In Vivo Detection of Changes Related to Cortical Columnar Organization and Neuroinflammation Across the AD Continuum.

BACKGROUND: Alzheimer's disease (AD) neuropathology reveals progressive microstructural alterations of cortical architecture. Recent studies reported intriguing biphasic trajectories of cortical structural changes in the early stages of Alzheimer's disease (AD), comprising decreased mean diffusivity (MD) and increased cortical thickness in cognitively normal amyloid-positive individuals, ahead of increases and decreases, respectively, in subsequent disease stages. OBJECTIVE: To better understand the cytoarchitectural correlates of these observations, we assessed novel cortical diffusion tensor imaging (DTI) metrics that are correlated with disruption of cortical minicolumns and protein deposition. DESIGN: Cross-sectional and longitudinal analysis of whole brain and temporal lobe cortical diffusivity measures. Investigation of associations between baseline cortical diffusivity values and 24-month longitudinal structural-MRI changes. Investigations of the relationships between cortical diffusivity measures and biomarkers of neuroinflammation. SETTING: Alzheimer's Disease Neuroimaging Initiative (ADNI). PARTICIPANTS: Twenty-four amyloid-negative controls (CN-), 28 amyloid-positive controls (CN+), 46 amyloid-positive subjects with mild cognitive impairment (MCI+) and 22 amyloid-positive subjects with AD were included. MEASUREMENTS: 3DT1 and DTI scans at baseline and approximately 24-month follow-up were used to calculate cortical MD and three novel cortical diffusivity measures: the angle between the radial minicolumnar axis and the principal diffusion direction (AngleR); the diffusion components perpendicular to the minicolumns (PerpPD+), and the principal diffusion component parallel with the minicolumns (ParlPD). Cortical macrostructural measurements (cortical volume fraction and cortical thickness), were used to test the hypothesis that baseline cortical diffusivity values can predict change in structural MRI outcomes over approximately 24 months. CSF soluble TREM2 and progranulin (PGRN) concentrations were used to investigate associations with microglial activity and potentially other aspects of neuroinflammation. RESULTS: Cortical diffusivity metrics revealed a dependence on disease stage, with AngleR and PerpPD+ displaying biphasic relationships and ParlPD a monotonic relationship with clinical severity. The novel metrics were able to differentiate between Amyloid+ and Amyloid- controls (AngleR) and to differentiate among disease stages along the AD continuum (PerpPD+). Linear regression revealed significant associations between baseline cortical diffusivity values and subsequent 24-month longitudinal structural-MRI changes. AngleR values were significantly associated with CSF sTREM2 and PGRN concentrations. CONCLUSIONS: Cortical diffusivity parameters reflecting minicolumnar organization and neuroinflammation may provide a sensitive and biologically interpretable measurement of cortex quality and microstructure across the AD continuum.

Estimating anatomical trajectories with Bayesian mixed-effects modeling.

We introduce a mass-univariate framework for the analysis of whole-brain structural trajectories using longitudinal Voxel-Based Morphometry data and Bayesian inference. Our approach to developmental and aging longitudinal studies characterizes heterogeneous structural growth/decline between and within groups. In particular, we propose a probabilistic generative model that parameterizes individual and ensemble average changes in brain structure using linear mixed-effects models of age and subject-specific covariates. Model inversion uses Expectation Maximization (EM), while voxelwise (empirical) priors on the size of individual differences are estimated from the data. Bayesian inference on individual and group trajectories is realized using Posterior Probability Maps (PPM). In addition to parameter inference, the framework affords comparisons of models with varying combinations of model order for fixed and random effects using model evidence. We validate the model in simulations and real MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) project. We further demonstrate how subject specific characteristics contribute to individual differences in longitudinal volume changes in healthy subjects, Mild Cognitive Impairment (MCI), and Alzheimer's Disease (AD).

Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects.

Structural imaging based on MRI is an integral component of the clinical assessment of patients with potential dementia. We here propose an individualized Gaussian process-based inference scheme for clinical decision support in healthy and pathological aging elderly subjects using MRI. The approach aims at quantitative and transparent support for clinicians who aim to detect structural abnormalities in patients at risk of Alzheimer's disease or other types of dementia. Firstly, we introduce a generative model incorporating our knowledge about normative decline of local and global gray matter volume across the brain in elderly. By supposing smooth structural trajectories the models account for the general course of age-related structural decline as well as late-life accelerated loss. Considering healthy subjects' demography and global brain parameters as informative about normal brain aging variability affords individualized predictions in single cases. Using Gaussian process models as a normative reference, we predict new subjects' brain scans and quantify the local gray matter abnormalities in terms of Normative Probability Maps (NPM) and global z-scores. By integrating the observed expectation error and the predictive uncertainty, the local maps and global scores exploit the advantages of Bayesian inference for clinical decisions and provide a valuable extension of diagnostic information about pathological aging. We validate the approach in simulated data and real MRI data. We train the GP framework using 1238 healthy subjects with ages 18-94 years, and predict in 415 independent test subjects diagnosed as healthy controls, Mild Cognitive Impairment and Alzheimer's disease.

Multiparameter MR imaging in the 6-OPRI variant of inherited prion disease.

BACKGROUND AND PURPOSE: Inherited prion diseases represent over 15% of human prion cases and are a frequent cause of early onset dementia. The purpose of this study was to define the distribution of changes in cerebral volumetric and microstructural parenchymal tissues in a specific inherited human prion disease mutation combining VBM with VBA of cerebral MTR and MD. MATERIALS AND METHODS: VBM and VBA of cerebral MTR and MD were performed in 16 healthy control participants and 9 patients with the 6-OPRI mutation. An analysis of covariance consisting of diagnostic grouping with age and total intracranial volume as covariates was performed. RESULTS: On VBM, there was a significant reduction in gray matter volume in patients compared with control participants in the basal ganglia, perisylvian cortex, lingual gyrus, and precuneus. Significant MTR reduction and MD increases were more anatomically extensive than volume differences on VBM in the same cortical areas, but MTR and MD changes were not seen in the basal ganglia. CONCLUSIONS: Gray matter and WM changes were seen in brain areas associated with motor and cognitive functions known to be impaired in patients with the 6-OPRI mutation. There were some differences in the anatomic distribution of MTR-VBA and MD-VBA changes compared with VBM, likely to reflect regional variations in the type and degree of the respective pathophysiologic substrates. Combined analysis of complementary multiparameter MR imaging data furthers our understanding of prion disease pathophysiology.

Distinct neuropsychological profiles correspond to distribution of cortical thinning in inherited prion disease caused by insertional mutation.

BACKGROUND: The human prion diseases are a group of universally fatal neurodegenerative disorders associated with the auto-catalytic misfolding of the normal cell surface prion protein (PrP). Mutations causative of inherited human prion disease (IPD) include an insertion of six additional octapeptide repeats (6-OPRI) and a missense mutation (P102L) with large families segregating for each mutation residing in southern England. Here we report for the first time the neuropsychological and clinical assessments in these two groups. METHOD: The cognitive profiles addressing all major domains were obtained for 26 patients (18 6-OPRI, 8 P102L) and the cortical thickness determined using 1.5T MRI in a subset of 10 (six 6-OPRI, four P102L). RESULTS: The cognitive profiles were different in patients with the two mutations in the symptomatic phase of the disease. The 6-OPRI group had lower premorbid optimal levels of functioning (assessed on the NART) than the P102L group. In the symptomatic phase of the disease the 6-OPRI patients had significantly more executive dysfunction than the P102L group and were more impaired on tests of perception and nominal functions. There was anecdotal evidence of low premorbid social performance in the 6-OPRI but not P102L patients. Cortical thinning distribution correlated with the neuropsychological profile in the 6-OPRI group principally involving the parietal, occipital and posterior frontal regions. The small number of patients in the P102L group precluded statistical comparison between the groups. CONCLUSIONS: The 6-OPRI patients had more widespread and severe cognitive dysfunction than the P102L group and this correlated with cortical thinning distribution.

Pitfalls in the use of voxel-based morphometry as a biomarker: examples from huntington disease.

BACKGROUND AND PURPOSE: VBM is increasingly used in the study of neurodegeneration, and recently there has been interest in its potential as a biomarker. However, although it is largely "automated," VBM is rarely implemented consistently across studies, and changing user-specified options can alter the results in a way similar to the very biologic differences under investigation. MATERIALS AND METHODS: This work uses data from patients with HD to demonstrate the effects of several user-specified VBM parameters and analyses: type and level of statistical correction, modulation, smoothing kernel size, adjustment for brain size, subgroup analysis, and software version. RESULTS: The results demonstrate that changing these options can alter results in a way similar to the biologic differences under investigation. CONCLUSIONS: If VBM is to be useful clinically or considered for use as a biomarker, there is a need for greater recognition of these issues and more uniformity in its application for the method to be both reproducible and valid.

Patterns of cortical thinning in the language variants of frontotemporal lobar degeneration.

BACKGROUND: Frontotemporal lobar degeneration (FTLD) is a clinically, genetically, and pathologically heterogeneous neurodegenerative disorder. Two subtypes commonly present with a language disorder: semantic dementia (SemD) and progressive nonfluent aphasia (PNFA). METHODS: Patients meeting consensus criteria for PNFA and SemD who had volumetric MRI of sufficient quality to allow cortical thickness analysis were recruited from a tertiary referral clinic: 44 (11 pathologically confirmed) patients with SemD and 32 (4 pathologically confirmed) patients with PNFA and 29 age-matched and gender-matched healthy controls were recruited. Cortical thickness analysis was performed using the Freesurfer software tools. RESULTS: Patients with SemD had significant cortical thinning in the left temporal lobe, particularly temporal pole, entorhinal cortex, and parahippocampal, fusiform, and inferior temporal gyri. A similar but less extensive pattern of loss was seen in the right temporal lobe and (with increasing severity) also in left orbitofrontal, inferior frontal, insular, and cingulate cortices. Patients with PNFA had involvement particularly of the left superior temporal lobe, inferior frontal lobe, and insula, and (with increasing severity) other areas in the left frontal, lateral temporal, and anterior parietal lobes. Similar patterns were seen in the pathologically confirmed cases. Patterns of cortical thinning differed between groups: SemD had significantly more cortical thinning in the temporal lobes bilaterally while PNFA had significantly more thinning in the frontal and parietal lobes. CONCLUSIONS: The language variants of frontotemporal lobar degeneration have distinctive and significantly different patterns of cortical thinning. Increasing disease severity is associated with spread of cortical thinning and the pattern of spread is consistent with progression of clinical deficits.