Amyloid, tau and metabolic PET correlates of cognition in early and late-onset Alzheimer's disease

A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables

Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET outcomes from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded highly accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study reveals current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.

Medial temporal lobe atrophy patterns in early- versus late-onset amnestic Alzheimer's disease

Background

The medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer's disease (EOAD). Yet, detailed examination of MTL subfield volumes and drivers of atrophy in amnestic EOAD is lacking.

Methods

BioFINDER-2 participants with memory impairment, abnormal amyloid-β status and tau-PET were included. Forty-one EOAD individuals aged ≤65 years and, as comparison, late-onset AD (LOAD, ≥70 years, n=154) and Aβ-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured.

Results

AD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups, although LOAD showed thinner entorhinal cortices compared to EOAD. EOAD showed lower WMH compared to LOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity was found.

Conclusions

We found in vivo evidence for MTL atrophy in amnestic EOAD and overall similar levels to LOAD of MTL tau pathology and co-pathologies.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease

Identifying individuals with early stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would allow professionals and loved ones to make better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. In this study, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes (Posterior Cortical Atrophy, logopenic variant Primary Progressive Aphasia, and amnestic syndrome with multi-domain impairment and age of onset < 65 years). All patients underwent structural magnetic resonance imaging (MRI), tau (18F-Flortaucipir) PET, and amyloid (either 18F-Florbetaben or 11C-Pittsburgh Compound B) PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Our sample of early atypical AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, d = 0.95. These AD patients showed prominent baseline tau burden in posterior cortical regions including the major nodes of the default mode network, including the angular gyrus, posterior cingulate cortex/precuneus, and lateral temporal cortex. Greater baseline tau in the broader default mode network predicted faster clinical decline. Tau in the default mode network was the strongest predictor of clinical decline, outperforming baseline clinical impairment, tau in other functional networks, and the magnitude of cortical atrophy and amyloid burden in the default mode network. Overall, these findings point to the contribution of baseline tau burden within the default mode network of the cerebral cortex to predicting the magnitude of clinical decline in a sample of atypical early AD patients one year later. This simple measure based on a tau PET scan could aid the development of a personalized prognostic, monitoring, and treatment plan tailored to each individual patient, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

Is Alzheimer disease a disease?

Dementia, a prevalent condition among older individuals, has profound societal implications. Extensive research has resulted in no cure for what is perceived as the most common dementing illness: Alzheimer disease (AD). AD is defined by specific brain abnormalities - amyloid-β plaques and tau protein neurofibrillary tangles - that are proposed to actively influence the neurodegenerative process. However, conclusive evidence of amyloid-β toxicity is lacking, the mechanisms leading to the accumulation of plaques and tangles are unknown, and removing amyloid-β has not halted neurodegeneration. So, the question remains, are we making progress towards a solution? The complexity of AD is underscored by numerous genetic and environmental risk factors, and diverse clinical presentations, suggesting that AD is more akin to a syndrome than to a traditional disease, with its pathological manifestation representing a convergence of pathogenic pathways. Therefore, a solution requires a multifaceted approach over a single 'silver bullet'. Improved recognition and classification of conditions that converge in plaques and tangle accumulation and their treatment requires the use of multiple strategies simultaneously.

What can pediatricians learn from adult inherited metabolic diseases?

The field of inherited metabolic diseases (IMD) has initially emerged and developed over decades in pediatric departments. Still, today, about 50% of patients with IMD are adults, and adult metabolic medicine (AMM) is getting more structured at national and international levels. There are several domains in which pediatricians can learn from AMM. First, long-term evolution of IMD patients, especially those treated since childhood, is critical to determine nutritional and neuropsychiatric outcomes in adults so that these outcomes can be better monitored, and patient care adjusted as much as possible from childhood. Conversely, the observation of attenuated phenotypes in adults of IMD known to present with severe phenotypes in children calls for caution in the development of newborn screening programs and, more largely, in the interpretation of next-generation sequencing data. Third, it is important for pediatricians to be familiar with adult-onset IMD as they expand our understanding of metabolism, including in children, such as oxysterols and glycogen metabolism. Last, the identification of common molecular and cellular mechanisms in neurodevelopment and neurodegeneration opens the way to synergistic therapeutic developments that will benefit both fields of pediatric and adult medicine. Overall, these observations underline the need of strong interdisciplinarity between pediatricians and adult specialists for the diagnosis and the treatment of IMD well beyond the issues of patient transition from pediatric to adult medicine.

Plasma oligomer beta-amyloid is associated with disease severity and cerebral amyloid deposition in Alzheimer's disease spectrum

BACKGROUND

Multimer detection system-oligomeric amyloid-β (MDS-OAβ) is a measure of plasma OAβ, which is associated with Alzheimer's disease (AD) pathology. However, the relationship between MDS-OAβ and disease severity of AD is not clear. We aimed to investigate MDS-OAβ levels in different stages of AD and analyze the association between MDS-OAβ and cerebral Aβ deposition, cognitive function, and cortical thickness in subjects within the AD continuum.

METHODS

In this cross-sectional study, we analyzed a total 126 participants who underwent plasma MDS-OAβ, structural magnetic resonance image of brain, and neurocognitive measures using Korean version of the Consortium to Establish a Registry for Alzheimer's Disease, and cerebral Aβ deposition or amyloid positron emission tomography (A-PET) assessed by [18F] flutemetamol PET. Subjects were divided into 4 groups: N = 39 for normal control (NC), N = 31 for A-PET-negative mild cognitive impairment (MCI) patients, N = 30 for A-PET-positive MCI patients, and N = 22 for AD dementia patients. The severity of cerebral Aβ deposition was expressed as standard uptake value ratio (SUVR).

RESULTS

Compared to the NC (0.803 ± 0.27), MDS-OAβ level was higher in the A-PET-negative MCI group (0.946 ± 0.137) and highest in the A-PET-positive MCI group (1.07 ± 0.17). MDS-OAβ level in the AD dementia group was higher than in the NC, but it fell to that of the A-PET-negative MCI group level (0.958 ± 0.103). There were negative associations between MDS-OAβ and cognitive function and both global and regional cerebral Aβ deposition (SUVR). Cortical thickness of the left fusiform gyrus showed a negative association with MDS-OAβ when we excluded the AD dementia group.

CONCLUSIONS

These findings suggest that MDS-OAβ is not only associated with neurocognitive staging, but also with cerebral Aβ burden in patients along the AD continuum.

The Effects of PICALM rs3851179 and Age on Brain Atrophy and Cognition Along the Alzheimer's Disease Continuum

Rs3851179, a variant of PICALM gene, and age are the risk factors of Alzheimer's disease (AD). AD is divided into early-onset AD (EOAD, < 65 years) and late-onset AD (LOAD, ≥ 65 years) by age. The purpose was to investigate the impact of different genotypes of PICALM rs3851179 on brain atrophy and cognitive decline across the AD continuum in different age groups. Four hundred seven cognitive normal (CN) controls, 362 mild cognitive impairment (MCI) patients, and 94 AD patients were enrolled to assess the interaction between AD continuum, age status, and PICALM on gray matter volume (GMV), global cognition, memory function, and executive function using full factorial ANCOVA (3 × 2 × 2). The interaction between AD continuum and PICALM significantly affected the GMV of the left putamen (PUT.L). rs3851179 A-allele carriers did not show a significant decrease in PUT.L GMV from CN to MCI to AD, while GG-allele carriers did. The interaction between AD continuum and age status was significant on GMV of the left angular gyrus (ANG.L) and right superior occipital gyrus (SOG.R). LOAD had higher GMV of ANG.L and SOG.R than EOAD. The interactive effects among AD continuum, age status, and PICALM were not significant on GMV but were significant on global cognition and executive function. The A-allele was found to have a protective effect on global cognition and executive function in EOAD, but not significantly so in LOAD. PICALM rs3851179 A-allele might alleviate the atrophy of PUT.L across the AD continuum than GG-allele. Age status did not affect the interaction between AD continuum and PICALM on brain atrophy. The ANG.L and SOG.R atrophied more severely in EOAD than in LOAD. Rs3851179 A-allele was protective for global cognition and executive function in EOAD.

A single-domain antibody for the detection of pathological Tau protein in the early stages of oligomerization

BACKGROUND

Soluble oligomeric forms of Tau protein have emerged as crucial players in the propagation of Tau pathology in Alzheimer's disease (AD). Our objective is to introduce a single-domain antibody (sdAb) named 2C5 as a novel radiotracer for the efficient detection and longitudinal monitoring of oligomeric Tau species in the human brain.

METHODS

The development and production of 2C5 involved llama immunization with the largest human Tau isoform oligomers of different maturation states. Subsequently, 2C5 underwent comprehensive in vitro characterization for affinity and specificity via Enzyme-Linked Immunosorbent Assay and immunohistochemistry on human brain slices. Technetium-99m was employed to radiolabel 2C5, followed by its administration to healthy mice for biodistribution analysis.

RESULTS

2C5 exhibited robust binding affinity towards Tau oligomers (Kd = 6.280 nM ± 0.557) and to Tau fibers (Kd = 5.024 nM ± 0.453), with relatively weaker binding observed for native Tau protein (Kd = 1791 nM ± 8.714) and amyloid peptide (Kd > 10,000 nM). Remarkably, this SdAb facilitated immuno-histological labeling of pathological forms of Tau in neurons and neuritic plaques, yielding a high-contrast outcome in AD patients, closely mirroring the performance of reference antibodies AT8 and T22. Furthermore, 2C5 SdAb was successfully radiolabeled with 99mTc, preserving stability for up to 6 h post-radiolabeling (radiochemical purity > 93%). However, following intravenous injection into healthy mice, the predominant uptake occurred in kidneys, amounting to 115.32 ± 3.67, 97.70 ± 43.14 and 168.20 ± 34.52% of injected dose per gram (% ID/g) at 5, 10 and 45 min respectively. Conversely, brain uptake remained minimal at all measured time points, registering at 0.17 ± 0.03, 0.12 ± 0.07 and 0.02 ± 0.01% ID/g at 5, 10 and 45 min post-injection respectively.

CONCLUSION

2C5 demonstrates excellent affinity and specificity for pathological Tau oligomers, particularly in their early stages of oligomerization. However, the current limitation of insufficient blood-brain barrier penetration necessitates further modifications before considering its application in nuclear medicine imaging for humans.

Small vessel cerebrovascular disease is associated with cognition in prospective Alzheimer's clinical trial participants

BACKGROUND

Secondary prevention clinical trials for Alzheimer's disease (AD) target amyloid accumulation in asymptomatic, amyloid-positive individuals, but it is unclear to what extent other pathophysiological processes, such as small vessel cerebrovascular disease, account for participant performance on the primary cognitive outcomes in those trials. White matter hyperintensities are areas of increased signal on T2-weighted magnetic resonance imaging (MRI) that reflect small vessel cerebrovascular disease. They are associated with cognitive functioning in older adults and with clinical presentation and course of AD, particularly when distributed in posterior brain regions. The purpose of this study was to examine to what degree regional WMH volume is associated with performance on the primary cognitive outcome measure in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study, a secondary prevention trial.

METHODS

Data from 1791 participants (59.5% women, mean age (SD) 71.6 (4.74)) in the A4 study and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) companion study at the screening visit were used to quantify WMH volumes on T2-weighted fluid-attenuated inversion recovery (FLAIR) MR images. Cognition was assessed with the preclinical Alzheimer cognitive composite (PACC). We tested the association of total and regional WMH volumes with PACC performance, adjusting for age, education, and amyloid positivity status, with general linear models. We also considered interactions between WMH and amyloid positivity status.

RESULTS

Increased frontal and parietal lobe WMH volume was associated with poorer performance on the PACC. While amyloid positivity was also associated with lower cognitive test scores, WMH volumes did not interact with amyloid positivity status.

CONCLUSION

These results highlight the potential of small vessel cerebrovascular disease to drive AD-related cognitive profiles. Measures of small vessel cerebrovascular disease should be considered when evaluating outcome in trials, both as potential effect modifiers and as a possible target for intervention or prevention.

Decoding the diagnostic potential of T cell repertoires in peripheral blood of patients from amnestic mild cognitive impairment to Alzheimer's disease

Alzheimer's disease (AD) is currently an incurable neurodegenerative disorder and is the most common etiological cause of dementia. Consequently, it has severe burden on its patients and on their caregivers and represents a global health concern. Clinical investigations have indicated that a dysregulation of peripheral T cell immune homeostasis may be involved in the pathogenesis of AD, as well as in the early stages of AD, characterized by mild cognitive impairment (MCI). However, the characteristics and concomitant feasibility of the use of T-cell receptor (TCR) typing for disease diagnosis remains largely unknown. We employed a high-throughput sequencing and multidimensional bioinformatics analyses for the identification of TCR repertoires present in peripheral blood samples of 10 patients with amnestic MCI (aMCI), 10 patients with AD, and 10 healthy controls (HCs). Based on the characteristics of the TCR repertoires in the amount and diversity of combinations of V-J, the spectrum of immune defense, and differentially expressed genes (DEGs), single and specific TCR profiles were observed in the patient samples of aMCI and AD compared to profiles of HCs. In particular, the diversity of TCR clonotypes manifested a pattern of "decreased first and then increased" pattern during the progression from aMCI to AD, a pattern that was not observed in HC samples. Additionally, a total of 46 and 35 amino acid CDR3 sequences with consistent and reverse expressive abundance with diversity of TCR clonotypes were identified, respectively. Taken together, we provide novel and essential preliminary evidence demonstrating the presence of diversity of T cell repertoires from differentially expressed V-J gene segments and amino acid clonotypes using peripheral blood samples from patients with AD, aMCI, and from HC. Such findings have the potential to reveal potential mechanisms through which aMCI progresses to AD and provide a reference for the future development of immune-related diagnoses and therapies for AD.

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.

Preserving cognitive function in patients with Alzheimer's disease: The Alzheimer's disease neuroprotection research initiative (ADNRI)

The global trend toward aging populations has resulted in an increase in the occurrence of Alzheimer's disease (AD) and associated socioeconomic burdens. Abnormal metabolism of amyloid-β (Aβ) has been proposed as a significant pathomechanism in AD, supported by results of recent clinical trials using anti-Aβ antibodies. Nonetheless, the cognitive benefits of the current treatments are limited. The etiology of AD is multifactorial, encompassing Aβ and tau accumulation, neuroinflammation, demyelination, vascular dysfunction, and comorbidities, which collectively lead to widespread neurodegeneration in the brain and cognitive impairment. Hence, solely removing Aβ from the brain may be insufficient to combat neurodegeneration and preserve cognition. To attain effective treatment for AD, it is necessary to (1) conduct extensive research on various mechanisms that cause neurodegeneration, including advances in neuroimaging techniques for earlier detection and a more precise characterization of molecular events at scales ranging from cellular to the full system level; (2) identify neuroprotective intervention targets against different neurodegeneration mechanisms; and (3) discover novel and optimal combinations of neuroprotective intervention strategies to maintain cognitive function in AD patients. The Alzheimer's Disease Neuroprotection Research Initiative's objective is to facilitate coordinated, multidisciplinary efforts to develop systemic neuroprotective strategies to combat AD. The aim is to achieve mitigation of the full spectrum of pathological processes underlying AD, with the goal of halting or even reversing cognitive decline.

Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS)

INTRODUCTION

We aimed to describe baseline amyloid-beta (Aβ) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD).

METHODS

We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ-) based on the combination of visual read by expert reader and image quantification.

RESULTS

243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants.

DISCUSSION

LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD.

HIGHLIGHTS

72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.

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.

Accelerating Alzheimer's therapeutic development: The past and future of clinical trials

Alzheimer's disease (AD) research has entered a new era with the recent positive phase 3 clinical trials of the anti-Aβ antibodies lecanemab and donanemab. Why did it take 30 years to achieve these successes? Developing potent therapies for reducing fibrillar amyloid was key, as was selection of patients at relatively early stages of disease. Biomarkers of the target pathologies, including amyloid and tau PET, and insights from past trials were also critical to the recent successes. Moving forward, the challenge will be to develop more efficacious therapies with greater efficiency. Novel trial designs, including combination therapies and umbrella and basket protocols, will accelerate clinical development. Better diversity and inclusivity of trial participants are needed, and blood-based biomarkers may help to improve access for medically underserved groups. Incentivizing innovation in both academia and industry through public-private partnerships, collaborative mechanisms, and the creation of new career paths will be critical to build momentum in these exciting times.

Advanced brain imaging for the diagnosis of Alzheimer disease

PURPOSE OF REVIEW

The purpose is to review the latest advances of brain imaging for the diagnosis of Alzheimer disease (AD).

RECENT FINDINGS

Brain imaging techniques provide valuable and complementary information to support the diagnosis of Alzheimer disease in clinical and research settings. The recent FDA accelerated approvals of aducanumab, lecanemab and donanemab made amyloid-PET critical in helping determine the optimal window for anti-amyloid therapeutic interventions. Tau-PET, on the other hand, is considered of key importance for the tracking of disease progression and for monitoring therapeutic interventions in clinical trials. PET imaging for microglial activation, astrocyte reactivity and synaptic degeneration are still new techniques only used in the research field, and more studies are needed to validate their use in the clinical diagnosis of AD. Finally, artificial intelligence has opened new prospective in the early detection of AD using MRI modalities.

SUMMARY

Brain imaging techniques using PET improve our understanding of the different AD-related pathologies and their relationship with each other along the course of disease. With more robust validation, machine learning and deep learning algorithms could be integrated with neuroimaging modalities to serve as valuable tools for clinicians to make early diagnosis and prognosis of AD.

Generation of Conventional 18F-FDG PET Images from 18F-Florbetaben PET Images Using Generative Adversarial Network: A Preliminary Study Using ADNI Dataset

Background and Objectives: ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) (PET_FDG) image can visualize neuronal injury of the brain in Alzheimer's disease. Early-phase amyloid PET image is reported to be similar to PET_FDG image. This study aimed to generate PET_FDG images from ¹⁸F-florbetaben PET (PET_FBB) images using a generative adversarial network (GAN) and compare the generated PET_FDG (PET_GE-FDG) with real PET_FDG (PET_RE-FDG) images using the structural similarity index measure (SSIM) and the peak signal-to-noise ratio (PSNR). Materials and Methods: Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, 110 participants with both PET_FDG and PET_FBB images at baseline were included. The paired PET_FDG and PET_FBB images included six and four subset images, respectively. Each subset image had a 5 min acquisition time. These subsets were randomly sampled and divided into 249 paired PET_FDG and PET_FBB subset images for the training datasets and 95 paired subset images for the validation datasets during the deep-learning process. The deep learning model used in this study is composed of a GAN with a U-Net. The differences in the SSIM and PSNR values between the PET_GE-FDG and PET_RE-FDG images in the cycleGAN and pix2pix models were evaluated using the independent Student's t-test. Statistical significance was set at p ≤ 0.05. Results: The participant demographics (age, sex, or diagnosis) showed no statistically significant differences between the training (82 participants) and validation (28 participants) groups. The mean SSIM between the PET_GE-FDG and PET_RE-FDG images was 0.768 ± 0.135 for the cycleGAN model and 0.745 ± 0.143 for the pix2pix model. The mean PSNR was 32.4 ± 9.5 and 30.7 ± 8.0. The PET_GE-FDG images of the cycleGAN model showed statistically higher mean SSIM than those of the pix2pix model (p < 0.001). The mean PSNR was also higher in the PET_GE-FDG images of the cycleGAN model than those of pix2pix model (p < 0.001). Conclusions: We generated PET_FDG images from PET_FBB images using deep learning. The cycleGAN model generated PET_GE-FDG images with a higher SSIM and PSNR values than the pix2pix model. Image-to-image translation using deep learning may be useful for generating PET_FDG images. These may provide additional information for the management of Alzheimer's disease without extra image acquisition and the consequent increase in radiation exposure, inconvenience, or expenses.

Characterizing Early-Onset Alzheimer Disease Using Multiprobe PET/MRI: An AT(N) Framework-Based Study

PURPOSE

Early-onset Alzheimer disease (EOAD) is rare, highly heterogeneous, and associated with poor prognosis. This AT(N) Framework-based study aimed to compare multiprobe PET/MRI findings between EOAD and late-onset Alzheimer disease (LOAD) patients and explore potential imaging biomarkers for characterizing EOAD.

METHODS

Patients with AD who underwent PET/MRI in our PET center were retrospectively reviewed and grouped according to the age at disease onset: EOAD, younger than 60 years; and LOAD, 60 years or older. Clinical characteristics were recorded. All study patients had positive β-amyloid PET imaging; some patients also underwent 18 F-FDG and 18 F-florzolotau PET. Imaging of the EOAD and LOAD groups was compared using region-of-interest and voxel-based analysis. Correlation of onset age and regional SUV ratios were also evaluated.

RESULTS

One hundred thirty-three patients were analyzed (75 EOAD and 58 LOAD patients). Sex ( P = 0.515) and education ( P = 0.412) did not significantly differ between groups. Mini-Mental State Examination score was significantly lower in the EOAD group (14.32 ± 6.74 vs 18.67 ± 7.20, P = 0.004). β-Amyloid deposition did not significantly differ between groups. Glucose metabolism in the frontal, parietal, precuneus, temporal, occipital lobe, and supramarginal and angular gyri was significantly lower in the EOAD group (n = 49) than in the LOAD group (n = 44). In voxel-based morphometry analysis, right posterior cingulate/precuneus atrophy was more obvious in the EOAD ( P < 0.001), although no voxel survived family-wise error correction. Tau deposition in the precuneus, parietal lobe, and angular, supramarginal, and right middle frontal gyri was significantly higher in the EOAD group (n = 18) than in the LOAD group (n = 13).

CONCLUSIONS

Multiprobe PET/MRI showed that tau burden and neuronal damage are more severe in EOAD than in LOAD. Multiprobe PET/MRI may be useful to assess the pathologic characteristics of EOAD.