Combining neuropsychological assessment and structural neuroimaging to identify early Alzheimer's disease in a memory clinic cohort.

INTRODUCTION: The current study examined the contributions of comprehensive neuropsychological assessment and volumetric assessment of selected mesial temporal subregions on structural magnetic resonance imaging (MRI) to identify patients with amnestic mild cognitive impairment (aMCI) and mild probable Alzheimer's disease (AD) dementia in a memory clinic cohort. METHODS: Comprehensive neuropsychological assessment and automated entorhinal, transentorhinal, and hippocampal volume measurements were conducted in 40 healthy controls, 38 patients with subjective memory symptoms, 16 patients with aMCI, 16 patients with mild probable AD dementia. Multinomial logistic regression was used to compare the neuropsychological and MRI measures. RESULTS: Combining the neuropsychological and MRI measures improved group membership prediction over the MRI measures alone but did not improve group membership prediction over the neuropsychological measures alone. CONCLUSION: Comprehensive neuropsychological assessment was an important tool to evaluate cognitive impairment. The mesial temporal volumetric MRI measures contributed no diagnostic value over and above the determinations made through neuropsychological assessment.

An Informatics Platform for the Management of Data for Australian Dementia Network (ADNeT) Initiative.

Alzheimer's disease and other dementias are becoming more prevalent and placing increasing burdens on the community. The ADNeT Screening and Trials initiative aims to improve research outcomes by identifying people with an increased risk of developing these diseases and directing them to suitable clinical trials. To support the initiative, we have developed a modular informatics platform utilizing private cloud deployment to securely manage operational and research data across six clinical sites.

Longitudinal trajectories of basal forebrain volume in normal aging and Alzheimer's disease.

Dysfunction of the cholinergic basal forebrain (BF) system and amyloid-ß (Aß) deposition are early pathological features in Alzheimer's disease (AD). However, their association in early AD is not well-established. This study investigated the nature and magnitude of volume loss in the BF, over an extended period, in 516 older adults who completed Aß-PET and serial magnetic resonance imaging scans. Individuals were grouped at baseline according to the presence of cognitive impairment (CU, CI) and Aß status (Aß-, Aß+). Longitudinal volumetric changes in the BF and hippocampus were assessed across groups. The results indicated that high Aß levels correlated with faster volume loss in the BF and hippocampus, and the effect of Aß varied within BF subregions. Compared to CU Aß+ individuals, Aß-related loss among CI Aß+ adults was much greater in the predominantly cholinergic subregion of Ch4p, whereas no difference was observed for the Ch1/Ch2 region. The findings support early and substantial vulnerability of the BF and further reveal distinctive degeneration of BF subregions during early AD.

Biostatistical Estimation of Tau Threshold Hallmarks (BETTH) Algorithm for Human Tau PET Imaging Studies.

A methodology for determining tau PET thresholds is needed to confidently detect early tau deposition. We compared multiple threshold-determining methods in participants who underwent either 18F-flortaucipir or 18F-MK-6240 PET scans. Methods: 18F-flortaucipir (n = 798) and 18F-MK-6240 (n = 216) scans were processed and sampled to obtain regional SUV ratios. Subsamples of the cohorts were based on participant diagnosis, age, amyloid-ß status (positive or negative), and neurodegeneration status (positive or negative), creating older-adult (age ≥ 55 y) cognitively unimpaired (amyloid-ß-negative, neurodegeneration-negative) and cognitively impaired (mild cognitive impairment/Alzheimer disease, amyloid-ß-positive, neurodegeneration-positive) groups, and then were further subsampled via matching to reduce significant differences in diagnostic prevalence, age, and Mini-Mental State Examination score. We used the biostatistical estimation of tau threshold hallmarks (BETTH) algorithm to determine sensitivity and specificity in 6 composite regions. Results: Parametric double receiver operating characteristic analysis yielded the greatest joint sensitivity in 5 of the 6 regions, whereas hierarchic clustering, gaussian mixture modeling, and k-means clustering all yielded perfect joint specificity (2.00) in all regions. Conclusion: When 18F-flortaucipir and 18F-MK-6240 are used, Alzheimer disease-related tau status is best assessed using 2 thresholds, a sensitivity one based on parametric double receiver operating characteristic analysis and a specificity one based on gaussian mixture modeling, delimiting an uncertainty zone indicating participants who may require further evaluation.

Increased Resolution of Structural MRI at 3T Improves Estimation of Regional Cortical Degeneration in Individual Dementia Patients Using Surface Thickness Maps.

BACKGROUND: Objective measurement of regional cortical atrophy in individual patients would be a highly desirable adjunct for diagnosis of degenerative dementias. OBJECTIVE: We hypothesized that increasing the resolution of magnetic resonance scans would improve the sensitivity of cortical atrophy detection for individual patients. METHODS: 46 participants including 8 semantic-variant primary progressive aphasia (svPPA), seven posterior cortical atrophy (PCA), and 31 cognitively unimpaired participants underwent clinical assessment and 3.0T brain scans. SvPPA and PCA were chosen because there is overwhelming prior knowledge of the expected atrophy pattern. Two sets of T1-weighted images with 0.8 mm3 (HighRes) and conventional 1.0 mm3 (ConvRes) resolution were acquired. The cortical ribbon was segmented using FreeSurfer software to obtain surface-based thickness maps. Inter-sequence performance was assessed in terms of cortical thickness and sub-cortical volume reproducibility, signal-to-noise and contrast-to-noise ratios. For clinical cases, diagnostic effect size (Cohen's d) and lesion distribution (z-score and t-value maps) were compared between HighRes and ConvRes scans. RESULTS: The HighRes scans produced higher image quality scores at 90 seconds extra scan time. The effect size of cortical thickness differences between patients and cognitively unimpaired participants was 15-20% larger for HighRes scans. HighRes scans showed more robust patterns of atrophy in expected regions in each and every individual patient. CONCLUSIONS: HighRes T1-weighted scans showed superior precision for identifying the severity of cortical atrophy in individual patients, offering a proof-of-concept for clinical translation. Studying svPPA and PCA, two syndromes with well-defined focal atrophy patterns, offers a method to clinically validate and contrast automated algorithms.

Validating ASHS-T1 automated entorhinal and transentorhinal cortical segmentation in Alzheimer's disease.

The current study aimed to validate entorhinal and transentorhinal cortical volumes measured by the automated segmentation tool Automatic Segmentation of Hippocampal Subfields (ASHS-T1). The study sample comprised 34 healthy controls (HCs), 37 individuals with amnestic mild cognitive impairment (aMCI), and 29 individuals with Alzheimer's disease (AD) dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Entorhinal and transentorhinal cortical volumes were assessed using ASHS-T1, manual segmentation, as well as a widely used automated segmentation tool, FreeSurfer v6.0.1. Mean differences, intraclass correlation coefficients, and Bland-Altman plots were computed. ASHS-T1 tended to underestimate entorhinal and transentorhinal cortical volumes relative to manual segmentation and FreeSurfer. There was variable consistency and low agreement between ASHS-T1 and manual segmentation volumes. There was low-to-moderate consistency and low agreement between ASHS-T1 and FreeSurfer volumes. There was a trend toward higher consistency and agreement for the entorhinal cortex in the aMCI and AD groups compared to the HC group. Despite the differences in volume measurements, ASHS-T1 was sensitive to entorhinal and transentorhinal cortical atrophy in both early and late disease stages. Based on the current study, ASHS-T1 appears to be a promising tool for automated entorhinal and transentorhinal cortical volume measurement in individuals with likely underlying AD.

Evaluation of novel data-driven metrics of amyloid ß deposition for longitudinal PET studies.

PURPOSE: Positron emission tomography (PET) provides in vivo quantification of amyloid-ß (Aß) pathology. Established methods for assessing Aß burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria. METHODS: Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aß load), the Aß-PET pathology accumulation index (Aß index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aß accumulation. RESULTS: All metrics showed good reliability. Aß load, Aß index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aß index and Aß load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aß load compared to the CL. CONCLUSION: Among the novel data-driven metrics evaluated, the Aß load, the Aß index and the CLNMF can provide comparable performance to more established quantification methods of Aß PET tracer uptake. The CLNMF and Aß load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.

CenTauR: Toward a universal scale and masks for standardizing tau imaging studies.

INTRODUCTION: Recently, an increasing number of tau tracers have become available. There is a need to standardize quantitative tau measures across tracers, supporting a universal scale. We developed several cortical tau masks and applied them to generate a tau imaging universal scale. METHOD: One thousand forty-five participants underwent tau scans with either 18F-flortaucipir, 18F-MK6240, 18F-PI2620, 18F-PM-PBB3, 18F-GTP1, or 18F-RO948. The universal mask was generated from cognitively unimpaired amyloid beta (Aß)- subjects and Alzheimer's disease (AD) patients with Aß+. Four additional regional cortical masks were defined within the constraints of the universal mask. A universal scale, the CenTauRz, was constructed. RESULTS: None of the regions known to display off-target signal were included in the masks. The CenTauRz allows robust discrimination between low and high levels of tau deposits. DISCUSSION: We constructed several tau-specific cortical masks for the AD continuum and a universal standard scale designed to capture the location and degree of abnormality that can be applied across tracers and across centers. The masks are freely available at https://www.gaain.org/centaur-project.

Disease progression modelling of Alzheimer's disease using probabilistic principal components analysis.

The recent biological redefinition of Alzheimer's Disease (AD) has spurred the development of statistical models that relate changes in biomarkers with neurodegeneration and worsening condition linked to AD. The ability to measure such changes may facilitate earlier diagnoses for affected individuals and help in monitoring the evolution of their condition. Amongst such statistical tools, disease progression models (DPMs) are quantitative, data-driven methods that specifically attempt to describe the temporal dynamics of biomarkers relevant to AD. Due to the heterogeneous nature of this disease, with patients of similar age experiencing different AD-related changes, a challenge facing longitudinal mixed-effects-based DPMs is the estimation of patient-realigning time-shifts. These time-shifts are indispensable for meaningful biomarker modelling, but may impact fitting time or vary with missing data in jointly estimated models. In this work, we estimate an individual's progression through Alzheimer's disease by combining multiple biomarkers into a single value using a probabilistic formulation of principal components analysis. Our results show that this variable, which summarises AD through observable biomarkers, is remarkably similar to jointly estimated time-shifts when we compute our scores for the baseline visit, on cross-sectional data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Reproducing the expected properties of clinical datasets, we confirm that estimated scores are robust to missing data or unavailable biomarkers. In addition to cross-sectional insights, we can model the latent variable as an individual progression score by repeating estimations at follow-up examinations and refining long-term estimates as more data is gathered, which would be ideal in a clinical setting. Finally, we verify that our score can be used as a pseudo-temporal scale instead of age to ignore some patient heterogeneity in cohort data and highlight the general trend in expected biomarker evolution in affected individuals.

A universal neocortical mask for Centiloid quantification.

INTRODUCTION: The Centiloid (CL) project was developed to harmonize the quantification of amyloid beta (Aß) positron emission tomography (PET) scans to a unified scale. The CL neocortical mask was defined using 11C Pittsburgh compound B (PiB), overlooking potential differences in regional distribution among Aß tracers. We created a universal mask using an independent dataset of five Aß tracers, and investigated its impact on inter-tracer agreement, tracer variability, and group separation. METHODS: Using data from the Alzheimer's Dementia Onset and Progression in International Cohorts (ADOPIC) study (Australian Imaging Biomarkers and Lifestyle + Alzheimer's Disease Neuroimaging Initiative + Open Access Series of Imaging Studies), age-matched pairs of mild Alzheimer's disease (AD) and healthy controls (HC) were selected: 18F-florbetapir (N = 147 pairs), 18F-florbetaben (N = 22), 18F-flutemetamol (N = 10), 18F-NAV (N = 42), 11C-PiB (N = 63). The images were spatially and standardized uptake value ratio normalized. For each tracer, the mean AD-HC difference image was thresholded to maximize the overlap with the standard neocortical mask. The universal mask was defined as the intersection of all five masks. It was evaluated on the Global Alzheimer's Association Interactive Network (GAAIN) head-to-head datasets in terms of inter-tracer agreement and variance in the young controls (YC) and on the ADOPIC dataset comparing separation between HC/AD and HC/mild cognitive impairment (MCI). RESULTS: In the GAAIN dataset, the universal mask led to a small reduction in the variance of the YC, and a small increase in the inter-tracer agreement. In the ADOPIC dataset, it led to a better separation between HC/AD and HC/MCI at baseline. DISCUSSION: The universal CL mask led to an increase in inter-tracer agreement and group separation. Those increases were, however, very small, and do not provide sufficient benefits to support departing from the existing standard CL mask, which is suitable for the quantification of all Aß tracers. HIGHLIGHTS: This study built an amyloid universal mask using a matched cohort for the five most commonly used amyloid positron emission tomography tracers.There was a high overlap between each tracer-specific mask.Differences in quantification and group separation between the standard and universal mask were small.The existing standard Centiloid mask is suitable for the quantification of all amyloid beta tracers.

Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods.

PURPOSE: Amyloid positron emission tomography (PET) with [18F]florbetaben (FBB) is an established tool for detecting Aß deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification. METHODS: This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), AmyloidIQ) that used several metrics to estimate Aß load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled. RESULTS: The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods. CONCLUSION: This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness.

Automatic classification of distal radius fracture using a two-stage ensemble deep learning framework.

Distal radius fractures (DRFs) are one of the most common types of wrist fracture and can be subdivided into intra- and extra-articular fractures. Compared with extra-articular DRFs which spare the joint surface, intra-articular DRFs extend to the articular surface and can be more difficult to treat. Identification of articular involvement can provide valuable information about the characteristics of fracture patterns. In this study, a two-stage ensemble deep learning framework was proposed to differentiate intra- and extra-articular DRFs automatically on posteroanterior (PA) view wrist X-rays. The framework firstly detects the distal radius region of interest (ROI) using an ensemble model of YOLOv5 networks, which imitates the clinicians' search pattern of zooming in on relevant regions to assess abnormalities. Secondly, an ensemble model of EfficientNet-B3 networks classifies the fractures in the detected ROIs into intra- and extra-articular. The framework achieved an area under the receiver operating characteristic curve of 0.82, an accuracy of 0.81, a true positive rate of 0.83 and a false positive rate of 0.27 (specificity of 0.73) for differentiating intra- from extra-articular DRFs. This study has demonstrated the potential in automatic DRF characterization using deep learning on clinically acquired wrist radiographs and can serve as a baseline for further research in incorporating multi-view information for fracture classification.

Tau, ß-Amyloid, and Glucose Metabolism Following Service-Related Traumatic Brain Injury in Vietnam War Veterans: The Australian Imaging Biomarkers and Lifestyle Study of Aging-Veterans Study (AIBL-VETS).

Traumatic brain injury (TBI) is common among military veterans and has been associated with an increased risk of dementia. It is unclear if this is due to increased risk for Alzheimer's disease (AD) or other mechanisms. This case control study sought evidence for AD, as defined by the 2018 National Institute on Aging - Alzheimer's Association (NIA-AA) research framework, by measuring tau, ß-amyloid, and glucose metabolism using positron emission tomography (PET) in veterans with service-related TBI. Seventy male Vietnam war veterans-40 with TBI (age 68.0 ± 2.5 years) and 30 controls (age 70.1 ± 5.3 years)-with no prior diagnosis of dementia or mild cognitive impairment underwent ß-amyloid (18F-Florbetaben), tau (18F-Flortaucipir), and fluorodeoxyglucose (18F-FDG) PET. The TBI cohort included 15 participants with mild, 16 with moderate, and nine with severe injury. ß-Amyloid level was calculated using the Centiloid (CL) method and tau was measured by standardized uptake value ratios (SUVRs) using the cerebellar cortex as reference region. Analyses were adjusted for age and APOE-e4. The findings were validated in an independent cohort from the Department of Defense-Alzheimer's Disease Neuroimaging Initiative (DOD ADNI) study. There were no significant nor trending differences in ß-amyloid or tau levels or 18F-FDG uptake between the TBI and control groups before and after controlling for covariates. The ß-amyloid and tau findings were replicated in the DOD ADNI validation cohort and persisted when the Australian Imaging Biomarkers and Lifestyle study of aging-Veterans study (AIBL-VETS) and DOD ADNI cohorts were combined (114 TBI vs. 87 controls in total). In conclusion, no increase in the later life accumulation of the neuropathological markers of AD in veterans with a remote history of TBI was identified.

Plasma Glial Fibrillary Acidic Protein Is Associated with 18F-SMBT-1 PET: Two Putative Astrocyte Reactivity Biomarkers for Alzheimer's Disease.

BACKGROUND: Astrocyte reactivity is an early event along the Alzheimer's disease (AD) continuum. Plasma glial fibrillary acidic protein (GFAP), posited to reflect astrocyte reactivity, is elevated across the AD continuum from preclinical to dementia stages. Monoamine oxidase-B (MAO-B) is also elevated in reactive astrocytes observed using 18F-SMBT-1 PET in AD. OBJECTIVE: The objective of this study was to evaluate the association between the abovementioned astrocyte reactivity biomarkers. METHODS: Plasma GFAP and Aß were measured using the Simoa® platform in participants who underwent brain 18F-SMBT-1 and Aß-PET imaging, comprising 54 healthy control (13 Aß-PET+ and 41 Aß-PET-), 11 mild cognitively impaired (3 Aß-PET+ and 8 Aß-PET-) and 6 probable AD (5 Aß-PET+ and 1 Aß-PET-) individuals. Linear regressions were used to assess associations of interest. RESULTS: Plasma GFAP was associated with 18F-SMBT-1 signal in brain regions prone to early Aß deposition in AD, such as the supramarginal gyrus (SG), posterior cingulate (PC), lateral temporal (LT) and lateral occipital cortex (LO). After adjusting for age, sex, APOE ɛ4 genotype, and soluble Aß (plasma Aß42/40 ratio), plasma GFAP was associated with 18F-SMBT-1 signal in the SG, PC, LT, LO, and superior parietal cortex (SP). On adjusting for age, sex, APOE ɛ4 genotype and insoluble Aß (Aß-PET), plasma GFAP was associated with 18F-SMBT-1 signal in the SG. CONCLUSION: There is an association between plasma GFAP and regional 18F-SMBT-1 PET, and this association appears to be dependent on brain Aß load.

Rates of regional tau accumulation in ageing and across the Alzheimer's disease continuum: an AIBL 18F-MK6240 PET study.

BACKGROUND: Tau positron emission tomography (PET) imaging enables longitudinal observation of tau accumulation in Alzheimer's disease (AD). 18F-MK6240 is a high affinity tracer for the paired helical filaments of tau in AD, widely used in clinical trials, despite sparse longitudinal natural history data. We aimed to evaluate the natural history of tau accumulation, and the impact of disease stage and reference region on the magnitude and effect size of regional change. METHODS: One hundred and eighty-four participants: 89 cognitively unimpaired (CU) beta-amyloid negative (Aß-), 44 CU Aß+, 51 cognitively impaired Aß+ (26 with mild cognitive impairment [MCI] and 25 with dementia) had follow-up 18F-MK6240 PET for one to four years (median 1.48). Regional standardised uptake value ratios (SUVR) were generated. Two reference regions were examined: cerebellar cortex and eroded subcortical white matter. FINDINGS: CU Aß- participants had very low rates of tau accumulation in the mesial temporal lobe (MTL). In CU Aß+, significantly higher rate of accumulation was seen in the MTL (particularly the amygdala), extending into the inferior temporal lobes. In MCI Aß+, the rate of accumulation was greatest in the lateral temporal, parietal and lateral occipital cortex, and plateaued in the MTL. Accumulation was global in AD Aß+, except for a plateau in the MTL. The eroded subcortical white matter reference region showed no significant advantage over the cerebellar cortex and appeared prone to spill-over in AD participants. Data fitting suggested approximately 15-20 years to accumulate tau to typical AD levels. INTERPRETATION: Tau accumulation occurs slowly. Rates vary according to brain region, disease stage and tend to plateau at high levels. Rates of tau accumulation are best measured in the MTL and inferior temporal cortex in preclinical AD and in large neocortical areas, in MCI and AD. FUNDING: NHMRC; Cerveau Technologies.

Tau and amyloid biomarkers modify the degree to which cognitive reserve and brain reserve predict cognitive decline.

OBJECTIVE: Brain reserve, cognitive reserve, and education are thought to protect against late-life cognitive decline, but these variables have not been directly compared to one another in the same model, using future cognitive and functional decline as outcomes. We sought to determine whether the influence of these protective factors on executive function (EF) and daily function decline was dependent upon Alzheimer's disease (AD) pathology severity, as measured by the total tau to beta-amyloid (T-τ/Aß1-42) ratio in cerebrospinal fluid (CSF). METHOD: Participants were 1201 older adult volunteers in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Brain reserve was defined using a composite index of structural brain volumes (total brain matter, hippocampus, and white matter hyperintensity). Cognitive reserve was defined as the variance in episodic memory performance not explained by brain integrity and demographics. RESULTS: At higher levels of T-τ/Aß1-42, brain and cognitive reserve predicted slower decline in EF. Only brain reserve attenuated decline at lower levels of T-τ/Aß1-42. Education had no independent association with cognitive decline. CONCLUSIONS: These results point to a hierarchy of protection against aging- and disease-associated cognitive decline. When pathology is low, only structural brain integrity predicts rate of future EF decline. The ability of cognitive reserve to predict future EF decline becomes stronger as CSF biomarker evidence of AD increases. Although education is typically thought of as a proxy for cognitive reserve, it did not show any protective effects on cognition after accounting for brain integrity and the residual cognitive reserve index.

Cerebrospinal fluid levels of fatty acid-binding protein 3 are associated with likelihood of amyloidopathy in cognitively healthy individuals.

Introduction: Fatty acid-binding protein 3 (FABP3) is a biomarker of neuronal membrane disruption, associated with lipid dyshomeostasis-a notable Alzheimer's disease (AD) pathophysiological change. We assessed the association of cerebrospinal fluid (CSF) FABP3 levels with brain amyloidosis and the likelihood/risk of developing amyloidopathy in cognitively healthy individuals. Methods: FABP3 levels were measured in CSF samples of cognitively healthy participants, > 60 years of age (n = 142), from the Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing (AIBL). Results: FABP3 levels were positively associated with baseline brain amyloid beta (Aß) load as measured by standardized uptake value ratio (SUVR, standardized ß = 0.22, P = .009) and predicted the change in brain Aß load (standardized ß = 0.32, P = .004). Higher levels of CSF FABP3 (above median) were associated with a likelihood of amyloidopathy (odds ratio [OR] 2.28, 95% confidence interval [CI] 1.12 to 4.65, P = .023). Discussion: These results support inclusion of CSF FABP3 as a biomarker in risk-prediction models of AD.

Plasma p-tau181/Aß1-42 ratio predicts Aß-PET status and correlates with CSF-p-tau181/Aß1-42 and future cognitive decline.

Background: In Alzheimer's disease (AD), plasma amyloid beta (Aß)1-42 and phosphorylated tau (p-tau) predict high amyloid status from Aß positron emission tomography (PET); however, the extent to which combination of these plasma assays can predict remains unknown. Methods: Prototype Simoa assays were used to measure plasma samples from participants who were either cognitively normal (CN) or had mild cognitive impairment (MCI)/AD in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Results: The p-tau181/Aß1-42 ratio showed the best prediction of Aß-PET across all participants (area under the curve [AUC] = 0.905, 95% confidence interval [CI]: 0.86-0.95) and in CN (AUC = 0.873; 0.80-0.94), and symptomatic (AUC = 0.908; 0.82-1.00) adults. Plasma p-tau181/Aß1-42 ratio correlated with cerebrospinal fluid (CSF) p-tau181 (Elecsys, Spearman's ρ = 0.74, P < 0.0001) and predicted abnormal CSF Aß (AUC = 0.816; 0.74-0.89). The p-tau181/Aß1-42 ratio also predicted future rates of cognitive decline assessed by AIBL Preclinical Alzheimer Cognitive Composite or Clinical Dementia Rating Sum of Boxes (P < 0.0001). Discussion: Plasma p-tau181/Aß1-42 ratio predicted both Aß-PET status and cognitive decline, demonstrating potential as both a diagnostic aid and as a screening and prognostic assay for preclinical AD trials.

Quantifiable brain atrophy synthesis for benchmarking of cortical thickness estimation methods.

Cortical thickness (CTh) is routinely used to quantify grey matter atrophy as it is a significant biomarker in studying neurodegenerative and neurological conditions. Clinical studies commonly employ one of several available CTh estimation software tools to estimate CTh from brain MRI scans. In recent years, machine learning-based methods emerged as a faster alternative to the main-stream CTh estimation methods (e.g. FreeSurfer). Evaluation and comparison of CTh estimation methods often include various metrics and downstream tasks, but none fully covers the sensitivity to sub-voxel atrophy characteristic of neurodegeneration. In addition, current evaluation methods do not provide a framework for the intra-method region-wise evaluation of CTh estimation methods. Therefore, we propose a method for brain MRI synthesis capable of generating a range of sub-voxel atrophy levels (global and local) with quantifiable changes from the baseline scan. We further create a synthetic test set and evaluate four different CTh estimation methods: FreeSurfer (cross-sectional), FreeSurfer (longitudinal), DL+DiReCT and HerstonNet. DL+DiReCT showed superior sensitivity to sub-voxel atrophy over other methods in our testing framework. The obtained results indicate that our synthetic test set is suitable for benchmarking CTh estimation methods on both global and local scales as well as regional inter-and intra-method performance comparison.

Residual reserve index modifies the effect of amyloid pathology on fluorodeoxyglucose metabolism: Implications for efficiency and capacity in cognitive reserve.

Background: The residual approach to measuring cognitive reserve (using the residual reserve index) aims to capture cognitive resilience conferred by cognitive reserve, but may be confounded by factors representing brain resilience. We sought to distinguish between brain and cognitive resilience by comparing interactions between the residual reserve index and amyloid, tau, and neurodegeneration ["AT(N)"] biomarkers when predicting executive function. We hypothesized that the residual reserve index would moderate at least one path from an AT(N) biomarker to executive function (consistent with cognitive resilience), as opposed to moderating a path between two AT(N) biomarkers (suggestive of brain resilience). Methods: Participants (N = 332) were from the Alzheimer's Disease Neuroimaging Initiative. The residual reserve index represented the difference between observed and predicted memory performance (a positive residual reserve index suggests higher cognitive reserve). AT(N) biomarkers were: CSF ß-amyloid1-42/ß-amyloid1-40 (A), plasma phosphorylated tau-181 (T), and FDG metabolism in AD-specific regions ([N]). AT(N) biomarkers (measured at consecutive time points) were entered in a sequential mediation model testing the indirect effects from baseline amyloid to executive function intercept (third annual follow-up) and slope (baseline to seventh follow-up), via tau and/or FDG metabolism. The baseline residual reserve index was entered as a moderator of paths between AT(N) biomarkers (e.g., amyloid-tau), and paths between AT(N) biomarkers and executive function. Results: The residual reserve index interacted with amyloid pathology when predicting FDG metabolism: the indirect effect of amyloid → FDG metabolism → executive function intercept and slope varied as a function of the residual reserve index. With lower amyloid pathology, executive function performance was comparable at different levels of the residual reserve index, but a higher residual reserve index was associated with lower FDG metabolism. With higher amyloid pathology, a higher residual reserve index predicted better executive function via higher FDG metabolism. Conclusion: The effect of the residual reserve index on executive function performance via FDG metabolism was consistent with cognitive resilience. This suggests the residual reserve index captures variation in cognitive reserve; specifically, neural efficiency, and neural capacity to upregulate metabolism to enhance cognitive resilience in the face of greater amyloid pathology. Implications for future research include the potential bidirectionality between neural efficiency and amyloid accumulation.