic resonance imaging (fMRI) documented left-hemispheric language organization (six female, 8-28 years). MRI data were analysed with SPM12, CAT12, and custom scripts. Language lateralization indices were determined by fMRI within a prefrontal mask and right-hemispheric grey matter group differences by voxel-based morphometry (VBM).

RESULTS

FMRI revealed left-dominance in seven patients with typical language organization (TYP) and right-dominance in seven patients with atypical language organization (ATYP) of 14 patients. VBM analysis of all patients versus controls showed grey matter reductions in the middle temporal gyrus of patients. A comparison between the two patient subgroups revealed an increase of grey matter in the middle frontal gyrus in the ATYP group. Voxel-based regression analysis confirmed that grey matter increases in the middle frontal gyrus were correlated with atypical language organization.

INTERPRETATION

Compatible with a non-specific lesion effect, we found areas of grey matter reduction in patients as compared to TDC. The grey matter increase in the middle frontal gyrus seems to reflect a specific compensatory effect in patients with atypical language organization.

WHAT THIS PAPER ADDS

Perinatal stroke leads to decreased grey matter in the contralesional hemisphere. Atypical language organization is associated with grey matter increases in contralesional language areas.

Elevated Intraocular Pressure Moderated Brain Morphometry in High-tension Glaucoma: a Structural MRI Study

High-tension glaucoma (HTG) is one of the most common forms of primary open angle glaucoma. The purpose of this study was to assess in HTG brain, whether the elevated intraocular pressure (IOP) had an effect on the brain morphological alterations via structural MRI. We acquired T1WI structural MRI images from 56 subjects including 36 HTG patients and 20 healthy controls. We tested whether the brain morphometry was associated with the mean IOP in HTG patients. Moreover, we conducted moderation analysis to assess the interactions between subject type (HTG - healthy controls) and IOP. In HTG group, cortical thickness was negatively correlated with the mean IOP in the left rostral middle frontal gyrus, left pars triangularis, right precentral gyrus, left postcentral gyrus, left superior temporal gyrus (p < 0.05, FDR corrected). Four of the five regions negatively correlated with mean IOP showed reduced cortical thickness in HTG group compared with healthy controls, which were the left rostral middle frontal gyrus, left pars triangularis, left postcentral gyrus and left superior temporal gyrus (p < 0.05, FDR corrected). IOP moderated the interaction between subject type and cortical thickness of the left rostral middle frontal gyrus (p = 0.0017), left pars triangularis (p = 0.0011), left postcentral gyrus (p = 0.0040) and left superior temporal gyrus (p = 0.0066). Elevated IOP may result brain morphometry alterations such as cortical thinning. The relationship between IOP and brain morphometry underlines the importance of the IOP regulation for HTG patients.

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission

PURPOSE

Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA).

METHODS

FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level.

RESULTS

Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912).

CONCLUSION

Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.

VentRa: distinguishing frontotemporal dementia from psychiatric disorders

The volume of the lateral ventricles is a reliable and sensitive indicator of brain atrophy and disease progression in behavioural variant frontotemporal dementia. In this study, we validate our previously developed automated tool using ventricular features (known as VentRa) for the classification of behavioural variant frontotemporal dementia versus a mixed cohort of neurodegenerative, vascular and psychiatric disorders from a clinically representative independent dataset. Lateral ventricles were segmented for 1110 subjects-14 behavioural variant frontotemporal dementia, 30 other frontotemporal dementia, 70 Lewy body disease, 898 Alzheimer's disease, 62 vascular brain injury and 36 primary psychiatric disorder from the publicly accessible National Alzheimer's Coordinating Center dataset to assess the performance of VentRa. Using ventricular features to discriminate behavioural variant frontotemporal dementia subjects from primary psychiatric disorders, VentRa achieved an accuracy rate of 84%, a sensitivity rate of 71% and a specificity rate of 89%. VentRa was able to identify behavioural variant frontotemporal dementia from a mixed age-matched cohort (i.e. other frontotemporal dementia, Lewy body disease, Alzheimer's disease, vascular brain injury and primary psychiatric disorders) and to correctly classify other disorders as 'not compatible with behavioral variant frontotemporal dementia' with a specificity rate of 83%. The specificity rates against each of the other individual cohorts were 80% for other frontotemporal dementia, 83% for Lewy body disease, 83% for Alzheimer's disease, 84% for vascular brain injury and 89% for primary psychiatric disorders. VentRa is a robust and generalizable tool with potential usefulness for improving the diagnostic certainty of behavioural variant frontotemporal dementia, particularly for the differential diagnosis with primary psychiatric disorders.

Multi-scale V-net architecture with deep feature CRF layers for brain extraction

BACKGROUND

Brain extraction is a computational necessity for researchers using brain imaging data. However, the complex structure of the interfaces between the brain, meninges and human skull have not allowed a highly robust solution to emerge. While previous methods have used machine learning with structural and geometric priors in mind, with the development of Deep Learning (DL), there has been an increase in Neural Network based methods. Most proposed DL models focus on improving the training data despite the clear gap between groups in the amount and quality of accessible training data between.

METHODS

We propose an architecture we call Efficient V-net with Additional Conditional Random Field Layers (EVAC+). EVAC+ has 3 major characteristics: (1) a smart augmentation strategy that improves training efficiency, (2) a unique way of using a Conditional Random Fields Recurrent Layer that improves accuracy and (3) an additional loss function that fine-tunes the segmentation output. We compare our model to state-of-the-art non-DL and DL methods.

RESULTS

Results show that even with limited training resources, EVAC+ outperforms in most cases, achieving a high and stable Dice Coefficient and Jaccard Index along with a desirable lower Surface (Hausdorff) Distance. More importantly, our approach accurately segmented clinical and pediatric data, despite the fact that the training dataset only contains healthy adults.

CONCLUSIONS

Ultimately, our model provides a reliable way of accurately reducing segmentation errors in complex multi-tissue interfacing areas of the brain. We expect our method, which is publicly available and open-source, to be beneficial to a wide range of researchers.

EEG Frequency Correlates with α2-Receptor Density in Parkinson's Disease

INTRODUCTION

Increased theta and delta power and decreased alpha and beta power, measured with quantitative electroencephalography (EEG), have been demonstrated to have utility for predicting the development of dementia in patients with Parkinson's disease (PD). Noradrenaline modulates cortical activity and optimizes cognitive processes. We claim that the loss of noradrenaline may explain cognitive impairment and the pathological slowing of EEG waves. Here, we test the relationship between the number of noradrenergic α2 adrenoceptors and changes in the spectral EEG ratio in patients with PD.

METHODS

We included nineteen patients with PD and thirteen healthy control (HC) subjects in the study. We used positron emission tomography (PET) with [11C]yohimbine to quantify α2 adrenoceptor density. We used EEG power in the delta (δ, 1.5-3.9 Hz), theta (θ, 4-7.9 Hz), alpha (α, 8-12.9 Hz) and beta (β, 13-30 Hz) bands in regression analyses to test the relationships between α2 adrenoceptor density and EEG band power.

RESULTS

PD patients had higher power in the theta and delta bands compared to the HC volunteers. Patients' theta band power was inversely correlated with α2 adrenoceptor density in the frontal cortex. In the HC subjects, age was correlated with, and occipital background rhythm frequency (BRF) was inversely correlated with, α2 adrenoceptor density in the frontal cortex, while occipital BRF was inversely correlated with α2 adrenoceptor density in the thalamus.

CONCLUSIONS

The findings support the claim that the loss or dysfunction of noradrenergic neurotransmission may relate to the parallel processes of cognitive decline and EEG slowing.

A multicenter, single-arm, phase II clinical trial of adrenomedullin in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy

Background

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), the most common form of hereditary cerebral small vessel disease (SVD), currently lacks disease-modifying treatments. Adrenomedullin (AM), a vasoactive peptide with angiogenic, vasodilatory, anti-inflammatory, and anti-oxidative properties, shows potential effects on the neuro-glial-vascular unit.

Objective

The AdrenoMedullin for CADASIL (AMCAD) study aims to assess the efficacy and safety of AM in patients with CADASIL.

Sample size

Overall, 60 patients will be recruited.

Methods

The AMCAD is a multicenter, investigator-initiated, single-arm phase II trial. Patients with a confirmed CADASIL diagnosis, based on NOTCH3 genetic testing, will receive an 8-h AM treatment (15 ng/kg/min) for 14 days following a baseline assessment (from day 1 to day 14). Follow-up evaluations will be performed on days 15, 28, 90, and 180.

Study outcomes

The primary endpoint is the cerebral blood flow change rate in the frontal cortex, evaluated using arterial spin labeling magnetic resonance imaging, from baseline to day 28. Summary statistics, 95% confidence intervals, and a one-sample t-test will be used for analysis.

Conclusion

The AMCAD study aims to represent the therapeutic potential of AM in patients with CADASIL, addressing an unmet medical need in this challenging condition.

Clinical Trial Registration

jRCT 2,051,210,117 (https://jrct.niph.go.jp/en-latest-detail/jRCT2051210117).

Cortical and subcortical morphometric changes and their relation to cognitive impairment in isolated REM sleep behavior disorder

OBJECTIVE

To date, very few studies have focused on structural changes and their association with cognitive performance in isolated REM sleep behaviour disorder (iRBD). Moreover, the results of these studies are inconclusive. This study aims to evaluate differences in the associations between brain morphology and cognitive tests in iRBD and healthy controls.

METHODS

Sixty-three patients with iRBD and thirty-six controls underwent MRI with a 3 T scanner. The cognitive performance was assessed by a comprehensive neuropsychological battery. Based on performance, the iRBD group was divided into two subgroups with (iRBD-MCI) and without mild cognitive impairment (iRBD-NC). The high-resolution T1-weighted images were analysed using an automated atlas segmentation tool, voxel-based (VBM) and deformation-based (DBM) morphometry to identify between-group differences and correlations with cognitive performance.

RESULTS

VBM, DBM and the comparison of ROI volumes yielded no significant differences between iRBD and controls. In the iRBD group, significant correlations in VBM were found between several cortical and subcortical structures primarily located in the temporal, parietal, occipital lobe, cerebellum, and basal ganglia and three cognitive tests assessing psychomotor speed and one memory test. Between-group analysis of cognition revealed a significant difference between iRBD-MCI and iRBD-NC in tests including a processing speed component.

CONCLUSIONS

iRBD shows deficits in several cognitive tests that correlate with morphological changes, the most prominent of which is in psychomotor speed and visual attention as measured by the TMT-A and associated with the volume of striatum, insula, cerebellum, temporal lobe, pallidum and amygdala.

Differences in Alzheimer's Disease-Related Pathology Profiles Across Apolipoprotein Groups

The apolipoprotein (APOE) ɛ4 allele is a risk factor for Alzheimer's disease (AD), whereas the ɛ2 allele is thought to be protective against AD. Few studies have examined the relationship between brain pathologies, atrophy, white matter hyperintensities (WMHs) and APOE status in those with the ɛ2ɛ4 genotype and results are inconsistent for those with an ɛ2 allele. Alzheimer's disease neuroimaging participants were divided into 1 of 4 APOE allele profiles (E4 = ɛ4ɛ4 or ɛ3ɛ4; E2 = ɛ2ɛ2 or ɛ2ɛ3; E3 = ɛ3ɛ3; or E24 = ɛ2ɛ4). Linear mixed models examined the relationship between APOE profiles and brain changes (i.e., regional WMHs, ventricle size, hippocampal and entorhinal cortex volume, amyloid level, and phosphorylated tau measures), while controlling for age, sex, education, and diagnostic status at baseline and over time. APOE ɛ4 was associated with increased pathology, whereas ɛ2 positivity is associated with reduced baseline and lower accumulation of pathologies and neurodegeneration. APOE ɛ2ɛ4 was similar to ɛ4 (increased neurodegeneration) but with a slower rate of change. The strong associations observed between APOE and pathology show the importance of how genetic factors influence structural brain changes. These findings suggest that ɛ2ɛ4 genotype is related to increased declines associated with the ɛ4 as opposed to the protective effects of the ɛ2. These findings have important implications for initiating treatments and interventions. Given that people with the ɛ2ɛ4 genotype can expect to have increased atrophy, they should be considered (alongside those with an ɛ4) in targeted interventions to reduce brain changes that occur with AD.

Abnormal functional neurocircuitry underpinning emotional processing in fibromyalgia

Fibromyalgia, a condition characterized by chronic pain, is frequently accompanied by emotional disturbances. Here we aimed to study brain activation and functional connectivity (FC) during processing of emotional stimuli in fibromyalgia. Thirty female patients with fibromyalgia and 31 female healthy controls (HC) were included. Psychometric tests were administered to measure alexithymia, affective state, and severity of depressive and anxiety symptoms. Next, participants performed an emotion processing and regulation task during functional magnetic resonance imaging (fMRI). We performed a 2 × 2 ANCOVA to analyze main effects and interactions of the stimuli valence (positive or negative) and group (fibromyalgia or HC) on brain activation. Generalized psychophysiological interaction analysis was used to assess task-dependent FC of brain regions previously associated with emotion processing and fibromyalgia (i.e., hippocampus, amygdala, anterior insula, and pregenual anterior cingulate cortex [pACC]). The left superior lateral occipital cortex showed more activation in fibromyalgia during emotion processing than in HC, irrespective of valence. Moreover, we found an interaction effect (valence x group) in the FC between the left pACC and the precentral and postcentral cortex, and central operculum, and premotor cortex. These results suggest abnormal brain activation and connectivity underlying emotion processing in fibromyalgia, which could help explain the high prevalence of psychopathological symptoms in this condition.

Evaluation of Non-Invasive Methods for (R)-[11C]PK11195 PET Image Quantification in Multiple Sclerosis

This study aims to evaluate non-invasive PET quantification methods for (R)-[11C]PK11195 uptake measurement in multiple sclerosis (MS) patients and healthy controls (HC) in comparison with arterial input function (AIF) using dynamic (R)-[11C]PK11195 PET and magnetic resonance images. The total volume of distribution (VT) and distribution volume ratio (DVR) were measured in the gray matter, white matter, caudate nucleus, putamen, pallidum, thalamus, cerebellum, and brainstem using AIF, the image-derived input function (IDIF) from the carotid arteries, and pseudo-reference regions from supervised clustering analysis (SVCA). Uptake differences between MS and HC groups were tested using statistical tests adjusted for age and sex, and correlations between the results from the different quantification methods were also analyzed. Significant DVR differences were observed in the gray matter, white matter, putamen, pallidum, thalamus, and brainstem of MS patients when compared to the HC group. Also, strong correlations were found in DVR values between non-invasive methods and AIF (0.928 for IDIF and 0.975 for SVCA, p < 0.0001). On the other hand, (R)-[11C]PK11195 uptake could not be differentiated between MS patients and HC using VT values, and a weak correlation (0.356, p < 0.0001) was found between VTAIF and VTIDIF. Our study shows that the best alternative for AIF is using SVCA for reference region modeling, in addition to a cautious and appropriate methodology.

Hand function after neonatal stroke: A graph model based on basal ganglia and thalami structure

INTRODUCTION

Neonatal arterial ischemic stroke (NAIS) is a common model to study the impact of a unilateral early brain insult on developmental brain plasticity and the appearance of long-term outcomes. Motor difficulties that may arise are typically related to poor function of the affected (contra-lesioned) hand, but surprisingly also of the ipsilesional hand. Although many longitudinal studies after NAIS have shown that predicting the occurrence of gross motor difficulties is easier, accurately predicting hand motor function (for both hands) from morphometric MRI remains complicated. The hypothesis of an association between the structural organization of the basal ganglia (BG) and thalamus with hand motor function seems intuitive given their key role in sensorimotor function. Neuroimaging studies have frequently investigated these structures to evaluate the correlation between their volumes and motor function following early brain injury. However, the results have been controversial. We hypothesize the involvement of other structural parameters.

METHOD

The study involves 35 children (mean age 7.3 years, SD 0.4) with middle cerebral artery NAIS who underwent a structural T1-weighted 3D MRI and clinical examination to assess manual dexterity using the Box and Blocks Test (BBT). Graphs are used to represent high-level structural information of the BG and thalami (volumes, elongations, distances) measured from the MRI. A graph neural network (GNN) is proposed to predict children's hand motor function through a graph regression. To reduce the impact of external factors on motor function (such as behavior and cognition), we calculate a BBT score ratio for each child and hand.

RESULTS

The results indicate a significant correlation between the score ratios predicted by our method and the actual score ratios of both hands (p < 0.05), together with a relatively high accuracy of prediction (mean L1 distance < 0.03). The structural information seems to have a different influence on each hand's motor function. The affected hand's motor function is more correlated with the volume, while the 'unaffected' hand function is more correlated with the elongation of the structures. Experiments emphasize the importance of considering the whole macrostructural organization of the basal ganglia and thalami networks, rather than the volume alone, to predict hand motor function.

CONCLUSION

There is a significant correlation between the structural characteristics of the basal ganglia/thalami and motor function in both hands. These results support the use of MRI macrostructural features of the basal ganglia and thalamus as an early biomarker for predicting motor function in both hands after early brain injury.

Volume-based and Surface-Based Methods in Autism Compared with Healthy Controls Are Free surfer and CAT12 in Agreement?

Objectives

Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental disorders, and early detection is crucial. This study aims to identify the Regions of Interest (ROIs) with significant differences between healthy controls and individuals with autism, as well as evaluate the agreement between FreeSurfer 6 (FS6) and Computational Anatomy Toolbox (CAT12) methods.

Materials & Methods

Surface-based and volume-based features were extracted from FS software and CAT12 toolbox for Statistical Parametric Mapping (SPM) software to estimate ROI-wise biomarkers. These biomarkers were compared between 18 males Typically Developing Controls (TDCs) and 40 male subjects with ASD to assess group differences for each method. Finally, agreement and regression analyses were performed between the two methods for TDCs and ASD groups.

Results

Both methods revealed ROIs with significant differences for each parameter. The Analysis of Covariance (ANCOVA) showed that both TDCs and ASD groups indicated a significant relationship between the two methods (p<0.001). The R2 values for TDCs and ASD groups were 0.692 and 0.680, respectively, demonstrating a moderate correlation between CAT12 and FS6. Bland-Altman graphs showed a moderate level of agreement between the two methods.

Conclusion

The moderate correlation and agreement between CAT12 and FS6 suggest that while some consistency is observed in the results, CAT12 is not a superior substitute for FS6 software. Further research is needed to identify a potential replacement for this method.

Flow-augmentation STA-MCA bypass for acute and subacute ischemic stroke due to internal carotid artery occlusion and the role of advanced neuroimaging with hemodynamic and flow-measurement in the decision-making: preliminary data

Background

A major clinical challenge is the adequate identification of patients with acute (<1 week) and subacute (1-6 weeks) ischemic stroke due to internal carotid artery (ICA) occlusion who could benefit from a surgical revascularization after a failure of endovascular and/or medical treatment. Recently, two novel quantitative imaging modalities have been introduced: (I) quantitative magnetic resonance angiography (qMRA) with non-invasive optimal vessel analysis (NOVA) for quantification of blood flow in major cerebral arteries (in mL/min), and (II) blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging to assess cerebrovascular reactivity (CVR). The aim of this study is to present our cohort of patients who underwent surgical revascularization in the acute and subacute phase of ischemic stroke as well as to demonstrate the importance of hemodynamic and flow assessment for the decision-making regarding surgical revascularization in patients with acute and subacute stroke and ICA-occlusion.

Methods

Symptomatic patients with acute and subacute ischemic stroke because of persistent ICA-occlusion despite optimal medical/endovascular recanalization therapy who were treated at the Neuroscience Clinical Center of the University Hospital Zurich underwent both BOLD-CVR and qMRA-NOVA to study the hemodynamic and collateral vessel status. Patients selected for surgical revascularization according to our previously published flowchart were included in this prospective cohort study. Repeated NOVA and BOLD-CVR investigations were done after bypass surgery as follow up as well as clinical follow up. Continuous BOLD-CVR and qMRA-NOVA variables were compared using paired Student t-test.

Results

Between May 2019 and September 2022, superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery was performed in 12 patients with acute and subacute stroke because of ICA-occlusion despite of optimal endovascular and/or medical treatment prior to the surgery. Impaired BOLD-CVR in the occluded vascular territory [MCA territory: ipsilateral vs. contralateral: -0.03±0.07 vs. 0.11±0.07 %BOLD/mmHgCO2, P<0.001] as well as reduced hemispheric flow with qMRA-NOVA (ipsilateral vs. contralateral: 228.00±54.62 vs. 384.50±70.99 mL/min, P=0.01) were measured indicating insufficient collateralization. Post-operative qMRA-NOVA showed improved hemispheric flow (via bypass) (pre-bypass vs. post-bypass: 236.60±76.45 vs. 334.20±131.33 mL/min, P=0.02) and the 3-month-follow-up with BOLD-CVR showed improved cerebral hemodynamics (MCA territory: pre-bypass vs. post-bypass: -0.01±0.05 vs. 0.06±0.03 %BOLD/mmHgCO2, P=0.02) in all patients studied.

Conclusions

Quantitative assessment with BOLD-CVR and qMRA-NOVA allows us to evaluate the pre- and post-operative cerebral hemodynamics and collateral vessel status in patients with acute/subacute stroke due to ICA occlusion who may benefit from surgical revascularization after failure of endovascular/medical treatment.

Lower cerebral blood flow predicts cognitive decline in patients with vascular cognitive impairment

INTRODUCTION

Chronic cerebral hypoperfusion is one of the assumed pathophysiological mechanisms underlying vascular cognitive impairment (VCI). We investigated the association between baseline cerebral blood flow (CBF) and cognitive decline after 2 years in patients with VCI and reference participants.

METHODS

One hundred eighty-one participants (mean age 66.3 ± 7.4 years, 43.6% women) underwent arterial spin labeling (ASL) magnetic resonance imaging (MRI) and neuropsychological assessment at baseline and at 2-year follow-up. We determined the association between baseline global and lobar CBF and cognitive decline with multivariable regression analysis.

RESULTS

Lower global CBF at baseline was associated with more global cognitive decline in VCI and reference participants. This association was most profound in the domain of attention/psychomotor speed. Lower temporal and frontal CBF at baseline were associated with more cognitive decline in memory.

DISCUSSION

Our study supports the role of hypoperfusion in the pathophysiological and clinical progression of VCI.

HIGHLIGHTS

Impaired cerebral blood flow (CBF) at baseline is associated with faster cognitive decline in VCI and normal aging. Our results suggest that low CBF precedes and contributes to the development of vascular cognitive impairment. CBF determined by ASL might be used as a biomarker to monitor disease progression or treatment responses in VCI.

High-Frequency Hearing Loss, Hippocampal Volume, and Motoric Cognitive Risk Syndrome in Older Adults in China: A Population-Based Study

Background

Little is known about the associations of hearing loss, hippocampal volume, and motoric cognitive risk syndrome (MCR) in older adults.

Objective

We aimed to investigate the associations of hearing loss with MCR and hippocampal volume; and the interaction of hearing loss with hippocampal volume on MCR.

Methods

This population-based cross-sectional study included 2,540 dementia-free participants (age≥60 years; 56.5% women) in the baseline examination of the Multimodal Interventions to Delay Dementia and Disability in rural China. Data were collected through face-to-face interviews, clinical examination, and laboratory tests. Hearing function was assessed using pure tone audiometry test. In the subsample (n = 661), hippocampal volume was assessed on structural magnetic resonance images. Data were analyzed with logistic regression models.

Results

In the total sample, MCR was diagnosed in 246 persons (9.7%). High-frequency hearing loss was significantly associated with an increased likelihood of MCR and slow gait. In the subsample, the restricted cubic spline plots indicated an inverted U-shaped nonlinear relationship between high-frequency hearing performance and hippocampal volume. Moreover, greater hippocampal volume was significantly associated with a deduced likelihood of MCR and subjective cognitive decline (SCD). In addition, there were statistical interactions of high-frequency hearing loss with hippocampal volume on MCR and slow gait (p for interaction < 0.05), such that the associations were statistically significant only among participants free of high-frequency hearing loss.

Conclusions

High-frequency hearing loss was associated with an increased likelihood of MCR in older adults. The hippocampus might play a part in the relationship of high-frequency hearing loss and MCR.

Unraveling glioblastoma diversity: Insights into methylation subtypes and spatial relationships

Background

The purpose of this study was to elucidate the relationship between distinct brain regions and molecular subtypes in glioblastoma (GB), focusing on integrating modern statistical tools and molecular profiling to better understand the heterogeneity of Isocitrate Dehydrogenase wild-type (IDH-wt) gliomas.

Methods

This retrospective study comprised 441 patients diagnosed with new IDH-wt glioma between 2009 and 2020 at Heidelberg University Hospital. The diagnostic process included preoperative magnetic resonance imaging and molecular characterization, encompassing IDH-status determination and subclassification, through DNA-methylation profiling. To discern and map distinct brain regions associated with specific methylation subtypes, a support-vector regression-based lesion-symptom mapping (SVR-LSM) was employed. Lesion maps were adjusted to 2 mm³ resolution. Significance was assessed with beta maps, using a threshold of P < .005, with 10 000 permutations and a cluster size minimum of 100 voxels.

Results

Of 441 initially screened glioma patients, 423 (95.9%) met the inclusion criteria. Following DNA-methylation profiling, patients were classified into RTK II (40.7%), MES (33.8%), RTK I (18%), and other methylation subclasses (7.6%). Between molecular subtypes, there was no difference in tumor volume. Using SVR-LSM, distinct brain regions correlated with each subclass were identified: MES subtypes were associated with left-hemispheric regions involving the superior temporal gyrus and insula cortex, RTK I with right frontal regions, and RTK II with 3 clusters in the left hemisphere.

Conclusions

This study linked molecular diversity and spatial features in glioblastomas using SVR-LSM. Future studies should validate these findings in larger, independent cohorts to confirm the observed patterns.

Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach

The recent progress in the development of in vivo biomarkers is rapidly changing how neurodegenerative diseases are conceptualized and diagnosed and how clinical trials are designed today. Alzheimer's disease (AD) - the most common neurodegenerative disorder - is characterized by a complex neuropathology involving the deposition of extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles (NFTs) of hyperphosphorylated tau proteins, accompanied by the activation of glial cells, i.e., astrocytes and microglia, and neuroinflammatory response, leading to neurodegeneration and cognitive dysfunction. An increasing diversity of positron emission tomography (PET) imaging radiotracers is available to selectively target the different pathophysiological processes of AD. Along with the success of Aβ PET and the more recent tau PET imaging, there is a great interest to develop PET tracers to image glial reactivity and neuroinflammation. While most research to date has focused on imaging microgliosis, there is an upsurge of interest in imaging reactive astrocytes in the AD continuum. There is increasing evidence that reactive astrocytes are morphologically and functionally heterogeneous, with different subtypes that express different markers and display various homeostatic or detrimental roles across disease stages. Therefore, multiple biomarkers are desirable to unravel the complex phenomenon of reactive astrocytosis. In the field of in vivo PET imaging in AD, the research concerning reactive astrocytes has predominantly focused on targeting monoamine oxidase B (MAO-B), most often using either 11C-deuterium-L-deprenyl (11C-DED) or 18F-SMBT-1 PET tracers. Additionally, imidazoline2 binding (I2BS) sites have been imaged using 11C-BU99008 PET. Recent studies in our group using 11C-DED PET imaging suggest that astrocytosis may be present from the early stages of disease development in AD. This chapter provides a detailed description of the practical approach used for the analysis of 11C-DED PET imaging data in a multitracer PET paradigm including 11C-Pittsburgh compound B (11C-PiB) and 18F-fluorodeoxyglucose (18F-FDG). The multitracer PET approach allows investigating the comparative regional and temporal patterns of in vivo brain astrocytosis, fibrillar Aβ deposition, glucose metabolism, and brain structural changes. It may also contribute to understanding the potential role of novel plasma biomarkers of reactive astrocytes, in particular the glial fibrillary acidic protein (GFAP), at different stages of disease progression. This chapter attempts to stimulate further research in the field, including the development of novel PET tracers that may allow visualizing different aspects of the complex astrocytic and microglial response in neurodegenerative diseases. Progress in the field will contribute to the incorporation of PET imaging of glial reactivity and neuroinflammation as biomarkers with clinical application and motivate further investigation on glial cells as therapeutic targets in AD and other neurodegenerative diseases.

Do Tau Deposition and Glucose Metabolism Dissociate in Alzheimer's Disease Trajectory?

Background

Tau aggregation demonstrates close associations with hypometabolism in Alzheimer's disease (AD), although differing pathophysiological processes may underlie their development.

Objective

To establish whether tau deposition and glucose metabolism have different trajectories in AD progression and evaluate the utility of global measures of these pathological hallmarks in predicting cognitive deficits.

Methods

279 participants with amyloid-β (Aβ) status, and T1-weighted MRI scans, were selected from the Alzheimer's Disease Neuroimaging Initiative (http://adni.loni.usc.edu). We created the standard uptake value ratio images using Statistical Parametric Mapping 12 for [18F]AV1451-PET (tau) and [18F]FDG-PET (glucose metabolism) scans. Voxel-wise group and single-subject level SPM analysis evaluated the relationship between global [18F]FDG-PET and [18F]AV1451-PET depending on the Aβ status. Linear models assessed whether tau deposition or glucose metabolism better predicted clinical progression.

Results

There was a dissociation between global cerebral glucose hypometabolism and global tau load in amyloid-positive AD and amyloid-negative mild cognitive impairment (MCI) (p > 0.05). Global hypometabolism was only associated with global cortical tau in amyloid-positive MCI. Voxel-level single subject tau load better predicted neuropsychological performance, Alzheimer's disease assessment scale-cognitive (ADAS-Cog) 13 score, and one-year change compared with regional and global hypometabolism.

Conclusions

A dissociation between tau pathology and glucose metabolism at a global level in AD could imply that other pathological processes influence glucose metabolism. Furthermore, as tau is a better predictor of clinical progression, these processes may have independent trajectories and require independent consideration in the context of therapeutic interventions.

Sex differences in risk factors, burden, and outcomes of cerebrovascular disease in Alzheimer's disease populations

BACKGROUND

White matter hyperintensities (WMHs) are associated with cognitive decline and progression to mild cognitive impairment (MCI) and dementia. It remains unclear if sex differences influence WMH progression or the relationship between WMH and cognition.

METHODS

Linear mixed models examined the relationship between risk factors, WMHs, and cognition in males and females.

RESULTS

Males exhibited increased WMH progression in occipital, but lower progression in frontal, total, and deep than females. For males, history of hypertension was the strongest contributor, while in females, the vascular composite was the strongest contributor to WMH burden. WMH burden was more strongly associated with decreases in global cognition, executive functioning, memory, and functional activities in females than males.

DISCUSSION

Controlling vascular risk factors may reduce WMH in both males and females. For males, targeting hypertension may be most important to reduce WMHs. The results have implications for therapies/interventions targeting cerebrovascular pathology and subsequent cognitive decline.

HIGHLIGHTS

Hypertension is the main vascular risk factor associated with WMH in males A combination of vascular risk factors contributes to WMH burden in females Only small WMH burden differences were observed between sexes Females' cognition was more negatively impacted by WMH burden than males Females with WMHs may have less resilience to future pathology.

Improved myelin water fraction mapping with deep neural networks using synthetically generated 3D data

We introduce a generative model for synthesis of large scale 3D datasets for quantitative parameter mapping of myelin water fraction (MWF). Our model combines a MR physics signal decay model with an accurate probabilistic multi-component parametric T2 model. We synthetically generate a wide variety of high quality signals and corresponding parameters from a wide range of naturally occurring prior parameter values. To capture spatial variation, the generative signal decay model is combined with a generative spatial model conditioned on generic tissue segmentations. Synthesized 3D datasets can be used to train any convolutional neural network (CNN) based architecture for MWF estimation. Our source code is available at: https://github.com/quin-med-harvard-edu/synthmap Reduction of acquisition time at the expense of lower SNR, as well as accuracy and repeatability of MWF estimation techniques, are key factors that affect the adoption of MWF mapping in clinical practice. We demonstrate that the synthetically trained CNN provides superior accuracy over the competing methods under the constraints of naturally occurring noise levels as well as on the synthetically generated images at low SNR levels. Normalized root mean squared error (nRMSE) is less than 7% on synthetic data, which is significantly lower than competing methods. Additionally, the proposed method yields a coefficient of variation (CoV) that is at least 4x better than the competing method on intra-session test-retest reference dataset.