European Association of Nuclear Medicine and European Academy of Neurology recommendations for the use of brain 18 F-fluorodeoxyglucose positron emission tomography in neurodegenerative cognitive impairment and dementia: Delphi consensus

A multi-scale feature selection module based architecture for the diagnosis of Alzheimer's disease on [18F]FDG PET

OBJECTIVE

Alzheimer's disease (AD) is a prevalent form of dementia worldwide as a cryptic neurodegenerative disease. The symptoms of AD will last for several years, which brings great mental and economic burden to patients and their families. Unfortunately, the complete cure of AD still faces great challenges. Therefore, it is crucial to diagnose the disease in the early stage.

MATERIALS AND METHODS

The Visual Geometry Group (VGG) network serves as the backbone for feature extraction, which could reduce the time cost of network training to a certain extent. In order to better extract image information and pay attention to the association information in the images, the group convolutional module and the multi-scale RNN-based feature selection module are proposed. The dataset employed in the study are drawn from [18F]FDG-PET images within the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

RESULTS

Comprehensive experimental results show that the proposed model outperforms several competing approaches in AD-related diagnostic tasks. In addition, the model reduces the number of parameters of the model compared to the backbone model, from 134.27 M to 17.36 M. Furthermore, the ablation reaserch is conducted to confirm the effectiveness of the proposed module.

CONCLUSIONS

The paper introduces a lightweight network architecture for the early diagnosis of AD. In contrast to analogous methodologies, the proposed method yields acceptable results.

Diagnostic performance of molecular imaging methods in predicting the progression from mild cognitive impairment to dementia: an updated systematic review

PURPOSE

Epidemiological and logistical reasons are slowing the clinical validation of the molecular imaging biomarkers in the initial stages of neurocognitive disorders. We provide an updated systematic review of the recent advances (2017-2022), highlighting methodological shortcomings.

METHODS

Studies reporting the diagnostic accuracy values of the molecular imaging techniques (i.e., amyloid-, tau-, [18F]FDG-PETs, DaT-SPECT, and cardiac [123I]-MIBG scintigraphy) in predicting progression from mild cognitive impairment (MCI) to dementia were selected according to the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) method and evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Main eligibility criteria were as follows: (1) ≥ 50 subjects with MCI, (2) follow-up ≥ 3 years, (3) gold standard: progression to dementia or diagnosis on pathology, and (4) measures of prospective accuracy.

RESULTS

Sensitivity (SE) and specificity (SP) in predicting progression to dementia, mainly to Alzheimer's dementia were 43-100% and 63-94% for [18F]FDG-PET and 64-94% and 48-93% for amyloid-PET. Longitudinal studies were lacking for less common disorders (Dementia with Lewy bodies-DLB and Frontotemporal lobe degeneration-FTLD) and for tau-PET, DaT-SPECT, and [123I]-MIBG scintigraphy. Therefore, the accuracy values from cross-sectional studies in a smaller sample of subjects (n > 20, also including mild dementia stage) were chosen as surrogate outcomes. DaT-SPECT showed 47-100% SE and 71-100% SP in differentiating Lewy body disease (LBD) from non-LBD conditions; tau-PET: 88% SE and 100% SP in differentiating DLB from Posterior Cortical Atrophy. [123I]-MIBG scintigraphy differentiated LBD from non-LBD conditions with 47-100% SE and 71-100% SP.

CONCLUSION

Molecular imaging has a moderate-to-good accuracy in predicting the progression of MCI to Alzheimer's dementia. Longitudinal studies are sparse in non-AD conditions, requiring additional efforts in these settings.

Evaluation of the Therapeutical Effect of Matricaria Chamomilla Extract vs. Galantamine on Animal Model Memory and Behavior Using 18F-FDG PET/MRI

The memory-enhancing activity of Matricaria chamomilla hydroalcoholic extract (MCE) is already being investigated by behavioral and biochemical assays in scopolamine-induced amnesia rat models, while the effects of scopolamine (Sco) on cerebral glucose metabolism are examined as well. Nevertheless, the study of the metabolic profile determined by an enriched MCE has not been performed before. The present experiments compared metabolic quantification in characteristic cerebral regions and behavioral characteristics for normal, only diseased, diseased, and MCE- vs. Galantamine (Gal)-treated Wistar rats. A memory deficit was induced by four weeks of daily intraperitoneal Sco injection. Starting on the eighth day, the treatment was intraperitoneally administered 30 min after Sco injection for a period of three weeks. The memory assessment comprised three maze tests. Glucose metabolism was quantified after the 18F-FDG PET examination. The right amygdala, piriform, and entorhinal cortex showed the highest differential radiopharmaceutical uptake of the 50 regions analyzed. Rats treated with MCE show metabolic similarity with normal rats, while the Gal-treated group shows features closer to the diseased group. Behavioral assessments evidenced a less anxious status and a better locomotor activity manifested by the MCE-treated group compared to the Gal-treated group. These findings prove evident metabolic ameliorative qualities of MCE over Gal classic treatment, suggesting that the extract could be a potent neuropharmacological agent against amnesia.

Behavioral and dysexecutive variant of Alzheimer's disease: Insights from structural and molecular imaging studies

Frontal variant Alzheimer's disease (AD) manifests with either behavioral or dysexecutive syndromes. Recent efforts to gain a deeper understanding of this phenotype have led to a re-conceptualization of frontal AD. Behavioral (bAD) and dysexecutive (dAD) phenotypes could be considered subtypes, as suggested by both clinical and neuroimaging studies. In this review, we focused on imaging studies to highlight specific brain patterns in these two uncommon clinical AD phenotypes. Although studies did not compare directly these two variants, a common epicenter located in the frontal cortex could be inferred. On the contrary, 18F-FDG-PET findings suggested differing metabolic patterns, with bAD showing specific involvement of frontal regions and dAD exhibiting widespread alterations. Structural MRI findings confirmed this pattern, suggesting that degeneration might involve neural circuits associated with behavioral control in bAD and attentional networks in dAD. Furthermore, molecular imaging has identified different neocortical tau distribution in bAD and dAD patients compared to typical AD patients, although the distribution is remarkably heterogeneous. In contrast, Aβ deposition patterns are less differentiated between these atypical variants and typical AD. Although preliminary, these findings underscore the complexity of AD frontal phenotypes and suggest that they represent distinct entities. Further research is essential to refine our understanding of the pathophysiological mechanisms in frontal AD.

PET Imaging in Dementia: Mini-Review and Canadian Perspective for Clinical Use

PET imaging is increasingly recognized as an important diagnostic tool to investigate patients with cognitive disturbances of possible neurodegenerative origin. PET with 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), assessing glucose metabolism, provides a measure of neurodegeneration and allows a precise differential diagnosis among the most common neurodegenerative diseases, such as Alzheimer's disease, frontotemporal dementia or dementia with Lewy bodies. PET tracers specific for the pathological deposits characteristic of different neurodegenerative processes, namely amyloid and tau deposits typical of Alzheimer's Disease, allow the visualization of these aggregates in vivo. [18F]FDG and amyloid PET imaging have reached a high level of clinical validity and are since 2022 investigations that can be offered to patients in standard clinical care in most of Canada.This article will briefly review and summarize the current knowledge on these diagnostic tools, their integration into diagnostic algorithms as well as perspectives for future developments.

The role of plasma neurofilament light chain and glial fibrillary acidic protein in subjective cognitive decline and mild cognitive impairment

INTRODUCTION AND AIM

NfL and GFAP are promising blood-based biomarkers for Alzheimer's disease. However, few studies have explored plasma GFAP in the prodromal and preclinical stages of AD. In our cross-sectional study, our aim is to investigate the role of these biomarkers in the earliest stages of AD.

MATERIALS AND METHODS

We enrolled 40 patients (11 SCD, 21 MCI, 8 AD dementia). All patients underwent neurological and neuropsychological examinations, analysis of CSF biomarkers (Aβ42, Aβ42/Aβ40, p-tau, t-tau), Apolipoprotein E (APOE) genotype analysis and measurement of plasma GFAP and NfL concentrations. Patients were categorized according to the ATN system as follows: normal AD biomarkers (NB), carriers of non-Alzheimer's pathology (non-AD), prodromal AD, or AD with dementia (AD-D).

RESULTS

GFAP was lower in NB compared to prodromal AD (p = 0.003, d = 1.463) and AD-D (p = 0.002, d = 1.695). NfL was lower in NB patients than in AD-D (p = 0.011, d = 1.474). NfL demonstrated fair accuracy (AUC = 0.718) in differentiating between NB and prodromal AD, with a cut-off value of 11.65 pg/mL. GFAP showed excellent accuracy in differentiating NB from prodromal AD (AUC = 0.901) with a cut-off level of 198.13 pg/mL.

CONCLUSIONS

GFAP exhibited excellent accuracy in distinguishing patients with normal CSF biomarkers from those with prodromal AD. Our results support the use of this peripheral biomarker for detecting AD in patients with subjective and objective cognitive decline.

European intersocietal recommendations for the biomarker-based diagnosis of neurocognitive disorders

The recent commercialisation of the first disease-modifying drugs for Alzheimer's disease emphasises the need for consensus recommendations on the rational use of biomarkers to diagnose people with suspected neurocognitive disorders in memory clinics. Most available recommendations and guidelines are either disease-centred or biomarker-centred. A European multidisciplinary taskforce consisting of 22 experts from 11 European scientific societies set out to define the first patient-centred diagnostic workflow that aims to prioritise testing for available biomarkers in individuals attending memory clinics. After an extensive literature review, we used a Delphi consensus procedure to identify 11 clinical syndromes, based on clinical history and examination, neuropsychology, blood tests, structural imaging, and, in some cases, EEG. We recommend first-line and, if needed, second-line testing for biomarkers according to the patient's clinical profile and the results of previous biomarker findings. This diagnostic workflow will promote consistency in the diagnosis of neurocognitive disorders across European countries.

Kinetic Modeling of Brain [18-F]FDG Positron Emission Tomography Time Activity Curves with Input Function Recovery (IR) Method

Accurate positron emission tomography (PET) data quantification relies on high-quality input plasma curves, but venous blood sampling may yield poor-quality data, jeopardizing modeling outcomes. In this study, we aimed to recover sub-optimal input functions by using information from the tail (5th-100th min) of curves obtained through the frequent sampling protocol and an input recovery (IR) model trained with reference curves of optimal shape. Initially, we included 170 plasma input curves from eight published studies with clamp [18F]-fluorodeoxyglucose PET exams. Model validation involved 78 brain PET studies for which compartmental model (CM) analysis was feasible (reference (ref) + training sets). Recovered curves were compared with original curves using area under curve (AUC), max peak standardized uptake value (maxSUV). CM parameters (ref + training sets) and fractional uptake rate (FUR) (all sets) were computed. Original and recovered curves from the ref set had comparable AUC (d = 0.02, not significant (NS)), maxSUV (d = 0.05, NS) and comparable brain CM results (NS). Recovered curves from the training set were different from the original according to maxSUV (d = 3) and biologically plausible according to the max theoretical K1 (53//56). Brain CM results were different in the training set (p < 0.05 for all CM parameters and brain regions) but not in the ref set. FUR showed reductions similarly in the recovered curves of the training and test sets compared to the original curves (p < 0.05 for all regions for both sets). The IR method successfully recovered the plasma inputs of poor quality, rescuing cases otherwise excluded from the kinetic modeling results. The validation approach proved useful and can be applied to different tracers and metabolic conditions.

An imaging review of the hippocampus and its common pathologies

The hippocampus is a complex structure located in the mesial temporal lobe that plays a critical role in cognitive and memory-related processes. The hippocampal formation consists of the dentate gyrus, hippocampus proper, and subiculum, and its importance in the neural circuitry makes it a key anatomic structure to evaluate in neuroimaging studies. Advancements in imaging techniques now allow detailed assessment of hippocampus internal architecture and signal features that has improved identification and characterization of hippocampal abnormalities. This review aims to summarize the neuroimaging features of the hippocampus and its common pathologies. It provides an overview of the hippocampal anatomy on magnetic resonance imaging and discusses how various imaging techniques can be used to assess the hippocampus. The review explores neuroimaging findings related to hippocampal variants (incomplete hippocampal inversion, sulcal remnant and choroidal fissure cysts), and pathologies of neoplastic (astrocytoma and glioma, ganglioglioma, dysembryoplastic neuroepithelial tumor, multinodular and vacuolating neuronal tumor, and metastasis), epileptic (mesial temporal sclerosis and focal cortical dysplasia), neurodegenerative (Alzheimer's disease, progressive primary aphasia, and frontotemporal dementia), infectious (Herpes simplex virus and limbic encephalitis), vascular (ischemic stroke, arteriovenous malformation, and cerebral cavernous malformations), and toxic-metabolic (transient global amnesia and opioid-associated amnestic syndrome) etiologies.

The impact of tau deposition and hypometabolism on cognitive impairment and longitudinal cognitive decline

INTRODUCTION

Tau and neurodegeneration strongly correlate with cognitive impairment, as compared to amyloid. However, their contribution in explaining cognition and predicting cognitive decline in memory clinics remains unclarified.

METHODS

We included 94 participants with Mini-Mental State Examination (MMSE), tau positron emission tomography (PET), amyloid PET, fluorodeoxyglucose (FDG) PET, and MRI scans from Geneva Memory Center. Linear regression and mediation analyses tested the independent and combined association between biomarkers, cognitive performance, and decline. Linear mixed-effects and Cox proportional hazards models assessed biomarkers' prognostic values.

RESULTS

Metabolism had the strongest association with cognition (r = 0.712; p < 0.001), followed by tau (r = -0.682; p < 0.001). Neocortical tau showed the strongest association with cognitive decline (r = -0.677; p < 0.001). Metabolism mediated the association between tau and cognition and marginally mediated the one with decline. Tau positivity represented the strongest risk factor for decline (hazard ratio = 32).

DISCUSSION

Tau and neurodegeneration synergistically contribute to global cognitive impairment while tau drives decline. The tau PET superior prognostic value supports its implementation in memory clinics.

HIGHLIGHTS

Hypometabolism has the strongest association with concurrent cognitive impairment. Neocortical tau pathology is the main determinant of cognitive decline over time. FDG-PET has a superior value compared to MRI as a measure of neurodegeneration. The prognostic value of tau-PET exceeded all other neuroimaging modalities.

Effects of amyloid beta and dopaminergic depletion on perfusion and clinical symptoms

INTRODUCTION

Although mixed pathologies are common in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), the effects of amyloid beta and dopaminergic depletion on brain perfusion and clinical symptoms have not been elucidated.

METHODS

In 99 cognitive impairment patients due to AD and/or DLB and 32 controls, 18F-florbetaben (FBB) and dual-phase dopamine transporter (DAT) positron emission tomography (PET) were performed to measure the FBB standardized uptake value ratio (SUVR), striatal DAT uptakes, and brain perfusion.

RESULTS

Higher FBB-SUVR and lower ventral striatal DAT uptake were intercorrelated and, respectively, associated with left entorhinal/temporo-parietal-centered hypoperfusion and vermis/hippocampal-centered hyperperfusion, whereas regional perfusion mediated clinical symptoms and cognition.

DISCUSSION

Amyloid beta deposition and striatal dopaminergic depletion contribute to regional perfusion changes, clinical symptoms, and cognition in the spectrum of normal aging and cognitive impairment due to AD and/or LBD.

HIGHLIGHTS

Amyloid beta (Aβ) deposition was associated with ventral striatal dopaminergic depletion. Aβ deposition and dopaminergic depletion correlated with perfusion. Aβ deposition correlated with hypoperfusion centered in the left entorhinal cortex. Dopaminergic depletion correlated with hyperperfusion centered in the vermis. Perfusion mediated the Aβ deposition/dopaminergic depletion's effects on cognition.

Quantitative cellular changes in multiple system atrophy brains

Multiple system atrophy (MSA) is a neurodegenerative disorder characterised by a combined symptomatology of parkinsonism, cerebellar ataxia, autonomic failure and corticospinal dysfunction. In brains of MSA patients, the hallmark lesion is the aggregation of misfolded alpha-synuclein in oligodendrocytes. Even though the underlying pathological mechanisms remain poorly understood, the evidence suggests that alpha-synuclein aggregation in oligodendrocytes may contribute to the neurodegeneration seen in MSA. The primary aim of this review is to summarise the published stereological data on the total number of neurons and glial cell subtypes (oligodendrocytes, astrocytes and microglia) and volumes in brains from MSA patients. Thus, we include in this review exclusively the reports of unbiased quantitative data from brain regions including the neocortex, nuclei of the cerebrum, the brainstem and the cerebellum. Furthermore, we compare and discuss the stereological results in the context of imaging findings and MSA symptomatology. In general, the stereological results agree with the common neuropathological findings of neurodegeneration and gliosis in brains from MSA patients and support a major loss of nigrostriatal neurons in MSA patients with predominant parkinsonism (MSA-P), as well as olivopontocerebellar atrophy in MSA patients with predominant cerebellar ataxia (MSA-C). Surprisingly, the reports indicate only a minor loss of oligodendrocytes in sub-cortical regions of the cerebrum (glial cells not studied in the cerebellum) and negligible changes in brain volumes. In the past decades, the use of stereological methods has provided a vast amount of accurate information on cell numbers and volumes in the brains of MSA patients. Combining different techniques such as stereology and diagnostic imaging (e.g. MRI, PET and SPECT) with clinical data allows for a more detailed interdisciplinary understanding of the disease and illuminates the relationship between neuropathological changes and MSA symptomatology.

The Sporadic Early-onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) Cohort

INTRODUCTION

Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker.

METHODS

We analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment.

RESULTS

The EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment.

DISCUSSION

The EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD.

HIGHLIGHTS

We developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.

Combined 18F-FDG PET-CT markers in dementia with Lewy bodies

INTRODUCTION

18F-Fluoro-deoxyglucose-positron emission tomography (FDG-PET) is a supportive biomarker in dementia with Lewy bodies (DLB) diagnosis and its advanced analysis methods, including radiomics and machine learning (ML), were developed recently. The aim of this study was to evaluate the FDG-PET diagnostic performance in predicting a DLB versus Alzheimer's disease (AD) diagnosis.

METHODS

FDG-PET scans were visually and semi-quantitatively analyzed in 61 patients. Radiomics and ML analyses were performed, building five ML models: (1) clinical features; (2) visual and semi-quantitative PET features; (3) radiomic features; (4) all PET features; and (5) overall features.

RESULTS

At follow-up, 34 patients had DLB and 27 had AD. At visual analysis, DLB PET signs were significantly more frequent in DLB, having the highest diagnostic accuracy (86.9%). At semi-quantitative analysis, the right precuneus, superior parietal, lateral occipital, and primary visual cortices showed significantly reduced uptake in DLB. The ML model 2 had the highest diagnostic accuracy (84.3%).

DISCUSSION

FDG-PET is a valuable tool in DLB diagnosis, having visual and semi-quantitative analyses with the highest diagnostic accuracy at ML analyses.

Automatic covariance pattern analysis outperforms visual reading of 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in variant progressive supranuclear palsy

BACKGROUND

To date, studies on positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP-RS).

OBJECTIVES

To evaluate FDG-PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice.

METHODS

This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non-RS variants of PSP (vPSP), and 46 age-matched healthy controls. Two state-of-the art methods for the interpretation of FDG-PET were compared: visual analysis supported by voxel-based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP-related pattern.

RESULTS

Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false-negative cases was 10% in the PSP-RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false-negative cases was 0% in the PSP-RS subsample and 15% in the vPSP subsample.

CONCLUSIONS

Visual interpretation of FDG-PET supported by voxel-based testing provides good accuracy for the detection of PSP-RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP-RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false-positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel-based testing of FDG-PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Physical activity interventions in older adults with a cognitive impairment: A critical review of reviews

This critical review explores the review material on physical activity combined with cognitive stimulation interventions in older adults with cognitive impairment and/or dementia. A critical, systematic, review of the review method was used, considering four electronic databases: WEB OF SCIENCE, SCOPUS, MEDLINE, and the COCHRANE ELECTRONIC LIBRARY. The search terms "exercise," "physical activity," "cognitive impairment," "dementia," and "systematic review" were used. All available reviews were marked against predetermined inclusion and exclusion criteria. There were 32 reviews that met the inclusion criteria. A combination of various types of training and aerobic exercises were the most frequently reported interventions; meanwhile, dual task training programs (combining physical exercise with cognitive stimulation), functional training programs along with exercises combination, aerobic exercise as well as strength, stretching, or balance workouts were also reported. The evidence is compelling; exercise can improve physical health by ensuring cognitive, psychological, and behavioral benefits. Overall, exercise can improve the physical and mental health of people living with dementia: there is sufficient evidence to recommend multimodal exercise.

Different associations between amyloid-βeta 42, amyloid-βeta 40, and amyloid-βeta 42/40 with soluble phosphorylated-tau and disease burden in Alzheimer's disease: a cerebrospinal fluid and fluorodeoxyglucose-positron emission tomography study

BACKGROUND

Despite the high sensitivity of cerebrospinal fluid (CSF) amyloid beta (Aβ)42 to detect amyloid pathology, the Aβ42/Aβ40 ratio (amyR) better estimates amyloid load, with higher specificity for Alzheimer's disease (AD). However, whether Aβ42 and amyR have different meanings and whether Aβ40 represents more than an Aβ42-corrective factor remain to be clarified. Our study aimed to compare the ability of Aβ42 and amyR to detect AD pathology in terms of p-tau/Aβ42 ratio and brain glucose metabolic patterns using fluorodeoxyglucose-positron emission tomography (FDG-PET).

METHODS

CSF biomarkers were analyzed with EUROIMMUN ELISA. We included 163 patients showing pathological CSF Aβ42 and normal p-tau (A + T -  = 98) or pathological p-tau levels (A + T +  = 65) and 36 control subjects (A - T -). A + T - patients were further stratified into those with normal (CSFAβ42 + /amyR -  = 46) and pathological amyR (CSFAβ42 + /amyR +  = 52). We used two distinct cut-offs to determine pathological values of p-tau/Aβ42: (1) ≥ 0.086 and (2) ≥ 0.122. FDG-PET patterns were evaluated in a subsample of patients (n = 46) and compared to 24 controls.

RESULTS

CSF Aβ40 levels were the lowest in A - T - and in CSFAβ42 + /amyR - , higher in CSFAβ42 + /amyR + and highest in A + T + (F = 50.75; p < 0.001), resembling CSF levels of p-tau (F = 192; p < 0.001). We found a positive association between Aβ40 and p-tau in A - T - (β = 0.58; p < 0.001), CSFAβ42 + /amyR - (β = 0.47; p < 0.001), and CSFAβ42 + /amyR + patients (β = 0.48; p < 0.001) but not in A + T + . Investigating biomarker changes as a function of amyR, we observed a weak variation in CSF p-tau (+ 2 z-scores) and Aβ40 (+ 0.8 z-scores) in the normal amyR range, becoming steeper over the pathological threshold of amyR (p-tau: + 5 z-scores, Aβ40: + 4.5 z-score). CSFAβ42 + /amyR + patients showed a significantly higher probability of having pathological p-tau/Aβ42 than CSFAβ42 + /amyR - (cut-off ≥ 0.086: OR 23.3; cut-off ≥ 0.122: OR 8.8), which however still showed pathological values of p-tau/Aβ42 in some cases (cut-off ≥ 0.086: 35.7%; cut-off ≥ 0.122: 17.3%) unlike A - T - . Accordingly, we found reduced FDG metabolism in the temporoparietal regions of CSFAβ42 + /amyR - compared to controls, and further reduction in frontal areas in CSFAβ42 + /amyR + , like in A + T + .

CONCLUSIONS

Pathological p-tau/Aβ42 and FDG hypometabolism typical of AD can be found in patients with decreased CSF Aβ42 levels alone. AmyR positivity, associated with higher Aβ40 levels, is accompanied by higher CSF p-tau and widespread FDG hypometabolism.

Depression and Pseudodementia: Decoding the Intricate Bonds in an Italian Outpatient Setting

In spite of the uncertainties of its diagnostic framework, pseudodementia may be conceptualized as a condition characterized by depressive symptoms and cognitive impairment in the absence of dementia. Given the controversies on this topic, the aim of the present study was to assess neurological and cognitive dysfunctions in a sample of elderly depressed subjects, and the eventual relationship between cognitive impairment and depressive symptoms. Fifty-seven elderly depressed outpatients of both sexes were included in the study. A series of rating scales were used to assess diagnoses, depressive and cognitive impairment. Comparisons for continuous variables were performed with the independent-sample Student's t-test. Comparisons for categorical variables were conducted by the χ2 test (or Fisher's exact test when appropriate). The correlations between between socio-demographic characteristics and clinical features, as well as between cognitive impairment and depressive symptoms were explored by Pearson's correlation coefficient or Spearman's rank correlation. Our data showed the presence of a mild-moderate depression and of a mild cognitive impairment that was only partially related to the severity of depression. These dysfunctions became more evident when analyzing behavioral responses, besides cognitive functions. A high educational qualification seemed to protect against cognitive decline, but not against depression. Single individuals were more prone to cognitive disturbance but were similar to married subjects in terms of the severity of depressive symptoms. Previous depressive episodes had no impact on the severity of depression or cognitive functioning. Although data are needed to draw firm conclusions, our findings strengthen the notion that pseudodementia represents a borderline condition between depression and cognitive decline that should be rapidly identified and adequately treated.

Diagnostic accuracy of cerebral [18F]FDG PET in atypical parkinsonism

BACKGROUND

Atypical parkinsonism (AP) often presents with Parkinson's symptoms but has a much worse long-term prognosis. The diagnosis is presently based on clinical criteria, but a cerebral positron emission tomography (PET) scan with [18F]fluoro-2-deoxy-2-D-glucose ([18F]FDG) may assist in the diagnosis of AP such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), and Lewy body dementia (DLB). Only few studies have evaluated the sensitivity and specificity of [18F]FDG PET for separating the diseases in a mixed patient population, which we aim to assess in a retrospective material.

RESULTS

We identified 156 patients referred for a cerebral [18F]FDG PET for suspicion of AP during 2017-2019. The [18F]FDG PET was analysed by a nuclear medicine specialist blinded to clinical information but with access to dopamine transporter imaging. The reference standard was the follow-up clinical diagnosis (follow-up: 6-72 months). The overall accuracy for correct classification was 74%. Classification sensitivity (95% confidence interval, CI) and specificity (95% CI) for MSA (n = 20) were 1.00 (0.83-1.00) and 0.91 (0.85-0.95), for DLB/Parkinson with dementia (PDD) (n = 26) were 0.81 (0.61-0.93) and 0.97 (0.92-0.99) and for CBD/PSP (n = 68) were 0.62 (0.49-0.73) and 0.97 (0.90-0.99).

CONCLUSIONS

Our results support the additional use of [18F]FDG PET for the clinical diagnosis of AP with moderate to high sensitivity and specificity. Use of [18F]FDG PET may be beneficial for prognosis and supportive treatment of the patients and useful for future clinical treatment trials.

FDG-PET versus Amyloid-PET Imaging for Diagnosis and Response Evaluation in Alzheimer's Disease: Benefits and Pitfalls

In June 2021, the US Federal Drug and Food Administration (FDA) granted accelerated approval for the antibody aducanumab and, in January 2023, also for the antibody lecanemab, based on a perceived drug-induced removal of cerebral amyloid-beta as assessed by amyloid-PET and, in the case of lecanemab, also a presumption of limited clinical efficacy. Approval of the antibody donanemab is awaiting further data. However, published trial data indicate few, small and uncertain clinical benefits, below what is considered "clinically meaningful" and similar to the effect of conventional medication. Furthermore, a therapy-related decrease in the amyloid-PET signal may also reflect increased cell damage rather than simply "amyloid removal". This interpretation is more consistent with increased rates of amyloid-related imaging abnormalities and brain volume loss in treated patients, relative to placebo. We also challenge the current diagnostic criteria for AD based on amyloid-PET imaging biomarkers and recommend that future anti-AD therapy trials apply: (1) diagnosis of AD based on the co-occurrence of cognitive decline and decreased cerebral metabolism assessed by FDA-approved FDG-PET, (2) therapy efficacy determined by favorable effect on cognitive ability, cerebral metabolism by FDG-PET, and brain volumes by MRI, and (3) neuropathologic examination of all deaths occurring in these trials.

Characterization of neuroinflammation pattern in anti-LGI1 encephalitis based on TSPO PET and symptom clustering analysis

PURPOSE

TSPO PET with radioligand [18F]DPA-714 is an emerging molecular imaging technique that reflects cerebral inflammation and microglial activation, and it has been recently used in central nervous system diseases. In this study, we aimed to investigate the neuroinflammation pattern of anti-leucine-rich glioma-inactivated 1 (LGI1) protein autoimmune encephalitis (AIE) and to evaluate its possible correlation with clinical phenotypes.

METHODS

Twenty patients with anti-LGI1 encephalitis from the autoimmune encephalitis cohort in Huashan Hospital and ten with other AIE and non-inflammatory diseases that underwent TSPO PET imaging were included in the current study. Increased regional [18F]DPA-714 retention in anti-LGI1 encephalitis was detected on a voxel basis using statistic parametric mapping analysis. Multiple correspondence analysis and hierarchical clustering were conducted for discriminate subgroups in anti-LGI1 encephalitis. Standardized uptake value ratios normalized to the cerebellum (SUVRc) were calculated for semiquantitative analysis of TSPO PET features between different LGI1-AIE subgroups.

RESULTS

Increased regional retention of [18F]DPA-714 was identified in the bilateral hippocampus, caudate nucleus, and frontal cortex in LGI1-AIE patients. Two subgroups of LGI1-AIE patients were distinguished based on the top seven common symptoms. Patients in cluster 1 had a high frequency of facio-brachial dystonic seizures than those in cluster 2 (p = 0.004), whereas patients in cluster 2 had a higher frequency of general tonic-clonic (GTC) seizures than those in cluster 1 (p < 0.001). Supplementary motor area and superior frontal gyrus showed higher [18F]DPA-714 retention in cluster 2 patients compared with those in cluster 1 (p = 0.024; p = 0.04, respectively).

CONCLUSIONS

Anti-LGI1 encephalitis had a distinctive molecular imaging pattern presented by TSPO PET scan. LGI1-AIE patients with higher retention of [18F]DPA-714 in the frontal cortex were more prone to present with GTC seizures. Further studies are required for verifying its value in clinical application.

Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer's disease-related pattern

BACKGROUND

Alzheimer's disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer's disease (AD). While ADRP is being introduced into research, the effect of the size of the identification cohort and the effect of the resolution of identification and validation images on ADRP's performance need to be clarified.

METHODS

240 2-[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography images [120 AD/120 cognitive normals (CN)] were selected from the Alzheimer's disease neuroimaging initiative database. A total of 200 images (100 AD/100 CN) were used to identify different versions of ADRP using a scaled subprofile model/principal component analysis. For this purpose, five identification groups were randomly selected 25 times. The identification groups differed in the number of images (20 AD/20 CN, 30 AD/30 CN, 40 AD/40 CN, 60 AD/60 CN, and 80 AD/80 CN) and image resolutions (6, 8, 10, 12, 15 and 20 mm). A total of 750 ADRPs were identified and validated through the area under the curve (AUC) values on the remaining 20 AD/20 CN with six different image resolutions.

RESULTS

ADRP's performance for the differentiation between AD patients and CN demonstrated only a marginal average AUC increase, when the number of subjects in the identification group increases (AUC increase for about 0.03 from 20 AD/20 CN to 80 AD/80 CN). However, the average of the lowest five AUC values increased with the increasing number of participants (AUC increase for about 0.07 from 20 AD/20 CN to 30 AD/30 CN and for an additional 0.02 from 30 AD/30 CN to 40 AD/40 CN). The resolution of the identification images affects ADRP's diagnostic performance only marginally in the range from 8 to 15 mm. ADRP's performance stayed optimal even when applied to validation images of resolution differing from the identification images.

CONCLUSIONS

While small (20 AD/20 CN images) identification cohorts may be adequate in a favorable selection of cases, larger cohorts (at least 30 AD/30 CN images) shall be preferred to overcome possible/random biological differences and improve ADRP's diagnostic performance. ADRP's performance stays stable even when applied to the validation images with a resolution different than the resolution of the identification ones.

Brain positron emission tomography (PET) and cognitive abnormalities one year after COVID-19

Emerging evidence indicates that the etiologic agent responsible for coronavirus disease 2019 (COVID-19), can cause neurological complications. COVID-19 may induce cognitive impairment through multiple mechanisms. The aim of the present study was to describe the possible neuropsychological and metabolic neuroimaging consequences of COVID-19 12 months after patients' hospital discharge. We retrospectively recruited 7 patients (age [mean ± SD] = 56 years ± 12.39, 4 men) who had been hospitalized for COVID-19 with persistent neuropsychological deficits 12 months after hospital discharge. All patients underwent cognitive assessment and brain (¹⁸F-FDG) PET/CT, and one also underwent ¹⁸F-amyloid PET/CT. Of the seven patients studied, four had normal glucose metabolism in the brain. Three patients showed various brain hypometabolism patterns: (1) unilateral left temporal mesial area hypometabolism; (2) pontine involvement; and (3) bilateral prefrontal area abnormalities with asymmetric parietal impairment. The patient who showed the most widespread glucose hypometabolism in the brain underwent an ¹⁸F-amyloid PET/CT to assess the presence of Aβ plaques. This examination showed significant Aβ deposition in the superior and middle frontal cortex, and in the posterior cingulate cortex extending mildly in the rostral and caudal anterior cingulate areas. Although some other reports have already suggested that brain hypometabolism may be associated with cognitive impairment at shorter intervals from SarsCov-2 infection, our study is the first to assess cognitive functions, brain metabolic activity and in a patient also amyloid PET one year after COVID-19, demonstrating that cerebral effects of COVID-19 can largely outlast the acute phase of the disease and even be followed by amyloid deposition.

Analysis of positron emission tomography hypometabolic patterns and neuropsychiatric symptoms in patients with dementia syndromes

AIMS

To estimate the proportions of specific hypometabolic patterns and their association with neuropsychiatric symptoms (NPS) in patients with cognitive impairment (CI).

METHODS

This multicenter study with 1037 consecutive patients was conducted from December 2012 to December 2019. ¹⁸ F-FDG PET and clinical/demographic information, NPS assessments were recorded and analyzed to explore the associations between hypometabolic patterns and clinical features by correlation analysis and multivariable logistic regression models.

RESULTS

Patients with clinical Alzheimer's disease (AD, 81.6%, 605/741) and dementia with Lewy bodies (67.9%, 19/28) mostly had AD-pattern hypometabolism, and 76/137 (55.5%) of patients with frontotemporal lobar degeneration showed frontal and anterior temporal pattern (FT-P) hypometabolism. Besides corticobasal degeneration, patients with behavioral variant frontotemporal dementia (36/58), semantic dementia (7/10), progressive non-fluent aphasia (6/9), frontotemporal lobar degeneration and amyotrophic lateral sclerosis (3/5), and progressive supranuclear palsy (21/37) also mostly showed FT-P hypometabolism. The proportion of FT-P hypometabolism was associated with the presence of hallucinations (R = 0.171, p = 0.04), anxiety (R = 0.182, p = 0.03), and appetite and eating abnormalities (R = 0.200, p = 0.01) in AD.

CONCLUSION

Specific hypometabolic patterns in FDG-PET are associated with NPS and beneficial for the early identification and management of NPS in patients with CI.

Adjustment for the Age- and Gender-Related Metabolic Changes Improves the Differential Diagnosis of Parkinsonism

Age and gender are the important factors for brain metabolic declines in both normal aging and neurodegeneration, and the confounding effects may influence early and differential diagnosis of neurodegenerative diseases based on the [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET). We aimed to explore the potential of the adjustment of age- and gender-related confounding factors on [18F]FDG PET images in differentiation of Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supra-nuclear palsy (PSP). Eight hundred and seventy-seven clinically definitely diagnosed Parkinsonian patients from a benchmark Huashan Parkinsonian PET imaging database were included. An age- and gender-adjusted Z (AGAZ) score was established based on the gender-specific longitudinal metabolic changes on healthy subjects. AGAZ scores and standardized uptake value ratio (SUVR) values were quantified at regional-level and support vector machine-based error-correcting output codes method was applied for classification. Additional references of the classifications based on metabolic pattern scores were included. The feature-based AGAZ score showed the best performance in classification (accuracy for PD, MSA, PSP: 93.1%, 96.3%, 94.8%). In both genders, the AGAZ score consistently achieved the best efficiency, and the improvements compared to the conventional SUVR value for PD, MSA, and PSP mainly laid in specificity (Male: 5.7%; Female: 11.1%), sensitivity (Male: 7.2%; Female: 7.3%), and sensitivity (Male: 7.3%; Female: 17.2%). Female patients benefited more from the adjustment on [18F]FDG PET in MSA and PSP groups (absolute net reclassification index, p < 0.001). Collectively, the adjustment of age- and gender-related confounding factors may improve the differential diagnosis of Parkinsonism. Particularly, the diagnosis of female Parkinsonian population has the best improvement from this correction.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00079-6.

Differences in Striatal Metabolism in [18F]FDG PET in Parkinson's Disease and Atypical Parkinsonism

Neurodegenerative parkinsonisms affect mainly cognitive and motor functions and are syndromes of overlapping symptoms and clinical manifestations such as tremor, rigidness, and bradykinesia. These include idiopathic Parkinson's disease (PD) and the atypical parkinsonisms, namely progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), multiple system atrophy (MSA) and dementia with Lewy body (DLB). Differences in the striatal metabolism among these syndromes are evaluated using [18F]FDG PET, caused by alterations to the dopaminergic activity and neuronal loss. A study cohort of three patients with PD, 29 with atypical parkinsonism (10 PSP, 6 CBD, 2 MSA, 7 DLB, and 4 non-classifiable), and a control group of 25 patients with normal striatal metabolism is available. Standardized uptake value ratios (SUVR) are extracted from the striatum, and the caudate and the putamen separately. SUVRs are compared among the study groups. In addition, hemispherical and caudate-putamen differences are evaluated in atypical parkinsonisms. Striatal hypermetabolism is detected in patients with PD, while atypical parkinsonisms show hypometabolism, compared to the control group. Hemispherical differences are observed in CBD, MSA and DLB, with the latter also showing statistically significant caudate-putamen asymmetry (p = 0.018). These results indicate disease-specific metabolic uptake patterns in the striatum that can support the differential diagnosis.

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model

BACKGROUND

In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans.

RESULTS

Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis.

CONCLUSIONS

TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones.

Impact of normative brain volume reports on the diagnosis of neurodegenerative dementia disorders in neuroradiology: A real-world, clinical practice study

Background: Normative brain volume reports (NBVR) are becoming more available in the work-up of patients with suspected dementia disorders, potentially leveraging the value of structural MRI in clinical settings. The present study aims to investigate the impact of NBVRs on the diagnosis of neurodegenerative dementia disorders in real-world clinical practice.

Methods: We retrospectively analyzed data of 112 memory clinic patients, who were consecutively referred for MRI and 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) during a 12-month period. Structural MRI was assessed by two residents with 2 and 3 years of neuroimaging experience. Statements and diagnostic confidence regarding the presence of a neurodegenerative disorder in general (first level) and Alzheimer’s disease (AD) pattern in particular (second level) were recorded without and with NBVR information. FDG-PET served as the reference standard.

Results: Overall, despite a trend towards increased accuracy, the impact of NBVRs on diagnostic accuracy was low and non-significant. We found a significant drop of sensitivity (0.75–0.58; p < 0.001) and increase of specificity (0.62–0.85; p < 0.001) for rater 1 at identifying patients with neurodegenerative dementia disorders. Diagnostic confidence increased for rater 2 (p < 0.001).

Conclusions: Overall, NBVRs had a limited impact on diagnostic accuracy in real-world clinical practice. Potentially, NBVR might increase diagnostic specificity and confidence of neuroradiology residents. To this end, a well-defined framework for integration of NBVR in the diagnostic process and improved algorithms of NBVR generation are essential.

European consensus for the diagnosis of MCI and mild dementia: Preparatory phase

INTRODUCTION

Etiological diagnosis of neurocognitive disorders of middle-old age relies on biomarkers, although evidence for their rational use is incomplete. A European task force is defining a diagnostic workflow where expert experience fills evidence gaps for biomarker validity and prioritization. We report methodology and preliminary results.

METHODS

Using a Delphi consensus method supported by a systematic literature review, 22 delegates from 11 relevant scientific societies defined workflow assumptions.

RESULTS

We extracted diagnostic accuracy figures from literature on the use of biomarkers in the diagnosis of main forms of neurocognitive disorders. Supported by this evidence, panelists defined clinical setting (specialist outpatient service), application stage (MCI-mild dementia), and detailed pre-assessment screening (clinical-neuropsychological evaluations, brain imaging, and blood tests).

DISCUSSION

The Delphi consensus on these assumptions set the stage for the development of the first pan-European workflow for biomarkers' use in the etiological diagnosis of middle-old age neurocognitive disorders at MCI-mild dementia stages.

HIGHLIGHTS

Rational use of biomarkers in neurocognitive disorders lacks consensus in Europe. A consensus of experts will define a workflow for the rational use of biomarkers. The diagnostic workflow will be patient-centered and based on clinical presentation. The workflow will be updated as new evidence accrues.

Differential Diagnosis of Alzheimer Disease vs. Mild Cognitive Impairment Based on Left Temporal Lateral Lobe Hypomethabolism on 18F-FDG PET/CT and Automated Classifiers

Purpose: We evaluate the ability of Artificial Intelligence with automatic classification methods applied to semi-quantitative data from brain ¹⁸F-FDG PET/CT to improve the differential diagnosis between Alzheimer Disease (AD) and Mild Cognitive Impairment (MCI). Procedures: We retrospectively analyzed a total of 150 consecutive patients who underwent diagnostic evaluation for suspected AD (n = 67) or MCI (n = 83). All patients received brain 18F-FDG PET/CT according to the international guidelines, and images were analyzed both Qualitatively (QL) and Quantitatively (QN), the latter by a fully automated post-processing software that produced a z score metabolic map of 25 anatomically different cortical regions. A subset of n = 122 cases with a confirmed diagnosis of AD (n = 53) or MDI (n = 69) by 18–24-month clinical follow-up was finally included in the study. Univariate analysis and three automated classification models (classification tree –ClT-, ridge classifier –RC- and linear Support Vector Machine –lSVM-) were considered to estimate the ability of the z scores to discriminate between AD and MCI cases in. Results: The univariate analysis returned 14 areas where the z scores were significantly different between AD and MCI groups, and the classification accuracy ranged between 74.59% and 76.23%, with ClT and RC providing the best results. The best classification strategy consisted of one single split with a cut-off value of ≈ −2.0 on the z score from temporal lateral left area: cases below this threshold were classified as AD and those above the threshold as MCI. Conclusions: Our findings confirm the usefulness of brain 18F-FDG PET/CT QL and QN analyses in differentiating AD from MCI. Moreover, the combined use of automated classifications models can improve the diagnostic process since its use allows identification of a specific hypometabolic area involved in AD cases in respect to MCI. This data improves the traditional 18F-FDG PET/CT image interpretation and the diagnostic assessment of cognitive disorders.

Depressive Pseudodementia with Reversible AD-like Brain Hypometabolism: A Case Report and a Review of the Literature

Recent European guidelines recommend using brain FDG-PET to differentiate between Alzheimer's disease (AD) and depressive pseudodementia (DP), with specific hypometabolism patterns across the former group, and typically normal or frontal hypometabolism in the latter. We report the case of a 74 years-old man with DP (MMSE 16/30), whose FDG-PET visual rating and semiquantitative analysis closely mimicked the typical AD pattern, showing severe hypometabolism in bilateral precuneus, parietal and temporal lobes, and sparing frontal areas, suggesting the diagnosis of moderate AD. Shortly after starting antidepressant polytherapy, he underwent formal NPS testing, which revealed moderate impairment of episodic memory and mild impairment on executive and visuospatial tests, judged consistent with neurodegenerative dementia and concomitant depression. Over the following two years, he improved dramatically: repeated NPS assessment did not show significant deficits, and FDG-PET showed restoration of cerebral metabolism. The confirmation of PET findings via semiquantitative analysis, and their reversion to normality with antidepressant treatment, proved the non-neurodegenerative origin of the initial AD-like FDG-PET abnormalities. We review similar cases and provide a comprehensive analysis of their implications, concluding that reversible FDG-PET widespread hypometabolism might represent a biomarker of pseudodementia. Therefore, we suggest caution when interpreting FDG-PET scans of depressed patients with cognitive impairment.

Cognitive and Brain Metabolism Profiles of Mild Cognitive Impairment in Prodromal Alpha-Synucleinopathy

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.

Biomarkers Related to Synaptic Dysfunction to Discriminate Alzheimer's Disease from Other Neurological Disorders

Recently, the synaptic proteins neurogranin (Ng) and α-synuclein (α-Syn) have attracted scientific interest as potential biomarkers for synaptic dysfunction in neurodegenerative diseases. In this study, we measured the CSF Ng and α-Syn concentrations in patients affected by AD (n = 69), non-AD neurodegenerative disorders (n-AD = 50) and non-degenerative disorders (n-ND, n = 98). The concentrations of CSF Ng and α-Syn were significantly higher in AD than in n-AD and n-ND. Moreover, the Aβ42/Ng and Aβ42/α-Syn ratios showed statistically significant differences between groups and discriminated AD patients from n-AD patients, better than Ng or α-Syn alone. Regression analyses showed an association of higher Ng concentrations with MMSE < 24, pathological Aβ 42/40 ratios, pTau, tTau and the ApoEε4 genotype. Aβ 42/Ng was associated with MMSE < 24, an AD-related FDG-PET pattern, the ApoEε4 genotype, pathological Aβ 42 levels and Aβ 42/40 ratios, pTau, and tTau. Moreover, APO-Eε4 carriers showed higher Ng concentrations than non-carriers. Our results support the idea that the Aβ 42/Ng ratio is a reliable index of synaptic dysfunction/degeneration able to discriminate AD from other neurological conditions.

Diagnosis and management of Parkinson's disease dementia and dementia with Lewy bodies: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology

Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB) represent the second most common type of degenerative dementia in patients aged 65 years and older, leading to progressive cognitive dysfunction and impaired quality of life. This study aims to provide a consensus based on a systematic Brazilian literature review and a comprehensive international review concerning PDD and DLB. Moreover, we sought to report on and give recommendations about the best diagnostic approaches focusing on primary and secondary care. Based on the available data, we recommend clinicians to apply at least one brief global cognitive instrument to assess PDD, such as the Mini-Mental State Examination and preferably the Montreal Cognitive Assessment and the Addenbrooke's Cognitive Examination-Revised. Validated instruments to accurately assess functional abilities in Brazilian PD patients are still incipient. Further studies should focus on biomarkers with Brazilian cohorts.

Diagnosis and management of Parkinson’s disease dementia and dementia with Lewy bodies: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology

ABSTRACT Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB) represent the second most common type of degenerative dementia in patients aged 65 years and older, leading to progressive cognitive dysfunction and impaired quality of life. This study aims to provide a consensus based on a systematic Brazilian literature review and a comprehensive international review concerning PDD and DLB. Moreover, we sought to report on and give recommendations about the best diagnostic approaches focusing on primary and secondary care. Based on the available data, we recommend clinicians to apply at least one brief global cognitive instrument to assess PDD, such as the Mini-Mental State Examination and preferably the Montreal Cognitive Assessment and the Addenbrooke’s Cognitive Examination-Revised. Validated instruments to accurately assess functional abilities in Brazilian PD patients are still incipient. Further studies should focus on biomarkers with Brazilian cohorts.

Current Potential for Clinical Optimization of Social Cognition Assessment for Frontotemporal Dementia and Primary Psychiatric Disorders

Dodich and colleagues recently reviewed the evidence supporting clinical use of social cognition assessment in behavioral variant frontotemporal dementia (Dodich et al., 2021). Here, we comment on their methods and present an initiative to address some of the limitations that emerged from their study. In particular, we established the social cognition workgroup within the Neuropsychiatric International Consortium Frontotemporal dementia (scNIC-FTD), aiming to validate social cognition assessment for diagnostic purposes and tracking of change across clinical situations.

Consistent Abnormalities in Metabolic Patterns of Lewy Body Dementias

BACKGROUND

Whether dementia with Lewy bodies (DLB) and Parkinson's disease (PD) dementia (PDD) represent the same disease, distinct entities, or conditions within the same spectrum remains controversial.

OBJECTIVE

The objective of this study was to provide new insight into this debate by separately identifying disease-specific metabolic patterns and comparing them with each other and with previously established PD-related pattern (PDRP).

METHODS

Patients with DLB (n = 67), patients with PDD (n = 50), and healthy control subjects (HCs; n = 15) with brain ¹⁸ F-fluorodeoxyglucose positron emission tomography were enrolled as cohorts A and B for pattern identification and validation, respectively. Patients with PD (n = 30) were included for discrimination. Twenty-one participants had two scans. The principal component analysis was applied for pattern identification (DLB-related pattern [DLBRP], PDD-related pattern [PDDRP]). Similarities and differences among three patterns were assessed by pattern topography, pattern expression, clinical correlations cross-sectionally, and pattern expression changes longitudinally.

RESULTS

DLBRP and PDDRP shared highly similar topographies, with relative hypometabolism mainly in the middle temporal gyrus, middle occipital gyrus, lingual gyrus, precuneus, cuneus, angular gyrus, superior and inferior parietal gyrus, middle and inferior frontal gyrus, cingulate, and caudate, and relative hypermetabolism in the cerebellum, putamen, thalamus, precentral/postcentral gyrus, and paracentral lobule, which were more extensive than the PDRP. Patients with DLB and PDD could not be distinguished successfully by any pattern, but patients with PD were easily recognized, especially by DLBRP and PDDRP. The pattern expression of DLBRP and PDDRP showed similar efficacy in cross-sectional disease severity assessment and longitudinal progression monitoring.

CONCLUSIONS

The consistent abnormalities in metabolic patterns of DLB and PDD might underline the potential continuum across the clinical spectrum from PD to DLB. © 2022 International Parkinson and Movement Disorder Society.

Preference Testing in Medical Devices: Current Framework and Regulatory Gaps

Preference testing is a valuable source of information that can be provided by both healthcare professionals (HCPs) and patients (users). It can be used to improve the design and development of medical devices by feeding into device usability and, ultimately, risk management. Furthermore, it can aid with selecting the most appropriate clinical endpoints to be used in the clinical evaluation of a device and increase patient engagement by incorporating patient-relevant outcomes. Preference testing is widely conducted in the food industry but is not widespread in the medical field due to limited guidelines and a lack of regulatory framework. As such, manufacturers may be unaware of the benefits of preference testing and fail to take full advantage of it, or conversely, may use inappropriate methodology and/or analyses and consequently fail to collect meaningful data. In this position paper, we aim to highlight the benefits and uses of preference testing, along with potential methods that could be used for preference testing of medical devices. A key step towards the wider implementation of preference testing in medical devices is for the publication of international standards and guidelines for the collection, assessment, and implementation of preference data into the life cycle of a medical device.

Identification and validation of Alzheimer's disease-related metabolic brain pattern in biomarker confirmed Alzheimer's dementia patients

Metabolic brain biomarkers have been incorporated in various diagnostic guidelines of neurodegenerative diseases, recently. To improve their diagnostic accuracy a biologically and clinically homogeneous sample is needed for their identification. Alzheimer's disease-related pattern (ADRP) has been identified previously in cohorts of clinically diagnosed patients with dementia due to Alzheimer's disease (AD), meaning that its diagnostic accuracy might have been reduced due to common clinical misdiagnosis. In our study, we aimed to identify ADRP in a cohort of AD patients with CSF confirmed diagnosis, validate it in large out-of-sample cohorts and explore its relationship with patients' clinical status. For identification we analyzed 2-[18F]FDG PET brain scans of 20 AD patients and 20 normal controls (NCs). For validation, 2-[18F]FDG PET scans from 261 individuals with AD, behavioral variant of frontotemporal dementia, mild cognitive impairment and NC were analyzed. We identified an ADRP that is characterized by relatively reduced metabolic activity in temporoparietal cortices, posterior cingulate and precuneus which co-varied with relatively increased metabolic activity in the cerebellum. ADRP expression significantly differentiated AD from NC (AUC = 0.95) and other dementia types (AUC = 0.76-0.85) and its expression correlated with clinical measures of global cognition and neuropsychological indices in all cohorts.

Positron Emission Tomography-Based Assessment of Cognitive Impairment and Dementias, Critical Role of Fluorodeoxyglucose in such Settings

Positron emission tomography (PET) has been a key component in the diagnostic armamentarium for assessing neurodegenerative diseases such as Alzheimer or Parkinson disease. PET imaging has been useful for diagnosing these disorders, identifying their pathophysiology, and following their treatment. Further, PET imaging has been extensively used for both clinical and research purposes, particularly for helping with potential therapeutic approaches for managing neurodegenerative diseases. This article will review the current literature regarding PET imaging in patients with neurodegenerative disorders. This includes an evaluation of the most commonly used tracer fluorodeoxyglucose that measures cerebral glucose metabolism, tracers that assess neurotransmitter systems, and tracers designed to reveal disease-specific pathophysiological processes. With the continuing development of an expanding variety of radiopharmaceuticals, PET imaging will likely play a prominent role in future research and clinical applications for neurodegenerative diseases.

Artificial Intelligence on FDG PET Images Identifies Mild Cognitive Impairment Patients with Neurodegenerative Disease

The purpose of this project is to develop and validate a Deep Learning (DL) FDG PET imaging algorithm able to identify patients with any neurodegenerative diseases (Alzheimer's Disease (AD), Frontotemporal Degeneration (FTD) or Dementia with Lewy Bodies (DLB)) among patients with Mild Cognitive Impairment (MCI). A 3D Convolutional neural network was trained using images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The ADNI dataset used for the model training and testing consisted of 822 subjects (472 AD and 350 MCI). The validation was performed on an independent dataset from La Fe University and Polytechnic Hospital. This dataset contained 90 subjects with MCI, 71 of them developed a neurodegenerative disease (64 AD, 4 FTD and 3 DLB) while 19 did not associate any neurodegenerative disease. The model had 79% accuracy, 88% sensitivity and 71% specificity in the identification of patients with neurodegenerative diseases tested on the 10% ADNI dataset, achieving an area under the receiver operating characteristic curve (AUC) of 0.90. On the external validation, the model preserved 80% balanced accuracy, 75% sensitivity, 84% specificity and 0.86 AUC. This binary classifier model based on FDG PET images allows the early prediction of neurodegenerative diseases in MCI patients in standard clinical settings with an overall 80% classification balanced accuracy.

Differential Diagnosis Between Alzheimer's Disease-Related Depression and Pseudo-Dementia in Depression: A New Indication for Amyloid-β Imaging?

BACKGROUND

Alzheimer's disease and depression can start with combined cognitive and depressive symptoms [1, 2]. Accurate differential diagnosis is desired to initiate specific treatment.

OBJECTIVE

We investigated whether amyloid-β PET imaging can discriminate both entities.

METHODS

This retrospective observational study included 39 patients (20 female, age = 70±11years) with both cognitive and depressive symptoms who underwent amyloid-β PET imaging and in whom clinical follow-up data was available. Amyloid-β PET was carried out applying [18F]Florbetaben or [11C]PiB. The PET images were analyzed by standardized visual and relative-quantitative evaluation. Based on clinical follow-up (median of 2.4 years [range 0.3 to 7.0 years, IQR = 3.7 years] after amyloid PET imaging which was not considered in obtaining a definite diagnosis), discrimination ability between AD-related depression and pseudo-dementia in depression/depression with other comorbidities was determined.

RESULTS

Visually, all 10 patients with pseudo-dementia in depression and all 15 patients with other depression were rated as amyloid-β-negative; 2 of 14 patients with AD-related depression were rated amyloid-β-negative. ROC curve analysis of the unified composite standardized uptake value ratios (cSUVRs) was able to discriminate pseudo-dementia in depression from AD-related depression with high accuracy (AUC = 0.92). Optimal [18F]Florbetaben discrimination cSUVR threshold was 1.34. In congruence with the visual PET analysis, the resulting sensitivity of the relative-quantitative analysis was 86% with a specificity of 100% .

CONCLUSION

Amyloid-β PET can differentiate AD-related depression and pseudo-dementia in depression. Prospective clinical studies are warranted to confirm this result and to potentially broaden the spectrum of clinical applications for amyloid-β PET imaging.

Functional Imaging for Neurodegenerative Diseases

Diagnosis and monitoring of neurodegenerative diseases has changed profoundly over the past twenty years. Biomarkers are now included in most diagnostic procedures as well as in clinical trials. Neuroimaging biomarkers provide access to brain structure and function over the course of neurodegenerative diseases. They have brought new insights into a wide range of neurodegenerative diseases and have made it possible to describe some of the imaging challenges in clinical populations. MRI mainly explores brain structure while molecular imaging, functional MRI and electro- and magnetoencephalography examine brain function. In this paper, we describe and analyse the current and potential contribution of MRI and molecular imaging in the field of neurodegenerative diseases.

Imaging Aspects of the Hippocampus

The hippocampus is one of the most sophisticated structures in the brain, owing to its complex anatomy, intriguing functions, relationship with other structures, and relevant associated symptoms. Despite being a structure analyzed for centuries, its anatomy and physiology in the human body are still being extensively studied, as well as associated pathologic conditions and potential biomarkers. It can be affected by a broad group of diseases that can be classified as congenital, degenerative, infectious or inflammatory, neoplastic, vascular, or toxic-metabolic disease. The authors present the anatomy and close structures, function, and development of the hippocampus, as well as an original algorithm for imaging diagnosis. The algorithm includes pathologic conditions that typically affect the hippocampus and groups them into nodular (space occupying) and nonnodular pathologic conditions, serving as a guide to narrow the differential diagnosis. MRI is the imaging modality of choice for evaluation of the hippocampus, and CT and nuclear medicine also improve the analysis. The MRI differential diagnosis depends on anatomic recognition and careful characterization of associated imaging findings such as volumetric changes, diffusion restriction, cystic appearance, hyperintensity at T1-weighted imaging, enhancement, or calcification, which play a central role in diagnosis along with clinical findings. Some pathologic conditions arising from surrounding structures such as the amygdala are also important to recognize. Pathologic conditions of the hippocampus can be a challenge to diagnose because they usually manifest as similar clinical syndromes, so the imaging findings play a potential role in guiding the final diagnosis. Online supplemental material is available for this article. ^©RSNA, 2022.

Validity of cingulate–precuneus–temporo-parietal hypometabolism for single-subject diagnosis of biomarker-proven atypical variants of Alzheimer’s Disease

The aim of our study was to establish empirically to what extent reduced glucose uptake in the precuneus, posterior cingulate and/or temporo-parietal cortex (PCTP), which is thought to indicate brain amyloidosis in patients with dementia or MCI due to Alzheimer’s Disease (AD), permits to distinguish amyloid-positive from amyloid-negative patients with non-classical AD phenotypes at the single-case level. We enrolled 127 neurodegenerative patients with cognitive impairment and a positive (n. 63) or negative (n. 64) amyloid marker (cerebrospinal fluid or amy-PET). Three rating methods of FDG-PET scan were applied: purely qualitative visual interpretation of uptake images (VIUI), and visual reading assisted by a semi-automated and semi-quantitative tool: INLAB, provided by the Italian National Research Council, or Cortex ID Suite, marketed by GE Healthcare. Fourteen scans (11.0%) patients remained unclassified by VIUI or INLAB procedures, therefore, validity values were computed on the remaining 113 cases. The three rating approaches showed good total accuracy (77–78%), good to optimal sensitivity (81–93%), but poorer specificity (62–75%). VIUI showed the highest sensitivity and the lowest specificity, and also the highest proportion of unclassified cases. Cases with asymmetric temporo-parietal hypometabolism and a progressive aphasia or corticobasal clinical profile, in particular, tended to be rated as AD-like, even if biomarkers indicated non-amyloid pathology. Our findings provide formal support to the value of PCTP hypometabolism for single-level diagnosis of amyloid pathophysiology in atypical AD, but also highlight the risk of qualitative assessment to misclassify patients with non-AD PPA or CBS underpinned by asymmetric temporo-parietal hypometabolism.