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Vascular contribution to cognitive impairment (VCI) and dementia is related to etiologies that may affect the neurophysiological mechanisms regulating brain arousal and generating electroencephalographic (EEG) activity. A multidisciplinary expert panel reviewed the clinical literature and reached consensus about the EEG measures consistently found as abnormal in VCI patients with dementia. As compared to cognitively unimpaired individuals, those VCI patients showed (1) smaller amplitude of resting state alpha (8-12 Hz) rhythms dominant in posterior regions; (2) widespread increases in amplitude of delta (< 4 Hz) and theta (4-8 Hz) rhythms; and (3) delayed N200/P300 peak latencies in averaged event-related potentials, especially during the detection of auditory rare target stimuli requiring participants' responses in "oddball" paradigms. The expert panel formulated the following recommendations: (1) the above EEG measures are not specific for VCI and should not be used for its diagnosis; (2) they may be considered as "neural synchronization" biomarkers to enlighten the relationships between features of the VCI-related cerebrovascular lesions and abnormalities in neurophysiological brain mechanisms; and (3) they may be tested in future clinical trials as prognostic biomarkers and endpoints of interventions aimed at normalizing background brain excitability and vigilance in wakefulness., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objective: This retrospective and exploratory study tested the accuracy of artificial neural networks (ANNs) at detecting Alzheimer's disease patients with dementia (ADD) based on input variables extracted from resting-state electroencephalogram (rsEEG), structural magnetic resonance imaging (sMRI) or both., Methods: For the classification exercise, the ANNs had two architectures that included stacked (autoencoding) hidden layers recreating input data in the output. The classification was based on LORETA source estimates from rsEEG activity recorded with 10-20 montage system (19 electrodes) and standard sMRI variables in 89 ADD and 45 healthy control participants taken from a national database., Results: The ANN with stacked autoencoders and a deep leaning model representing both ADD and control participants showed classification accuracies in discriminating them of 80%, 85%, and 89% using rsEEG, sMRI, and rsEEG + sMRI features, respectively. The two ANNs with stacked autoencoders and a deep leaning model specialized for either ADD or control participants showed classification accuracies of 77%, 83%, and 86% using the same input features., Conclusions: The two architectures of ANNs using stacked (autoencoding) hidden layers consistently reached moderate to high accuracy in the discrimination between ADD and healthy control participants as a function of the rsEEG and sMRI features employed., Significance: The present results encourage future multi-centric, prospective and longitudinal cross-validation studies using high resolution EEG techniques and harmonized clinical procedures towards clinical applications of the present ANNs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Cognitive impairment following SARS-CoV-2 infection is being increasingly recognized as an acute and possibly also long-term sequela of the disease. Direct viral entry as well as systemic mechanisms such as cytokine storm are thought to contribute to neuroinflammation in these patients. Biomarkers of COVID-19-induced cognitive impairment are currently lacking, but there is some limited evidence that SARS-CoV-2 could preferentially target the frontal lobes, as suggested by behavioral and dysexecutive symptoms, fronto-temporal hypoperfusion on MRI, EEG slowing in frontal regions, and frontal hypometabolism on 18F-FDG-PET. Possible confounders include cognitive impairment due to hypoxia and mechanical ventilation and post-traumatic stress disorder. Conversely, patients already suffering from dementia, as well as their caregivers, have been greatly impacted by the disruption of their care caused by COVID-19. Patients with dementia have experienced worsening of cognitive, behavioral, and psychological symptoms, and the rate of COVID-19-related deaths is disproportionately high among cognitively impaired people. Multiple factors, such as difficulties in remembering and executing safeguarding procedures, age, comorbidities, residing in care homes, and poorer access to hospital standard of care play a role in the increased morbidity and mortality. Non-pharmacological interventions and new technologies have shown a potential for the management of patients with dementia, and for the support of their caregivers.

In cognitively normal patients, mild hyperglycemia selectively decreases 18F-Fluorodeoxyglucose (FDG) uptake in the posterior brain, reproducing Alzheimer disease pattern, hampering the diagnostic accuracy of this widely used tool. This phenomenon might involve either a heterogeneous response of glucose metabolism or a different sensitivity to hyperglycemia-related redox stress. Indeed, previous studies reported a close link between FDG uptake and activation of a specific pentose phosphate pathway (PPP), triggered by hexose-6P-dehydrogenase (H6PD) and contributing to fuel NADPH-dependent antioxidant responses in the endoplasmic reticulum (ER). To clarify this issue, dynamic positron emission tomography was performed in 40 BALB/c mice four weeks after administration of saline ( n = 17) or 150 mg/kg streptozotocin ( n = 23, STZ). Imaging data were compared with biochemical and histological indexes of glucose metabolism and redox balance. Cortical FDG uptake was homogeneous in controls, while it was selectively decreased in the posterior brain of STZ mice. This difference was independent of the activity of enzymes regulating glycolysis and cytosolic PPP, while it was paralleled by a decreased H6PD catalytic function and enhanced indexes of oxidative damage. Thus, the relative decrease in FDG uptake of the posterior brain reflects a lower activation of ER-PPP in response to hyperglycemia-related redox stress in these areas.

Electroencephalography (EEG) slowing with prealpha dominant frequency (DF) in posterior derivations is a biomarker for dementia with Lewy bodies (DLB) diagnosis, in contrast with Alzheimer's disease (AD). However, an intrasubject re-evaluation of the original data, which contributed to the identification of EEG DLB biomarker, showed that DF was slower in anterior than posterior derivations. We suppose this anterior-posterior gradient of DF slowing could arise in DLB from a thalamocortical dysrhythmia, differently involving the anterior and posterior cortical areas, and correlating with cognitive impairment (Mini-Mental State Examination). EEG was recorded in 144 DLB, 116 AD, and 65 controls from 7 Centers of the European DLB Consortium. Spectra were divided into delta, theta, prealpha, alpha frequency bands. In DLB, mean DF was prealpha both anteriorly and posteriorly, but lower anteriorly (p < 0.001). In 14% of DLB, DF was prealpha anteriorly, whereas alpha posteriorly. In AD and controls, DF was constantly alpha. EEG slowing in DLB correlated with cognitive impairment. Thalamocortical dysrhythmia gives rise to prealpha rhythm with an anterior-posterior gradient and correlates with impaired cognition., (Copyright © 2020 Elsevier Inc. All rights reserved.)

People with type 2 diabetes are at an increased risk of cognitive impairment and dementia (including Alzheimer's disease), as well as subtle forms of cognitive dysfunction. Current diabetes guidelines recommend screening for cognitive impairment in groups at high risk and providing guidance for diabetes management in patients with diabetes and cognitive impairment. Yet, no disease-modifying treatment is available and important questions remain about the mechanisms underlying diabetes-associated cognitive dysfunction. These mechanisms are likely to be multifactorial and different for subtle and more severe forms of diabetes-associated cognitive dysfunction. Over the past years, research on dementia, brain ageing, diabetes, and vascular disease has identified novel biomarkers of specific dementia aetiologies, brain parenchymal injury, and cerebral blood flow and metabolism. These markers shed light on the processes underlying diabetes-associated cognitive dysfunction, have clear applications in current research and increasingly in clinical diagnosis, and might ultimately guide targeted treatment., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background and Purpose: Biomarkers support the aetiological diagnosis of neurocognitive disorders in vivo. Incomplete evidence is available to drive clinical decisions; available diagnostic algorithms are generic and not very helpful in clinical practice. The aim was to develop a biomarker-based diagnostic algorithm for mild cognitive impairment patients, leveraging on knowledge from recognized national experts., Methods: With a Delphi procedure, experienced clinicians making variable use of biomarkers in clinical practice and representing five Italian scientific societies (neurology - Società Italiana di Neurologia per le Demenze; neuroradiology - Associazione Italiana di Neuroradiologia; biochemistry - Società Italiana di Biochimica Clinica; psychogeriatrics - Associazione Italiana di Psicogeriatria; nuclear medicine - Associazione Italiana di Medicina Nucleare) defined the theoretical framework, relevant literature, the diagnostic issues to be addressed and the diagnostic algorithm. An N-1 majority defined consensus achievement., Results: The panellists chose the 2011 National Institute on Aging and Alzheimer's Association diagnostic criteria as the reference theoretical framework and defined the algorithm in seven Delphi rounds. The algorithm includes baseline clinical and cognitive assessment, blood examination, and magnetic resonance imaging with exclusionary and inclusionary roles; dopamine transporter single-photon emission computed tomography (if no/unclear parkinsonism) or metaiodobenzylguanidine cardiac scintigraphy for suspected dementia with Lewy bodies with clear parkinsonism (round VII, votes (yes-no-abstained): 3-1-1); 18 F-fluorodeoxyglucose positron emission tomography for suspected frontotemporal lobar degeneration and low diagnostic confidence of Alzheimer's disease (round VII, 4-0-1); cerebrospinal fluid for suspected Alzheimer's disease (round IV, 4-1-0); and amyloid positron emission tomography if cerebrospinal fluid was not possible/accepted (round V, 4-1-0) or inconclusive (round VI, 5-0-0)., Conclusions: These consensus recommendations can guide clinicians in the biomarker-based aetiological diagnosis of mild cognitive impairment, whilst guidelines cannot be defined with evidence-to-decision procedures due to incomplete evidence., (© 2019 European Academy of Neurology.)

Electrophysiology provides a real-time readout of neural functions and network capability in different brain states, on temporal (fractions of milliseconds) and spatial (micro, meso, and macro) scales unmet by other methodologies. However, current international guidelines do not endorse the use of electroencephalographic (EEG)/magnetoencephalographic (MEG) biomarkers in clinical trials performed in patients with Alzheimer's disease (AD), despite a surge in recent validated evidence. This position paper of the ISTAART Electrophysiology Professional Interest Area endorses consolidated and translational electrophysiological techniques applied to both experimental animal models of AD and patients, to probe the effects of AD neuropathology (i.e., brain amyloidosis, tauopathy, and neurodegeneration) on neurophysiological mechanisms underpinning neural excitation/inhibition and neurotransmission as well as brain network dynamics, synchronization, and functional connectivity, reflecting thalamocortical and corticocortical residual capacity. Converging evidence shows relationships between abnormalities in EEG/MEG markers and cognitive deficits in groups of AD patients at different disease stages. The supporting evidence for the application of electrophysiology in AD clinical research as well as drug discovery pathways warrants an international initiative to include the use of EEG/MEG biomarkers in the main multicentric projects planned in AD patients, to produce conclusive findings challenging the present regulatory requirements and guidelines for AD studies., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Elderly patients with mild cognitive impairment (MCI) may develop a Lewy body disease; their neuroimaging features at presentation are largely unknown. We present an intriguing group of 13 patients with MCI preceding (2.9 ± 1.9 years) parkinsonism (MCI-P), and eventually dementia 4.6 ± 1.6 years later (6 patients), whereas 7 patients remained dementia free after 4.7 ± 2.7 years. Neuropsychological tests, dopamine transporter (DAT) single photon emission computed tomography, and 18 F-fluorodeoxyglucose positron emission tomography were compared with healthy controls and with cognitively normal patients with Parkinson's disease (PD-MOT). Compared to controls, MCI-P but not PD-MOT showed significant posterior temporo-parieto-occipital hypometabolism. Basal ganglia DAT uptake was similar between MCI-P and PD-MOT. Patients who converted to dementia were older, tended to have higher movement disorder society-unified Parkinson's disease rating scale scores and developed at least another clinical core feature fulfilling the criteria for probable dementia with Lewy bodies (DLB). Concurrent impairment of Corsi span and semantic verbal fluency, or of temporal lobe hypometabolism at baseline and reduced putamen-to-caudate ratio on DAT-SPECT at parkinsonism onset, both predicted (p < 0.001) the evolution to dementia. The constructs of Park cognitive subtype and prodromal Lewy body dementia partially overlap; functional imaging and neuropsychology may help in characterizing the patients and in tracking the risk toward dementia., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: To evaluate brain 18 Fluorodeoxyglucose PET (FDG-PET) differences among patients with a clinical diagnosis of corticobasal syndrome (CBS) and distinct underling primary pathologies., Methods: We studied 29 patients with a diagnosis of CBS who underwent FDG-PET scan and postmortem neuropathologic examination. Patients were divided into subgroups on the basis of primary pathologic diagnosis: CBS-corticobasal degeneration (CBS-CBD) (14 patients), CBS-Alzheimer disease (CBS-AD) (10 patients), and CBS-progressive supranuclear palsy (CBS-PSP) (5 patients). Thirteen age-matched healthy patients who underwent FDG-PET were the control group (HC). FDG-PET scans were compared between the subgroups and the HC using SPM-12, with a threshold of p FWE < 0.05., Results: There were no differences in Mattis Dementia Rating Scale or finger tapping scores between CBS groups. Compared to HC, the patients with CBS presented significant hypometabolism in frontoparietal regions, including the perirolandic area, basal ganglia, and thalamus of the clinically more affected hemisphere. Patients with CBS-CBD showed a similar pattern with a more marked, bilateral involvement of the basal ganglia. Patients with CBS-AD presented with posterior, asymmetric hypometabolism, including the lateral parietal and temporal lobes and the posterior cingulate. Finally, patients with CBS-PSP disclosed a more anterior hypometabolic pattern, including the medial frontal regions and the anterior cingulate. A conjunction analysis revealed that the primary motor cortex was the only common area of hypometabolism in all groups, irrespective of pathologic diagnosis., Discussion and Conclusions: In patients with CBS, different underling pathologies are associated with different patterns of hypometabolism. Our data suggest that FDG-PET scans could help in the etiologic diagnosis of CBS., (© 2019 American Academy of Neurology.)

Purpose: The aim of this study was to verify the reliability and generalizability of an automatic tool for the detection of Alzheimer-related hypometabolic pattern based on a Support-Vector-Machine (SVM) model analyzing 18 F-fluorodeoxyglucose (FDG) PET data., Methods: The SVM model processed metabolic data from anatomical volumes of interest also considering interhemispheric asymmetries. It was trained on a homogeneous dataset from a memory clinic center and tested on an independent multicentric dataset drawn from the Alzheimer's Disease Neuroimaging Initiative. Subjects were included in the study and classified based on a diagnosis confirmed after an adequate follow-up time., Results: The accuracy of the discrimination between patients with Alzheimer Disease (AD), in either prodromal or dementia stage, and normal aging subjects was 95.8%, after cross-validation, in the training set. The accuracy of the same model in the testing set was 86.5%. The role of the two datasets was then reversed, and the accuracy was 89.8% in the multicentric training set and 88.0% in the monocentric testing set. The classification rate was also evaluated in different subgroups, including non-converter mild cognitive impairment (MCI) patients, subjects with MCI reverted to normal conditions and subjects with non-confirmed memory concern. The percent of pattern detections increased from 77% in early prodromal AD to 91% in AD dementia, while it was about 10% for healthy controls and non-AD patients., Conclusions: The present findings show a good level of reproducibility and generalizability of a model for detecting the hypometabolic pattern in AD and confirm the accuracy of FDG-PET in Alzheimer disease.

Background/objective: Idiopathic REM sleep behavior disorder (iRBD) often precedes Parkinson's disease (PD) and other alpha-synucleinopathies. The aim of the study is to investigate brain glucose metabolism of patients with RBD and PD by means of a multidimensional scaling approach, using18F-FDG-PET as a biomarker of synaptic function., Methods: Thirty-six iRBD patients (64.1±6.5 y, 32 M), 72 PD patients, and 79 controls (65.6±9.4 y, 53 M) underwent brain 18F-FDG-PET. PD patients were divided according to the absence (PD, 32 subjects; 68.4±8.5 y, 15 M) or presence (PDRBD, 40 subjects; 71.8±6.6 y, 29 M) of RBD. 18F-FDG-PET scans were used to independently discriminate subjects belonging to four categories: controls (RBD no, PD no), iRBD (RBD yes, PD no), PD (RBD no, PD yes) and PDRBD (RBD yes, PD yes)., Results: The discriminant analysis was moderately accurate in identifying the correct category. This is because the model mostly confounds iRBD and PD, thus the intermediate classes. Indeed, iRBD, PD and PDRBD were progressively located at increasing distance from controls and are ordered along a single dimension (principal coordinate analysis) indicating the presence of a single flux of variation encompassing both RBD and PD conditions., Conclusion: Data-driven approach to brain 18F-FDG-PET showed only moderate discrimination between iRBD and PD patients, highlighting brain glucose metabolism heterogeneity among such patients. iRBD should be considered as a marker of an ongoing condition that may be picked-up in different stages across patients and thus express different brain imaging features and likely different clinical trajectories.

Auditory "oddball" event-related potentials (aoERPs), resting state functional magnetic resonance imaging (rsfMRI) connectivity, and electroencephalographic (rsEEG) rhythms were tested as longitudinal functional biomarkers of prodromal Alzheimer's disease (AD). Data were collected at baseline and four follow-ups at 6, 12, 18, and 24 months in amnesic mild cognitive impairment (aMCI) patients classified in two groups: "positive" (i.e., "prodromal AD"; n = 81) or "negative" (n = 63) based on a diagnostic marker of AD derived from cerebrospinal samples (Aβ42/P-tau ratio). A linear mixed model design was used to test functional biomarkers for Group, Time, and Group×Time effects adjusted by nuisance covariates (only data until conversion to dementia was used). Functional biomarkers that showed significant Group effects ("positive" versus "negative", p < 0.05) regardless of Time were 1) reduced rsfMRI connectivity in both the default mode network (DMN) and the posterior cingulate cortex (PCC), both also giving significant Time effects (connectivity decay regardless of Group); 2) increased rsEEG source activity at delta (<4 Hz) and theta (4-8 Hz) rhythms and decreased source activity at low-frequency alpha (8-10.5 Hz) rhythms; and 3) reduced parietal and posterior cingulate source activities of aoERPs. Time×Group effects showed differential functional biomarker progression between groups: 1) increased rsfMRI connectivity in the left parietal cortex of the DMN nodes, consistent with compensatory effects and 2) increased limbic source activity at theta rhythms. These findings represent the first longitudinal characterization of functional biomarkers of prodromal AD relative to "negative" aMCI patients based on 5 serial recording sessions over 2 years.

Background: Several automatic tools have been implemented for semi-quantitative assessment of brain [18]F-FDG-PET., Objective: We aimed to head-to-head compare the diagnostic performance among three statistical parametric mapping (SPM)-based approaches, another voxel-based tool (i.e., PALZ), and a volumetric region of interest (VROI-SVM)-based approach, in distinguishing patients with prodromal Alzheimer's disease (pAD) from controls., Methods: Sixty-two pAD patients (MMSE score = 27.0±1.6) and one hundred-nine healthy subjects (CTR) (MMSE score = 29.2±1.2) were enrolled in five centers of the European Alzheimer's Disease Consortium. The three SPM-based methods, based on different rationales, included 1) a cluster identified through the correlation analysis between [18]F-FDG-PET and a verbal memory test (VROI-1), 2) a VROI derived from the comparison between pAD and CTR (VROI-2), and 3) visual analysis of individual maps obtained by the comparison between each subject and CTR (SPM-Maps). The VROI-SVM approach was based on 6 VROI plus 6 VROI asymmetry values derived from the pAD versus CTR comparison thanks to support vector machine (SVM)., Results: The areas under the ROC curves between pAD and CTR were 0.84 for VROI-1, 0.83 for VROI-2, 0.79 for SPM maps, 0.87 for PALZ, and 0.95 for VROI-SVM. Pairwise comparisons of Youden index did not show statistically significant differences in diagnostic performance between VROI-1, VROI-2, SPM-Maps, and PALZ score whereas VROI-SVM performed significantly (p < 0.005) better than any of the other methods., Conclusion: The study confirms the good accuracy of [18]F-FDG-PET in discriminating healthy subjects from pAD and highlights that a non-linear, automatic VROI classifier based on SVM performs better than the voxel-based methods.

Background: amyloid-PET reading has been classically implemented as a binary assessment, although the clinical experience has shown that the number of borderline cases is non negligible not only in epidemiological studies of asymptomatic subjects but also in naturalistic groups of symptomatic patients attending memory clinics. In this work we develop a model to compare and integrate visual reading with two independent semi-quantification methods in order to obtain a tracer-independent multi-parametric evaluation., Methods: We retrospectively enrolled three cohorts of cognitively impaired patients submitted to 18 F-florbetaben (53 subjects), 18 F-flutemetamol (62 subjects), 18 F-florbetapir (60 subjects) PET/CT respectively, in 6 European centres belonging to the EADC. The 175 scans were visually classified as positive/negative following approved criteria and further classified with a 5-step grading as negative, mild negative, borderline, mild positive, positive by 5 independent readers, blind to clinical data. Scan quality was also visually assessed and recorded. Semi-quantification was based on two quantifiers: the standardized uptake value (SUVr) and the ELBA method. We used a sigmoid model to relate the grading with the quantifiers. We measured the readers accord and inconsistencies in the visual assessment as well as the relationship between discrepancies on the grading and semi-quantifications., Conclusion: It is possible to construct a map between different tracers and different quantification methods without resorting to ad-hoc acquired cases. We used a 5-level visual scale which, together with a mathematical model, delivered cut-offs and transition regions on tracers that are (largely) independent from the population. All fluorinated tracers appeared to have the same contrast and discrimination ability with respect to the negative-to-positive grading. We validated the integration of both visual reading and different quantifiers in a more robust framework thus bridging the gap between a binary and a user-independent continuous scale., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Early Alzheimer's disease (AD) detection using cerebrospinal fluid (CSF) biomarkers has been recommended as enrichment strategy for trials involving mild cognitive impairment (MCI) patients., Objective: To model a prodromal AD trial for identifying MRI structural biomarkers to improve subject selection and to be used as surrogate outcomes of disease progression., Methods: APOE ɛ4 specific CSF Aβ42/P-tau cut-offs were used to identify MCI with prodromal AD (Aβ42/P-tau positive) in the WP5-PharmaCog (E-ADNI) cohort. Linear mixed models were performed 1) with baseline structural biomarker, time, and biomarker×time interaction as factors to predict longitudinal changes in ADAS-cog13, 2) with Aβ42/P-tau status, time, and Aβ42/P-tau status×time interaction as factors to explain the longitudinal changes in MRI measures, and 3) to compute sample size estimation for a trial implemented with the selected biomarkers., Results: Only baseline lateral ventricle volume was able to identify a subgroup of prodromal AD patients who declined faster (interaction, p = 0.003). Lateral ventricle volume and medial temporal lobe measures were the biomarkers most sensitive to disease progression (interaction, p≤0.042). Enrichment through ventricular volume reduced the sample size that a clinical trial would require from 13 to 76%, depending on structural outcome variable. The biomarker needing the lowest sample size was the hippocampal subfield GC-ML-DG (granule cells of molecular layer of the dentate gyrus) (n = 82 per arm to demonstrate a 20% atrophy reduction)., Conclusion: MRI structural biomarkers can enrich prodromal AD with fast progressors and significantly decrease group size in clinical trials of disease modifying drugs.

Background: In Alzheimer's disease (AD) diagnosis, both cerebrospinal fluid (CSF) biomarkers and FDG-PET sometimes give inconclusive results., Objective: To evaluate the incremental diagnostic value of FDG-PET over CSF biomarkers, and vice versa, in patients with mild cognitive impairment (MCI) and suspected AD, in which the first biomarker resulted inconclusive., Methods: A consecutive series of MCI patients was retrospectively selected from two Memory Clinics where, as per clinical routine, either the first biomarker choice is FDG-PET and CSF biomarkers are only used in patients with uninformative FDG-PET, or vice versa. We defined criteria of uncertainty in interpretation of FDG-PET and CSF biomarkers, according to current evidence. The final diagnosis was established according to clinical-neuropsychological follow-up of at least one year (mean 4.4±2.2)., Results: When CSF was used as second biomarker after FDG-PET, 14 out of 36 (39%) received informative results. Among these 14 patients, 11 (79%) were correctly classified with respect to final diagnosis, thus with a relative incremental value of CSF over FDG-PET of 30.6%. When FDG-PET was used as second biomarker, 26 out of 39 (67%) received informative results. Among these 26 patients, 15 (58%) were correctly classified by FDG-PET with respect to final diagnosis, thus with a relative incremental value over CSF of 38.5%., Conclusion: Our real-world data confirm the added values of FDG-PET (or CSF) in a diagnostic pathway where CSF (or FDG-PET) was used as first biomarkers in suspected AD. These findings should be replicated in larger studies with prospective enrolment according to a Phase III design.

Background and Purpose: Recommendations for using fluorodeoxyglucose positron emission tomography (FDG-PET) to support the diagnosis of dementing neurodegenerative disorders are sparse and poorly structured., Methods: Twenty-one questions on diagnostic issues and on semi-automated analysis to assist visual reading were defined. Literature was reviewed to assess study design, risk of bias, inconsistency, imprecision, indirectness and effect size. Critical outcomes were sensitivity, specificity, accuracy, positive/negative predictive value, area under the receiver operating characteristic curve, and positive/negative likelihood ratio of FDG-PET in detecting the target conditions. Using the Delphi method, an expert panel voted for/against the use of FDG-PET based on published evidence and expert opinion., Results: Of the 1435 papers, 58 papers provided proper quantitative assessment of test performance. The panel agreed on recommending FDG-PET for 14 questions: diagnosing mild cognitive impairment due to Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD) or dementia with Lewy bodies (DLB); diagnosing atypical AD and pseudo-dementia; differentiating between AD and DLB, FTLD or vascular dementia, between DLB and FTLD, and between Parkinson's disease and progressive supranuclear palsy; suggesting underlying pathophysiology in corticobasal degeneration and progressive primary aphasia, and cortical dysfunction in Parkinson's disease; using semi-automated assessment to assist visual reading. Panellists did not support FDG-PET use for pre-clinical stages of neurodegenerative disorders, for amyotrophic lateral sclerosis and Huntington disease diagnoses, and for amyotrophic lateral sclerosis or Huntington-disease-related cognitive decline., Conclusions: Despite limited formal evidence, panellists deemed FDG-PET useful in the early and differential diagnosis of the main neurodegenerative disorders, and semi-automated assessment helpful to assist visual reading. These decisions are proposed as interim recommendations., (© 2018 EAN.)

Purpose: To assess the clinical utility of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) for detection of early signs of neurodegeneration in conditions of increased risk for Alzheimer's disease (AD) as defined by: subjective cognitive decline (SCD), evidence of cerebral amyloid-pathology, apolipoprotein E (APOE) ε4-positive genotype, or autosomal dominant forms of AD (ADAD) in asymptomatic stages., Methods: A comprehensive literature search was conducted using the PICO model to extract evidence from relevant studies. An expert panel then voted using the Delphi method on three different diagnostic scenarios., Results: The level of empirical study evidence for the use of FDG-PET to detect meaningful early signs of neurodegeneration was considered to be poor for ADAD and lacking for SCD and asymptomatic persons at risk, based on APOE ε4-positive genotype or cerebral amyloid pathology. Consequently, and consistent with current diagnostic criteria, panelists decided not to recommend routine clinical use of FDG-PET in these situations and to currently mainly reserve it for research purposes., Conclusion: Currently, there is limited evidence on which to base recommendations regarding the clinical routine use of FDG-PET to detect diagnostically meaningful early signs of neurodegeneration in asymptomatic subjects with ADAD, with APOE ε4-positive genotype, or with cerebral amyloid pathology, and in subjects with SCD. Future prospective studies are warranted and in part already ongoing, aiming to assess the added value of FDG-PET in this context beyond research applications.

Purpose: A joint effort of the European Association of Nuclear Medicine (EANM) and the European Academy of Neurology (EAN) aims at clinical guidance for the use of FDG-PET in neurodegenerative diseases. This paper addresses the diagnostic utility of FDG-PET over clinical/neuropsychological assessment in the differentiation of the three forms of primary progressive aphasia (PPA)., Methods: Seven panelists were appointed by the EANM and EAN and a literature search was performed by using harmonized PICO (Population, Intervention, Comparison, Outcome) question keywords. The studies were screened for eligibility, and data extracted to assess their methodological quality. Critical outcomes were accuracy indices in differentiating different PPA clinical forms. Subsequently Delphi rounds were held with the extracted data and quality assessment to reach a consensus based on both literature and expert opinion., Results: Critical outcomes for this PICO were available in four of the examined papers. The level of formal evidence supporting clinical utility of FDG-PET in differentiating among PPA variants was considered as poor. However, the consensual recommendation was defined on Delphi round I, with six out of seven panelists supporting clinical use., Conclusions: Quantitative evidence demonstrating utility or lack thereof is still missing. Panelists decided consistently to provide interim support for clinical use based on the fact that a typical atrophy or metabolic pattern is needed for PPA according to the diagnostic criteria, and the synaptic failure detected by FDG-PET is an earlier phenomenon than atrophy. Also, a normal FDG-PET points to a non-neurodegenerative cause.

Background: We explored the presence of both reserve and resilience in late-converter mild cognitive impairment due to Alzheimer's disease (MCI-AD) and in patients with slowly progressing amyloid-positive MCI by assessing the topography and extent of neurodegeneration with respect to both "aggressive" and typically progressing phenotypes and in the whole group of patients with MCI, grounding the stratification on education level., Methods: We analyzed 94 patients with MCI-AD followed until conversion to dementia and 39 patients with MCI who had brain amyloidosis (AMY+ MCI), all with available baseline 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) results. Using a data-driven approach based on conversion time, patients with MCI-AD were divided into typical AD and late-converter subgroups. Similarly, on the basis of annual rate of Mini Mental State Examination score reduction, AMY+ MCI group was divided, obtaining smoldering (first tertile) and aggressive (third tertile) subgroups. Finally, we divided the whole group (MCI-AD and AMY+ MCI) according to years of schooling, obtaining four subgroups: poorly educated (Low-EDUC; first quartile), patients with average education (Average-EDUC; second quartile), highly educated (High-EDUC; third quartile), and exceptionally educated (Except-EDUC; fourth quartile). FDG-PET of typical AD, late converters, and aggressive and smoldering AMY+ MCI subgroups, as well as education level-based subgroups, were compared with healthy volunteer control subjects (CTR) and within each group using a two-samples t test design (SPM8; p < 0.05 family-wise error-corrected)., Results: Late converters were characterized by relatively preserved metabolism in the right middle temporal gyrus (Brodmann area [BA] 21) and in the left orbitofrontal cortex (BA 47) with respect to typical AD. When compared with CTR, the High-EDUC subgroup demonstrated a more extended bilateral hypometabolism in the posterior parietal cortex, posterior cingulate cortex, and precuneus than the Low- and Average-EDUC subgroups expressing the same level of cognitive impairment. The Except-EDUC subgroup showed a cluster of significant hypometabolism including only the left posterior parietal cortex (larger than the Low- and Average-EDUC subgroups but not further extended with respect to the High-EDUC subgroup)., Conclusions: Middle and inferior temporal gyri may represent sites of resilience rather than a hallmark of a more aggressive pattern (when hypometabolic). These findings thus support the existence of a relatively homogeneous AD progression pattern of hypometabolism despite AD heterogeneity and interference of cognitive reserve. In fact, cortical regions whose "metabolic resistance" was associated with slower clinical progression had different localization with respect to the regions affected by education-related reserve.

The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) score was matched between the ADMCI and DLBMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROCC) classified these sources across individuals. Compared to Nold, IAF showed marked slowing in DLBMCI and moderate in ADMCI. Furthermore, the posterior alpha 2 and alpha 3 source activities were more abnormal in the ADMCI than the DLBMCI group, while widespread delta source activities were more abnormal in the DLBMCI than the ADMCI group. The posterior delta and alpha sources correlated with the MMSE score and correctly classified the Nold and MCI individuals (area under the ROCC >0.85). In conclusion, the ADMCI and DLBMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test the clinical validity of these rsEEG markers.

We investigated the expression of the Alzheimer's disease-related metabolic brain pattern (ADRP) in 18 F-FDG-PET scans of 44 controls, 27 patients with mild cognitive impairment (MCI) who did not convert to Alzheimer's disease (AD) after five or more years of clinical follow-up, 95 MCI patients who did develop AD dementia on clinical follow-up, and 55 patients with mild-to-moderate AD. The ADRP showed good sensitivity (84%) and specificity (86%) for MCI-converters when compared to controls, but limited specificity when compared to MCI non-converters (66%). Assessment of 18 F-FDG-PET scans on a case-by-case basis using the ADRP may be useful for quantifying disease progression.

Brain connectivity has been assessed in several neurodegenerative disorders investigating the mutual correlations between predetermined regions or nodes. Selective breakdown of brain networks during progression from normal aging to Alzheimer disease dementia (AD) has also been observed. Methods: We implemented independent-component analysis of 18 F-FDG PET data in 5 groups of subjects with cognitive states ranging from normal aging to AD-including mild cognitive impairment (MCI) not converting or converting to AD-to disclose the spatial distribution of the independent components in each cognitive state and their accuracy in discriminating the groups. Results: We could identify spatially distinct independent components in each group, with generation of local circuits increasing proportionally to the severity of the disease. AD-specific independent components first appeared in the late-MCI stage and could discriminate converting MCI and AD from nonconverting MCI with an accuracy of 83.5%. Progressive disintegration of the intrinsic networks from normal aging to MCI to AD was inversely proportional to the conversion time. Conclusion: Independent-component analysis of 18 F-FDG PET data showed a gradual disruption of functional brain connectivity with progression of cognitive decline in AD. This information might be useful as a prognostic aid for individual patients and as a surrogate biomarker in intervention trials., (© 2017 by the Society of Nuclear Medicine and Molecular Imaging.)

The use of Alzheimer's disease (AD) biomarkers is supported in diagnostic criteria, but their maturity for clinical routine is still debated. Here, we evaluate brain fluorodeoxyglucose positron emission tomography (FDG PET), a measure of cerebral glucose metabolism, as a biomarker to identify clinical and prodromal AD according to the framework suggested for biomarkers in oncology, using homogenous criteria with other biomarkers addressed in parallel reviews. FDG PET has fully achieved phase 1 (rational for use) and most of phase 2 (ability to discriminate AD subjects from healthy controls or other forms of dementia) aims. Phase 3 aims (early detection ability) are partly achieved. Phase 4 studies (routine use in prodromal patients) are ongoing, and only preliminary results can be extrapolated from retrospective observations. Phase 5 studies (quantify impact and costs) have not been performed. The results of this study show that specific efforts are needed to complete phase 3 evidence, in particular comparing and combining FDG PET with other biomarkers, and to properly design phase 4 prospective studies as a basis for phase 5 evaluations., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The assessment of the degree of order of brain metabolism by means of a statistical mechanistic approach applied to FDG-PET, allowed us to characterize healthy subjects as well as patients with mild cognitive impairment and Alzheimer's Disease (AD). The intensity signals from 24 volumes of interest were submitted to principal component analysis (PCA) giving rise to a major first principal component whose eigenvalue was a reliable cumulative index of order. This index linearly decreased from 77 to 44% going from normal aging to AD patients with intermediate conditions between these values (r=0.96, p<0.001). Bootstrap analysis confirmed the statistical significance of the results. The progressive detachment of different brain regions from the first component was assessed, allowing for a purely data driven reconstruction of already known maximally affected areas. We demonstrated for the first time the reliability of a single global index of order in discriminating groups of cognitively impaired patients with different clinical outcome. The second relevant finding was the identification of clusters of regions relevant to AD pathology progressively separating from the first principal component through different stages of cognitive impairment, including patients cognitively impaired but not converted to AD. This paved the way to the quantitative assessment of the functional networking status in individual patients., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The assessment of in vivo18F images targeting amyloid deposition is currently carried on by visual rating with an optional quantification based on standardized uptake value ratio (SUVr) measurements. We target the difficulties of image reading and possible shortcomings of the SUVr methods by validating a new semi-quantitative approach named ELBA. ELBA involves a minimal image preprocessing and does not rely on small, specific regions of interest (ROIs). It evaluates the whole brain and delivers a geometrical/intensity score to be used for ranking and dichotomic assessment. The method was applied to adniimages 18F-florbetapir images from the ADNI database. Five expert readers provided visual assessment in blind and open sessions. The longitudinal trend and the comparison to SUVr measurements were also evaluated. ELBA performed with area under the roc curve (AUC) = 0.997 versus the visual assessment. The score was significantly correlated to the SUVr values (r = 0.86, p < 10-4). The longitudinal analysis estimated a test/retest error of ≃2.3%. Cohort and longitudinal analysis suggests that the ELBA method accurately ranks the brain amyloid burden. The expert readers confirmed its relevance in aiding the visual assessment in a significant number (85) of difficult cases. Despite the good performance, poor and uneven image quality constitutes the major limitation.

Introduction: The association between Parkinson Disease (PD) and REM sleep behavior disorder (RBD) has been related to a specific, malignant clinical phenotype. Definite RBD diagnosis requires video-polysomnography that is often unfeasible. A malignant clinical PD-RBD phenotype could be expected also in PD patients with probable RBD. Aim of this cross-sectional study was to evaluate whether a more severe neuropsychological and functional neuroimaging phenotype can be identified in PD patients with probable RBD., Methods: Thirty-eight de novo, drug naïve PD patients underwent a first-line clinical assessment and a second-line multimodal assessment, including neuropsychological evaluation, (123)I-FP-CIT-SPECT and (18)F-FDG-PET, which were compared between PD patients with (PD + RBD+) and without (PD + RBD-) probable RBD., Results: On first-line assessment, PD + RBD + patients had significantly more constipation (p = 0.02) and showed worse olfaction (p = 0.01) compared with PD + RBD-while the two groups were similar as for age, presence of orthostatic hypotension, UPDRS-III and MMSE scores. On second-line assessment, PD + RBD + patients showed a worse neuropsychological test profile, more severe nigro-striatal dopaminergic impairment, mainly at caudate level in the less affected hemisphere (p = 0.004) and impaired brain glucose metabolism, with relative hypometabolism in posterior cortical regions and relative hypermetabolism mainly in anterior regions of the more affected hemisphere (p = 0.015)., Conclusions: PD patients with probable RBD are likely to have a more severe neuropsychological and functional brain-imaging phenotype already at the time of diagnosis., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Purpose: The diagnosis of behavioural variant frontotemporal dementia (bvFTD) is challenging during the predementia stage when symptoms are subtle and confounding. Morphological and functional neuroimaging can be particularly helpful during this stage but few data are available., Methods: We retrospectively selected 25 patients with late-onset probable bvFTD. Brain structural MRI and FDG PET were performed during the predementia stage (mean MMSE score 27.1 ± 2.5) on average 2 years before. The findings with the two imaging modalities were compared (SPM8) with those in a group of 20 healthy subjects. The bvFTD patients were divided into two subgroups: those with predominant disinhibition (bvFTD+) and those with apathy (bvFTD-)., Results: Hypometabolism exceeded grey matter (GM) density reduction in terms of both extension and statistical significance in all comparisons. In the whole bvFTD group, hypometabolism involved the bilateral medial, inferior and superior lateral frontal cortex, anterior cingulate, left temporal and right parietal cortices and the caudate nuclei. GM density reduction was limited to the right frontal cortex and the left medial temporal lobe. In bvFTD+ patients hypometabolism was found in the bilateral medial and basal frontal cortex, while GM reduction involved the left anterior cingulate and left inferior frontal cortices, and the right insula. In bvFTD- patients, atrophy and mainly hypometabolism involved the lateral frontal cortex and the inferior parietal lobule., Conclusion: These findings suggest that hypometabolism is more extensive than, and thus probably precedes, atrophy in predementia late-onset bvFTD, underscoring different topographic involvement in disinhibited and apathetic presentations. If confirmed in a larger series, these results should prompt biomarker operationalization in bvFTD, especially for patient selection in therapeutic clinical trials.

Understanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within-site test-retest reliability and the across-site reproducibility consistency of DMN-derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue-based regression, PESTICA and FSL-FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z-scores and, albeit less markedly, the cluster-size in the DMN; in particular, FSL-FIX tended to increase the DMN z-scores compared to others. Within-site test-retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5-11% for DMN z-scores and cluster-size reliability. DMN pattern overlap was in the range 60-65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL-FIX and Tissue-based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC = 0.67) for the DMN z-scores relative to NPC. Overall these findings support the use of rPNC methods like tissue-based or FSL-FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. Hum Brain Mapp 37:2114-2132, 2016. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Objectives: Positron emission tomography (PET) and volume of interest (VOI) analysis have recently shown in amyotrophic lateral sclerosis (ALS) an accuracy of 93% in differentiating patients from controls. The aim of this study was to disclose by spatial independent component analysis (ICA) the brain networks involved in ALS pathological processes and evaluate their discriminative value in separating patients from controls., Experimental Design: Two hundred fifty-nine ALS patients and 40 age- and sex-matched control subjects underwent brain 18F-2-fluoro-2-deoxy-D-glucose PET (FDG-PET). Spatial ICA of the preprocessed FDG-PET images was performed. Intensity values were converted to z-scores and binary masks were used as data-driven VOIs. The accuracy of this classifier was tested versus a validated system processing intensity signals in 27 brain meta-VOIs. A support vector machine was independently applied to both datasets and the 'leave-one-out' technique verified the general validity of results., Principal Observations: The 8 components selected as pathophysiologically meaningful discriminated patients from controls with 99.0% accuracy, the discriminating value of bilateral cerebellum/midbrain alone representing 96.3%. Among the meta-VOIs, right temporal lobe alone reached an accuracy of 93.7%., Conclusions: Spatial ICA identified in a very large cohort of ALS patients distinct spatial networks showing a high discriminatory value, improving substantially on the previously obtained accuracy. The cerebellar/midbrain component accounted for the highest accuracy in separating ALS patients from controls. Spatial ICA and multivariate analysis perform better than univariate semi-quantification methods in identifying the neurodegenerative features of ALS and pave the way for inclusion of PET in clinical trials and early diagnosis., (© 2015 Wiley Periodicals, Inc.)

To date, limited data are available regarding the inter-site consistency of test-retest reproducibility of functional connectivity measurements, in particular with regard to integrity of the Default Mode Network (DMN) in elderly participants. We implemented a harmonized resting-state fMRI protocol on 13 clinical scanners at 3.0T using vendor-provided sequences. Each site scanned a group of 5 healthy elderly participants twice, at least a week apart. We evaluated inter-site differences and test-retest reproducibility of both temporal signal-to-noise ratio (tSNR) and functional connectivity measurements derived from: i) seed-based analysis (SBA) with seed in the posterior cingulate cortex (PCC), ii) group independent component analysis (ICA) separately for each site (site ICA), and iii) consortium ICA, with group ICA across the whole consortium. Despite protocol harmonization, significant and quantitatively important inter-site differences remained in the tSNR of resting-state fMRI data; these were plausibly driven by hardware and pulse sequence differences across scanners which could not be harmonized. Nevertheless, the tSNR test-retest reproducibility in the consortium was high (ICC=0.81). The DMN was consistently extracted across all sites and analysis methods. While significant inter-site differences in connectivity scores were found, there were no differences in the associated test-retest error. Overall, ICA measurements were more reliable than PCC-SBA, with site ICA showing higher reproducibility than consortium ICA. Across the DMN nodes, the PCC yielded the most reliable measurements (≈4% test-retest error, ICC=0.85), the medial frontal cortex the least reliable (≈12%, ICC=0.82) and the lateral parietal cortices were in between (site ICA). Altogether these findings support usage of harmonized multisite studies of resting-state functional connectivity to characterize longitudinal effects in studies that assess disease progression and treatment response., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Increasing evidence has shown that morphological and functional neuroimaging may help to understand the pathophysiological mechanisms leading to behavioral disturbances in patients with genetic or sporadic frontotemporal dementia (FTD). The C9orf72 expansion was found in association with the N267S TARDBP mutation in two siblings with behavioral-variant FTD (bvFTD). In one of them with very mild dementia, MRI showed symmetric atrophy of temporal, inferolateral and orbital frontal cortex, while [18F]FDG-PET disclosed more extended hypometabolism in dorsolateral and inferolateral frontal cortex, anterior cingulate, and caudate nucleus. Hypometabolism in right lateral and orbital frontal cortex was confirmed also in comparison with a group of sporadic bvFTD patients. These findings appear as the neuroimaging hallmark of double C9orf72 and TARDBP gene mutation with a bvFTD phenotype.

An emerging issue in neuroimaging is to assess the diagnostic reliability of PET and its application in clinical practice. We aimed at assessing the accuracy of brain FDG-PET in discriminating patients with MCI due to Alzheimer's disease and healthy controls. Sixty-two patients with amnestic MCI and 109 healthy subjects recruited in five centers of the European AD Consortium were enrolled. Group analysis was performed by SPM8 to confirm metabolic differences. Discriminant analyses were then carried out using the mean FDG uptake values normalized to the cerebellum computed in 45 anatomical volumes of interest (VOIs) in each hemisphere (90 VOIs) as defined in the Automated Anatomical Labeling (AAL) Atlas and on 12 meta-VOIs, bilaterally, obtained merging VOIs with similar anatomo-functional characteristics. Further, asymmetry indexes were calculated for both datasets. Accuracy of discrimination by a Support Vector Machine and the AAL VOIs was tested against a validated method (PALZ). At the voxel level SMP8 showed a relative hypometabolism in the bilateral precuneus, and posterior cingulate, temporo-parietal and frontal cortices. Discriminant analysis classified subjects with an accuracy ranging between .91 and .83 as a function of data organization. The best values were obtained from a subset of 6 meta-VOIs plus 6 asymmetry values reaching an area under the ROC curve of .947, significantly larger than the one obtained by the PALZ score. High accuracy in discriminating MCI converters from healthy controls was reached by a non-linear classifier based on SVM applied on predefined anatomo-functional regions and inter-hemispheric asymmetries. Data pre-processing was automated and simplified by an in-house created Matlab-based script encouraging its routine clinical use. Further validation toward nonconverter MCI patients with adequately long follow-up is needed.

Diagnostic accuracy in FDG-PET imaging highly depends on the operating procedures. In this clinical study on dementia, we compared the diagnostic accuracy at a single-subject level of a) Clinical Scenarios, b) Standard FDG Images and c) Statistical Parametrical (SPM) Maps generated via a new optimized SPM procedure. We evaluated the added value of FDG-PET, either Standard FDG Images or SPM Maps, to Clinical Scenarios. In 88 patients with neurodegenerative diseases (Alzheimer's Disease-AD, Frontotemporal Lobar Degeneration-FTLD, Dementia with Lewy bodies-DLB and Mild Cognitive Impairment-MCI), 9 neuroimaging experts made a forced diagnostic decision on the basis of the evaluation of the three types of information. There was also the possibility of a decision of normality on the FDG-PET images. The clinical diagnosis confirmed at a long-term follow-up was used as the gold standard. SPM Maps showed higher sensitivity and specificity (96% and 84%), and better diagnostic positive (6.8) and negative (0.05) likelihood ratios compared to Clinical Scenarios and Standard FDG Images. SPM Maps increased diagnostic accuracy for differential diagnosis (AD vs. FTD; beta 1.414, p = 0.019). The AUC of the ROC curve was 0.67 for SPM Maps, 0.57 for Clinical Scenarios and 0.50 for Standard FDG Images. In the MCI group, SPM Maps showed the highest predictive prognostic value (mean LOC = 2.46), by identifying either normal brain metabolism (exclusionary role) or hypometabolic patterns typical of different neurodegenerative conditions.

Objective: We investigated a large sample of patients with amyotrophic lateral sclerosis (ALS) at rest in order to assess the value of (18)F-2-fluoro-2-deoxy-d-glucose ((18)F-FDG) PET as a biomarker to discriminate patients from controls., Methods: A total of 195 patients with ALS and 40 controls underwent brain (18)F-FDG-PET, most within 5 months of diagnosis. Spinal and bulbar subgroups of ALS were also investigated. Twenty-five bilateral cortical and subcortical volumes of interest and cerebellum were taken into account, and (18)F-FDG uptakes were individually normalized by whole-brain values. Group analyses investigated the ALS-related metabolic changes. Discriminant analysis investigating sensitivity and specificity was performed using the 51 volumes of interest as well as age and sex. Metabolic connectivity was explored by voxel-wise interregional correlation analysis., Results: Hypometabolism was found in frontal, motor, and occipital cortex and hypermetabolism in midbrain, temporal pole, and hippocampus in patients with ALS compared to controls. A similar metabolic pattern was also found in the 2 subgroups. Discriminant analysis showed a sensitivity of 95% and a specificity of 83% in separating patients from controls. Connectivity analysis found a highly significant positive correlation between midbrain and white matter in corticospinal tracts in patients with ALS., Conclusions: (18)F-FDG distribution changes in ALS showed a clear pattern of hypometabolism in frontal and occipital cortex and hypermetabolism in midbrain. The latter might be interpreted as the neurobiological correlate of diffuse subcortical gliosis. Discriminant analysis resulted in high sensitivity and specificity in differentiating patients with ALS from controls. Once validated by diseased-control studies, the present methodology might represent a potentially useful biomarker for ALS diagnosis., Classificaton of Evidence: This study provides Class III evidence that (18)F-FDG-PET accurately distinguishes patients with ALS from normal controls (sensitivity 95.4%, specificity 82.5%)., (© 2014 American Academy of Neurology.)

Unlabelled: Serotonin-mediated mechanisms, in particular via the serotonin transporter (SERT), are thought to have an effect on food intake and play an important role in the pathophysiology of obesity. However, imaging studies that examined the correlation between body mass index (BMI) and SERT are sparse and provided contradictory results. The aim of this study was to further test the association between SERT and BMI in a large cohort of healthy subjects., Methods: 127 subjects of the ENC DAT database (58 females, age 52 ± 18 years, range 20-83, BMI 25.2 ± 3.8 kg/m(2), range 18.2-41.1) were analysed using region-of-interest (ROI) and voxel-based approaches to calculate [(123)I]FP-CIT specific-to-nonspecific binding ratios (SBR) in the hypothalamus/thalamus and midbrain/brainstem as SERT-specific target regions., Results: In the voxel-based analysis, SERT availability and BMI were positively associated in the thalamus, but not in the midbrain. In the ROI-analysis, the interaction between gender and BMI showed a trend with higher correlation coefficient for men in the midbrain albeit not significant (0.033SBRm(2)/kg, p=0.1)., Conclusions: The data are in agreement with previous PET findings of an altered central serotonergic tone depending on BMI, as a probable pathophysiologic mechanism in obesity, and should encourage further clinical studies in obesity targeting the serotonergic system., (Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.)

Purpose: The role of oxidative stress is increasingly recognized in cognitive disorders of the elderly, notably Alzheimer's disease (AD). In these subjects brain(18)F-FDG PET is regarded as a reliable biomarker of neurodegeneration. We hypothesized that oxidative stress could play a role in impairing brain glucose utilization in elderly subjects with increasing severity of cognitive disturbance., Methods: The study group comprised 85 subjects with cognitive disturbance of increasing degrees of severity including 23 subjects with subjective cognitive impairment (SCI), 28 patients with mild cognitive impairment and 34 patients with mild AD. In all subjects brain FDG PET was performed and plasma activities of extracellular superoxide dismutase (eSOD), catalase and glutathione peroxidase were measured. Voxel-based analysis (SPM8) was used to compare FDG PET between groups and to evaluate correlations between plasma antioxidants and glucose metabolism in the whole group of subjects, correcting for age and Mini-Mental State Examination score., Results: Brain glucose metabolism progressively decreased in the bilateral posterior temporoparietal and cingulate cortices across the three groups, from SCI to mild AD. eSOD activity was positively correlated with glucose metabolism in a large area of the left temporal lobe including the superior, middle and inferior temporal gyri and the fusiform gyrus., Conclusion: These results suggest a role of oxidative stress in the impairment of glucose utilization in the left temporal lobe structures in elderly patients with cognitive abnormalities, including AD and conditions predisposing to AD. Further studies exploring the oxidative stress-energy metabolism axis are considered worthwhile in larger groups of these patients in order to identify pivotal pathophysiological mechanisms and innovative therapeutic opportunities.

We evaluated the brain metabolic correlates of main indexes of a widely used word list learning test, the Rey Auditory Verbal Memory Test (RAVLT), in a group of elderly subjects with memory complaints. Fifty-four subjects (age: 72.02 ± 7.45; Mini-Mental State Examination (MMSE) score: 28.9 ± 1.24) presenting at a memory clinic complaining of memory deficit, but not demented, and thirty controls (age: 71.87 ± 7.08; MMSE score: 29.1 ± 1.1) were included. Subjects with memory complaints included both patients with (amnestic mild cognitive impairment, aMCI) and without (subjective memory complaints, SMC) impairment on memory tests. All subjects underwent 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), analyzed with statistical parametric. Patients with aMCI but not those with SMC showed the expected posterior cingulate-precuneus and parietal hypometabolism as compared to controls. Correlation was determined for between four indexes of the RAVLT and brain metabolism. The results show a significant correlation between the delayed recall score and metabolism in posterior cingulate gyrus of both hemispheres and in left precuneus, as well as between a score of long-term percent retention and metabolism in left posterior cingulate gyrus, precuneus, and orbitofrontal areas. These correlations survived correction for age, education, and MMSE score. No correlation was found between immediate or total recall scores and glucose metabolism. These data show the relevant role of posterior cingulate-precuneus and orbitofrontal cortices in retention and retrieval of de-contextualized verbal memory material in a group of elderly subjects with memory complaints and shed light on the topography of synaptic dysfunction in these subjects, overlapping that found in the earliest stages of Alzheimer-type neurodegeneration.

Large-scale longitudinal multi-site MRI brain morphometry studies are becoming increasingly crucial to characterize both normal and clinical population groups using fully automated segmentation tools. The test-retest reproducibility of morphometry data acquired across multiple scanning sessions, and for different MR vendors, is an important reliability indicator since it defines the sensitivity of a protocol to detect longitudinal effects in a consortium. There is very limited knowledge about how across-session reliability of morphometry estimates might be affected by different 3T MRI systems. Moreover, there is a need for optimal acquisition and analysis protocols in order to reduce sample sizes. A recent study has shown that the longitudinal FreeSurfer segmentation offers improved within session test-retest reproducibility relative to the cross-sectional segmentation at one 3T site using a nonstandard multi-echo MPRAGE sequence. In this study we implement a multi-site 3T MRI morphometry protocol based on vendor provided T1 structural sequences from different vendors (3D MPRAGE on Siemens and Philips, 3D IR-SPGR on GE) implemented in 8 sites located in 4 European countries. The protocols used mild acceleration factors (1.5-2) when possible. We acquired across-session test-retest structural data of a group of healthy elderly subjects (5 subjects per site) and compared the across-session reproducibility of two full-brain automated segmentation methods based on either longitudinal or cross-sectional FreeSurfer processing. The segmentations include cortical thickness, intracranial, ventricle and subcortical volumes. Reproducibility is evaluated as absolute changes relative to the mean (%), Dice coefficient for volume overlap and intraclass correlation coefficients across two sessions. We found that this acquisition and analysis protocol gives comparable reproducibility results to previous studies that used longer acquisitions without acceleration. We also show that the longitudinal processing is systematically more reliable across sites regardless of MRI system differences. The reproducibility errors of the longitudinal segmentations are on average approximately half of those obtained with the cross sectional analysis for all volume segmentations and for entorhinal cortical thickness. No significant differences in reliability are found between the segmentation methods for the other cortical thickness estimates. The average of two MPRAGE volumes acquired within each test-retest session did not systematically improve the across-session reproducibility of morphometry estimates. Our results extend those from previous studies that showed improved reliability of the longitudinal analysis at single sites and/or with non-standard acquisition methods. The multi-site acquisition and analysis protocol presented here is promising for clinical applications since it allows for smaller sample sizes per MRI site or shorter trials in studies evaluating the role of potential biomarkers to predict disease progression or treatment effects., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Purpose: Dopamine transporter (DAT) imaging with [(123)I]FP-CIT (DaTSCAN) is an established diagnostic tool in parkinsonism and dementia. Although qualitative assessment criteria are available, DAT quantification is important for research and for completion of a diagnostic evaluation. One critical aspect of quantification is the availability of normative data, considering possible age and gender effects on DAT availability. The aim of the European Normal Control Database of DaTSCAN (ENC-DAT) study was to generate a large database of [(123)I]FP-CIT SPECT scans in healthy controls., Methods: SPECT data from 139 healthy controls (74 men, 65 women; age range 20-83 years, mean 53 years) acquired in 13 different centres were included. Images were reconstructed using the ordered-subset expectation-maximization algorithm without correction (NOACSC), with attenuation correction (AC), and with both attenuation and scatter correction using the triple-energy window method (ACSC). Region-of-interest analysis was performed using the BRASS software (caudate and putamen), and the Southampton method (striatum). The outcome measure was the specific binding ratio (SBR)., Results: A significant effect of age on SBR was found for all data. Gender had a significant effect on SBR in the caudate and putamen for the NOACSC and AC data, and only in the left caudate for the ACSC data (BRASS method). Significant effects of age and gender on striatal SBR were observed for all data analysed with the Southampton method. Overall, there was a significant age-related decline in SBR of between 4 % and 6.7 % per decade., Conclusion: This study provides a large database of [(123)I]FP-CIT SPECT scans in healthy controls across a wide age range and with balanced gender representation. Higher DAT availability was found in women than in men. An average age-related decline in DAT availability of 5.5 % per decade was found for both genders, in agreement with previous reports. The data collected in this study may serve as a reference database for nuclear medicine centres and for clinical trials using [(123)I]FP-CIT SPECT as the imaging marker.

Purpose: To identify the neurobiological traits of amyotrophic lateral sclerosis (ALS) and to elucidate functional differences between ALS of spinal and bulbar onset. We hypothesized that glucose metabolism distribution might vary between groups., Methods: The study groups comprised 32 patients with ALS of either bulbar (n = 13) or spinal (n = 19) onset and 22 subjects as controls. They were investigated by [(18)F]fluorodeoxyglucose (FDG) positron emission tomography (FDG PET), comparing the patient groups with each other and with the controls by statistical parametric mapping., Results: Highly significant relative increases in glucose metabolism distribution were found in the group comprising all 32 ALS patients as compared with the controls in the bilateral amygdalae, midbrain, pons and cerebellum. Relative hypermetabolism was also found in patients with spinal onset as compared with the controls in the right midbrain. In patients with bulbar onset compared with the controls and with patients with spinal onset, large relatively hypometabolic areas were found in the bilateral frontal cortex, right insula, anterior cingulate, precuneus and inferior parietal lobe. Patients with spinal onset had significantly higher scores in a neuropsychological test assessing verbal fluency compared with patients with bulbar onset., Conclusion: This large FDG PET investigation provided unprecedented evidence of relatively increased metabolism in the amygdalae, midbrain and pons in ALS patients as compared with control subjects, possibly due to local activation of astrocytes and microglia. Highly significant relative decreases in metabolism were found in large frontal and parietal regions in the bulbar onset patients as compared with the spinal onset patients and the controls, suggesting a differential metabolic and neuropsychological state between the two conditions.

Cognitive impairment in Parkinson's disease (PD) and atypical parkinsonian syndromes is gaining increased clinical significance. The neurochemical and neuropathological basis in the various parkinsonian forms and even in an individual patient are not fully elucidated yet and could be heterogeneous. Loss of dopaminergic, cholinergic and noradrenergic innervation has been suggested to be the underlying neurochemical deficits for cognitive impairment and dementia in PD, but the onset of cognitive impairment and the progression to dementia may not share the same underlying neurochemical basis. Similarly, pathological evidence is also heterogeneous, ranging from subcortical pathology, limbic or cortical Lewy body type degeneration, and Alzheimer's type pathology that can be found even in the same patient with PD dementia (PDD). Typically, the prototype of early cognitive deficit in PD is a dysexecutive syndrome, but other cognitive domains are more involved when dementia develops, mainly including visuospatial, language and memory dysfunction. Functional radionuclide neuroimaging, by means of single-photon emission computed tomography and positron emission tomography, are contributing to characterize the topographic cortical pattern of cognitive impairment, as well as to define the underlying neurochemical deficit. Lastly, the advent of amyloid PET may help clarifying the meaning of amyloid load in diffuse Lewy body disease and PDD. Knowing the neurochemical and pathophysiological substrate of cognitive deficit in patients with PD or other degenerative Parkinsonisms may help the clinician in understanding the clinical condition of an individual patient in order to plan pharmacological and non-pharmacological intervention. The introduction of acetylcholinesterase inhibitors for therapy of PDD is an example of information integration between clinical-neuropsychological and pathophysiological-neurochemical aspects obtained also with the key contribution of functional neuroimaging.

Purpose: Subtle cognitive impairment is recognized in the first stages of Parkinson's disease (PD), including executive, memory and visuospatial dysfunction, but its pathophysiological basis is still debated., Methods: Twenty-six consecutive, drug-naïve, de novo PD patients underwent an extended neuropsychological battery, dopamine transporter (DAT) and brain perfusion single photon emission computed tomography (SPECT). We previously reported that nigrocaudate impairment correlates with executive functions, and nigroputaminal impairment with visuospatial abilities. Here perfusion SPECT was first compared between the PD group and age-matched controls (CTR). Then, perfusion SPECT was correlated with both DAT SPECT and four neuropsychological factors by means of voxel-based analysis (SPM8) with a height threshold of p < 0.005 at peak level and p < 0.05 false discovery rate-corrected at cluster level. Both perfusion and DAT SPECT images were flipped in order to have the more affected hemisphere (MAH), defined clinically, on the same side., Results: Significant hypoperfusion was found in an occipital area of the MAH in PD patients as compared to CTR. Executive functions directly correlated with brain perfusion in bilateral posterior cingulate cortex and precuneus in the less affected hemisphere (LAH), while verbal memory directly correlated with perfusion in the precuneus, inferior parietal lobule and superior temporal gyrus in the LAH. Furthermore, positive correlation was highlighted between nigrocaudate and nigroputaminal impairment and brain perfusion in the precuneus, posterior cingulate and parahippocampal gyri of the LAH., Conclusion: These data support the evidence showing an early involvement of the cholinergic system in the early cognitive dysfunction and point to a more relevant role of parietal lobes and posterior cingulate in executive functions in PD.

A subtle cognitive impairment can be detected early in the course of Parkinson's disease (PD). Executive, memory and visuospatial functions are specifically affected, but the underlying pathophysiological basis is not well elucidated yet and may be heterogeneous. The recent identification of a PD-related cognitive metabolic pattern (PDCP), including hypometabolism in associative frontal, parietal and posterior limbic structures, has integrated the classical notion of a striato-frontal syndrome at the basis of cognitive dys-function. Recent evidence suggests that whilst executive dys-function is seen in virtually all PD patients, visuospatial and memory impairment may share a higher risk for the subsequent development of dementia. By means of perfusion SPECT and [18F]FDG-PET, cortical dys-function may be highlighted since the early stages, it is more evident in PD patients with Mild Cognitive Impairment (MCI), and reaches the maximum in PD dementia (PDD). Posterior temporo-parieto-occipital dys-function in associative and limbic cortex, closely resembling that found in Alzheimer's disease patients, is found in PDD, with a more severe occipital hypometabolism and a relatively milder hypometabolism in medial temporal lobe structures. Furthermore, deficit of acetylcholinesterase (AchE) can be found by means of [11C]MP4A-PET already in early stage of PD, especially in posterior regions, then becoming more severe in PDD and in dementia with Lewy bodies (DLB). Administration of AchE inhibitors to PDD patients increased brain metabolism in bilateral frontal and left parietal regions, and left posterior cingulate. Finally, the recent availability of radiopharmaceuticals able to disclose amyloid brain deposition has allowed to demonstrate amyloid load in a part of patients with PDD, possibly due to diffuse rather than neuritic plaques. Brain PET and SPECT have strongly contributed to the understanding of the pathophysiology of cognitive impairment in PD and may serve as probes to monitor the effects of therapeutic interventions., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Aim of this study was to investigate the functional compensation mechanism in incipient Alzheimer's disease (AD). Seventeen elderly healthy subjects and nine amnestic MCI patients with incipient AD underwent brain MR scan and 99mTc ECD SPECT. We processed all images with SPM2, we created t maps, showing the wholebrain GM atrophy and functional changes, and we properly masked them with each other in order to assess relatively preserved perfusion or depression. Incipient AD showed GM atrophy in the medial temporal and temporoparietal lobes, in the insula and in the retrosplenial cortex, and GM hypoperfusion in the medial temporal and temporoparietal lobes. Relatively preserved perfusion, we could hypothesize to be compensatory in the setting of neuronal loss, was found in the posterior cingulate, in the head of the hippocampus, in the amigdala, and in the insula bilaterally, while functional depression occurred in bilateral parahippocampal gyri. In AD, a perfusional compensatory mechanism takes place in the neocortex, while perfusional depression occurs in the medial temporal lobe. These results help understand the reactive phenomena induced by the brain to try and counteract the pathological changes of AD., (Copyright 2008 Elsevier Inc. All rights reserved.)

The guidelines summarize the current views of the European Association of Nuclear Medicine Neuroimaging Committee (ENC). The aims of the guidelines are to assist nuclear medicine practitioners in making recommendations, performing, interpreting and reporting the results of clinical dopamine D2 receptor SPECT or PET studies, and to achieve a high quality standard of dopamine D2 receptor imaging, which will increase the impact of this technique in neurological practice.The present document is an update of the first guidelines for SPECT using D2 receptor ligands labelled with (123)I [1] and was guided by the views of the Society of Nuclear Medicine Brain Imaging Council [2], and the individual experience of experts in European countries. The guidelines intend to present information specifically adapted to European practice. The information provided should be taken in the context of local conditions and regulations.

These guidelines summarize the current views of the European Association of Nuclear Medicine Neuroimaging Committee (ENC). The aim of the guidelines is to assist nuclear medicine practitioners when making recommendations, performing, interpreting, and reporting the results of clinical dopamine transporter (DAT) single photon emission computed tomography (SPECT) studies using (123)I-labelled radiopharmaceuticals. The aim is to achieve a high-quality standard of DAT SPECT imaging, which will increase the diagnostic impact of this technique in neurological practice. The present document is an update of the 2002 guidelines [1] and has been guided by the views of various national societies: the Task Group Neuro-Nuclear-Medicine of the German Society of Nuclear Medicine [2], a consensus statement of the imaging centres included in the "Kompetenznetz-Parkinson" sponsored by the German Federal Ministry of Education, and the Task Group of Neuro-Nuclear-Medicine of the French Society of Nuclear Medicine [3]. The guidelines reflect the individual experience of experts in European countries. The guidelines are intended to present information specifically adapted to European practice. The information provided should be taken in the context of local conditions and regulations.