Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET

The use of individual-based FDG-PET volume of interest in predicting conversion from mild cognitive impairment to dementia

BACKGROUND

Based on a longitudinal cohort design, the aim of this study was to investigate whether individual-based 18F fluorodeoxyglucose positron emission tomography (18F-FDG-PET) regional signals can predict dementia conversion in patients with mild cognitive impairment (MCI).

METHODS

We included 44 MCI converters (MCI-C), 38 non-converters (MCI-NC), 42 patients with Alzheimer's disease with dementia, and 40 cognitively normal controls. Data from annual cognitive measurements, 3D T1 magnetic resonance imaging (MRI) scans, and 18F-FDG-PET scans were used for outcome analysis. An individual-based FDG-PET approach was applied using seven volumes of interest (VOIs), Z transformed using a normal FDG-PET template. Hypometabolism was defined as a Z score < -2 of regional standard uptake value ratio. For the longitudinal cognitive test scores, generalized estimating equations were used. A linear mixed-effects model was used to compare the temporal impact of cortical hypometabolism and cortical thickness degeneration.

RESULTS

The clinical follow-up period was 6.6 ± 3.8 years (range 3.1 to 16.0 years). The trend of cognitive decline could differentiate MCI-C from MCI-NC after 3 years of follow-up. In the baseline 18F-FDG-PET scan of the patients with MCI, medial temporal lobe (MTL; 94.7% sensitivity, 80.5% specificity) and posterior cingulate cortex (PCC; 89.5% sensitivity, 73.1% specificity) hypometabolism predicted conversion with high accuracy. 18F-FDG-PET hypometabolism preceded dementia conversion at an interval of 3.70 ± 1.68 years and was earlier than volumetric changes, with the exception of the MTL.

CONCLUSIONS

Our finding supports the use of individual-based 18F-FDG-PET analysis to predict MCI conversion to dementia. Reduced FDG-PET metabolism in the MTL and PCC were strongly associated with future cognitive decline in the MCI-C group. Changes in 18F-FDG-PET occurred 1 to 8 years prior to conversion to dementia. Progressive hypometabolism in the PCC, precuneus and lateral temporal lobe, but not MTL, preceded MRI findings at the MCI stage.

Automated detection of Alzheimer's disease: a multi-modal approach with 3D MRI and amyloid PET

Recent advances in deep learning and imaging technologies have revolutionized automated medical image analysis, especially in diagnosing Alzheimer's disease through neuroimaging. Despite the availability of various imaging modalities for the same patient, the development of multi-modal models leveraging these modalities remains underexplored. This paper addresses this gap by proposing and evaluating classification models using 2D and 3D MRI images and amyloid PET scans in uni-modal and multi-modal frameworks. Our findings demonstrate that models using volumetric data learn more effective representations than those using only 2D images. Furthermore, integrating multiple modalities enhances model performance over single-modality approaches significantly. We achieved state-of-the-art performance on the OASIS-3 cohort. Additionally, explainability analyses with Grad-CAM indicate that our model focuses on crucial AD-related regions for its predictions, underscoring its potential to aid in understanding the disease's causes.

DPP-4 inhibition by linagliptin ameliorates age-related mild cognitive impairment by regulating microglia polarization in mice

Extensive preclinical evidence demonstrates a causative link between insulin signaling dysfunction and the pathogenesis of Alzheimer's disease (AD), and diabetic drugs may represent a promising approach to fighting AD. However, it remains to be determined which antidiabetic drugs are more effective in preventing cognitive impairment. Thus, the present study investigated the effect of dipeptidyl peptidase-4 (DPP-4) inhibitor linagliptin on cognitive impairment in middle-aged mice by comparing it with the effect of metformin. We found that DPP-4 activity increased in the hippocampus of middle-aged mice, and DPP-4 was mainly expressed by microglia rather than astrocytes and oligodendrocytes. DPP-4 directly regulated M1/M2 microglia polarization following LPS or IL-4 stimulation, while DPP-4 inhibitor, linagliptin, suppressed M1-polarized activation and induced M2-polarized activation. Both linagliptin and metformin enhanced cognitive ability, increased hippocampal synaptic plasticity and neurogenesis, and decreased age-related oxidative stress and inflammation by regulating microglia polarization in the hippocampus of middle-aged mice. The combination of linagliptin and metformin showed a maximum protective effect compared to the individual drugs alone. Loss of macrophage inflammatory protein-1α (MIP-1α), a DPP-4 substrate, abrogated the cognitive protection and anti-inflammation effects of linagliptin. Therefore, the current investigation exhibits a potential utility for DPP-4 inhibition in attenuating microglia-mediated inflammation and preventing mild cognitive impairment (MCI) in middle-aged mice, and the effect was partly mediated by MIP-1α.

A nonhuman primate model with Alzheimer's disease-like pathology induced by hippocampal overexpression of human tau

BACKGROUND

Alzheimer's disease (AD) is one of the most burdening diseases of the century with no disease-modifying treatment at this time. Nonhuman primates (NHPs) share genetic, anatomical, and physiological similarities with humans, making them ideal model animals for investigating the pathogenesis of AD and potential therapies. However, the use of NHPs in AD research has been hindered by the paucity of AD monkey models due to their long generation time, ethical considerations, and technical challenges in genetically modifying monkeys.

METHODS

Here, we developed an AD-like NHP model by overexpressing human tau in the bilateral hippocampi of adult rhesus macaque monkeys. We evaluated the pathological features of these monkeys with immunostaining, Nissl staining, cerebrospinal fluid (CSF) analysis, magnetic resonance imaging (MRI), positron emission tomography (PET), and behavioural tests.

RESULTS

We demonstrated that after hippocampal overexpression of tau protein, these monkeys displayed multiple pathological features of AD, including 3-repeat (3R)/4-repeat (4R) tau accumulation, tau hyperphosphorylation, tau propagation, neuronal loss, hippocampal atrophy, neuroinflammation, Aβ clearance deficits, blood vessel damage, and cognitive decline. More interestingly, the accumulation of both 3R and 4R tau is specific to NHPs but not found in adult rodents.

CONCLUSIONS

This work establishes a tau-induced AD-like NHP model with many key pathological and behavioural features of AD. In addition, our model may potentially become one of the AD NHP models adopted by researchers worldwide since it can be generated within 2 ~ 3 months through a single injection of AAVs into the monkey brains. Hence, our model NHPs may facilitate mechanistic studies and therapeutic treatments for AD.

The potential of blood neurofilament light as a marker of neurodegeneration for Alzheimer's disease

Over the past several years, there has been a surge in blood biomarker studies examining the value of plasma or serum neurofilament light (NfL) as a biomarker of neurodegeneration for Alzheimer's disease. However, there have been limited efforts to combine existing findings to assess the utility of blood NfL as a biomarker of neurodegeneration for Alzheimer's disease. In addition, we still need better insight into the specific aspects of neurodegeneration that are reflected by the elevated plasma or serum concentration of NfL. In this review, we survey the literature on the cross-sectional and longitudinal relationships between blood-based NfL levels and other, neuroimaging-based, indices of neurodegeneration in individuals on the Alzheimer's continuum. Then, based on the biomarker classification established by the FDA-NIH Biomarker Working group, we determine the utility of blood-based NfL as a marker for monitoring the disease status (i.e. monitoring biomarker) and predicting the severity of neurodegeneration in older adults with and without cognitive decline (i.e. a prognostic or a risk/susceptibility biomarker). The current findings suggest that blood NfL exhibits great promise as a monitoring biomarker because an increased NfL level in plasma or serum appears to reflect the current severity of atrophy, hypometabolism and the decline of white matter integrity, particularly in the brain regions typically affected by Alzheimer's disease. Longitudinal evidence indicates that blood NfL can be useful not only as a prognostic biomarker for predicting the progression of neurodegeneration in patients with Alzheimer's disease but also as a susceptibility/risk biomarker predicting the likelihood of abnormal alterations in brain structure and function in cognitively unimpaired individuals with a higher risk of developing Alzheimer's disease (e.g. those with a higher amyloid-β). There are still limitations to current research, as discussed in this review. Nevertheless, the extant literature strongly suggests that blood NfL can serve as a valuable prognostic and susceptibility biomarker for Alzheimer's disease-related neurodegeneration in clinical settings, as well as in research settings.

Objective sleep was longitudinally associated with brain amyloid burden in mild cognitive impairment

OBJECTIVE

Understanding the longitudinal association of objective sleep and physical activity with brain amyloid burden and cortical glucose metabolism has critical clinical and public health implications for dementia prevention in later life.

METHODS

We enrolled 118 individuals aged ≥65 years with mild cognitive impairment, who were followed up on from August 2015 to September 2019. All participants continuously wore an accelerometer sensor for 7 consecutive days every 3 months and received annual 11 C-Pittsburgh compound-B and 18 F-fluorodeoxyglucose positron emission tomography (PET). Sleep and physical activity parameters were assessed using accelerometer sensor data and PET imaging was quantified using a standardized uptake-value ratio. Fifty-seven participants (48.3%) completed a lifestyle factor assessment and PET imaging over the 3-year period. A linear mixed-effects model was applied to examine the longitudinal association of sleep and physical activity parameters with PET imaging over the 3-year period, controlling for potential confounders.

RESULTS

Sleep efficiency was inversely associated with amyloid uptake in the frontal lobe. Although sleep duration was positively associated with global amyloid uptake, particularly in the frontal lobe, their impact was extremely small. However, physical activity parameters were not significantly associated with the 11 C-Pittsburgh compound-B-uptake. Furthermore, sleep and physical activity parameters were not significantly associated with cortical glucose metabolism.

INTERPRETATION

Lower sleep efficiency could be an early symptom of greater brain amyloid burden at the mild cognitive impairment stage. Therefore, the assessment of sleep may be useful for identifying individuals at higher risk for brain amyloid burden. Future longer term observational studies are required to confirm these findings.

Atrophy, hypometabolism and implication regarding pathology in late-life major depression with suspected non-alzheimer pathophysiology (SNAP)

BACKGROUND

A substantial proportion of individuals with late-life major depression could be classified as having a suspected non-Alzheimer disease pathophysiology (SNAP), as indicated by a negative test for the biomarker β-amyloid (Aβ-) but a positive test for neurodegeneration (ND+). This study investigated the clinical features, characteristic patterns of brain atrophy and hypometabolism, and implications regarding pathology in this population.

METHODS

Forty-six amyloid-negative patients with late-life major depressive disorder (MDD) patients, including 23 SNAP (Aβ-/ND+) and 23 Aβ-/ND- MDD subjects, and 22 Aβ-/ND-healthy control subjects were included in this study. Voxel-wise group comparisons between the SNAP MDD, Aβ-/ND- MDD and control subjects were performed, adjusting for age, gender and level of education. For exploratory comparisons, 8 Aβ+/ND- and 4 Aβ+/ND + MDD patients were included in the Supplementary Material.

RESULTS

The SNAP MDD patients had atrophy extending to regions outside the hippocampus, predominately in the medial temporal, dorsomedial and ventromedial prefrontal cortex; hypometabolism involving a large portion of the lateral and medial prefrontal cortex in addition to the bilateral temporal, parietal and precuneus cortex within typical Alzheimer disease regions were observed. Metabolism ratios of the inferior to the medial temporal lobe were significantly elevated in the SNAP MDD patients. We further discussed the implications with regards to underlying pathologies.

CONCLUSION

The present study demonstrated characteristic patterns of atrophy and hypometabolism in patients with late-life major depression with SNAP. Identifying individuals with SNAP MDD may provide insights into currently unspecified neurodegenerative processes. Future refinement of neurodegeneration biomarkers is essential in order to identify potential pathological correlates while in vivo reliable pathological biomarkers are not forthcoming.

Side-by-side regions in dorsolateral prefrontal cortex estimated within the individual respond differentially to domain-specific and domain-flexible processes

A recurring debate concerns whether regions of primate prefrontal cortex (PFC) support domain-flexible or domain-specific processes. Here we tested the hypothesis with functional MRI (fMRI) that side-by-side PFC regions, within distinct parallel association networks, differentially support domain-flexible and domain-specialized processing. Individuals (N = 9) were intensively sampled, and all effects were estimated within their own idiosyncratic anatomy. Within each individual, we identified PFC regions linked to distinct networks, including a dorsolateral PFC (DLPFC) region coupled to the medial temporal lobe (MTL) and an extended region associated with the canonical multiple-demand network. We further identified an inferior PFC region coupled to the language network. Exploration in separate task data, collected within the same individuals, revealed a robust functional triple dissociation. The DLPFC region linked to the MTL was recruited during remembering and imagining the future, distinct from juxtaposed regions that were modulated in a domain-flexible manner during working memory. The inferior PFC region linked to the language network was recruited during sentence processing. Detailed analysis of the trial-level responses further revealed that the DLPFC region linked to the MTL specifically tracked processes associated with scene construction. These results suggest that the DLPFC possesses a domain-specialized region that is small and easily confused with nearby (larger) regions associated with cognitive control. The newly described region is domain specialized for functions traditionally associated with the MTL. We discuss the implications of these findings in relation to convergent anatomical analysis in the monkey.NEW & NOTEWORTHY Competing hypotheses link regions of prefrontal cortex (PFC) to domain-flexible or domain-specific processes. Here, using a precision neuroimaging approach, we identify a domain-specialized region in dorsolateral PFC, coupled to the medial temporal lobe and recruited for scene construction. This region is juxtaposed to, but distinct from, broader PFC regions recruited flexibly for cognitive control. Region distinctions align with broader network differences, suggesting that PFC regions gain dissociable processing properties via segregated anatomical projections.

Harmonization of brain PET images in multi-center PET studies using Hoffman phantom scan

BACKGROUND

Image harmonization has been proposed to minimize heterogeneity in brain PET scans acquired in multi-center studies. However, standard validated methods and software tools are lacking. Here, we assessed the performance of a framework for the harmonization of brain PET scans in a multi-center European clinical trial.

METHOD

Hoffman 3D brain phantoms were acquired in 28 PET systems and reconstructed using site-specific settings. Full Width at Half Maximum (FWHM) of the Effective Image Resolution (EIR) and harmonization kernels were estimated for each scan. The target EIR was selected as the coarsest EIR in the imaging network. Using "Hoffman 3D brain Analysis tool," indicators of image quality were calculated before and after the harmonization: The Coefficient of Variance (COV%), Gray Matter Recovery Coefficient (GMRC), Contrast, Cold-Spot RC, and left-to-right GMRC ratio. A COV% ≤ 15% and Contrast ≥ 2.2 were set as acceptance criteria. The procedure was repeated to achieve a 6-mm target EIR in a subset of scans. The method's robustness against typical dose-calibrator-based errors was assessed.

RESULTS

The EIR across systems ranged from 3.3 to 8.1 mm, and an EIR of 8 mm was selected as the target resolution. After harmonization, all scans met acceptable image quality criteria, while only 13 (39.4%) did before. The harmonization procedure resulted in lower inter-system variability indicators: Mean ± SD COV% (from 16.97 ± 6.03 to 7.86 ± 1.47%), GMRC Inter-Quartile Range (0.040-0.012), and Contrast SD (0.14-0.05). Similar results were obtained with a 6-mm FWHM target EIR. Errors of ± 10% in the DRO activity resulted in differences below 1 mm in the estimated EIR.

CONCLUSION

Harmonizing the EIR of brain PET scans significantly reduced image quality variability while minimally affecting quantitative accuracy. This method can be used prospectively for harmonizing scans to target sharper resolutions and is robust against dose-calibrator errors. Comparable image quality is attainable in brain PET multi-center studies while maintaining quantitative accuracy.

Prognostic value of imaging-based ATN profiles in a memory clinic cohort

PURPOSE

The ATN model represents a research framework used to classify subjects based on the presence or absence of Alzheimer's disease (AD) pathology through biomarkers for amyloid (A), tau (T), and neurodegeneration (N). The aim of this study was to assess the relationship between ATN profiles defined through imaging and cognitive decline in a memory clinic cohort.

METHODS

One hundred-eight patients from the memory clinic of Geneva University Hospitals underwent complete clinical and neuropsychological evaluation at baseline and 23 ± 5 months after inclusion, magnetic resonance imaging, amyloid and tau PET scans. ATN profiles were divided into four groups: normal, AD pathological change (AD-PC: A + T-N-, A + T-N +), AD pathology (AD-P: A + T + N-, A + T + N +), and suspected non-AD pathology (SNAP: A-T + N-, A-T-N + , A-T + N +).

RESULTS

Mini-Mental State Examination (MMSE) scores were significantly different among groups, both at baseline and follow-up, with the normal group having higher average MMSE scores than the other groups. MMSE scores changed significantly after 2 years only in AD-PC and AD-P groups. AD-P profile classification also had the largest number of decliners at follow-up (55%) and the steepest global cognitive decline compared to the normal group. Cox regression showed that participants within the AD-P group had a higher risk of cognitive decline (HR = 6.15, CI = 2.59-14.59), followed by AD-PC (HR = 3.16, CI = 1.17-8.52).

CONCLUSION

Of the different group classifications, AD-P was found to have the most significant effect on cognitive decline over a period of 2 years, highlighting the value of both amyloid and tau PET molecular imaging as prognostic imaging biomarkers in clinical practice.

Altered brain metabolism in frontotemporal dementia and psychiatric disorders: involvement of the anterior cingulate cortex

BACKGROUND

Behavioural symptoms and frontotemporal hypometabolism overlap between behavioural variant of frontotemporal dementia (bvFTD) and primary psychiatric disorders (PPD), hampering diagnostic distinction. Voxel-wise comparisons of brain metabolism might identify specific frontotemporal-(hypo)metabolic regions between bvFTD and PPD. We investigated brain metabolism in bvFTD and PPD and its relationship with behavioural symptoms, social cognition, severity of depressive symptoms and cognitive functioning.

RESULTS

Compared to controls, bvFTD showed decreased metabolism in the dorsal anterior cingulate cortex (dACC) (p < 0.001), orbitofrontal cortex (OFC), temporal pole, dorsolateral prefrontal cortex (dlPFC) and caudate, whereas PPD showed no hypometabolism. Compared to PPD, bvFTD showed decreased metabolism in the dACC (p < 0.001, p < 0.05_FWE), insula, Broca's area, caudate, thalamus, OFC and temporal cortex (p < 0.001), whereas PPD showed decreased metabolism in the motor cortex (p < 0.001). Across bvFTD and PPD, decreased metabolism in the temporal cortex (p < 0.001, p < 0.05_FWE), dACC and frontal cortex was associated with worse social cognition. Decreased metabolism in the dlPFC was associated with compulsiveness (p < 0.001). Across bvFTD, PPD and controls, decreased metabolism in the PFC and motor cortex was associated with executive dysfunctioning (p < 0.001).

CONCLUSIONS

Our findings indicate subtle but distinct metabolic patterns in bvFTD and PPD, most strongly in the dACC. The degree of frontotemporal and cingulate hypometabolism was related to impaired social cognition, compulsiveness and executive dysfunctioning. Our findings suggest that the dACC might be an important region to differentiate between bvFTD and PPD but needs further validation.

Persistent 18F-FDG Brain PET Fronto-Temporal Hypometabolism and Cognitive Symptoms Two Years after SARS-CoV-2 Infection: A Case Report

At least 10% of patients experience persistent symptoms after SARS-CoV-2 infection, a condition referred to as post-acute COVID-19, post-acute sequelae of SARS-CoV-2 infection (PASC), long COVID, long-haul COVID, long-term effects of COVID, post-COVID-19 and chronic COVID. In this report, we describe a case of persistent cognitive deficits developed after SARS-CoV-2 infection in a 40-year-old woman with a family history of early-onset Alzheimer's disease (EOAD) since her father was diagnosed with EOAD at the age of 50. We describe the clinical picture and workup, with special emphasis on the alterations of brain glucose metabolism evidenced by 18-fluoro-deoxy-glucose positron emission tomography (FDG-PET), which could be considered a useful marker of the presence and persistence of cognitive deficits.

Dobutamine-induced alternations in cerebral blood flow of healthy adults: a 3D pseudocontinuous arterial spin labeling study

BACKGROUND

It is unclear whether dobutamine, commonly used clinically in echocardiography and short-term congestive heart failure treatment for promoting increased myocardial contractility, affects brain microcirculatory behavior. Cerebral microcirculation plays an important role in ensuring adequate oxygen transport. Therefore, we investigated the effects of dobutamine on cerebral hemodynamics.

METHODS

Forty-eight healthy volunteers without cardiovascular or cerebrovascular disease underwent MRI to obtain cerebral blood flow (CBF) maps using 3D pseudocontinuous arterial spin labeling before and during the dobutamine stress test. Additionally, cerebrovascular morphology was obtained based on 3D-time-off-light (3D-TOF) magnetic resonance angiography (MRA). Electrocardiogram, heart rate (HR), respiration rate (RR), blood pressure, and blood oxygen were simultaneously recorded before and during dobutamine injection and during recovery (not during MRI). The anatomic features of the circle of Willis and the basilar artery (BA) diameter were assessed on MRA images by two radiologists with extensive neuroimaging experience. Binary logistic regression was used to test for the independent determinants of CBF changes.

RESULTS

HR, RR, systolic (SBP), and diastolic blood pressure (DBP) significantly increased after dobutamine infusion. Blood oxygen levels remained similar. Compared to the CBF in the resting state, the CBF values exhibited significantly lower CBF levels in both grey matter and white matter. Furthermore, compared with the CBF in the resting state, that in the stress state was decreased in the anterior circulation, mainly in the frontal lobe (voxel level P < 0.001, pixel level P < 0.05). Logistic regression showed that body mass index (BMI; odds ratio [OR] 5.80, 95% confidence interval [CI] 1.60-21.01, P = 0.008], resting SBP (OR 0.64, 95% CI 0.45-0.92, P = 0.014), and BA diameter (OR 11.04, 95% CI 1.05-116.53, P = 0.046) were significantly associated with frontal lobe CBF changes.

CONCLUSIONS

Dobutamine-induced stress significantly decreased CBF in the frontal lobe anterior circulation. Individuals with a high BMI and low SBP during the dobutamine stress test are more likely to have a stress-induced CBF decrease. Thus, attention should be paid to blood pressure, BMI, and cerebrovascular morphology of patients undergoing dobutamine stress echocardiography or those receiving intensive care or anesthesia.

Sex differences in default mode network connectivity in healthy aging adults

Women show an increased lifetime risk of Alzheimer's disease (AD) compared with men. Characteristic brain connectivity changes, particularly within the default mode network (DMN), have been associated with both symptomatic and preclinical AD, but the impact of sex on DMN function throughout aging is poorly understood. We investigated sex differences in DMN connectivity over the lifespan in 595 cognitively healthy participants from the Human Connectome Project-Aging cohort. We used the intrinsic connectivity distribution (a robust voxel-based metric of functional connectivity) and a seed connectivity approach to determine sex differences within the DMN and between the DMN and whole brain. Compared with men, women demonstrated higher connectivity with age in posterior DMN nodes and lower connectivity in the medial prefrontal cortex. Differences were most prominent in the decades surrounding menopause. Seed-based analysis revealed higher connectivity in women from the posterior cingulate to angular gyrus, which correlated with neuropsychological measures of declarative memory, and hippocampus. Taken together, we show significant sex differences in DMN subnetworks over the lifespan, including patterns in aging women that resemble changes previously seen in preclinical AD. These findings highlight the importance of considering sex in neuroimaging studies of aging and neurodegeneration.

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.

Accelerated hypometabolism with disease progression associated with faster cognitive decline among amyloid positive patients

Objective

To evaluate the progression of brain glucose metabolism among participants with biological signature of Alzheimer's disease (AD) and its relevance to cognitive decline.

Method

We studied 602 amyloid positive individuals who underwent 18F-fluorodeoxyglucose PET (FDG-PET) scan, 18F-AV-45 amyloid PET (AV45-PET) scan, structural MRI scan and neuropsychological examination, including 116 cognitively normal (CN) participants, 314 participants diagnosed as mild cognitive impairment (MCI), and 172 participants diagnosed as AD dementia. The first FDG-PET scan satisfying the inclusion criteria was considered as the baseline scan. Cross-sectional analysis were conducted with the baseline FDG-PET data to compare the regional differences between diagnostic groups after adjusting confounding factors. Among these participants, 229 participants (55 CN, 139 MCI, and 35 AD dementia) had two-year follow-up FDG-PET data available. Regional glucose metabolism was computed and the progression rates of regional glucose metabolism were derived from longitudinal FDG-PET scans. Then the group differences of regional progression rates were examined to assess whether glucose metabolism deficit accelerates or becomes stable with disease progression. The association of cognitive decline rate with baseline regional glucose metabolism, and progression rate in longitudinal data, were evaluated.

Results

Participants with AD dementia showed substantial glucose metabolism deficit than CN and MCI at left hippocampus, in addition to the traditionally reported frontal and parietal-temporal lobe. More substantial metabolic change was observed with the contrast AD - MCI than the contrast MCI - CN, even after adjusting time duration since cognitive symptom onset. With the longitudinal data, glucose metabolism was observed to decline the most rapidly in the AD dementia group and at a slower rate in MCI. Lower regional glucose metabolism was correlated to faster cognitive decline rate with mild-moderate correlations, and the progression rate was correlated to cognitive decline rate with moderate-large correlations.

Discussion and conclusion

Hippocampus was identified to experience hypometabolism in AD pathology. Hypometabolism accelerates with disease progression toward AD dementia. FDG-PET, particularly longitudinal scans, could potentially help predict how fast cognition declines and assess the impact of treatment in interventional trials.

Do Epilepsy Patients with Cognitive Impairment Have Alzheimer's Disease-like Brain Metabolism?

Although not classically considered together, there is emerging evidence that Alzheimer's disease (AD) and epilepsy share a number of features and that each disease predisposes patients to developing the other. Using machine learning, we have previously developed an automated fluorodeoxyglucose positron emission tomography (FDG-PET) reading program (i.e., MAD), and demonstrated good sensitivity (84%) and specificity (95%) for differentiating AD patients versus healthy controls. In this retrospective chart review study, we investigated if epilepsy patients with/without mild cognitive symptoms also show AD-like metabolic patterns determined by the MAD algorithm. Scans from a total of 20 patients with epilepsy were included in this study. Because AD diagnoses are made late in life, only patients aged ≥40 years were considered. For the cognitively impaired patients, four of six were identified as MAD+ (i.e., the FDG-PET image is classified as AD-like by the MAD algorithm), while none of the five cognitively normal patients was identified as MAD+ (χ² = 8.148, p = 0.017). These results potentially suggest the usability of FDG-PET in prognosticating later dementia development in non-demented epilepsy patients, especially when combined with machine learning algorithms. A longitudinal follow-up study is warranted to assess the effectiveness of this approach.

Frontoparietal 18F-FDG-PET hypo-metabolism in Lennox-Gastaut syndrome: further evidence highlighting the key network

INTRODUCTION

Lennox Gastaut syndrome (LGS) can be conceptualised as a "secondary network epilepsy", in which the shared electroclinical manifestations reflect epileptic recruitment of a common brain network, despite a range of underlying aetiologies. We aimed to identify the key networks recruited by the epileptic process of LGS using interictal 2-deoxy-2-(¹⁸F)fluoro-D-glucose positron emission tomography (¹⁸F-FDG-PET).

METHODS

Group analysis of cerebral ¹⁸F-FDG-PET, comparing 21 patients with LGS (mean age = 15 years) and 18 pseudo-controls (mean age = 19 years), studied at Austin Health Melbourne, between 2004 and 2015. To minimise the influence of individual patient lesions in the LGS group, we only studied brain hemispheres without structural MRI abnormalities. The pseudo-control group consisted of age- and sex-matched patients with unilateral temporal lobe epilepsy, using only the hemispheres contralateral to the side of epilepsy. Voxel-wise permutation testing compared ¹⁸F-FDG-PET uptake between groups. Associations were explored between areas of altered metabolism and clinical variables (age of seizure onset, proportion of life with epilepsy, and verbal/nonverbal ability). Penetrance maps were calculated to explore spatial consistency of altered metabolic patterns across individual patients with LGS.

RESULTS

Although not always readily apparent on visual inspection of individual patient scans, group analysis revealed hypometabolism in a network of regions including prefrontal and premotor cortex, anterior and posterior cingulate, inferior parietal lobule, and precuneus (p < 0.05, corrected for family-wise error). These brain regions tended to show a greater reduction in metabolism in non-verbal compared to verbal LGS patients, although this difference was not statistically significant. No areas of hypermetabolism were detected on group analysis, although ∼25 % of individual patients showed increased metabolism (relative to pseudo-controls) in the brainstem, putamen, thalamus, cerebellum, and pericentral cortex.

DISCUSSION

Interictal hypometabolism in frontoparietal cortex in LGS is compatible with our previous EEG-fMRI and SPECT studies showing that interictal bursts of generalised paroxysmal fast activity and tonic seizures recruit similar cortical regions. This study provides further evidence that these regions are central to the electroclinical expression of LGS.

Altered cerebral blood flow and white matter during wakeful rest in patients with obstructive sleep apnea: a population-based retrospective study

OBJECTIVES

To explore changes in cerebral blood flow (CBF) and white matter during wakeful rest in patients with obstructive sleep apnea (OSA).

METHODS

The subjects comprised OSA patients and age- and sex-matched non-sleep apnea (NSA) subjects from December 2020 to December 2021. All subjects underwent structural and arterial spin labeling MRI examinations using a 3.0 T MRI scanner. Intergroup differences in regional and global CBF and white matter hyperintensities (WMHs) were analyzed.

RESULTS

In this study, 100 (74 males) of 750 (439 males) subjects were diagnosed with OSA, so the prevalence of OSA in the general population was 13.3% (100/750), with 16.9% (74/439) in males and 8.4% (26/311) in females. Excluding four patients with incomplete imaging data, 96 OSA patients and 103 age- and sex-matched NSA subjects were included. At global level, OSA patients showed significantly decreased CBF values in gray matter and whole brain compared to NSA subjects (gray matter: p = 0.010; whole brain: p = 0.021). No significant difference in CBF values was found in WM between the two groups (p = 0.250). At regional level, compared with NSA subjects, patients with OSA exhibited significantly decreased regional CBF values mainly in right parietal lobe and right temporal lobe. Moreover, OSA patients had significantly higher WMHs burden than NSA subjects (p = 0.017).

CONCLUSIONS

OSA patients exhibit decreased global and regional CBF values and increased WMHs burden.

ADVANCES IN KNOWLEDGE

These findings provide a basis for exploring neuropathological changes of OSA and for early and appropriate treatment.

Regional Precuneus Cortical Hyperexcitability in Alzheimer's Disease Patients

OBJECTIVE

Neuronal excitation/inhibition (E/I) imbalance is a potential cause of neuronal network malfunctioning in Alzheimer's disease (AD), contributing to cognitive dysfunction. Here, we used a novel approach combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to probe cortical excitability in different brain areas known to be directly involved in AD pathology.

METHODS

We performed TMS-EEG recordings targeting the left dorsolateral prefrontal cortex (l-DLPFC), the left posterior parietal cortex (l-PPC), and the precuneus (PC) in a large sample of patients with mild-to-moderate AD (n = 65) that were compared with a group of age-matched healthy controls (n = 21).

RESULTS

We found that patients with AD are characterized by a regional cortical hyperexcitability in the PC and, to some extent, in the frontal lobe, as measured by TMS-evoked potentials. Notably, cortical excitability assessed over the l-PPC was comparable between the 2 groups. Furthermore, we found that the individual level of PC excitability was associated with the level of cognitive impairment, as measured with Mini-Mental State Examination, and with corticospinal fluid levels of Aβ₄₂ .

INTERPRETATION

Our data provide novel evidence that precuneus cortical hyperexcitability is a key feature of synaptic dysfunction in patients with AD. The current results point to the combined approach of TMS and EEG as a novel promising technique to measure hyperexcitability in patients with AD. This index could represent a useful biomarker to stage disease severity and evaluate response to novel therapies. ANN NEUROL 2023;93:371-383.

Amyloid-β PET in Alzheimer's disease: A systematic review and Bayesian meta-analysis

BACKGROUND

In recent years, longitudinal studies of Alzheimer's disease (AD) have been successively concluded. Our aim is to determine the efficacy of amyloid-β (Aβ) PET in diagnosing AD and early prediction of mild cognitive impairment (MCI) converting to AD. By pooling studies from different centers to explore in-depth whether diagnostic performance varies by population type, radiotracer type, and diagnostic approach, thus providing a more comprehensive theoretical basis for the subsequent widespread application of Aβ PET in the clinical setting.

METHODS

Relevant studies were searched through PubMed. The pooled sensitivities, specificities, DOR, and the summary ROC curve were obtained based on a Bayesian random-effects model.

RESULTS

Forty-eight studies, including 5967 patients, were included. Overall, the pooled sensitivity, specificity, DOR, and AUC of Aβ PET for diagnosing AD were 0.90, 0.80, 35.68, and 0.91, respectively. Subgroup analysis showed that Aβ PET had high sensitivity (0.91) and specificity (0.81) for differentiating AD from normal controls but very poor specificity (0.49) for determining AD from MCI. The pooled sensitivity and specificity were 0.84 and 0.62, respectively, for predicting the conversion of MCI to AD. The differences in diagnostic efficacy between visual assessment and quantitative analysis and between ¹¹ C-PIB PET and ¹⁸ F-florbetapir PET were insignificant.

CONCLUSIONS

The overall performance of Aβ PET in diagnosing AD is favorable, but the differentiation between MCI and AD patients should consider that some MCI may be at risk of conversion to AD and may be misdiagnosed. A multimodal diagnostic approach and machine learning analysis may be effective in improving diagnostic accuracy.

APOE alleles are associated with sex-specific structural differences in brain regions affected in Alzheimer's disease and related dementia

Alzheimer's disease is marked by intracellular tau aggregates in the medial temporal lobe (MTL) and extracellular amyloid aggregates in the default network (DN). Here, we examined codependent structural variations between the MTL's most vulnerable structure, the hippocampus (HC), and the DN at subregion resolution in individuals with Alzheimer's disease and related dementia (ADRD). By leveraging the power of the approximately 40,000 participants of the UK Biobank cohort, we assessed impacts from the protective APOE ɛ2 and the deleterious APOE ɛ4 Alzheimer's disease alleles on these structural relationships. We demonstrate ɛ2 and ɛ4 genotype effects on the inter-individual expression of HC-DN co-variation structural patterns at the population level. Across these HC-DN signatures, recurrent deviations in the CA1, CA2/3, molecular layer, fornix's fimbria, and their cortical partners related to ADRD risk. Analyses of the rich phenotypic profiles in the UK Biobank cohort further revealed male-specific HC-DN associations with air pollution and female-specific associations with cardiovascular traits. We also showed that APOE ɛ2/2 interacts preferentially with HC-DN co-variation patterns in estimating social lifestyle in males and physical activity in females. Our structural, genetic, and phenotypic analyses in this large epidemiological cohort reinvigorate the often-neglected interplay between APOE ɛ2 dosage and sex and link APOE alleles to inter-individual brain structural differences indicative of ADRD familial risk.

Retinal Vascular Physiology Biomarkers in a 5XFAD Mouse Model of Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disorder that affects the brain and retina and lacks reliable biomarkers for early diagnosis. As amyloid beta (Aβ) manifestations emerge prior to clinical symptoms and plaques of amyloid may cause vascular damage, identification of retinal vascular biomarkers may improve knowledge of AD pathophysiology and potentially serve as therapeutic targets. The purpose of the current study was to test the hypothesis that retinal hemodynamic and oxygen metrics are altered in 5XFAD mice.

METHODS

Thirty-two male mice were evaluated at 3 months of age: sixteen 5XFAD transgenic and sixteen wild-type mice. Spectral-domain optical coherence tomography, vascular oxygen tension, and blood flow imaging were performed in one eye of each mouse. After imaging, the imaged and fellow retinal tissues were submitted for histological sectioning and amyloid protein analysis, respectively. Protein analysis was also performed on the brain tissues.

RESULTS

Retinal physiological changes in venous diameter and blood velocity, arterial and venous oxygen contents, coupled with anatomical alterations in the thickness of retinal cell layers were detected in 5XFAD mice. Moreover, an increase in Aβ42 levels in both the retina and brain tissues was observed in 5XFAD mice. Significant changes in retinal oxygen delivery, metabolism, or extraction fraction were not detected. Based on compiled data from both groups, arterial oxygen content was inversely related to venous blood velocity and nerve fiber/ganglion cell layer thickness.

CONCLUSIONS

Concurrent alterations in retinal hemodynamic and oxygen metrics, thickness, and tissue Aβ42 protein levels in 5XFAD mice at 3 months of age corresponded to previously reported findings in human AD. Overall, these results suggest that this mouse model can be utilized for studying pathophysiology of AD and evaluating potential therapies.

Alzheimer's disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA

BACKGROUND

2-Deoxy-2-[¹⁸F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer's disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic ¹¹C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R₁), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs.

RESULTS

In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution.

CONCLUSION

rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA.

Decreased Cerebral Amyloid-β Depositions in Patients With a Lifetime History of Major Depression With Suspected Non-Alzheimer Pathophysiology

Cerebral amyloid-β (Aβ) depositions in depression in old age are controversial. A substantial proportion of individuals with late-life major depressive disorder (MDD) could be classified as having suspected non-Alzheimer’s disease pathophysiology (SNAP) by a negative test for the biomarker amyloid-β (Aβ−) but positive neurodegeneration (ND+). This study aimed to evaluate subthreshold Aβ loads in amyloid-negative MDD, particularly in SNAP MDD patients. This study included 46 amyloid-negative MDD patients: 23 SNAP (Aβ−/ND+) MDD and 23 Aβ−/ND− MDD, and 22 Aβ−/ND− control subjects. All subjects underwent ¹⁸F-florbetapir PET, FDG-PET, and MRI. Regions of interest (ROIs) and voxel-wise group comparisons were performed with adjustment for age, gender, and level of education. The SNAP MDD patients exhibited significantly deceased ¹⁸F-florbetapir uptakes in most cortical regions but not the parietal and precuneus cortex, as compared with the Aβ−/ND− MDD and control subjects (FDR correction, p < 0.05). No correlations of neuropsychological tests or depression characteristics with global cortical uptakes, but significant positive correlations between cognitive functions and adjusted hippocampal volumes among different groups were observed. The reduced Aβ depositions in the amyloid-negative MDD patients might be attributed mainly to the SNAP MDD patients. Our results indicated that meaningfully low amounts of subclinical Aβ might contain critical information on the non-amyloid-mediated pathogenesis.

Explainable AI toward understanding the performance of the top three TADPOLE Challenge methods in the forecast of Alzheimer’s disease diagnosis

The Alzheimer′s Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge is the most comprehensive challenge to date with regard to the number of subjects, considered features, and challenge participants. The initial objective of TADPOLE was the identification of the most predictive data, features, and methods for the progression of subjects at risk of developing Alzheimer′s. The challenge was successful in recognizing tree-based ensemble methods such as gradient boosting and random forest as the best methods for the prognosis of the clinical status in Alzheimer’s disease (AD). However, the challenge outcome was limited to which combination of data processing and methods exhibits the best accuracy; hence, it is difficult to determine the contribution of the methods to the accuracy. The quantification of feature importance was globally approached by all the challenge participant methods. In addition, TADPOLE provided general answers that focused on improving performance while ignoring important issues such as interpretability. The purpose of this study is to intensively explore the models of the top three TADPOLE Challenge methods in a common framework for fair comparison. In addition, for these models, the most meaningful features for the prognosis of the clinical status of AD are studied and the contribution of each feature to the accuracy of the methods is quantified. We provide plausible explanations as to why the methods achieve such accuracy, and we investigate whether the methods use information coherent with clinical knowledge. Finally, we approach these issues through the analysis of SHapley Additive exPlanations (SHAP) values, a technique that has recently attracted increasing attention in the field of explainable artificial intelligence (XAI).

Brain Glucose Hypometabolism and Iron Accumulation in Different Brain Regions in Alzheimer's and Parkinson's Diseases

The aim of this study was to examine the relationship between the presence of glucose hypometabolism (GHM) and brain iron accumulation (BIA), two potential pathological mechanisms in neurodegenerative disease, in different regions of the brain in people with late-onset Alzheimer's disease (AD) or Parkinson's disease (PD). Studies that conducted fluorodeoxyglucose positron emission tomography (FDG-PET) to map GHM or quantitative susceptibility mapping-magnetic resonance imaging (QSM-MRI) to map BIA in the brains of patients with AD or PD were reviewed. Regions of the brain where GHM or BIA were reported in each disease were compared. In AD, both GHM and BIA were reported in the hippocampus, temporal, and parietal lobes. GHM alone was reported in the cingulate gyrus, precuneus and occipital lobe. BIA alone was reported in the caudate nucleus, putamen and globus pallidus. In PD, both GHM and BIA were reported in thalamus, globus pallidus, putamen, hippocampus, and temporal and frontal lobes. GHM alone was reported in cingulate gyrus, caudate nucleus, cerebellum, and parietal and occipital lobes. BIA alone was reported in the substantia nigra and red nucleus. GHM and BIA are observed independent of one another in various brain regions in both AD and PD. This suggests that GHM is not always necessary or sufficient to cause BIA and vice versa. Hypothesis-driven FDG-PET and QSM-MRI imaging studies, where both are conducted on individuals with AD or PD, are needed to confirm or disprove the observations presented here about the potential relationship or lack thereof between GHM and BIA in AD and PD.

Possibility of Enlargement in Left Medial Temporal Areas Against Cerebral Amyloid Deposition Observed During Preclinical Stage

Neurodegenerative changes in the preclinical stage of Alzheimer’s disease (AD) have recently been the focus of attention because they may present a range of treatment opportunities. A total of 134 elderly volunteers who lived in a local community were investigated and grouped into preclinical and mild cognitive impairment stages according to the Clinical Dementia Rating test; we also estimated amyloid deposition in the brain using positron emission tomography (PET). A significant interaction between clinical stage and amyloid PET positivity on cerebral atrophy was observed in the bilateral parietal lobe, parahippocampal gyri, hippocampus, fusiform gyrus, and right superior and middle temporal gyri, as previously reported. Early AD-specific voxel of interest (VOI) analysis was also applied and averaged Z-scores in the right, left, bilateral, and right minus left medial temporal early AD specific area were computed. We defined these averaged Z-scores in the right, left, bilateral, and right minus left early AD specific VOI in medial temporal area as R-MedT-Atrophy-score, L-MedT-Atrophy-score, Bil-MedT-Atrophy-score, and R_L-MedT-Atrophy-score, respectively. It revealed that the R_L-MedT-Atrophy-scores were significantly larger in the amyloid-positive than in the amyloid-negative cognitively normal (CN) elderly group, that is, the right medial temporal areas were smaller than left in amyloid positive CN group and these left-right differences were significantly larger in amyloid positive than amyloid negative CN elderly group. The L-MedT-Atrophy-score was slightly larger (p = 0.073), that is, the left medial temporal area was smaller in the amyloid-negative CN group than in the amyloid-positive CN group. Conclusively, the left medial temporal area could be larger in CN participants with amyloid deposition than in those without amyloid deposition. The area under the receiver operating characteristic curve for differentiating amyloid positivity among CN participants using the R_L-MedT-Atrophy-scores was 0.73; the sensitivity and specificity were 0.828 and 0.606, respectively. Although not significant, a negative correlation was observed between the composite cerebral standardized uptake value ratio in amyloid PET images and L-MedT-Atrophy-score in CN group. The left medial temporal volume might become enlarged because of compensatory effects against AD pathology occurring at the beginning of the amyloid deposition.

Alzheimer's Disease as Type 3 Diabetes: Common Pathophysiological Mechanisms between Alzheimer's Disease and Type 2 Diabetes

Globally, the incidence of type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) epidemics is increasing rapidly and has huge financial and emotional costs. The purpose of the current review article is to discuss the shared pathophysiological connections between AD and T2DM. Research findings are presented to underline the vital role that insulin plays in the brain's neurotransmitters, homeostasis of energy, as well as memory capacity. The findings of this review indicate the existence of a mechanistic interplay between AD pathogenesis with T2DM and, especially, disrupted insulin signaling. AD and T2DM are interlinked with insulin resistance, neuroinflammation, oxidative stress, advanced glycosylation end products (AGEs), mitochondrial dysfunction and metabolic syndrome. Beta-amyloid, tau protein and amylin can accumulate in T2DM and AD brains. Given that the T2DM patients are not routinely evaluated in terms of their cognitive status, they are rarely treated for cognitive impairment. Similarly, AD patients are not routinely evaluated for high levels of insulin or for T2DM. Studies suggesting AD as a metabolic disease caused by insulin resistance in the brain also offer strong support for the hypothesis that AD is a type 3 diabetes.

60 Years of Achievements by KSNM in Neuroimaging Research

Nuclear medicine neuroimaging is able to show functional and molecular biologic abnormalities in various neuropsychiatric diseases. Therefore, it has played important roles in the clinical diagnosis and in research on the normal and pathological states of the brain. More than 400 outstanding studies have been conducted by Korean researchers over the past 60 years. In the 1990s, when multiheaded single-photon emission computed tomography (SPECT) scanners were first introduced in South Korea, stroke research using brain perfusion SPECT was conducted. With the spread of positron emission tomography (PET) scanners in the 2000s, research on the clinical usefulness of PET and the evaluation of pathophysiology in various diseases such as epilepsy, brain tumors, degenerative brain diseases, and other neuropsychiatric diseases were actively conducted using [¹⁸F]FDG and various neuroreceptor tracers. In the 2010s, with the clinical application of new radiopharmaceuticals for amyloid and tau imaging, research demonstrating the clinical usefulness of PET imaging and the pathophysiology of dementia has increased rapidly. It is expected that the role of nuclear medicine will expand with the development of new radiopharmaceuticals and analysis technologies, along with the application of artificial intelligence for early and differential diagnosis, and the development of therapeutic agents for degenerative brain diseases.

Mitochondria, energy, and metabolism in neuronal health and disease

Mitochondria are associated with various cellular activities critical to homeostasis, particularly in the nervous system. The plastic architecture of the mitochondrial network and its dynamic structure play crucial roles in ensuring that varying energetic demands are rapidly met to maintain neuronal and axonal energy homeostasis. Recent evidence associates ageing and neurodegeneration with anomalous neuronal metabolism, as age-dependent alterations of neuronal metabolism are now believed to occur prior to neurodegeneration. The brain has a high energy demand, which makes it particularly sensitive to mitochondrial dysfunction. Distinct cellular events causing oxidative stress or disruption of metabolism and mitochondrial homeostasis can trigger a neuropathology. This review explores the bioenergetic hypothesis for the neurodegenerative pathomechanisms, discussing factors leading to age-related brain hypometabolism and its contribution to cognitive decline. Recent research on the mitochondrial network in healthy nervous system cells, its response to stress and how it is affected by pathology, as well as current contributions to novel therapeutic approaches will be highlighted.

Altered Neurovascular Coupling in Unilateral Pulsatile Tinnitus

Objective

Altered cerebral blood flow (CBF) and regional homogeneity (ReHo) have been reported in pulsatile tinnitus (PT) patients. We aimed to explore regional neurovascular coupling changes in PT patients.

Materials and Methods

Twenty-four right PT patients and 25 sex- and age-matched normal controls were included in this study. All subjects received arterial spin labeling imaging to measure CBF and functional MRI to compute ReHo. CBF/ReHo ratio was used to assess regional neurovascular coupling between the two groups. We also analyzed the correlation between CBF/ReHo ratio and clinical data from the PT patients.

Results

PT patients exhibited increased CBF/ReHo ratio in left middle temporal gyrus and right angular gyrus than normal controls, and no decreased CBF/ReHo ratio was found. CBF/ReHo ratio in the left middle temporal gyrus of PT patients was positively correlated with Tinnitus Handicap Inventory score (r = 0.433, p = 0.035).

Conclusion

These findings indicated that patients with PT exhibit abnormal neurovascular coupling, which provides new information for understanding the neuropathological mechanisms underlying PT.

EANM procedure guidelines for brain PET imaging using [18F]FDG, version 3

The present procedural guidelines summarize the current views of the EANM Neuro-Imaging Committee (NIC). The purpose of these guidelines is to assist nuclear medicine practitioners in making recommendations, performing, interpreting, and reporting results of [¹⁸F]FDG-PET imaging of the brain. The aim is to help achieve a high-quality standard of [¹⁸F]FDG brain imaging and to further increase the diagnostic impact of this technique in neurological, neurosurgical, and psychiatric practice. The present document replaces a former version of the guidelines that have been published in 2009. These new guidelines include an update in the light of advances in PET technology such as the introduction of digital PET and hybrid PET/MR systems, advances in individual PET semiquantitative analysis, and current broadening clinical indications (e.g., for encephalitis and brain lymphoma). Further insight has also become available about hyperglycemia effects in patients who undergo brain [¹⁸F]FDG-PET. Accordingly, the patient preparation procedure has been updated. Finally, most typical brain patterns of metabolic changes are summarized for neurodegenerative diseases. The present guidelines are specifically intended to present information related to the European practice. The information provided should be taken in the context of local conditions and regulations.

18F-FDG-PET Imaging for Post-COVID-19 Brain and Skeletal Muscle Alterations

Scientific evidence concerning the subacute and long-term effects of coronavirus disease 2019 (COVID-19) is on the rise. It has been established that infection by serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a systemic process that involves multiple organs. The complications and long-term consequences of COVID-19 are diverse and patients need a multidisciplinary treatment approach in the acute and post-acute stages of the disease. A significant proportion of COVID-19 patients experience neurological manifestations, some enduring for several months post-recovery. However, brain and skeletal muscle changes resultant from SARS CoV-2 infection remain largely unknown. Here, we provide a brief overview of the current knowledge, and usefulness, of [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT) to investigate brain and skeletal muscles changes in Post-COVID-19 patients with persistent symptoms. Furthermore, a brief discussion of future ¹⁸F-FDG-PET/CT applications that might advance the current knowledge of the pathogenesis of post-COVID-19 is also provided.

Cerebral amyloid load determination in a clinical setting: interpretation of amyloid biomarker discordances aided by tau and neurodegeneration measurements

BACKGROUND

Alzheimer's disease (AD) diagnosis can be hindered by amyloid biomarkers discordances.

OBJECTIVE

We aim to interpret discordances between amyloid positron emission tomography (Amy-PET) and cerebrospinal fluid (CSF) (Aβ₄₂ and Aβ_42/40), using Amy-PET semiquantitative analysis, [¹⁸F]fluorodeoxyglucose (FDG)-PET pattern, and CSF assays.

METHOD

Thirty-six subjects with dementia or mild cognitive impairment, assessed by neuropsychological tests, structural and functional imaging, and CSF assays (Aβ₄₂, Aβ_42/40, p-tau, t-tau), were retrospectively examined. Amy-PET and FDG-PET scans were analyzed by visual assessment and voxel-based analysis. SUVR were calculated on Amy-PET scans.

RESULTS

Groups were defined basing on the agreement among CSF Aβ₄₂ (A), CSF Aβ_42/40 Ratio (R), and Amy-PET (P) dichotomic results ( ±). In discordant groups, CSF assays, Amy-PET semiquantification, and FDG-PET patterns supported the diagnosis suggested by any two agreeing amyloid biomarkers. In groups with discordant CSF Aβ₄₂, the ratio always agrees with Amy-PET results, solving both false-negative and false-positive Aβ₄₂ results, with Aβ₄₂ levels close to the cut-off in A + R-P- subjects. The A + R + P- group presented high amyloid deposition in relevant areas, such as precuneus, posterior cingulate cortex (PCC) and dorsolateral frontal inferior cortex at semiquantitative analysis.

CONCLUSION

The amyloid discordant cases could be overcome by combining CSF Aβ₄₂, CSF ratio, and Amy-PET results. The concordance of any 2 out of the 3 biomarkers seems to reveal the remaining one as a false result. A cut-off point review could avoid CSF Aβ₄₂ false-negative results. The regional semiquantitative Amy-PET analysis in AD areas, such as precuneus and PCC, could increase the accuracy in AD diagnosis.

Alzheimer's Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases

Dementia is broadly characterized by cognitive and psychological dysfunction that significantly impairs daily functioning. Dementia has many causes including Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD). Detection and differential diagnosis in the early stages of dementia remains challenging. Fueled by AD Neuroimaging Initiatives (ADNI) (Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. As such, the investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.), a number of neuroimaging biomarkers for AD have been proposed, yet it remains to be seen whether these markers are also sensitive to other types of dementia. We assessed AD-related metabolic patterns in 27 patients with diverse forms of dementia (five had probable/possible AD while others had atypical cases) and 20 non-demented individuals. All participants had positron emission tomography (PET) scans on file. We used a pre-trained machine learning-based AD designation (MAD) framework to investigate the AD-related metabolic pattern among the participants under study. The MAD algorithm showed a sensitivity of 0.67 and specificity of 0.90 for distinguishing dementia patients from non-dementia participants. A total of 18/27 dementia patients and 2/20 non-dementia patients were identified as having AD-like patterns of metabolism. These results highlight that many underlying causes of dementia have similar hypometabolic pattern as AD and this similarity is an interesting avenue for future research.

Evaluation of Age and Sex-Related Metabolic Changes in Healthy Subjects: An Italian Brain 18F-FDG PET Study

Background: 18F-fluorodeoxyglucose (18F-FDG) positron-emission-tomography (PET) allows detection of cerebral metabolic alterations in neurological diseases vs. normal aging. We assess age- and sex-related brain metabolic changes in healthy subjects, exploring impact of activity normalization methods. Methods: brain scans of Italian Association of Nuclear Medicine normative database (151 subjects, 67 Males, 84 Females, aged 20–84) were selected. Global mean, white matter, and pons activity were explored as normalization reference. We performed voxel-based and ROI analyses using SPM12 and IBM-SPSS software. Results: SPM proved a negative correlation between age and brain glucose metabolism involving frontal lobes, anterior-cingulate and insular cortices bilaterally. Narrower clusters were detected in lateral parietal lobes, precuneus, temporal pole and medial areas bilaterally. Normalizing on pons activity, we found a more significant negative correlation and no positive one. ROIs analysis confirmed SPM results. Moreover, a significant age × sex interaction effect was revealed, with worse metabolic reduction in posterior-cingulate cortices in females than males, especially in post-menopausal age. Conclusions: this study demonstrated an age-related metabolic reduction in frontal lobes and in some parieto-temporal areas more evident in females. Results suggested pons as the most appropriate normalization reference. Knowledge of age- and sex-related cerebral metabolic changes is critical to correctly interpreting brain 18F-FDG PET imaging.

Relationship between Cerebrospinal Fluid Matrix Metalloproteinases Levels and Brain Amyloid Deposition in Mild Cognitive Impairment

This study aimed to explore whether cerebrospinal fluid (CSF) levels of matrix metalloproteinases (MMPs), and their inhibitors (TIMPs) were associated with brain amyloid deposition, cortical glucose metabolism, and white matter lesions (WMLs) in individuals with amnestic mild cognitive impairment (MCI). A total of 33 individuals with amnestic MCI (mean age, 75.6 years) underwent ¹¹C-Pittsburgh compound B positron emission tomography (PiB-PET), ¹⁸F-fluorodeoxyglucose positron emission tomography, magnetic resonance imaging or computed tomography, and CSF analysis. PET uptake of the frontal and temporoparietal lobes and posterior cingulate gyrus was assessed using the cerebellar cortex as the reference region. WMLs were assessed by the Fazekas scale. CSF levels of MMPs and TIMPs were measured with bead-based multiplex assays. After adjusting for covariates, multiple linear regression analysis showed that CSF levels of MMP-2 were negatively correlated with global PiB uptake (p = 0.035), especially in the parietotemporal lobe and posterior cingulate gyrus (p = 0.016 and p = 0.041, respectively). Moreover, CSF levels of MMP-7 were positively correlated with the severity of WMLs (p = 0.033). CSF levels of MMP-2 and MMP-7 are associated with brain amyloid deposition and severity of WMLs, respectively. These findings provide valuable insights into the role of MMPs in amyloid β catabolism and blood-brain barrier integration at the MCI stage.

Novel Serum Biomarkers of Neurovascular Unit Associated with Cortical Amyloid Deposition

BACKGROUND

Whether blood biomarkers of neurovascular unit are associated with cortical amyloid deposition on positron emission tomography (PET) imaging remains unclear.

OBJECTIVE

To investigate the association between novel serum biomarkers of neurovascular unit, such as protein tyrosine phosphatase receptor type B (PTPRB), gap junction protein alpha-5 (GJA5), adenosine triphosphate-sensitive inward rectifier potassium channel-8 (KCNJ8), and von Willebrand factor (vWF), and cortical amyloid deposition.

METHODS

Between 2012 and 2018, 68 elderly individuals with amnestic mild cognitive impairment (32 men and 36 women; mean age 75.2 years) were enrolled. All participants underwent 11C-Pittsburgh compound-B (PiB)-PET, 18F-fluorodeoxyglucose-PET, and measurement of serum PTPRB, GJA5, KCNJ8, and vWF levels using commercially available human enzyme-linked immunosorbent assay kits. Based on the mean cortical standardized uptake value ratio, the participants were divided into two groups: PiB-negative group and PiB-positive group. Serum levels of PTPRB, GJA5, KCNJ8, and vWF were compared between the two groups. Multiple linear regression analysis was performed to investigate the relationship between serum PTPRB, GJA5, KCNJ8, and vWF levels and cortical amyloid deposition.

RESULTS

PTPRB and GJA5 levels were significantly lower and KCNJ8 and vWF levels were significantly higher in the PiB-positive group than in the PiB-negative group. PTPRB and GJA5 levels inversely correlated with mean PiB uptake, whereas KCNJ8 and vWF levels positively correlated with mean PiB uptake.

CONCLUSION

Serum levels of PTPRB, GJA5, KCNJ8, and vWF correlate with cortical amyloid deposition. These novel blood biomarkers of neurovascular unit are useful for identifying elderly individuals at risk of developing Alzheimer's disease.

The Evolution of Image Reconstruction in PET: From Filtered Back-Projection to Artificial Intelligence

PET can provide functional images revealing physiologic processes in vivo. Although PET has many applications, there are still some limitations that compromise its precision: the absorption of photons in the body causes signal attenuation; the dead-time limit of system components leads to the loss of the count rate; the scattered and random events received by the detector introduce additional noise; the characteristics of the detector limit the spatial resolution; and the low signal-to-noise ratio caused by the scan-time limit (eg, dynamic scans) and dose concern. The early PET reconstruction methods are analytical approaches based on an idealized mathematical model.

Comparison of the decreases in regional cerebral blood flow in the posterior cingulate cortex, precuneus, and parietal lobe between suspected non-Alzheimer's disease pathophysiology and Alzheimer's disease

BACKGROUND

Suspected non-Alzheimer's disease pathophysiology (SNAP) shows Alzheimer's disease (AD)-like neurodegeneration; however, amyloid β, which is a biological marker in AD, remains within normal levels. Since the effectiveness of anti-dementia drugs for AD on SNAP is unknown, it is important to distinguish between patients with SNAP and AD. We aimed to compare decreases in regional cerebral blood flow (rCBF) of the posterior cingulate cortex (PCC), precuneus, and parietal lobe critical to AD between SNAP and AD groups using the easy Z-score imaging system in single-photon emission computed tomography (eZIS-SPECT).

METHODS

We retrospectively analysed eZIS-SPECT data of 13 SNAP and 24 AD patients. The three indicators (severity, extent, and ratio) that distinguished AD patients from healthy controls in previous studies were automatically calculated and were compared between the SNAP and AD groups. Receiver operating characteristic curve analysis and the area under the curve (AUC) were used to evaluate the diagnostic performance of the three indicators of eZIS in discriminating between the two groups.

RESULTS

The mean values of severity, extent, and ratio were significantly lower in the SNAP group than in the AD group (P = 0.024, P = 0.044, and P = 0.045, respectively). The AUC values for severity, extent, and ratio were 0.668, 0.683, and 0.692, respectively.

CONCLUSIONS

The present study suggests that SNAP shows milder reduction of rCBF in the PCC, precuneus, and parietal lobe as compared to AD. However, it may be difficult to distinguish between SNAP and AD with the degrees of decrease in rCBF in these regions.

A Bayesian group lasso classification for ADNI volumetrics data

The primary objective of this paper is to develop a statistically valid classification procedure for analyzing brain image volumetrics data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) in elderly subjects with cognitive impairments. The Bayesian group lasso method thereby proposed for logistic regression efficiently selects an optimal model with the use of a spike and slab type prior. This method selects groups of attributes of a brain subregion encouraged by the group lasso penalty. We conduct simulation studies for high- and low-dimensional scenarios where our method is always able to select the true parameters that are truly predictive among a large number of parameters. The method is then applied on dichotomous response ADNI data which selects predictive atrophied brain regions and classifies Alzheimer's disease patients from healthy controls. Our analysis is able to give an accuracy rate of 80% for classifying Alzheimer's disease. The suggested method selects 29 brain subregions. The medical literature indicates that all these regions are associated with Alzheimer's patients. The Bayesian method of model selection further helps selecting only the subregions that are statistically significant, thus obtaining an optimal model.

Defective mitophagy and synaptic degeneration in Alzheimer's disease: Focus on aging, mitochondria and synapse

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by memory loss and multiple cognitive impairments. AD is marked by multiple cellular changes, including deregulation of microRNAs, activation of glia and astrocytes, hormonal imbalance, defective mitophagy, synaptic degeneration, in addition to extracellular neuritic amyloid-beta (Aβ) plaques, phosphorylated tau (P-tau), and intracellular neurofibrillary tangles (NFTs). Recent research in AD revealed that defective synaptic mitophagy leads to synaptic degeneration and cognitive dysfunction in AD neurons. Our critical analyses of mitochondria and Aβ and P-tau revealed that increased levels of Aβ and P-Tau, and abnormal interactions between Aβ and Drp1, P-Tau and Drp1 induced increased mitochondrial fragmentation and proliferation of dysfunctional mitochondria in AD neurons and depleted Parkin and PINK1 levels. These events ultimately lead to impaired clearance of dead and/or dying mitochondria in AD neurons. The purpose of our article is to highlight the recent research on mitochondria and synapses in relation to Aβ and P-tau, focusing on recent developments.

Regional glucose metabolic decreases with ageing are associated with microstructural white matter changes: a simultaneous PET/MR study

PURPOSE

Human ageing is associated with a regional reduction in cerebral neuronal activity as assessed by numerous studies on brain glucose metabolism and perfusion, grey matter (GM) density and white matter (WM) integrity. As glucose metabolism may impact energetics to maintain myelin integrity, but changes in functional connectivity may also alter regional metabolism, we conducted a cross-sectional simultaneous FDG PET/MR study in a large cohort of healthy volunteers with a wide age range, to directly assess the underlying associations between reduced glucose metabolism, GM atrophy and decreased WM integrity in a single ageing cohort.

METHODS

In 94 healthy subjects between 19.9 and 82.5 years (mean 50.1 ± 17.1; 47 M/47F, MMSE ≥ 28), simultaneous FDG-PET, structural MR and diffusion tensor imaging (DTI) were performed. Voxel-wise associations between age and grey matter (GM) density, RBV partial-volume corrected (PVC) glucose metabolism, white matter (WM) fractional anisotropy (FA) and mean diffusivity (MD), and age were assessed. Clusters representing changes in glucose metabolism correlating significantly with ageing were used as seed regions for tractography. Both linear and quadratic ageing models were investigated.

RESULTS

An expected age-related reduction in GM density was observed bilaterally in the frontal, lateral and medial temporal cortex, striatum and cerebellum. After PVC, relative FDG uptake was negatively correlated with age in the inferior and midfrontal, cingulate and parietal cortex and subcortical regions, bilaterally. FA decreased with age throughout the entire brain WM. Four white matter tracts were identified connecting brain regions with declining glucose metabolism with age. Within these, relative FDG uptake in both origin and target clusters correlated positively with FA (0.32 ≤ r ≤ 0.71) and negatively with MD (- 0.75 ≤ r ≤  - 0.41).

CONCLUSION

After appropriate PVC, we demonstrated that regional cerebral glucose metabolic declines with age and that these changes are related to microstructural changes in the interconnecting WM tracts. The temporal course and potential causality between ageing effects on glucose metabolism and WM integrity should be further investigated in longitudinal cohort PET/MR studies.

Decreased Alpha Peak Frequency Is Linked to Episodic Memory Impairment in Pathological Aging

The Free and Cued Selective Reminding Test (FCSRT) is a largely validated neuropsychological test for the identification of amnestic syndrome from the early stage of Alzheimer's disease (AD). Previous electrophysiological data suggested a slowing down of the alpha rhythm in the AD-continuum as well as a key role of this rhythmic brain activity for episodic memory processes. This study therefore investigates the link between alpha brain activity and alterations in episodic memory as assessed by the FCSRT. For that purpose, 37 patients with altered FCSRT performance underwent a comprehensive neuropsychological assessment, supplemented by 18F-fluorodeoxyglucose positron emission tomography/structural magnetic resonance imaging (18FDG-PET/MR), and 10 min of resting-state magnetoencephalography (MEG). The individual alpha peak frequency (APF) in MEG resting-state data was positively correlated with patients' encoding efficiency as well as with the efficacy of semantic cues in facilitating patients' retrieval of previous stored word. The APF also correlated positively with patients' hippocampal volume and their regional glucose consumption in the posterior cingulate cortex. Overall, this study demonstrates that alterations in the ability to learn and store new information for a relatively short-term period are related to a slowing down of alpha rhythmic activity, possibly due to altered interactions in the extended mnemonic system. As such, a decreased APF may be considered as an electrophysiological correlate of short-term episodic memory dysfunction accompanying pathological aging.

Optimal Combinations of AT(N) Biomarkers to Determine Longitudinal Cognition in the Alzheimer's Disease

Background: National Institute on Aging-Alzheimer's Association (NIA-AA) proposed the AT(N) system based on β-amyloid deposition, pathologic tau, and neurodegeneration, which considered the definition of Alzheimer's disease (AD) as a biological construct. However, the associations between different AT(N) combinations and cognitive progression have been poorly explored systematically. The aim of this study is to compare different AT(N) combinations using recognized biomarkers within the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Methods: A total of 341 participants were classified into cognitively unimpaired (CU; n = 200) and cognitively impaired (CI; n = 141) groups according to the clinical manifestations and neuropsychological tests. Cerebrospinal fluid (CSF) Aβ42 and amyloid-PET ([18F]flutemetamol) were used as biomarkers for A; CSF phosphorylated tau (p-tau) and tau-PET ([18F]flortaucipir) were used as biomarkers for T; CSF total tau (t-tau), hippocampal volume, temporal cortical thickness, [18F]fluorodeoxyglucose (FDG) PET, and plasma neurofilament light (NfL) were used as biomarkers for (N). Binary biomarkers were obtained from the Youden index and publicly available cutoffs. Prevalence of AT(N) categories was compared between different biomarkers within the group using related independent sample non-parametric test. The relationship between AT(N) combinations and 12-year longitudinal cognition was assessed using linear mixed-effects modeling. Results: Among the CU participants, A-T-(N)- was most common. More T+ were detected using p-tau than tau PET (p < 0.05), and more (N)+ were observed using fluid biomarkers (p < 0.001). A+T+(N)+ was more common in the CI group. Tau PET combined with cortical thickness best predicted cognitive changes in the CI group and MRI predicted changes in the CU group. Conclusions: These findings suggest that optimal AT(N) combinations to determine longitudinal cognition differ by cognitive status. Different biomarkers within a specific component for defining AT(N) cannot be used identically. Furthermore, different strategies for discontinuous biomarkers will be an important area for future studies.

Prediction of Subtle Cognitive Decline in Normal Aging: Added Value of Quantitative MRI and PET Imaging

Quantitative imaging processing tools have been proposed to improve clinic-radiological correlations but their added value at the initial stages of cognitive decline is still a matter of debate. We performed a longitudinal study in 90 community-dwelling elders with three neuropsychological assessments during a 4.5 year follow-up period, and visual assessment of medial temporal atrophy (MTA), white matter hyperintensities, cortical microbleeds (CMB) as well as amyloid positivity, and presence of abnormal FDG-PET patterns. Quantitative imaging data concerned ROI analysis of MRI volume, amyloid burden, and FDG-PET metabolism in several AD-signature areas. Multiple regression models, likelihood-ratio tests, and areas under the receiver operating characteristic curve (AUC) were used to compare quantitative imaging markers to visual inspection. The presence of more or equal to four CMB at inclusion and slight atrophy of the right MTL at follow-up were the only parameters to be independently related to the worst cognitive score explaining 6% of its variance. This percentage increased to 24.5% when the ROI-defined volume loss in the posterior cingulate cortex, baseline hippocampus volume, and MTL metabolism were also considered. When binary classification of cognition was made, the area under the ROC curve increased from 0.69 for the qualitative to 0.79 for the mixed imaging model. Our data reveal that the inclusion of quantitative imaging data significantly increases the prediction of cognitive changes in elderly controls compared to the single consideration of visual inspection.

Evaluation of the early-phase [18F]AV45 PET as an optimal surrogate of [18F]FDG PET in ageing and Alzheimer's clinical syndrome

Dual-phase [18F]AV45 positron emission tomography (PET) is highly promising in the assessment of neurodegenerative diseases, allowing to obtain information on both neurodegeneration (early-phase; eAV45) and amyloid deposition (late-phase; lAV45) which are highly complementary; yet eAV45 needs further evaluation. This study aims at validating eAV45 as an optimal proxy of [18F]FDG PET in a large mixed-population of healthy ageing and Alzheimer's clinical syndrome participants (n = 191) who had [18F]FDG PET, eAV45 and lAV45 scans. We found early time frame 0-4 min to give maximal correlation with [18F]FDG PET and minimal correlation with lAV45. Moreover, maximal overlap of [18F]FDG PET versus eAV45 associations with clinical diagnosis and cognition was obtained with pons scaling. Across reference regions, classification performance between clinical subgroups was similar for both eAV45 and [18F]FDG PET. These findings highlight the optimal use of eAV45 to assess neurodegeneration as a validated proxy of [18F]FDG PET. On top of this purpose, this study showed that combined [18F]AV45 PET dual-biomarker even outperformed [18F]FDG PET or lAV45 alone.