Implementation and Assessment of Tau Thresholds in Non-Demented Individuals as Predictors of Cognitive Decline in Tau Imaging Studies.

Background: Tau accumulation in Alzheimer's disease is associated with short term clinical progression and faster rates of cognitive decline in individuals with high amyloid-ß deposition. Defining an optimal threshold of tau accumulation predictive of cognitive decline remains a challenge. Objective: We tested the ability of regional tau PET sensitivity and specificity thresholds to predict longitudinal cognitive decline. We also tested the predictive performance of thresholds in the proposed new NIA-AA biological staging for Alzheimer's disease where multiple levels of tau positivity are used to stage participants. Methods: 18F-flortaucipir scans from 301 non-demented participants were processed and sampled. Four cognitive measures were assessed longitudinally. Regional standardized uptake value ratios were split into infra- and suprathreshold groups at baseline using previously derived thresholds. Survival analysis, log rank testing, and Generalized Estimation Equations assessed the relationship between the application of regional sensitivity/specificity thresholds and change in cognitive measures as well as tau threshold performance in predicting cognitive decline within the new NIA-AA biological staging. Results: The meta temporal region was best for predicting risk of short-term cognitive decline in suprathreshold, as compared to infrathreshold participants. When applying multiple levels of tau positivity, each subsequent level of tau identified cognitive decline at earlier timepoints. Conclusions: When using 18F-flortaucipir, meta temporal suprathreshold classification was associated with increased risk of cognitive decline, suggesting that abnormal tau deposition in the cortex predicts decline. Likewise, the application of multiple levels of tau clearly predicts the distinctive cognitive trajectories in the new NIA-AA biological staging framework.

Prediction of future cognitive decline among cognitively unimpaired individuals using measures of soluble phosphorylated tau or tau tangle pathology.

Plasma p-tau217 and Tau-PET are strong prognostic biomarkers in Alzheimer's disease (AD), but their relative performance in predicting future cognitive decline among cognitively unimpaired (CU) individuals is unclear. In this head-to-head comparison study including 9 cohorts and 1534 individuals, we found that plasma p-tau217 and medial temporal lobe Tau-PET signal showed similar associations with cognitive decline on a global cognitive composite test (R2 PET=0.32 vs R2 PLASMA=0.32, pdifference=0.812) and with progression to mild cognitive impairment (Hazard ratio[HR]PET=1.56[1.43-1.70] vs HRPLASMA=1.63[1.50-1.77], pdifference=0.627). Combined plasma and PET models were superior to the single biomarker models (R2=0.36, p<0.01). Furthermore, sequential selection using plasma p-tau217 and then Tau-PET reduced the number of participants required for a clinical trial by 94%, compared to a 75% reduction when using plasma p-tau217 alone. We conclude that plasma p-tau217 and Tau-PET showed similar performance for predicting future cognitive decline in CU individuals, and their sequential use (i.e., plasma p-tau217 followed by Tau-PET in a subset with high plasma p-tau217) is useful for screening in clinical trials in preclinical AD.

Harmonizing tau positron emission tomography in Alzheimer's disease: The CenTauR scale and the joint propagation model.

INTRODUCTION: Tau-positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis. METHODS: Using head-to-head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed "CenTauR" [CTR]). JPM is a statistical model that simultaneously models the relationships between head-to-head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale. RESULTS: A strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach. DISCUSSION: Preliminary findings using the JPM support the development and adoption of a universal scale for tau-PET quantification. HIGHLIGHTS: Tested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed "CenTauRs". Tested a Centiloid-like linear regression approach. Using five cohorts with head-to-head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.

Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning.

This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations.

Association of Basal Forebrain Atrophy With Cognitive Decline in Early Alzheimer Disease.

BACKGROUND AND OBJECTIVES: In early Alzheimer disease (AD), ß-amyloid (Aß) deposition is associated with volume loss in the basal forebrain (BF) and cognitive decline. However, the extent to which Aß-related BF atrophy manifests as cognitive decline is not understood. This study sought to characterize the relationship between BF atrophy and the decline in memory and attention in patients with early AD. METHODS: Participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study who completed Aß-PET imaging and repeated MRI and cognitive assessments were included. At baseline, participants were classified based on their clinical dementia stage and Aß status, yielding groups that were cognitively unimpaired (CU) Aß-, CU Aß+, and mild cognitive impairment (MCI) Aß+. Linear mixed-effects models were used to assess changes in volumetric measures of BF subregions and the hippocampus and changes in AIBL memory and attention composite scores for each group compared with CU Aß- participants. Associations between Aß burden, brain atrophy, and cognitive decline were evaluated and explored further using mediation analyses. RESULTS: The cohort included 476 participants (72.6 ± 5.9 years, 55.0% female) with longitudinal data from a median follow-up period of 6.1 years. Compared with the CU Aß- group (n = 308), both CU Aß+ (n = 107) and MCI Aß+ (n = 61) adults showed faster decline in BF and hippocampal volumes and in memory and attention (Cohen d = 0.73-1.74). Rates of atrophy in BF subregions and the hippocampus correlated with cognitive decline, and each individually mediated the impact of Aß burden on memory and attention decline. When all mediators were considered simultaneously, hippocampal atrophy primarily influenced the effect of Aß burden on memory decline (ß [SE] = -0.139 [0.032], proportion mediated [PM] = 28.0%) while the atrophy of the posterior nucleus basalis of Meynert in the BF (ß [SE] = -0.068 [0.029], PM = 13.1%) and hippocampus (ß [SE] = -0.121 [0.033], PM = 23.4%) distinctively influenced Aß-related attention decline. DISCUSSION: These findings highlight the significant role of BF atrophy in the complex pathway linking Aß to cognitive impairment in early stages of AD. Volumetric assessment of BF subregions could be essential in elucidating the relationships between the brain structure and behavior in AD.

Clinical Evidence for GLP-1 Receptor Agonists in Alzheimer's Disease: A Systematic Review.

Background: Alzheimer's disease (AD) is the most common cause of dementia. While preclinical studies have shown benefits of glucagon-like peptide 1 receptor agonists (GLP-1 RA) in targeting core AD pathology, clinical studies are limited. Objective: A systematic review was performed to evaluate GLP-1 RAs in AD for their potential to target core AD pathology and improve cognition. Methods: Searches were conducted via three different databases (PubMed, Embase, and Cochrane Library). Search terms included Medical Subject Headings (MeSH) terms: 'glucagon-like peptide 1 receptor agonist' and 'Alzheimer's disease', as well as entry terms 'GLP-1 RA', 'AD', and three types of GLP-1 RA: 'liraglutide', 'exenatide', and 'lixisenatide'. Results: A total of 1,444 studies were screened. Six articles that met criteria were included (four randomized control trials [RCTs] and two protocol studies). Two RCTs with amyloid-ß and tau biomarker endpoints did not observe an end of treatment difference between the placebo and treated groups. In three RCTs with cognitive endpoints, there was no end of treatment difference between placebo and treated groups. GLP-1 RA showed metabolic benefits, such as lower body mass index and improved glucose levels on oral glucose tolerance tests in treated groups. GLP-1 RA may mitigate the decline in cerebral glucose metabolism and show enhanced blood-brain glucose transport capacity using 18F-FDG PET, however, more data is needed. Conclusions: GLP-1 RA therapy did not alter amyloid-ß and tau biomarkers nor show improvements in cognition but showed potential metabolic and neuroprotective benefits.

Suboptimal self-reported sleep efficiency and duration are associated with faster accumulation of brain amyloid beta in cognitively unimpaired older adults.

INTRODUCTION: This study investigated whether self-reported sleep quality is associated with brain amyloid beta (Aß) accumulation. METHODS: Linear mixed effect model analyses were conducted for 189 cognitively unimpaired (CU) older adults (mean ± standard deviation 74.0 ± 6.2; 53.2% female), with baseline self-reported sleep data, and positron emission tomography-determined brain Aß measured over a minimum of three time points (range 33.3-72.7 months). Analyses included random slopes and intercepts, interaction for apolipoprotein E (APOE) ε4 allele status, and time, adjusting for sex and baseline age. RESULTS: Sleep duration <6 hours, in APOE ε4 carriers, and sleep efficiency <65%, in the whole sample and APOE ε4 non-carriers, is associated with faster accumulation of brain Aß. DISCUSSION: These findings suggest a role for self-reported suboptimal sleep efficiency and duration in the accumulation of Alzheimer's disease (AD) neuropathology in CU individuals. Additionally, poor sleep efficiency represents a potential route via which individuals at lower genetic risk may progress to preclinical AD. Highlights: In cognitively unimpaired older adults self-report sleep is associated with brain amyloid beta (Aß) accumulation.Across sleep characteristics, this relationship differs by apolipoprotein E (APOE) genotype.Sleep duration <6 hours is associated with faster brain Aß accumulation in APOE ε4 carriers.Sleep efficiency < 65% is associated with faster brain Aß accumulation in APOE ε4 non-carriers.Personalized sleep interventions should be studied for potential to slow Aß accumulation.

Association Between ß-Amyloid Accumulation and Incident Dementia in Individuals 80 Years or Older Without Dementia.

BACKGROUND AND OBJECTIVES: While the highest prevalence of dementia occurs in individuals older than 80 years, most imaging studies focused on younger populations. The rates of ß-amyloid (Aß) accumulation and the effect of Alzheimer disease (AD) pathology on progression to dementia in this age group remain unexplored. In this study, we examined the relationship between changes in Aß deposition over time and incident dementia in nondemented individuals followed during a period of 11 years. METHODS: We examined 94 participants (age 85.9 + 2.8 years) who had up to 5 measurements of Pittsburgh compound-B (PiB)-PET and clinical evaluations from 2009 to 2020. All 94 participants had 2 PiB-PET scans, 76 participants had 3 PiB-PET scans, 18 participants had 4 PiB-PET scans, and 10 participants had 5 PiB-PET scans. The rates of Aß deposition were compared with 120 nondemented individuals younger than 80 years (69.3 ± 5.4 years) from the Australian Imaging, Biomarker, and Lifestyle (AIBL) study who had 3 or more annual PiB-PET assessments. RESULTS: By 2020, 49% of the participants developed dementia and 63% were deceased. There was a gradual increase in Aß deposition in all participants whether they were considered Aß positive or negative at baseline. In a Cox model controlled for age, sex, education level, APOE-4 allele, baseline Mini-Mental State Examination, and mortality, short-term change in Aß deposition was not significantly associated with incident dementia (HR 2.19 (0.41-11.73). However, baseline Aß burden, cortical thickness, and white matter lesions volume were the predictors of incident dementia. Aß accumulation was faster (p = 0.01) in the older cohort (5.6%/year) when compared with AIBL (4.1%/year). In addition, baseline Aß deposition was a predictor of short-term change (mean time 1.88 years). DISCUSSION: There was an accelerated Aß accumulation in cognitively normal individuals older than 80 years. Baseline Aß deposition was a determinant of incident dementia and short-term change in Aß deposition suggesting that an active Aß pathologic process was present when these participants were cognitively normal. Consequently, age may not be a limiting factor for the use of the emergent anti-Aß therapies.

Brain 11ß-Hydroxysteroid Dehydrogenase Type 1 Occupancy by Xanamem™ Assessed by PET in Alzheimer's Disease and Cognitively Normal Individuals.

BACKGROUND: 11ß-hydroxysteroid dehydrogenase type 1 (11ß-HSD1) regulates intracellular cortisol and its inhibition by the small molecule inhibitor, Xanamem™, may provide a disease-modifying strategy for Alzheimer's disease (AD). Animal models suggest a range of 30-60% enzyme inhibition may suffice to provide neuroprotection. OBJECTIVE: To determine the regional brain occupancy of 11ß-HSD1 by Xanamem™ in cognitively normal participants (CN) and mild cognitive impairment (MCI)/mild AD patients to investigate potential dosing ranges for future efficacy studies. METHODS: Seventeen MCI/AD and 23 CN were included. Regional brain time-activity curves (TAC), standardized uptake values (SUV40-60) and volume of distribution (VT) from Logan plot with image derived input function from 11C-TARACT positron emission tomography (PET) were used to assess the degree of 11ß-HSD1 occupancy by increasing doses of Xanamem™ (5 mg, 10 mg, 20 mg or 30 mg daily for 7 days). RESULTS: All measures showed high 11ß-HSD1 occupancy with Xanamem to similar degree in CN and MCI/AD. The dose-response relationship was relatively flat above 5 mg. Respective median (interquartile range [Q1-Q3]) 11ß-HSD1 occupancy in the MCI/AD and CN groups after treatment with 10 mg Xanamem were 80% [79-81%] and 75% [71-76%] in the neocortex, 69% [64-70%] and 61% [52-63%] in the medial temporal lobe, 80% [79-80%] and 73% [68-73%] in the basal ganglia, and 71% [67-75%] and 66% [62-68%] in the cerebellum. CONCLUSIONS: TAC, SUV40-60, and VT measures indicate Xanamem achieves high target occupancy levels with near saturation at 10 mg daily. These data support exploration of doses of≤10 mg daily in future clinical studies.

Adaptación del llgoritmo maracas para segmentacón de la arteria carótida y cuaantificación de estenosis en imágenes aac / Adaptation of the MARACAS Algorithm for Carotid Artery Segmentation and Stenosis Quantification on CT Images

En este artículo se describen las adaptaciones hechas al algoritmo MARACAS para segmentar y cuantificar estructuras vasculares en imágenes TAC de la arteria carótida. El algoritmo MARACAS, que está basado en un modelo elástico y en un análisis de los valores y vectores propios de la matriz de inercia, fue inicialmente diseñado para segmentar una sola arteria en imágenes ARM. Las modificaciones están principalmente enfocadas a tratar las especificidades de las imágenes TAC, así como la presencia de bifurcaciones. Los algoritmos implementados en esta nueva versión se clasifican en dos niveles. 1. Los procesamientos de bajo nivel (filtrado de ruido y de artificios direccionales, presegmentación y realce) destinados a mejorar la calidad de la imagen y presegmentarla. Estas técnicas están basadas en información a priori sobre el ruido, los artificios y los intervalos típicos de niveles de gris del lumen, del fondo y de las calcificaciones. 2. Los procesamientos de alto nivel para extraer la línea central de la arteria, segmentar el lumen y cuantificar la estenosis. A este nivel, se aplican conocimientos a priori sobre la forma y anatomía de las estructuras vasculares. El método fue evaluado en 31 imágenes suministradas en el concurso Carotid Lumen Segmentation and Stenosis Grading Grand Challenge 2009. Los resultados obtenidos en la segmentación arrojaron un coeficiente de similitud de Dice promedio de 80,4% comparado con la segmentación de referencia, y el error promedio de la cuantificación de estenosis fue 14,4%.

This paper describes the adaptations of MARACAS algorithm to the segmentation and quantification of vascular structures in CTA images of the carotid artery. The MARACAS algorithm, which is based on an elastic model and on a multi-scale eigen-analysis of the inertia matrix, was originally designed to segment a single artery in MRA images. The modifications are primarily aimed at addressing the specificities of CT images and the bifurcations. The algorithms implemented in this new version are classified into two levels. 1. The low-level processing (filtering of noise and directional artifacts, enhancement and pre-segmentation) to improve the quality of the image and to pre-segment it. These techniques are based on a priori information about noise, artifacts and typical gray levels ranges of lumen, background and calcifications. 2. The high-level processing to extract the centerline of the artery, to segment the lumen and to quantify the stenosis. At this level, we apply a priori knowledge of shape and anatomy of vascular structures. The method was evaluated on 31 datasets from the Carotid Lumen Segmentation and Stenosis Grading Grand Challenge 2009. The segmentation results obtained an average of 80:4% Dice similarity score, compared to reference segmentations, and the mean stenosis quantification error was 14.4%.