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Background: Neuronal pentraxin-2 (NPTX2), crucial for synaptic functioning, declines in cerebrospinal fluid (CSF) as cognition deteriorates. The variations of CSF NPTX2 across mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and its association with brain metabolism remain elusive, albeit relevant for patient stratification and pathophysiological insights., Methods: We retrospectively analyzed 49 MCI-AD patients grouped by time until dementia (EMCI, n = 34 progressing within 2 years; LMCI, n = 15 progressing later/stable at follow-up). We analyzed demographic variables, cognitive status (MMSE score), and CSF NPTX2 levels using a commercial ELISA assay in EMCI, LMCI, and a control group of age-/sex-matched individuals with other non-dementing disorders (OND). Using [ 18 F]FDG PET scans for voxel-based analysis, we explored correlations between regional brain metabolism metrics and CSF NPTX2 levels in MCI-AD patients, accounting for age., Results: Baseline and follow-up MMSE scores were lower in LMCI than EMCI (p value = 0.006 and p < 0.001). EMCI exhibited significantly higher CSF NPTX2 values than both LMCI (p = 0.028) and OND (p = 0.006). We found a significant positive correlation between NPTX2 values and metabolism of bilateral precuneus in MCI-AD patients (p < 0.005 at voxel level, p < 0.05 with family-wise error correction at the cluster level)., Conclusions: Higher CSF NPTX2 in EMCI compared to controls and LMCI suggests compensatory synaptic responses to initial AD pathology. Disease progression sees these mechanisms overwhelmed, lowering CSF NPTX2 approaching dementia. Positive CSF NPTX2 correlation with precuneus glucose metabolism links to AD-related metabolic changes across MCI course. These findings posit CSF NPTX2 as a promising biomarker for both AD staging and progression risk stratification., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)

Purpose: Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA)., Methods: FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level., Results: Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R 2  = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912)., Conclusion: Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset., (© 2023. The Author(s).)

Background: SOMI (Stages of Objective Memory Impairment) is a novel classification that identifies six stages of memory decline in Alzheimer's Disease (AD) using the Free and Cued Selective Reminding Test (FCSRT). However, the relationship between SOMI stages and brain metabolism remains unexplored. This study aims to investigate the metabolic correlates of SOMI stages using FDG-PET in Mild Cognitive Impairment due to AD (MCI-AD) and early AD patients., Methods: One hundred twenty-nine-patients (99 aMCI-AD and 30 AD), and 42 healthy controls (HCs) (MMSE = 29.2 ± .8; age:69.1 ± 8.6 years; education:10.7 ± 3.8 years) who underwent an extensive neuropsychological battery including FCSRT and brain FDG-PET were enrolled. According to their clinical relevance and available sample sizes, SOMI-4 (N = 24 subjects; MMSE score:26.6 ± 2.6: age:75.4 ± 3.2; education:9.9 ± 4.5) and SOMI-5 groups (N = 97; MMSE:25.3 ± 2.6; age:73.9 ± 5.8; education:9.4 ± 4.1) were investigated., Results: Compared to HCs, SOMI-4 showed hypometabolism in the precuneus, medial temporal gyrus bilaterally, right pecuneus and angular gyrus. SOMI-5 exhibited broader hypometabolism, extending to the left posterior cingulate and medial frontal gyrus bilaterally. The conjunction analysis revealed overlapping areas in the precuneus, medial temporal gyrus bilaterally, and in the right angular gyrus and cuneus. The disjunction analysis identified SOMI-5 specific hypometabolism encompassing left inferior temporal gyrus, uncus and parahippocampal gyrus, and medial frontal gyrus bilaterally (p < .001, p-value (FWE) < .05)., Discussion: SOMI-4 relates to posterior hypometabolism, while SOMI-5 to more extensive hypometabolism further encompassing frontal cortices, suggesting SOMI as a biologically relevant classification system of memory decline., Conclusion: Memory decline staged with SOMI is associated with hypometabolism spreading in amnesic MCI-AD/AD, suggesting its usefulness as a clinical marker of increasing neurodegeneration., Competing Interests: Declaration of competing interest Dr. Pardini reports research support from Novartis and Nutricia and speakers fees from GEBiogen and Merk. Dr. Arnaldi reports speakers fee from Fidia. Dr. Morbelli reports speakers fees GE. All other authors do not report significant conflicts of interest., (Copyright © 2023. Published by Elsevier Ltd.)

Background: Discrepancy between caregiver and patient assessments of apathy in mild cognitive impairment (MCI) is considered an index of apathy unawareness, independently predicting progression to AD dementia. However, its neural underpinning are uninvestigated., Objective: To explore the [18F]FDG PET-based metabolic correlates of apathy unawareness measured through the discrepancy between caregiver and patient self-report, in patients diagnosed with MCI., Methods: We retrospectively studied 28 patients with an intermediate or high likelihood of MCI-AD, progressed to dementia over an average of two years, whose degree of apathy was evaluated by means of the Apathy Evaluation Scale (AES) for both patients (PT-AES) and caregivers (CG-AES). Voxel-based analysis at baseline was used to obtain distinct volumes of interest (VOIs) correlated with PT-AES, CG-AES, or their absolute difference (DISCR-AES). The resulting DISCR-AES VOI count densities were used as covariates in an inter-regional correlation analysis (IRCA) in MCI-AD patients and a group of matched healthy controls (HC)., Results: DISCR-AES negatively correlated with metabolism in bilateral parahippocampal gyrus, posterior cingulate cortex, and thalamus, PT-AES score with frontal and anterior cingulate areas, while there was no significant correlation between CG-AES and brain metabolism. IRCA revealed that MCI-AD patients exhibited reduced metabolic/functional correlations of the DISCR-AES VOI with the right cingulate gyrus and its anterior projections compared to HC., Conclusions: Apathy unawareness entails early disruption of the limbic circuitry rather than the classical frontal-subcortical pathways typically associated with apathy. This reaffirms apathy unawareness as an early and independent measure in MCI-AD, marked by distinct pathophysiological alterations.

Amyloid plaques are a neuropathologic hallmark of Alzheimer's disease (AD), which can be imaged through positron emission tomography (PET) technology using radiopharmaceuticals that selectively bind to the fibrillar aggregates of amyloid-β plaques (Amy-PET). Several radiotracers for amyloid PET have been validated ( 11 C-Pittsburgh compound B and the 18 F-labeled compounds such as 18 F-florbetaben, 18 F-florbetapir, and 18 F-flutemetamol). Images can be interpreted by means of visual/qualitative, semiquantitative, and quantitative criteria. Here, we summarize the main differences between the available radiotracers for Amy-PET, the proposed interpretation criteria, and main proposed quantification methods., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: A cut-off of -2 z-score for striatal or putaminal SBR has been to date arbitrarily used to define an abnormal DaT SPECT in patients with suspected neurodegenerative parkinsonism. We aimed to experimentally identify the most accurate z-score cut-offs for SBR of striatal and substriatal regions to independently discriminate PD and DLB, with respect to essential tremor (ET) and Alzheimer's disease (AD) respectively., Methods: Two-hundred twenty-five patients undergoing DaT SPECT were enrolled (seventy-five de novo PD, eighty ET, fifty DLB, and twenty AD). Semiquantification was computed by means of Datquant® software which returns measures of striatal SBR and z-scores with respect to 118 healthy volunteers belonging to the Parkinson's Progression Markers Initiative (PPMI). ROC analysis was used to identify most accurate cut-offs for z-score for striatum and substriatal regions (clinical diagnosis at follow-up as gold standard)., Results: Posterior putamen of the most affected hemisphere (MAH) with a z-score cut-off of  - 1.27 demonstrated the highest accuracy to differentiate between PD and ET (sensitivity 0.97, specificity 0.94). The whole putamen (z-score cut-off  - 0.96) was the most accurate parameter to support the diagnosis of DLB (sensitivity 0.74, specificity 0.95). Putamen to caudate ratio was accurate to detect PD (especially in early stages) while not DLB patients., Conclusion: We experimentally demonstrated that different substriatal regions and cut-offs for z-score of SBR should be considered to support the diagnosis of either PD or DLB. The identified less conservative cut-offs showed higher sensitivity without a measurable reduction in specificity with respect to the arbitrary  - 2 z-score., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: To date, there is no consensus on how to semi-quantitatively assess brain amyloid PET. Some approaches use late acquisition alone (e.g., ELBA, based on radiomic features), others integrate the early scan (e.g., TDr, which targets the area of maximum perfusion) and structural imaging (e.g., WMR, that compares kinetic behaviour of white and grey matter, or SI based on the kinetic characteristics of the grey matter alone). In this study SUVr, ELBA, TDr, WMR, and SI were compared. The latter - the most complete one - provided the reference measure for amyloid burden allowing to assess the efficacy and feasibility in clinical setting of the other approaches., Methods: We used data from 85 patients (aged 44-87) who underwent dual time-point PET/MRI acquisitions. The correlations with SI were computed and the methods compared with the visual assessment. Assuming SUVr, ELBA, TDr, and WMR to be independent measures, we linearly combined them to obtain more robust indices. Finally, we investigated possible associations between each quantifier and age in amyloid-negative patients., Results: Each quantifier exhibited excellent agreement with visual assessment and strong correlation with SI (average AUC = 0.99, ρ = 0.91). Exceptions to this were observed for subcortical regions with ELBA and WMR (ρ ELBA  = 0.44, ρ WMR  = 0.70). The linear combinations showed better performances than the individual methods. Significant associations were observed between TDr, WMR, SI, and age in amyloid-negative patients (p < 0.05)., Conclusion: Among the other methods, TDr came closest to the reference with less implementation complexity. Moreover, this study suggests that combining independent approaches gives better results than the individual procedure, so efforts should focus on multi-classifier systems for amyloid PET. Finally, the ability of techniques integrating blood perfusion to depict age-related variations in amyloid load in amyloid-negative subjects demonstrates the goodness of the estimate., (© 2022. The Author(s).)

We explored the brain metabolism correlates of emergent cerebrospinal fluid (CSF) biomarkers in a group of 26 patients with prodromal Alzheimer's disease (AD). Distinct volumes of interest (VOIs) expressed the sites of correlation between CSF biomarkers and brain metabolism as determined on [ 18 F]FDG-PET images, as well as of significant hypometabolism in patients compared to healthy controls. Neurogranin- and α-synuclein-VOIs included left precuneus and/or posterior cingulate cortex (PC and/or PCC) and partially overlapped hypometabolism at those sites. β-synuclein- and neurofilament light chain (NfL)-VOIs regarded either left or right lateral temporal areas, respectively, with partial overlap with hypometabolism only for the β-synuclein-VOI, whereas the NfL-VOI did not include hypometabolic regions. We speculate that CSF neurogranin and α-synuclein express an already established hippocampal damage leading to PC and/or PCC deafferentation and hypometabolism. β-synuclein may represent the progression of synaptopathy in the temporal lobe, while NfL the axonal injury in right temporal regions where neuronal loss is not yet evident., (Copyright © 2022. Published by Elsevier Inc.)

Importance: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design., Objective: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates., Design, Setting, and Participants: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria., Exposures: Alzheimer disease biomarkers detected on PET or in CSF., Main Outcomes and Measures: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations., Results: Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18)., Conclusions and Relevance: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.

Purpose: FDG-PET is an established supportive biomarker in dementia with Lewy bodies (DLB), but its diagnostic accuracy is unknown at the mild cognitive impairment (MCI-LB) stage when the typical metabolic pattern may be difficultly recognized at the individual level. Semiquantitative analysis of scans could enhance accuracy especially in less skilled readers, but its added role with respect to visual assessment in MCI-LB is still unknown., Methods: We assessed the diagnostic accuracy of visual assessment of FDG-PET by six expert readers, blind to diagnosis, in discriminating two matched groups of patients (40 with prodromal AD (MCI-AD) and 39 with MCI-LB), both confirmed by in vivo biomarkers. Readers were provided in a stepwise fashion with (i) maps obtained by the univariate single-subject voxel-based analysis (VBA) with respect to a control group of 40 age- and sex-matched healthy subjects, and (ii) individual odds ratio (OR) plots obtained by the volumetric regions of interest (VROI) semiquantitative analysis of the two main hypometabolic clusters deriving from the comparison of MCI-AD and MCI-LB groups in the two directions, respectively., Results: Mean diagnostic accuracy of visual assessment was 76.8 ± 5.0% and did not significantly benefit from adding the univariate VBA map reading (77.4 ± 8.3%) whereas VROI-derived OR plot reading significantly increased both accuracy (89.7 ± 2.3%) and inter-rater reliability (ICC 0.97 [0.96-0.98]), regardless of the readers' expertise., Conclusion: Conventional visual reading of FDG-PET is moderately accurate in distinguishing between MCI-LB and MCI-AD, and is not significantly improved by univariate single-subject VBA but by a VROI analysis built on macro-regions, allowing for high accuracy independent of reader skills., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Mild cognitive impairment (MCI) is a heterogeneous condition. Idiopathic REM sleep behavior disorder (iRBD) can be associated with MCI (MCI-RBD)., Objective: To investigate neuropsychological and brain metabolism features of patients with MCI-RBD by comparison with matched MCI-AD patients. To explore their predictive value toward conversion to a full-blown neurodegenerative disease., Methods: Seventeen MCI-RBD patients (73.6±6.5 years) were enrolled. Thirty-four patients with MCI-AD were matched for age (74.8±4.4 years), Mini-Mental State Exam score and education with a case-control criterion. All patients underwent a neuropsychological assessment and brain 18F-FDG-PET. Images were compared between groups to identify hypometabolic volumes of interest (MCI-RBD-VOI and MCI-AD-VOI). The dependency of whole-brain scaled metabolism levels in MCI-RBD-VOI and MCI-AD-VOI on neuropsychological test scores was explored with linear regression analyses in both groups, adjusting for age and education. Survival analysis was performed to investigate VOIs phenoconversion prediction power., Results: MCI-RBD group scored lower in executive functions and higher in verbal memory compared to MCI-AD group. Also, compared with MCI-AD, MCI-RBD group showed relative hypometabolism in a posterior brain area including cuneus, precuneus, and occipital regions while the inverse comparison revealed relative hypometabolism in the hippocampus/parahippocampal areas in MCI-AD group. MCI-RBD-VOI metabolism directly correlated with executive functions in MCI-RBD (p = 0.04). MCI-AD-VOI metabolism directly correlated with verbal memory in MCI-AD (p = 0.001). MCI-RBD-VOI metabolism predicted (p = 0.03) phenoconversion to an alpha-synucleinopathy. MCI-AD-VOI metabolism showed a trend (p = 0.07) in predicting phenoconversion to dementia., Conclusion: MCI-RBD and MCI-AD showed distinct neuropsychological and brain metabolism profiles, that may be helpful for both diagnosis and prognosis purposes.

Purpose: The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer's disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimer's disease (MCI-AD), and cognitively normal (CN) using fluorine 18 fluorodeoxyglucose PET (18F-FDG PET) and compare model's performance to that of multiple expert nuclear medicine physicians' readers., Materials and Methods: Retrospective 18F-FDG PET scans for AD, MCI-AD, and CN were collected from Alzheimer's disease neuroimaging initiative (556 patients from 2005 to 2020), and CN and DLB cases were from European DLB Consortium (201 patients from 2005 to 2018). The introduced 3D convolutional neural network was trained using 90% of the data and externally tested using 10% as well as comparison to human readers on the same independent test set. The model's performance was analyzed with sensitivity, specificity, precision, F1 score, receiver operating characteristic (ROC). The regional metabolic changes driving classification were visualized using uniform manifold approximation and projection (UMAP) and network attention., Results: The proposed model achieved area under the ROC curve of 96.2% (95% confidence interval: 90.6-100) on predicting the final diagnosis of DLB in the independent test set, 96.4% (92.7-100) in AD, 71.4% (51.6-91.2) in MCI-AD, and 94.7% (90-99.5) in CN, which in ROC space outperformed human readers performance. The network attention depicted the posterior cingulate cortex is important for each neurodegenerative disease, and the UMAP visualization of the extracted features by the proposed model demonstrates the reality of development of the given disorders., Conclusion: Using only 18F-FDG PET of the brain, a 3D deep learning model could predict the final diagnosis of the most common neurodegenerative disorders which achieved a competitive performance compared to the human readers as well as their consensus., (© 2021. The Author(s).)

Background: Neuropsychological assessment is still the basis for the first evaluation of patients with cognitive complaints. The Free and Cued Selective Reminding Test (FCSRT) generates several indices that could have different accuracy in the differential diagnosis between Alzheimer's disease (AD) and other disorders., Objective: In a consecutive series of naturalistic patients, the accuracy of the FCSRT indices in differentiating patients with either mild cognitive impairment (MCI) due to AD or AD dementia from other competing conditions was evaluated., Methods: We evaluated the accuracy of the seven FCSRT indices in differentiating patients with AD from other competing conditions in 434 consecutive outpatients, either at the MCI or at the early dementia stage. We analyzed these data through the receiver operating characteristics curve, and we then generated the odds-ratio map of the two indices with the best discriminative value between pairs of disorders., Results: The immediate and the delayed free total recall, the immediate total recall, and the index of sensitivity of cueing were the most useful indices and allowed to distinguish AD from dementia with Lewy bodies and psychiatric conditions with very high accuracy. Accuracy was instead moderate in distinguishing AD from behavioral variant frontotemporal dementia, vascular cognitive impairment, and other conditions., Conclusion: By using odd-ratio maps and comparison-customized cut-off scores, we confirmed that the FCSRT represents a useful tool to characterize the memory performance of patients with MCI and thus to assist the clinician in the diagnosis process, though with different accuracy values depending on the clinical hypothesis.

Introduction: We assessed the influence of education as a proxy of cognitive reserve and age on the dementia with Lewy bodies (DLB) metabolic pattern., Methods: Brain 18F-fluorodeoxyglucose positron emission tomography and clinical/demographic information were available in 169 probable DLB patients included in the European DLB-consortium database. Principal component analysis identified brain regions relevant to local data variance. A linear regression model was applied to generate age- and education-sensitive maps corrected for Mini-Mental State Examination score, sex (and either education or age)., Results: Age negatively covaried with metabolism in bilateral middle and superior frontal cortex, anterior and posterior cingulate, reducing the expression of the DLB-typical cingulate island sign (CIS). Education negatively covaried with metabolism in the left inferior parietal cortex and precuneus (making the CIS more prominent)., Discussion: These findings point out the importance of tailoring interpretation of DLB biomarkers considering the concomitant effect of individual, non-disease-related variables such as age and cognitive reserve., (© 2021 the Alzheimer's Association.)

From previous studies in healthy volunteers the prefrontal regions are deeply involved in prospective memory (PM), although little is known about the functional neural basis of PM in prodromal Alzheimer's disease (AD). To this end, we retrospectively recruited 18 patients with mild cognitive impairment caused by AD and 23 matched healthy control subjects who had undergone 18 F-fluorodeoxyglucose positron emission tomography and the PM-specific paradigm test. Brain metabolism was correlated with the PM score in the 2 groups separately to find those brain areas correlated with PM performance, which were then used as a hub for an inter-regional metabolic connectivity analyses (inter-regional correlation analysis). Of note, in mild cognitive impairment caused by AD, but not in healthy control subjects, PM score positively correlated with metabolic levels in the right anterior prefrontal cortex (middle and inferior frontal gyri), which disclosed a loss of interhemispheric connectivity in the inter-regional correlation analysis. According to our findings, the functioning of the right anterior prefrontal cortex and its interhemispheric metabolic connectivity is crucial in early AD to sustain PM performance, which deteriorates along with progressive metabolic failure of the interconnected areas., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Three different amyloid tracers labeled with 18-flourine have been introduced into clinical use. The leaflets of tracers indicate different visual criteria for PET reporting. In clinical practice, it is not yet ascertained whether these criteria are equivalent in terms of diagnostic accuracy or if anyone is better than another. We aimed to evaluate the inter and intra-rater variability of visual assessment of 18 F-Florbetapir PET/CT images among six independent readers with different clinical experience., Methods: We analyzed 252 PET/CT scans, visually assessed by each reader three times, applying independently the three different reading criteria proposed. Each reader evaluated the regional uptake specifying for each cortical region a numeric value of grading of positivity in order to assign a final score. At the end of each reading a level of confidence was determined by assigning a score from 0 (negative) to 4 (positive). After first reading, those cases in which the evaluations by two experienced readers did not match (discordant cases) were independently reevaluated merging all the three different visual interpretation criteria., Results: Good agreement was observed for visual interpretation among the six readers' confidence-level using independently the three visual reading criteria: ICC=0.83 (0.80-0.86) for 18 F-florbetapir, ICC=0.84 (0.81-0.87) for 18 F-florbetaben, and ICC=0.86 (0.83-0.88) for 18 F-flutemetamol reading. A good inter-rater agreement was observed for final-score too: ICC=0.74 (0.70-0.78) for 18 F-florbetapir; ICC=0.82 (0.79-0.85) for 18 F-florbetaben; ICC=0.84 (0.81-0.87) for 18 F-flutemetamol. Intra-rater agreement was good for final-score (from 0.76 to 0.90; P<0.001) and confidence-level (Spearman's rho from 0.89 to 1.00; P<0.001). Disagreement between the two experienced readers was observed in 22 of 252 cases (9%). The agreement converged over a second round of independent reading in 12 of 22 cases (54%), by merging all the criteria., Conclusions: All the criteria proposed are useful to determine the grading of positivity or negativity of amyloid deposition and their merging improves the diagnostic confidence and provides a better agreement.

Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and 18 F-fluorodeoxyglucose ( 18 F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloid-PET and 18 F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Purpose: To compare the incremental diagnostic value of amyloid-PET and CSF (Aβ42, tau, and phospho-tau) in AD diagnosis in patients with mild cognitive impairment (MCI) or mild dementia, in order to improve the definition of diagnostic algorithm., Methods: Two independent dementia experts provided etiological diagnosis and relative diagnostic confidence in 71 patients on 3 rounds, based on (1) clinical, neuropsychological, and structural MRI information alone; (2) adding one biomarker (CSF amyloid and tau levels or amyloid-PET with a balanced randomized design); and (3) adding the other biomarker., Results: Among patients with a pre-biomarker diagnosis of AD, negative PET induced significantly more diagnostic changes than amyloid-negative CSF at both rounds 2 (CSF 67%, PET 100%, P = 0.028) and 3 (CSF 0%; PET 78%, P < 0.001); PET induced a diagnostic confidence increase significantly higher than CSF on both rounds 2 and 3., Conclusions: Amyloid-PET should be prioritized over CSF biomarkers in the diagnostic workup of patients investigated for suspected AD, as it provides greater changes in diagnosis and diagnostic confidence., Trial Registration: EudraCT no.: 2014-005389-31.

Objective: Automated voxel-based analysis methods are used to detect cortical hypometabolism typical of Alzheimer's Disease (AD) on FDG-PET brain scans. We compared the accuracy of two clinically validated tools for their ability to identify those MCI subjects progressing to AD at followup, to evaluate the impact of the analysis method on FDG-PET diagnostic performance., Methods: SPMGrid and BRASS (Hermes Medical Solutions, Stockholm, Sweden) were tested on 131 MCI and elderly healthy controls from the EADC PET dataset. The concordance between the tools was tested by correlating the quantitative parameters (z- and t-values), calculated by the two software tools, and by measuring the topographical overlap of the abnormal regions (Dice score). Three independent expert readers blindly assigned a diagnosis based on the two map sets. We used conversion to AD dementia as the gold standard., Results: The t-map and z-map calculated with SPMGrid and BRASS, respectively, showed a good correlation (R > .50) for the majority of individual cases (128/131) and for the majority of selected regions of interest (ROIs) (98/116). The overlap of the hypometabolic patterns from the two tools was, however, poor (Dice score .36). The diagnostic performance was comparable, with BRASS showing significantly higher sensitivity (.82 versus .59) and SPMGrid showing higher specificity (.87 versus .52)., Conclusion: Despite similar diagnostic performance in predicting conversion to AD in MCI subjects, the two tools showed significant differences, and the maps provided by the tools showed limited overlap. These results underline the urgency for standardization across FDG-PET analysis methods for their use in clinical practice., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

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: 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: 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.

Background: A corollary of the reserve hypothesis is that what is regarded as pathological cortical metabolism in patients might vary according to education., Objective: The aim of this study is to assess the incremental diagnostic value of education-adjusted over unadjusted thresholds on the diagnostic accuracy of FDG-PET as a biomarker for Alzheimer disease (AD)., Methods: We compared cortical metabolism in 90 healthy controls and 181 AD patients from the Alzheimer Disease Neuroimaging Initiative (ADNI) database. The AUC of the ROC curve did not differ significantly between the whole group and the higher-education patients or the lower-education subjects., Results: The threshold of wMetaROI values providing 80% sensitivity was lower in higher-education patients and higher in the lower-education patients, compared to the standard threshold derived over the whole AD collective, without, however, significant changes in sensitivity and specificity., Conclusion: These data show that education, as a proxy of reserve, is not a major confounder in the diagnostic accuracy of FDG-PET in AD and the adoption of education-adjusted thresholds is not required in daily practice., (© 2018 S. Karger AG, Basel.)

Amyloid plaques are a neuropathologic hallmark of Alzheimer's disease (AD), which can be imaged through positron emission tomography (PET) technology using radiopharmaceuticals that selectively bind to the fibrillar aggregates of amyloid-β plaques (Amy-PET). Several radiotracers for amyloid PET have been investigated, including 11 C-Pittsburgh compound B and the 18 F-labeled compounds such as 18 F-florbetaben, 18 F-florbetapir, and 18 F-flutemetamol. Besides the injected radiotracer, images can be interpreted by means of visual/qualitative, semiquantitative, and quantitative criteria. Here we summarize the main differences between the available radiotracers for Amy-PET, the proposed interpretation criteria, and analytical methods.

Over the last 20 years the availability of magnetic resonance imaging and positron-emission tomography technologies as well as of cerebrospinal fluid biomarkers has allowed research and clinical approach to Alzheimer's disease (AD) to move towards the earliest manifestations of the disease. This new approach resulted in an increasing knowledge about in-vivo biological and neuropathological processes of each phase of the AD-related damage from preclinical, to mild cognitive impairment, and finally to dementia due to AD. The present narrative review deals with the available data as well as with the unsolved issued related to the incorporation of AD biomarkers into the clinical practice. Ongoing research efforts aiming to better define and implement the use of imaging AD biomarkers in clinical practice according to a patient-centered approach and sustainability for clinical-care systems are also discussed.

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.

Purpose: Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer's disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not., Methods: FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy., Results: The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients., Conclusion: In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD.

Purpose: We aimed to identify the cortical regions where hypometabolism can predict the speed of conversion to dementia in mild cognitive impairment due to Alzheimer's disease (MCI-AD)., Methods: We selected from the clinical database of our tertiary center memory clinic, eighty-two consecutive MCI-AD that underwent 18F-fluorodeoxyglucose (FDG) PET at baseline during the first diagnostic work-up and were followed up at least until their clinical conversion to AD dementia. The whole group of MCI-AD was compared in SPM8 with a group of age-matched healthy controls (CTR) to verify the presence of AD diagnostic-pattern; then the correlation between conversion time and brain metabolism was assessed to identify the prognostic-pattern. Significance threshold was set at p < 0.05 False-Discovery-Rate (FDR) corrected at peak and at cluster level. Each MCI-AD was then compared with CTR by means of a SPM single-subject analysis and grouped according to presence of AD diagnostic-pattern and prognostic-pattern. Kaplan-Meier-analysis was used to evaluate if diagnostic- and/or prognostic-patterns can predict speed of conversion to dementia., Results: Diagnostic-pattern corresponded to typical posterior hypometabolism (BA 7, 18, 19, 30, 31 and 40) and did not correlate with time to conversion, which was instead correlated with metabolic levels in right middle and inferior temporal gyri as well as in the fusiform gyrus (prognostic-pattern, BA 20, 21 and 38). At Kaplan-Meier analysis, patients with hypometabolism in the prognostic pattern converted to AD-dementia significantly earlier than patients not showing significant hypometabolism in the right middle and inferior temporal cortex (9 versus 19 months; Log rank p < 0.02, Breslow test: p < 0.003, Tarone-Ware test: p < 0.007)., Conclusion: The present findings support the role of FDG PET as a robust progression biomarker even in a naturalist population of MCI-AD. However, not the AD-typical diagnostic-pattern in posterior regions but the middle and inferior temporal metabolism captures speed of conversion to dementia in MCI-AD since baseline. The highlighted prognostic pattern is a further, independent source of heterogeneity in MCI-AD and affects a primary-endpoint on interventional clinical trials (time of conversion to dementia).

We investigated whether dementia risk factors were associated with prodromal Alzheimer's disease (AD) according to the International Working Group-2 and National Institute of Aging-Alzheimer's Association criteria, and with cognitive decline. A total of 1394 subjects with mild cognitive impairment from 14 different studies were classified according to these research criteria, based on cognitive performance and biomarkers. We compared the frequency of 10 risk factors between the subgroups, and used Cox-regression to examine the effect of risk factors on cognitive decline. Depression, obesity, and hypercholesterolemia occurred more often in individuals with low-AD-likelihood, compared with those with a high-AD-likelihood. Only alcohol use increased the risk of cognitive decline, regardless of AD pathology. These results suggest that traditional risk factors for AD are not associated with prodromal AD or with progression to dementia, among subjects with mild cognitive impairment. Future studies should validate these findings and determine whether risk factors might be of influence at an earlier stage (i.e., preclinical) of AD., (Copyright © 2017 Elsevier Inc. All rights reserved.)

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 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.)

Three sets of research criteria are available for diagnosis of Alzheimer's disease in subjects with mild cognitive impairment: the International Working Group-1, International Working Group-2, and National Institute of Aging-Alzheimer Association criteria. We compared the prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage according to these criteria. Subjects with mild cognitive impairment (n = 1607), 766 of whom had both amyloid and neuronal injury markers, were recruited from 13 cohorts. We used cognitive test performance and available biomarkers to classify subjects as prodromal Alzheimer's disease according to International Working Group-1 and International Working Group-2 criteria and in the high Alzheimer's disease likelihood group, conflicting biomarker groups (isolated amyloid pathology or suspected non-Alzheimer pathophysiology), and low Alzheimer's disease likelihood group according to the National Institute of Ageing-Alzheimer Association criteria. Outcome measures were the proportion of subjects with Alzheimer's disease at the mild cognitive impairment stage and progression to Alzheimer's disease-type dementia. We performed survival analyses using Cox proportional hazards models. According to the International Working Group-1 criteria, 850 (53%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 50% compared to 21% for subjects without prodromal Alzheimer's disease. According to the International Working Group-2 criteria, 308 (40%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 61% compared to 22% for subjects without prodromal Alzheimer's disease. According to the National Institute of Ageing-Alzheimer Association criteria, 353 (46%) subjects were in the high Alzheimer's disease likelihood group, 49 (6%) in the isolated amyloid pathology group, 220 (29%) in the suspected non-Alzheimer pathophysiology group, and 144 (19%) in the low Alzheimer's disease likelihood group. The 3-year progression rate to Alzheimer's disease-type dementia was 59% in the high Alzheimer's disease likelihood group, 22% in the isolated amyloid pathology group, 24% in the suspected non-Alzheimer pathophysiology group, and 5% in the low Alzheimer's disease likelihood group. Our findings support the use of the proposed research criteria to identify Alzheimer's disease at the mild cognitive impairment stage. In clinical settings, the use of both amyloid and neuronal injury markers as proposed by the National Institute of Ageing-Alzheimer Association criteria offers the most accurate prognosis. For clinical trials, selection of subjects in the National Institute of Ageing-Alzheimer Association high Alzheimer's disease likelihood group or the International Working Group-2 prodromal Alzheimer's disease group could be considered., (© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

We aimed to investigate the accuracy of FDG-PET to detect the Alzheimer's disease (AD) brain glucose hypometabolic pattern in 142 patients with amnestic mild cognitive impairment (aMCI) and 109 healthy controls. aMCI patients were followed for at least two years or until conversion to dementia. Images were evaluated by means of visual read by either moderately-skilled or expert readers, and by means of a summary metric of AD-like hypometabolism (PALZ score). Seventy-seven patients converted to AD-dementia after 28.6 ± 19.3 months of follow-up. Expert reading was the most accurate tool to detect these MCI converters from healthy controls (sensitivity 89.6%, specificity 89.0%, accuracy 89.2%) while two moderately-skilled readers were less (p < 0.05) specific (sensitivity 85.7%, specificity 79.8%, accuracy 82.3%) and PALZ score was less (p < 0.001) sensitive (sensitivity 62.3%, specificity 91.7%, accuracy 79.6%). Among the remaining 67 aMCI patients, 50 were confirmed as aMCI after an average of 42.3 months, 12 developed other dementia, and 3 reverted to normalcy. In 30/50 persistent MCI patients, the expert recognized the AD hypometabolic pattern. In 13/50 aMCI, both the expert and PALZ score were negative while in 7/50, only the PALZ score was positive due to sparse hypometabolic clusters mainly in frontal lobes. Visual FDG-PET reads by an expert is the most accurate method but an automated, validated system may be particularly helpful to moderately-skilled readers because of high specificity, and should be mandatory when even a moderately-skilled reader is unavailable.

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.

Unlabelled: This project aimed to investigate the metabolic basis for resilience to neurodegeneration (cognitive reserve) in highly educated patients with prodromal Alzheimer disease (AD)., Methods: Sixty-four patients with amnestic mild cognitive impairment who later converted to AD dementia during follow-up, and 90 controls, underwent brain (18)F-FDG PET. Both groups were divided into a poorly educated subgroup (42 controls and 36 prodromal AD patients) and a highly educated subgroup (48 controls and 28 prodromal AD patients). Brain metabolism was first compared between education-matched groups of patients and controls. Then, metabolism was compared between highly and poorly educated prodromal AD patients in both directions to identify regions of high education-related metabolic depression and compensation. The clusters of significant depression and compensation were further used as volumetric regions of interest (ROIs) in a brain interregional correlation analysis in each prodromal AD subgroup to explore metabolic connectivity. All analyses were performed by means of SPM8 (P < 0.001 uncorrected at peak level, P < 0.05 false discovery rate-corrected at cluster level; age, sex, Mini-Mental State Examination score, and center as nuisance)., Results: Highly educated prodromal AD patients showed more severe hypometabolism than poorly educated prodromal AD patients in the left inferior and middle temporal gyri and the left middle occipital gyrus (ROI depression). Conversely, they showed relative hypermetabolism in the right inferior, middle, and superior frontal gyri (ROI compensation). The sites of compensation, mainly corresponding to the right dorsolateral prefrontal cortex (DLFC), showed wide metabolic correlations with several cortical areas in both hemispheres (frontotemporal cortex, parahippocampal gyrus, and precuneus) in highly educated prodromal AD patients but not in poorly educated prodromal AD patients. To provide evidence on whether these metabolic correlations represent preservation of the physiologic networks of highly educated control subjects (neural reserve) or rather the recruitment of alternative networks (neural compensation), or a combination of the two, we performed metabolic connectivity analysis of the DLFC in highly educated controls as well. The correlation sites of right DLFC partly overlapped those of highly educated prodromal AD patients but were less extended., Conclusion: The present findings suggest that highly educated prodromal AD patients can cope better with the disease thanks to neural reserve but also to the recruitment of compensatory neural networks in which the right DLFC plays a key role.

We explored resting-state metabolic connectivity in prodromal Alzheimer's disease (pAD) patients and in healthy controls (CTR), through a voxel-wise interregional correlation analysis of 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) by means of statistical parametric mapping. Baseline 18F-fluorodeoxyglucose-positron emission tomography of 36 patients with amnestic mild cognitive impairment who converted to Alzheimer's disease (AD) dementia after an average time of 2 years (pAD) and of 105 CTR were processed. The area of hypometabolism in pAD showed less metabolic connectivity in patients than in CTR (autocorrelation and correlation with large temporal and frontal areas, respectively). pAD patients showed limited correlation even in selected nonhypometabolic areas, including the hippocampi and the dorsolateral prefrontal cortex (DLFC). On the contrary, in CTR group correlation was highlighted between hippocampi and precuneus/posterior cingulate and frontal cortex, and between dorsolateral prefrontal cortex and caudate nuclei and parietal cortex. The reduced metabolic connections both in hypometabolic and nonhypometabolic areas in pAD patients suggest that metabolic disconnection (reflecting early diaschisis) may antedate remote hypometabolism (early sign of synaptic degeneration)., (Copyright © 2012 Elsevier Inc. All rights reserved.)

This study describes late-onset Alzheimer's disease (LOAD) in the mild cognitive impairment (MCI) stage, debuting with seizures in a 72 year-old woman. Prodromal AD was consistently diagnosed with four among amyloidosis and neurodegeneration biomarkers about 1 year after onset of seizures. Genetic assessment demonstrated apolipoprotein E ε2/ε3 genotype and three intronic single nucleotide substitutions, two in presenilin 1 and one in amyloid-β protein precursor genes. This case of seizures at onset of LOAD with severe signs of brain amyloidosis and neurodegeneration but with just MCI leads to a re-appraisal of the intriguing relationship between AD pathology and neuron excitability in humans.

To unveil the brain metabolic correlates of (un)awareness of memory deficit in subjects with amnestic mild cognitive impairment (aMCI), forty-two outpatients underwent brain 18F-FDG-PET. Awareness of memory deficit was assessed with the Memory Complaint Questionnaire (MAC-Q), identifying two groups: low (MCI/unaware; 17 patients) and good (MCI/aware; 25 patients) aMCI awareness. Twenty-nine age-matched healthy subjects represented the control group. SPM2 was used to assess the correlation between brain metabolism and MAC-Q score, for comparisons between each patient group and controls, and between aMCI/unaware and aMCI/aware groups. The two aMCI groups were comparable in terms of age, gender, education, depression, and neuropsychological tests scores. In the whole 42-patient group, a positive correlation was found between MAC-Q score and metabolism in posterior cingulate cortex in both hemispheres and in inferior parietal lobule, middle cingulate cortex, precuneus and angular gyrus in the left hemisphere. Compared to controls, hypometabolism was found in aMCI/unaware in three large clusters, including precuneus, inferior parietal lobule and superior occipital gyrus, in the left hemisphere, and in inferior parietal lobule, angular gyrus and middle temporal gyrus in the right hemisphere. Smaller clusters of hypometabolism were found in bilateral temporal lobe in aMCI/aware. Hypometabolism in inferior parietal lobule, angular gyrus and superior temporal gyrus in the left hemisphere was highlighted in aMCI/unaware versus aMCI/aware. The significant correlation in all 42 aMCI patients points to posteromedial cortex as a key node of the network being involved in awareness of memory deficit. Patients with low awareness show a more severe hypometabolic pattern, typical of Alzheimer's disease and therefore could be more at risk of developing dementia.

Baseline brain single photon emission computed tomography (SPECT) was evaluated in eighty subjects with mild cognitive impairment (MCI) who were followed for a mean of about two years, when twelve patients developed Alzheimer's disease (AD), nineteen showed memory decline (D), and forty-three had normal cognition assessment (stable: S) (six drop-out). Volumetric Regions of Interest (VROI) analysis was performed in six associative cortical areas in each hemisphere. ANOVA for repeated measures showed significant effects for both the group (S, D, and AD; p < 0.004) and VROI (p < 0.0001) factors, with significant group*region interaction (p < 0.01). At post-hoc comparison, hippocampal VROIs values were lower in AD than in D and S, while parietal VROIs values were lower in D and AD than in S. These four VROI significantly correlated with verbal delayed recall score at follow-up visit. Receiver operating characteristic (ROC) curves for the mean hippocampal VROI value showed 0.81 sensitivity with 0.86 specificity in separation of S+D from AD (p < 0.0001), and 0.69 sensitivity with 0.75 specificity in separation of S from D+AD (p < 0.0002). ROC curves for the mean parietal VROI value showed 0.62 sensitivity with 0.70 specificity in separation of S from D+AD (p < 0.0002). Baseline SPECT can support outcome prediction in subjects with MCI.

The Development of Screening Guidelines and Clinical Criteria of Predementia Alzheimer's Disease (DESCRIPA) multicenter study enrolled patients with MCI or subjective cognitive complaints (SUBJ), a part of whom underwent optional brain perfusion SPECT. These patients were classified as SUBJ (n = 23), nonamnestic MCI (naMCI; n = 17) and amnestic MCI (aMCI; n = 40) based on neuropsychology. Twenty healthy subjects formed the control (CTR) group. Volumetric regions of interest (VROI) analysis was performed in six associative cortical areas in each hemisphere. ANOVA for repeated measures, corrected for age and center, showed significant differences between groups (p = 0.01) and VROI (p < 0.0001) with a significant group-region interaction (p = 0.029). In the post hoc comparison, SUBJ did not differ from CTR. aMCI disclosed reduced uptake in the left hippocampus and bilateral temporal cortex (compared with CTR) or in the left hippocampus and bilateral parietal cortex (compared with SUBJ). In the naMCI group, reduced VROI values were found in the bilateral temporal cortex and right frontal cortex. In the comparison between aMCI and naMCI, the former had lower values in the left parietal cortex and precuneus. Discriminant analysis between SUBJ/CTR versus all MCI patients allowed correct allocations in 73 % of cases. Mean VROI values were highly correlated (p < 0.0001) with the learning measure of a verbal memory test, especially in the bilateral precunei and parietal cortex and in the left hippocampus. In a subset of 70 patients, mean VROI values showed a significant correlation (p < 0.05) with the white matter hyperintensities score on MRI. In conclusion, MCI subtypes have different perfusion patterns. The aMCI group exhibited a pattern that is typical of early Alzheimer's disease, while the naMCI group showed a more anterior pattern of hypoperfusion. Instead, a homogeneous group effect was lacking in SUBJ.

Objective: To investigate the relationships between brain function and some of the most frequently impaired cognitive domains in the first stages of Alzheimer's disease (AD), we searched for correlation between the scores on 3 neuropsychological tests and brain perfusion, assessed by single photon emission computed tomography (SPECT) in patients with very mild AD., Methods: Twenty-nine consecutive outpatients (mean age 78.2+/-5.5) affected by probable AD in the very mild phase (i.e. with a score > or =20 on the mini-mental state examination, MMSE) underwent brain SPECT with (99m)Tc-ethylcisteinate dimer. For correlative purposes, word list learning (by the selective reminding test, SRT), constructional praxis test (CPT) and visual search test (VST) were chosen a priori out of an extended battery employed to diagnose AD at first patient evaluation. Voxel-based correlation analysis was achieved by statistical parametric mapping (SPM99) with a height threshold of P=0.005. Age, years of education and the MMSE score were inserted in the correlative analysis as confounding variables., Results: The SRT score showed correlation with brain perfusion in 3 clusters of the left hemisphere, including the post-central gyrus, the parietal precuneus, the inferior parietal lobule and the middle temporal gyrus, and in one cluster in the right hemisphere including the middle temporal gyrus and the middle occipital gyrus. The CPT score was significantly correlated with brain perfusion in the parietal precuneus and the posterior cingulate gyrus in the left hemisphere, whereas the VST score gave a significant correlation with brain perfusion in a left cluster including the parietal precuneus and the superior temporal gyrus., Conclusions: Cognitive impairment in very mild AD is reflected by brain dysfunction in posterior associative areas, with peculiar topographical differences proper of each domain. The parietal precuneus was a common site of correlation of all 3 neuropsychological tests. This region, together with the posterior cingulate and the superficial posterior temporal-parietal cortex, is thought to be affected by disconnection from the mesial temporal lobe, besides being directly affected by increased oxidative stress and by atrophy as well. The impairment of these areas is thought to contribute to cognitive decline in verbal memory, constructional praxis and visual sustained attention which are indeed among the earliest signs of cognitive impairment in AD., Significance: Assessing the relationships between neuropsychology and brain functional imaging is a key approach to clarify the pathophysiology of cognitive failure in AD; the specificity of these findings in AD remains to be proven through comparison with correlation achieved in matched controls.

Background: Assessment of nigrostriatal degeneration is a key element to discriminate between dementia with Lewy bodies (DLB) and Alzheimer disease (AD), and it is often evaluated using ioflupane (123I-FP-CIT) single-photon emission computed tomography (SPECT). Given the limited availability of 123I-FP-CIT SPECT, we evaluated if a mask-based approach to nigroputaminal magnetic resonance imaging (MRI) diffusion-weighted tractography could be able to capture microstructural changes reflecting nigroputaminal degeneration in DLB. Methods: A nigroputaminal bundle mask was delineated on 12 healthy volunteers (HV) and applied to MRI diffusion-weighted data of 18 subjects with DLB, 21 subjects with AD and another group of 12 HV. The correlation between nigroputaminal fractional anisotropy (FA) values and 123I-FP-CIT SPECT findings was investigated. Shapiro-Wilk, ANOVA, ANCOVA, and parametric correlation statistics as well as receiver operating characteristic (ROC) analysis were used. Results: DLB patients showed a higher nigroputaminal FA values compared with both AD and HV-controls groups (p = 0.001 for both comparisons), while no difference was observed between HV-controls and AD groups (p = 0.450); at ROC analysis, the area under the curve for the discriminating DLB and AD subjects was 0.820; FA values correlated with 123I-FP-CIT values (on the left, r = -0.670; on the right, r = -720). No significant differences were observed for the FA of the corticospinal tract across the three groups (p = 0.740). Conclusions: In DLB, nigroputaminal degeneration could be reliably assessed on MRI diffusion scans using a mask of nigroputaminal bundle trajectory. Nigroputaminal FA in DLB patients correlated with 123I-FP-CIT values data may allow to differentiate these patients from AD patients and HV-controls. [ABSTRACT FROM AUTHOR]