Biomarkers.

Background: Diffusion tensor imaging along perivascular spaces index (DTI-ALPS), which measures diffusivity increases in the perivascular spaces along the medullary veins, is being increasingly utilized as a surrogate marker of glymphatic clearance (Taoka et. al. Jpn J Radio 2017).

Biomarkers.

Background: Quantifying white matter using diffusion MRI (dMRI) has been proposed for measuring early microstructural tissue changes due to cerebral small vessel disease and aid in quantifying vascular contributions to cognitive impairment and dementia (VCID). Our goal was to compare the usefulness of longitudinal white matter changes in the commonly available diffusion MRI measures for VCID prevention trials.

Method: We included 718 participants over 50 years of age (mean age: 71.

Biomarkers.

Background: There has been a recent proliferation of various quantities based on single shell Diffusion Tensor Imaging (DTI) for capturing overall cerebrovascular health, especially Small Vessel Disease (SVD) as a single number. The existing literature has gaps in the comparison of these measures, so we evaluated them as predictors of both current and future White Matter Hyperintensity (WMH) as a proxy of SVD.

Method: Using baseline 3T MRI examinations (T1, DTI, FLAIR scans) of 598 participants (>60 years, amyloid negative, to limit to those on the SVD pathway) from the Mayo Clinic Study of Aging, we calculated five summary DTI quantities with varying degree of complexity.

Biomarkers.

Background: Dementia with Lewy bodies (DLB) frequently co-occurs with Alzheimer's disease (AD) pathologies, exacerbating disease progression. Biophysical models of diffusion imaging data, such as Neurite Orientation Dispersion and Density Imaging (NODDI), may reveal novel insights into the neurobiological substrates of AD on cortical and white matter microstructural injury.

Method: A cohort of 57 DLB patients on the DLB spectrum (33 clinically probable DLB and 14 prodromal DLB) and 57 cognitively unimpaired (CU) controls underwent NODDI and PET imaging with [F]-Flortaucipir and [C]-PiB (Table 1).

Biomarkers.

Background: Vascular contributions to cognitive impairment and dementia (VCID) are often comorbid with Alzheimer's disease and increase the risk of dementia. Blood-based biomarkers may be promising for identifying individuals at high risk for VCID due to small vessel disease (SVD).

Method: We included 1709 participants from the Mayo Clinic Study of Aging who had concurrent MRI, plasma neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) measured on the HD-X Simoa Quanterix platform, and clinical dementia rating scale (CDR).

Biomarkers.

Background: White matter (WM) damage is seen with neurodegenerative and cerebrovascular pathologies and contributes to cognitive dysfunction. We hypothesized that there are multiple disease progression patterns in WM microstructural changes related to aging and dementia, and these can be identified using SuStaIn (data-driven clustering algorithm for disease subtype and stage discovery) on multishell diffusion MRI (NODDI) data. NODDI provides information on cellular tissue architecture - neurite density index (NDI) measures packing density of axons and dendrites, and free water fraction (FWF) measures unrestricted water, e.

Alzheimer's Imaging Consortium.

Background: There has been a recent proliferation of various quantities based on single shell Diffusion Tensor Imaging (DTI) for capturing overall cerebrovascular health, especially Small Vessel Disease (SVD) as a single number. The existing literature has gaps in the comparison of these measures, so we evaluated them as predictors of both current and future White Matter Hyperintensity (WMH) as a proxy of SVD.

Method: Using baseline 3T MRI examinations (T1, DTI, FLAIR scans) of 598 participants (>60 years, amyloid negative, to limit to those on the SVD pathway) from the Mayo Clinic Study of Aging, we calculated five summary DTI quantities with varying degree of complexity.

Alzheimer's Imaging Consortium.

Background: Quantifying white matter using diffusion MRI (dMRI) has been proposed for measuring early microstructural tissue changes due to cerebral small vessel disease and aid in quantifying vascular contributions to cognitive impairment and dementia (VCID). Our goal was to compare the usefulness of longitudinal white matter changes in the commonly available diffusion MRI measures for VCID prevention trials.

Method: We included 718 participants over 50 years of age (mean age: 71.

Alzheimer's Imaging Consortium.

Background: White matter (WM) damage is seen with neurodegenerative and cerebrovascular pathologies and contributes to cognitive dysfunction. We hypothesized that there are multiple disease progression patterns in WM microstructural changes related to aging and dementia, and these can be identified using SuStaIn (data-driven clustering algorithm for disease subtype and stage discovery) on multishell diffusion MRI (NODDI) data. NODDI provides information on cellular tissue architecture - neurite density index (NDI) measures packing density of axons and dendrites, and free water fraction (FWF) measures unrestricted water, e.

Can integration of Alzheimer's plasma biomarkers with MRI, cardiovascular, genetics, and lifestyle measures improve cognition prediction?

There is increasing interest in Alzheimer's disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata.

NODDI in gray matter is a sensitive marker of aging and early AD changes.

Introduction: Age-related and Alzheimer's disease (AD) dementia-related neurodegeneration impact brain health. While morphometric measures from T1-weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker.

Advancing Tau PET Quantification in Alzheimer Disease with Machine Learning: Introducing THETA, a Novel Tau Summary Measure.

Alzheimer disease (AD) exhibits spatially heterogeneous 3- or 4-repeat tau deposition across participants. Our overall goal was to develop an automated method to quantify the heterogeneous burden of tau deposition into a single number that would be clinically useful. We used tau PET scans from 3 independent cohorts: the Mayo Clinic Study of Aging and Alzheimer's Disease Research Center (Mayo, = 1,290), the Alzheimer's Disease Neuroimaging Initiative (ADNI, = 831), and the Open Access Series of Imaging Studies (OASIS-3, = 430).

Comparative analysis of quantitative susceptibility mapping in preclinical dementia detection.

Purpose: This review aims to explore the role of Quantitative Susceptibility Mapping (QSM) in the early detection of neurodegenerative diseases, particularly Alzheimer's disease (AD) and Lewy body dementia (LBD). By examining QSM's ability to map brain iron deposition, we seek to highlight its potential as a diagnostic tool for preclinical dementia.

Methodology: QSM techniques involve the advanced processing of MRI phase images to reconstruct tissue susceptibility, employing methods such as spherical mean value filtering and Tikhonov regularization for accurate background field removal.

Sex and gender differences in cognitive resilience to aging and Alzheimer's disease.

Sex and gender-biological and social constructs-significantly impact the prevalence of protective and risk factors, influencing the burden of Alzheimer's disease (AD; amyloid beta and tau) and other pathologies (e.g., cerebrovascular disease) which ultimately shape cognitive trajectories.

White Matter Abnormalities Track Disease Progression in Multiple System Atrophy.

Background: White matter (WM) abnormalities have been implicated in clinically relevant functional decline in multiple system atrophy (MSA).

Objective: To identify the WM and gray matter (GM) abnormalities in MSA and assess the utility of longitudinal structural and diffusion changes as surrogate markers for tracking disease progression in MSA.

Methods: Twenty-seven participants with early MSA [15 with clinically predominant cerebellar (MSA-C) and 12 with clinically predominant parkinsonian features (MSA-P)] and 14 controls were enrolled as a part of our prospective, longitudinal study of synucleinopathies.

Longitudinal associations of reproductive factors and exogeneous estrogens with neuroimaging biomarkers of Alzheimer's disease and cerebrovascular disease.

Introduction: Female-specific reproductive factors and exogeneous estrogen use are associated with cognition in later life. However, the underlying mechanisms are not understood. The present study aimed to investigate the effect of reproductive factors on neuroimaging biomarkers of Alzheimer's disease (AD) and cerebrovascular pathologies.

Influences of amyloid-β and tau on white matter neurite alterations in dementia with Lewy bodies.

Dementia with Lewy bodies (DLB) is a neurodegenerative condition often co-occurring with Alzheimer's disease (AD) pathology. Characterizing white matter tissue microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) may help elucidate the biological underpinnings of white matter injury in individuals with DLB. In this study, diffusion tensor imaging (DTI) and NODDI metrics were compared in 45 patients within the dementia with Lewy bodies spectrum (mild cognitive impairment with Lewy bodies (n = 13) and probable dementia with Lewy bodies (n = 32)) against 45 matched controls using conditional logistic models.

Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population?

Background: White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, Alzheimer's imaging markers, namely amyloid and tau burden, and cognition.

Evaluation of 'Normal' Cognitive Functions and Correlation With MRI Volumetry: Towards a Definition of Vascular Cognitive Impairment.

Introduction It is important to establish criteria to define vascular cognitive impairment (VCI) in India as VCI is an image-based diagnosis and magnetic resonance imaging (MRI) changes resulting from age with prevalent vascular risk factors may confound MRI interpretation. The objective of this study was to establish normative community data for MRI volumetry including white matter hyperintensity volume (WMHV), correlated with age-stratified cognitive scores and vascular risk factors (VRFs), in adults aged 40 years and above.  Methods We screened 2651 individuals without known neurological morbidity, living in Mumbai and nearby rural areas, using validated Marathi translations of Kolkata Cognitive Battery (KCB) and geriatric depression score (GDS).

Vascular risk, gait, behavioral, and plasma indicators of VCID.

Introduction: Cost-effective screening tools for vascular contributions to cognitive impairment and dementia (VCID) has significant implications. We evaluated non-imaging indicators of VCID using magnetic resonance imaging (MRI)-measured white matter (WM) damage and hypothesized that these indicators differ based on age.

Methods: In 745 participants from the Mayo Clinic Study of Aging (≥50 years of age) with serial WM assessments from diffusion MRI and fluid-attenuated inversion recovery (FLAIR)-MRI, we examined associations between baseline non-imaging indicators (demographics, vascular risk factors [VRFs], gait, behavioral, plasma glial fibrillary acidic protein [GFAP], and plasma neurofilament light chain [NfL]) and WM damage across three age tertiles.

Advancing Tau-PET quantification in Alzheimer's disease with machine learning: introducing THETA, a novel tau summary measure.

Alzheimer's disease (AD) exhibits spatially heterogeneous 3R/4R tau pathology distributions across participants, making it a challenge to quantify extent of tau deposition. Utilizing Tau-PET from three independent cohorts, we trained and validated a machine learning model to identify visually positive Tau-PET scans from regional SUVR values and developed a novel summary measure, THETA, that accounts for heterogeneity in tau deposition. The model for identification of tau positivity achieved a balanced test accuracy of 95% and accuracy of ≥87% on the validation datasets.

Quantitative susceptibility mapping from basal ganglia and related structures: correlation with disease severity in progressive supranuclear palsy.

Objective: We examined whether mean magnetic susceptibility values from deep gray matter structures in patients with progressive supranuclear palsy (PSP) differed from those in patients with Parkinson's disease (PD) and healthy volunteers, and correlated with the PSP rating scale.

Methods: Head of caudate nucleus, putamen, globus pallidus, substantia nigra and red nucleus were the regions of interest. Mean susceptibility values from these regions in PSP patients were estimated using quantitative susceptibility mapping.

White Matter Degeneration Pathways Associated With Tau Deposition in Alzheimer Disease.

Background And Objectives: The dynamics of white matter (WM) changes are understudied in Alzheimer disease (AD). Our goal was to study the association between flortaucipir PET and WM health using neurite orientation dispersion and density imaging (NODDI) and evaluate its association with cognitive performance. Specifically, we focused on NODDI's Neurite Density Index (NDI), which aids in capturing axonal degeneration in WM and has greater specificity than single-shell diffusion MRI methods.

Cross-scanner harmonization methods for structural MRI may need further work: A comparison study.

The clinical usefulness MRI biomarkers for aging and dementia studies relies on precise brain morphological measurements; however, scanner and/or protocol variations may introduce noise or bias. One approach to address this is post-acquisition scan harmonization. In this work, we evaluate deep learning (neural style transfer, CycleGAN and CGAN), histogram matching, and statistical (ComBat and LongComBat) methods.