GANDALF: Generative Adversarial Networks with Discriminator-Adaptive Loss Fine-tuning for Alzheimer's Disease Diagnosis from MRI

Positron Emission Tomography (PET) is now regarded as the gold standard for the diagnosis of Alzheimer's Disease (AD). However, PET imaging can be prohibitive in terms of cost and planning, and is also among the imaging techniques with the highest dosage of radiation. Magnetic Resonance Imaging (MRI), in contrast, is more widely available and provides more flexibility when setting the desired image resolution. Unfortunately, the diagnosis of AD using MRI is difficult due to the very subtle physiological differences between healthy and AD subjects visible on MRI. As a result, many attempts have been made to synthesize PET images from MR images using generative adversarial networks (GANs) in the interest of enabling the diagnosis of AD from MR. Existing work on PET synthesis from MRI has largely focused on Conditional GANs, where MR images are used to generate PET images and subsequently used for AD diagnosis. There is no end-to-end training goal. This paper proposes an alternative approach to the aforementioned, where AD diagnosis is incorporated in the GAN training objective to achieve the best AD classification performance. Different GAN lossesare fine-tuned based on the discriminator performance, and the overall training is stabilized. The proposed network architecture and training regime show state-of-the-art performance for three- and four- class AD classification tasks.Comment: Accepted for publication at the MICCAI 2020 conferenc

Geometric Convolutional Neural Network for Analyzing Surface-Based Neuroimaging Data

The conventional CNN, widely used for two-dimensional images, however, is not directly applicable to non-regular geometric surface, such as a cortical thickness. We propose Geometric CNN (gCNN) that deals with data representation over a spherical surface and renders pattern recognition in a multi-shell mesh structure. The classification accuracy for sex was significantly higher than that of SVM and image based CNN. It only uses MRI thickness data to classify gender but this method can expand to classify disease from other MRI or fMRI dataComment: 29 page

[18F]AV-1451 binding in vivo mirrors the expected distribution of TDP-43 pathology in the semantic variant of primary progressive aphasia

Introduction Semantic dementia, including the semantic variant of primary progressive aphasia (svPPA), is strongly associated with TAR-DNA binding protein 43 (TDP-43) type C pathology. It provides a useful model in which to test the specificity of in vivo binding of the putative tau ligand [18F]AV-1451, which is elevated in frontotemporal lobar degeneration tauopathies. Methods and results Seven patients (five with svPPA and two with ‘right’ semantic dementia) and 12 healthy controls underwent positron emission tomography brain imaging with [18F]AV-1451. Two independent preprocessing methods were used. For both methods, all patients had clearly elevated binding potential (BPND (non-displaceable binding potential)) in temporal lobes, lateralising according to their clinical syndrome and evident in raw images. Region of interest analyses confirmed that BPND was significantly increased in temporal regions, insula and fusiform gyrus, consistent with those areas known to be most affected in semantic dementia. Hierarchical cluster analysis, based on the distribution of [18F]AV-1451 binding potential, separated semantic dementia from controls with 86% sensitivity and 100% specificity. Conclusions [18F]AV-1451 binds in vivo regions that are likely to contain TDP-43 and not significant tau pathology. While this suggests a non-tau target for [18F]AV-1451, the pathological regions in semantic dementia do not normally contain significant levels of recently proposed ‘off target’ binding sites for [18F]AV-1451, such as neuronal monoamine oxidase or neuromelanin. Postmortem and longitudinal data will be useful to assess the utility of [18F]AV-1451 to differentiate and track different types of frontotemporal lobar degeneration.This work was supported by the National Institute for Health Research Biomedical Research Centre and Biomedical Research Unit in Dementia; the Wellcome Trust (JBR 103838); the Association of British Neurologists and the Patrick Berthoud Charitable Trust (TEC)

Tau and atrophy: domain-specific relationships with cognition.

BackgroundLate-onset Alzheimer's disease (AD) is characterized by primary memory impairment, which then progresses towards severe deficits across cognitive domains. Here, we report how performance in cognitive domains relates to patterns of tau deposition and cortical thickness.MethodsWe analyzed data from 131 amyloid-β positive participants (55 cognitively normal, 46 mild cognitive impairment, 30 AD) of the Alzheimer's Disease Neuroimaging Initiative who underwent magnetic resonance imaging (MRI), flortaucipir (FTP) positron emission tomography, and neuropsychological testing. Surface-based vertex-wise and region-of-interest analyses were conducted between FTP and cognitive test scores, and between cortical thickness and cognitive test scores.ResultsFTP and thickness were differentially related to cognitive performance in several domains. FTP-cognition associations were more widespread than thickness-cognition associations. Further, FTP-cognition patterns reflected cortical systems that underlie different aspects of cognition.ConclusionsOur findings indicate that AD-related decline in domain-specific cognitive performance reflects underlying progression of tau and atrophy into associated brain circuits. They also suggest that tau-PET may have better sensitivity to this decline than MRI-derived measures of cortical thickness

PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets, serving not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data, also known as PET-BIDS, and share several open-access datasets curated following PET-BIDS along with tools for conversion, validation and analysis of PET-BIDS datasets

Obesity impacts brain metabolism and structure independently of amyloid and tau pathology in healthy elderly

Altres ajuts: This study was supported by [...], and the CIBERNED program (Program 1, Alzheimer Disease to Alberto Lleó and SIGNAL study, www.signalstudy.es); and partly jointly funded by Fondo Europeo de Desarrollo Regional, Unión Europea, Una manera de hacer Europa. This work was also supported by the National Institutes of Health (NIA grants 1R01AG056850 - 01A1; R21AG056974, and R01AG061566 to Juan Fortea), Fundació La Marató de TV3 (20141210 to Juan Fortea, 044412 to Amanda Jiménez and Rafael Blesa). This work was also supported by [...] and a grant from the Fundació Bancaria La Caixa to Rafael Blesa. The work of Adriana Pané is supported by the " Ajut a la Recerca Josep Font" (Hospital Clinic de Barcelona). Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). [...]. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org).Midlife obesity is a risk factor for dementia. We investigated the impact of obesity on brain structure, metabolism, and cerebrospinal fluid (CSF) core Alzheimer's disease (AD) biomarkers in healthy elderly. We selected controls from ADNI2 with CSF AD biomarkers and/or fluorodeoxyglucose positron emission tomography (FDG-PET) and 3T-MRI. We measured cortical thickness, FDG uptake, and CSF amyloid beta (Aβ)1-42, p-tau, and t-tau levels. We performed regression analyses between these biomarkers and body mass index (BMI). We included 201 individuals (mean age 73.5 years, mean BMI 27.4 kg/m 2). Higher BMI was related to less cortical thickness and higher metabolism in brain areas typically not involved in AD (family-wise error [FWE] <0.05), but not to AD CSF biomarkers. It is notable that the impact of obesity on brain metabolism and structure was also found in amyloid negative individuals. In the cognitively unimpaired elderly, obesity has differential effects on brain metabolism and structure independent of an underlying AD pathophysiology

Brain serotonin 4 receptor binding is inversely associated with verbal memory recall

BACKGROUND: We have previously identified an inverse relationship between cerebral serotonin 4 receptor (5‐HT (4)R) binding and nonaffective episodic memory in healthy individuals. Here, we investigate in a novel sample if the association is related to affective components of memory, by examining the association between cerebral 5‐HT (4)R binding and affective verbal memory recall. METHODS: Twenty‐four healthy volunteers were scanned with the 5‐HT (4)R radioligand [(11)C]SB207145 and positron emission tomography, and were tested with the Verbal Affective Memory Test‐24. The association between 5‐HT (4)R binding and affective verbal memory was evaluated using a linear latent variable structural equation model. RESULTS: We observed a significant inverse association across all regions between 5‐HT (4)R binding and affective verbal memory performances for positive (p = 5.5 × 10(−4)) and neutral (p = .004) word recall, and an inverse but nonsignificant association for negative (p = .07) word recall. Differences in the associations with 5‐HT (4)R binding between word categories (i.e., positive, negative, and neutral) did not reach statistical significance. CONCLUSION: Our findings replicate our previous observation of a negative association between 5‐HT (4)R binding and memory performance in an independent cohort and provide novel evidence linking 5‐HT (4)R binding, as a biomarker for synaptic 5‐HT levels, to the mnestic processing of positive and neutral word stimuli in healthy humans

High brain serotonin levels in migraine between attacks:A 5-HT₄ receptor binding PET study

Migraine has been hypothesized to be a syndrome of chronic low serotonin (5-HT) levels, but investigations of brain 5-HT levels have given equivocal results. Here, we used positron emission tomography (PET) imaging of the 5-HT4 receptor as a proxy for brain 5-HT levels. Given that the 5-HT4 receptor is inversely related to brain 5-HT levels, we hypothesized that between attacks migraine patients would have higher 5-HT4 receptor binding compared to controls. Eighteen migraine patients without aura (migraine free >48 h), and 16 age- and sex-matched controls underwent PET scans after injection of [11C]SB207145, a specific 5-HT4 receptor radioligand. An investigator blinded to group calculated a neocortical mean [11C]SB207145 binding potential (BPND). Three migraine patients reported a migraine attack within 48 h after the scan and were excluded from the primary analysis. Comparing 15 migraine patients and 16 controls, we found that migraine patients have significantly lower neocortical 5-HT4 receptor binding than controls (0.60 ± 0.09 vs. 0.67 ± 0.05, p = .024), corrected for 5-HTTLPR genotype, sex and age. We found no association between 5-HT4 receptor binding and attack frequency, years with migraine or time since last migraine attack. Our finding of lower 5-HT4 receptor binding in migraine patients is suggestive of higher brain 5-HT levels. This is in contrast with the current belief that migraine is associated with low brain 5-HT levels. High brain 5-HT levels may represent a trait of the migraine brain or it could be a consequence of migraine attacks. Keywords: Headache, Pain, Neuroimaging, Brain, Serotonergic mechanism