Optimizing PiB-PET SUVR change-over-time measurement by a large-scale analysis of longitudinal reliability, plausibility, separability, and correlation with MMSE

AbstractQuantitative measurements of change in β-amyloid load from Positron Emission Tomography (PET) images play a critical role in clinical trials and longitudinal observational studies of Alzheimer's disease. These measurements are strongly affected by methodological differences between implementations, including choice of reference region and use of partial volume correction, but there is a lack of consensus for an optimal method. Previous works have examined some relevant variables under varying criteria, but interactions between them prevent choosing a method via combined meta-analysis. In this work, we present a thorough comparison of methods to measure change in β-amyloid over time using Pittsburgh Compound B (PiB) PET imaging.MethodsWe compare 1,024 different automated software pipeline implementations with varying methodological choices according to four quality metrics calculated over three-timepoint longitudinal trajectories of 129 subjects: reliability (straightness/variance); plausibility (lack of negative slopes); ability to predict accumulator/non-accumulator status from baseline value; and correlation between change in β-amyloid and change in Mini Mental State Exam (MMSE) scores.Results and conclusionFrom this analysis, we show that an optimal longitudinal measure of β-amyloid from PiB should use a reference region that includes a combination of voxels in the supratentorial white matter and those in the whole cerebellum, measured using two-class partial volume correction in the voxel space of each subject's corresponding anatomical MR image

Age and sex impact plasma NFL and t-Tau trajectories in individuals with subjective memory complaints : a 3-year follow-up study

Background Plasma neurofilament light (NFL) and total Tau (t-Tau) proteins are candidate biomarkers for early stages of Alzheimer's disease (AD). The impact of biological factors on their plasma concentrations in individuals with subjective memory complaints (SMC) has been poorly explored. We longitudinally investigate the effect of sex, age, APOE epsilon 4 allele, comorbidities, brain amyloid-beta (A beta) burden, and cognitive scores on plasma NFL and t-Tau concentrations in cognitively healthy individuals with SMC, a condition associated with AD development. Methods Three hundred sixteen and 79 individuals, respectively, have baseline and three-time point assessments (at baseline, 1-year, and 3-year follow-up) of the two biomarkers. Plasma biomarkers were measured with an ultrasensitive assay in a mono-center cohort (INSIGHT-preAD study). Results We show an effect of age on plasma NFL, with women having a higher increase of plasma t-Tau concentrations compared to men, over time. The APOE epsilon 4 allele does not affect the biomarker concentrations while plasma vitamin B12 deficiency is associated with higher plasma t-Tau concentrations. Both biomarkers are correlated and increase over time. Baseline NFL is related to the rate of A beta deposition at 2-year follow-up in the left-posterior cingulate and the inferior parietal gyri. Baseline plasma NFL and the rate of change of plasma t-Tau are inversely associated with cognitive score. Conclusion We find that plasma NFL and t-Tau longitudinal trajectories are affected by age and female sex, respectively, in SMC individuals. Exploring the influence of biological variables on AD biomarkers is crucial for their clinical validation in blood

Body mass index and two-year change of in vivo Alzheimers disease pathologies in cognitively normal older adults

Background Low body mass index (BMI) or underweight status in late life is associated with an increased risk of dementia or Alzheimers disease (AD). However, the relationship between late-life BMI and prospective longitudinal changes of in-vivo AD pathology has not been investigated. Methods This prospective longitudinal study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimers Disease (KBASE). A total of 194 cognitive normal older adults were included in the analysis. BMI at baseline was measured, and two-year changes in brain Aβ and tau deposition on PET imaging were used as the main outcomes. Linear mixed-effects (LME) models were used to examine the relationships between late-life BMI and longitudinal change in AD neuropathological biomarkers. Results A lower BMI at baseline was significantly associated with a greater increase in tau deposition in AD-signature region over 2 years (β, -0.018; 95% CI, -0.028 to -0.004; p = .008), In contrast, BMI was not related to two-year changes in global Aβ deposition (β, 0.0002; 95% CI, -0.003 to 0.002, p = .671). An additional exploratory analysis for each sex showed lower baseline BMI was associated with greater increases in tau deposition in males (β, -0.027; 95% CI, -0.046 to -0.009; p = 0.007), but not in females. Discussion The findings suggest that lower BMI in late-life may predict or contribute to the progression of tau pathology over the subsequent years in cognitively unimpaired older adults

Age and sex impact plasma NFL and t-Tau trajectories in individuals with subjective memory complaints: a 3-year follow-up study

BACKGROUND: Plasma neurofilament light (NFL) and total Tau (t-Tau) proteins are candidate biomarkers for early stages of Alzheimer's disease (AD). The impact of biological factors on their plasma concentrations in individuals with subjective memory complaints (SMC) has been poorly explored. We longitudinally investigate the effect of sex, age, APOE ε4 allele, comorbidities, brain amyloid-β (Aβ) burden, and cognitive scores on plasma NFL and t-Tau concentrations in cognitively healthy individuals with SMC, a condition associated with AD development. METHODS: Three hundred sixteen and 79 individuals, respectively, have baseline and three-time point assessments (at baseline, 1-year, and 3-year follow-up) of the two biomarkers. Plasma biomarkers were measured with an ultrasensitive assay in a mono-center cohort (INSIGHT-preAD study). RESULTS: We show an effect of age on plasma NFL, with women having a higher increase of plasma t-Tau concentrations compared to men, over time. The APOE ε4 allele does not affect the biomarker concentrations while plasma vitamin B12 deficiency is associated with higher plasma t-Tau concentrations. Both biomarkers are correlated and increase over time. Baseline NFL is related to the rate of Aβ deposition at 2-year follow-up in the left-posterior cingulate and the inferior parietal gyri. Baseline plasma NFL and the rate of change of plasma t-Tau are inversely associated with cognitive score. CONCLUSION: We find that plasma NFL and t-Tau longitudinal trajectories are affected by age and female sex, respectively, in SMC individuals. Exploring the influence of biological variables on AD biomarkers is crucial for their clinical validation in blood

Alzheimer’s Dementia : The Emerging Role of Positron Emission Tomography

Open Access via Sage AgreementPeer reviewedPublisher PD

Assessment Of The Interplay Between Regional β-Amyloid Burden And White Matter Hyperintensities On Cognition And Default Mode Network In Clinically Normal Older Participants

Objective: Alzheimer’s disease (AD) and subcortical vascular dementia are considered the most common pathologic contributors to dementia in the aging population. Both frequently coexist in over 80% of community dwelling adults with dementia. The neuropathological development of AD arguably begins with β-amyloid (Aβ) deposition in the brain. This series of studies aims to test the hypothesis that early focal regional amyloid deposition in the brain is associated with cognitive performance in specific cognitive domain scores in preclinical AD (pAD) (study1). Since mixed dementia is widely recognized as the norm rather than the exception, the second study aimed to explore the relation between regional and global Aβ and WMH with core cognitive function (executive function (EF) and memory) scores in cognitively normal (CN) older adults (study2). Finally, the relationship between WMH and Aβ is strongly determined by the spatial distribution of the two pathologies, so the third study aimed to quantify Aβ in Default mode network (DMN) regions to examine whether cerebral small vessels disease (SVD) disruption of connectivity affects Aβ deposition in disconnected DMN regions (study3). Method: Global and regional Standard Uptake Value ratios (SUVr) from Aβ-PET, WMH volumes from MRI FLAIR images, and cognitive test scores were analyzed across a sample of CN participants. Linear regression models adjusted for age, sex and education used to assess the relationships between regional SUVr and cognitive test scores across 99 CN from Sanders Brown Center on Aging (study1). Moderation, and mediation modeling were used to define the interplay between global, regional Aβ and WMHs measures in relation to EF and memory composite scores outcomes at baseline and after approximately 2 years across a sample of 714 CN from the Alzheimer’s Disease Neuroimaging Initiative ADNI (study2). The association of WMH volume in anatomically defined white matter tracts of atlas-based fiber tract with Aβ SUVr specifically in connected cortical regions within DMN was tested across sample of 74 CN from ADNI3. Results: EF performance was associated with increased regional SUVr in the precuneus and posterior cingulate regions only (p \u3c 0.05). The moderation regression analysis showed additive effects of Aβ and WMH over baseline memory and EF scores (p =0.401 and 0.061 respectively) and synergistic effects over follow-up EF (p \u3c 0.05). Through mediation analysis, the data from study 2 showed that WMH affects, mediated by global and regional amyloid burden, are responsible for baseline cognitive performance deficits in memory and EF. Finally, the regression analysis from study 3 demonstrated that increased WMH volumes in superior longitudinal fasciculus (SLF) was associated with increased regional SUVr in inferior parietal lobule (IPL) (p \u3c 0.05). Conclusion: While the prevailing view in the field suggests that memory performance is the earliest clinical hallmark of AD, the present data demonstrate that changes in EF, mediated by Aβ deposition in the precuneus and posterior cingulate may precede memory decline in pAD. After adding the second key driver of cognitive decline in CN, the finding suggested that WMH dependent changes in baseline cognitive performance are related to direct effect of WMH and an indirect effect through both global and regional Aβ burden. Further studies are needed to show the longitudinal influences of WMH on Aβ distributions in participants with mixed dementia

Joint Analysis of PET/MR Data for Improved PET Quantification

Quantitative pharmacokinetic analysis of Positron Emission Tomography (PET) data typically requires a dynamic scan of at least one hour, which poses a challenge for both clinical and research studies. Instead, in standard practice, a static 10 minute scan is used to calculate the standardised uptake value ratio (SUVR). SUVR approximates tracer binding but is biased by blood flow changes, rendering it unsuitable for longitudinal studies. In this thesis, the availability of magnetic resonance imaging (MRI) data, simultaneously acquired from a PET-MR scanner is exploited to reduce the time required for accurate PET quantification. The main body of this work comprises the development of a framework to incorporate blood flow information from arterial spin labelled (ASL) MRI data into the existing simplified reference tissue model (SRTM) to replace the early phase of the PET data, reducing the acquisition time. This reduced acquisition time (RT-) SRTM was evaluated on [18F]-florbetapir data for the estimation of both regional average and voxelwise amyloid burden (BPND), and was validated against the gold standard BPND using a 60 minute scan. The first step of the RT-SRTM requires the PET tracer delivery parameter, R1, to be estimated from the ASL cerebral blood flow (CBF) maps. Several methods were evaluated: linear regression using region as a covariate, multi-atlas propagation with image fusion, and deep learning based regression using a convolutional neural network. The RT-SRTM was shown to facilitate accurate regional voxelwise quantification in half the acquisition time (30 minutes). Additionally, deep learning based regression was used to learn the model which maps ASL-CBF and dynamic PET data to BPND in a single step (SSDL). The SS-DL model exploits all available information, and avoids noise sensitive voxelwise fitting. This allows the acquisition time to be cut to 15 minutes, and facilitates accurate voxelwise BPND quantification on a timescale manageable for almost all patients and studies