The Parkinson's progression markers initiative (PPMI) - establishing a PD biomarker cohort.

Objective: The Parkinson's Progression Markers Initiative (PPMI) is an observational, international study designed to establish biomarker-defined cohorts and identify clinical, imaging, genetic, and biospecimen Parkinson's disease (PD) progression markers to accelerate disease-modifying therapeutic trials.

Methods: A total of 423 untreated PD, 196 Healthy Control (HC) and 64 SWEDD (scans without evidence of dopaminergic deficit) subjects were enrolled at 24 sites. To enroll PD subjects as early as possible following diagnosis, subjects were eligible with only asymmetric bradykinesia or tremor plus a dopamine transporter (DAT) binding deficit on SPECT imaging.

Longitudinal Change of Clinical and Biological Measures in Early Parkinson's Disease: Parkinson's Progression Markers Initiative Cohort.

Objective: The objective of this study was to assess longitudinal change in clinical and dopamine transporter imaging outcomes in early, untreated PD.

Methods: We describe 5-year longitudinal change of the MDS-UPDRS and other clinical measures using results from the Parkinson's Progression Markers Initiative, a longitudinal cohort study of early Parkinson's disease (PD) participants untreated at baseline. We also provide data on the longitudinal change in dopamine transporter 123-I Ioflupane striatal binding and correlation between the 2 measures.

Data-driven regions of interest for longitudinal change in three variants of frontotemporal lobar degeneration.

Introduction: Longitudinal imaging of neurodegenerative disorders is a potentially powerful biomarker for use in clinical trials. In Alzheimer's disease, studies have demonstrated that empirically derived regions of interest (ROIs) can provide more reliable measurement of disease progression compared with anatomically defined ROIs.

Methods: We set out to derive ROIs with optimal effect size for quantifying longitudinal change in a hypothetical clinical trial by comparing atrophy rates in 44 patients with behavioral variant of frontotemporal dementia (bvFTD), 30 with the semantic variant primary progressive aphasia (svPPA), and 26 with the nonfluent variant PPA (nfvPPA) to atrophy in 97 cognitively healthy controls.

Progression of Regional Microstructural Degeneration in Parkinson's Disease: A Multicenter Diffusion Tensor Imaging Study.

This study aimed to identify the utility of diffusion tensor imaging (DTI) in measuring the regional distribution of abnormal microstructural progression in patients with Parkinson's disease who were enrolled in the Parkinson's progression marker initiative (PPMI). One hundred and twenty two de-novo PD patients (age = 60.5±9) and 50 healthy controls (age = 60.

Diagnostic utility of ASL-MRI and FDG-PET in the behavioral variant of FTD and AD.

Objective: To compare the values of arterial spin-labeled (ASL) MRI and fluorodeoxyglucose (FDG) PET in the diagnosis of behavioral variant of frontotemporal dementia (bvFTD) and Alzheimer's disease (AD).

Methods: Partial least squares logistic regression was used to identify voxels with diagnostic value in cerebral blood flow (CBF) and cerebral metabolic rate of glucose (CMRgl) maps from patients with bvFTD ( = 32) and AD ( = 28), who were compared with each other and with cognitively normal controls (CN, = 15). Diagnostic values of these maps were compared with each other.

Progression of brain atrophy in PSP and CBS over 6 months and 1 year.

Objective: To examine the utility and reliability of volumetric MRI in measuring disease progression in the 4 repeat tauopathies, progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), to support clinical development of new tau-directed therapeutic agents.

Methods: Six- and 12-month changes in regional MRI volumes and PSP Rating Scale scores were examined in 55 patients with PSP and 33 patients with CBS (78% amyloid PET negative) compared to 30 normal controls from a multicenter natural history study. Longitudinal voxel-based morphometric analyses identified patterns of volume loss, and region-of-interest analyses examined rates of volume loss in brainstem (midbrain, pons, superior cerebellar peduncle), cortical, and subcortical regions based on previously validated atlases.

Data-driven regions of interest for longitudinal change in frontotemporal lobar degeneration.

Current research is investigating the potential utility of longitudinal measurement of brain structure as a marker of drug effect in clinical trials for neurodegenerative disease. Recent studies in Alzheimer's disease (AD) have shown that measurement of change in empirically derived regions of interest (ROIs) allows more reliable measurement of change over time compared with regions chosen a-priori based on known effects of AD on brain anatomy. Frontotemporal lobar degeneration (FTLD) is a devastating neurodegenerative disorder for which there are no approved treatments.

Progression of Microstructural Degeneration in Progressive Supranuclear Palsy and Corticobasal Syndrome: A Longitudinal Diffusion Tensor Imaging Study.

Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) are both 4 microtubule binding repeat tauopathy related disorders. Clinical trials need new biomarkers to assess the effectiveness of tau-directed therapies. This study investigated the regional distribution of longitudinal diffusion tensor imaging changes, measured by fractional anisotropy, radial and axial diffusivity over 6 months median interval, in 23 normal control subjects, 35 patients with PSP, and 25 patients with CBS.

Discriminative Power of Arterial Spin Labeling Magnetic Resonance Imaging and 18F-Fluorodeoxyglucose Positron Emission Tomography Changes for Amyloid-β-Positive Subjects in the Alzheimer's Disease Continuum.

Background: Recent studies have demonstrated that arterial spin labeling magnetic resonance imaging (ASL-MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) identify similar regional abnormalities and have comparable diagnostic accuracy in Alzheimer's disease (AD). The agreement between these modalities in the AD continuum, which is an important concept for early detection and disease monitoring, is yet unclear.

Objective: We aimed to assess the ability of the cerebral blood flow (CBF) measures from ASL-MRI and cerebral metabolic rate for glucose (CMRgl) measures from FDG-PET to distinguish amyloid-β-positive (Aβ+) subjects in the AD continuum from healthy controls.

Multimodal imaging in Alzheimer's disease: validity and usefulness for early detection.

Alzheimer's disease is a progressive neurodegenerative disease that typically manifests clinically as an isolated amnestic deficit that progresses to a characteristic dementia syndrome. Advances in neuroimaging research have enabled mapping of diverse molecular, functional, and structural aspects of Alzheimer's disease pathology in ever increasing temporal and regional detail. Accumulating evidence suggests that distinct types of imaging abnormalities related to Alzheimer's disease follow a consistent trajectory during pathogenesis of the disease, and that the first changes can be detected years before the disease manifests clinically.

Diffusion imaging of nigral alterations in early Parkinson's disease with dopaminergic deficits.

Background: This study reports the baseline characteristics of diffusion tensor imaging data in Parkinson's disease (PD) patients and healthy control subjects from the Parkinson's Progression Markers Initiative. The main goals were to replicate previous findings of abnormal diffusion imaging values from the substantia nigra. in a large multicenter cohort and determine whether nigral diffusion alterations are associated with dopamine deficits.

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2.

Introduction: Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders.

Methods: We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2).

Amyloid in dementia associated with familial FTLD: not an innocent bystander.

Patients with frontotemporal lobar degeneration (FTLD) can show superimposed amyloid pathology, though the impact of amyloid on the clinical presentation of FTLD is not well characterized. This cross-sectional case-control study compared clinical features, fluorodeoxyglucose-positron emission tomography metabolism and gray matter volume loss in 30 patients with familial FTLD in whom amyloid status was confirmed with autopsy or Pittsburgh compound B-PET. Compared to the amyloid-negative patients, the amyloid-positive patients performed significantly worse on several cognitive tests and showed hypometabolism and volume loss in more temporoparietal regions.

Diffusion tensor imaging of the nigrostriatal fibers in Parkinson's disease.

Background: Parkinson's disease (PD) is histopathologically characterized by the loss of dopamine neurons in the substantia nigra pars compacta. The depletion of these neurons is thought to reduce the dopaminergic function of the nigrostriatal pathway, as well as the neural fibers that link the substantia nigra to the striatum (putamen and caudate), causing a dysregulation in striatal activity that ultimately leads to lack of movement control. Based on diffusion tensor imaging, visualizing this pathway and measuring alterations of the fiber integrity remain challenging.

Directed network motifs in Alzheimer's disease and mild cognitive impairment.

Directed network motifs are the building blocks of complex networks, such as human brain networks, and capture deep connectivity information that is not contained in standard network measures. In this paper we present the first application of directed network motifs in vivo to human brain networks, utilizing recently developed directed progression networks which are built upon rates of cortical thickness changes between brain regions. This is in contrast to previous studies which have relied on simulations and in vitro analysis of non-human brains.

Bayesian segmentation of brainstem structures in MRI.

In this paper we present a method to segment four brainstem structures (midbrain, pons, medulla oblongata and superior cerebellar peduncle) from 3D brain MRI scans. The segmentation method relies on a probabilistic atlas of the brainstem and its neighboring brain structures. To build the atlas, we combined a dataset of 39 scans with already existing manual delineations of the whole brainstem and a dataset of 10 scans in which the brainstem structures were manually labeled with a protocol that was specifically designed for this study.

Quantitative framework for prospective motion correction evaluation.

Purpose: Establishing a framework to evaluate performances of prospective motion correction (PMC) MRI considering motion variability between MRI scans.

Methods: A framework was developed to obtain quantitative comparisons between different motion correction setups, considering that varying intrinsic motion patterns between acquisitions can induce bias. Intrinsic motion was considered by replaying in a phantom experiment the recorded motion trajectories from subjects.

A fast algorithm for denoising magnitude diffusion-weighted images with rank and edge constraints.

Purpose: To accelerate denoising of magnitude diffusion-weighted images subject to joint rank and edge constraints.

Methods: We extend a previously proposed majorize-minimize method for statistical estimation that involves noncentral χ distributions to incorporate joint rank and edge constraints. A new algorithm is derived which decomposes the constrained noncentral χ denoising problem into a series of constrained Gaussian denoising problems each of which is then solved using an efficient alternating minimization scheme.

Sensitive measures of executive dysfunction in non-demented Parkinson's disease.

Background: We examined the sensitivity of different executive function measures for detecting deficits in Parkinson's disease patients without dementia.

Methods: Twenty-one non-demented PD subjects and 21 neurologically healthy controls were administered widely used clinical executive functioning measures as well as the NIH EXAMINER battery, which produces Cognitive Control, Working Memory, and Verbal Fluency scores, along with an overall Executive Composite score, using psychometrically matched scales.

Results: No significant differences between groups were observed on widely used clinical measures.

Variables associated with hippocampal atrophy rate in normal aging and mild cognitive impairment.

The goal of this study was to identify factors contributing to hippocampal atrophy rate (HAR) in clinically normal older adults (NC) and participants with mild cognitive impairment (MCI). Longitudinal HAR was measured on T1-weighted magnetic resonance imaging, and the contribution of age, gender, apolipoprotein E (ApoE) ε4 status, intracranial volume, white matter lesions, and β-amyloid (Aβ) levels to HAR was determined using linear regression. Age-related effects of HAR were compared in Aβ positive (Aβ+) and Aβ negative (Aβ-) participants.

Directed progression brain networks in Alzheimer's disease: properties and classification.

This article introduces a new approach in brain connectomics aimed at characterizing the temporal spread in the brain of pathologies like Alzheimer's disease (AD). The main instrument is the development of "directed progression networks" (DPNets), wherein one constructs directed edges between nodes based on (weakly) inferred directions of the temporal spreading of the pathology. This stands in contrast to many previously studied brain networks where edges represent correlations, physical connections, or functional progressions.

Association of brain amyloid-β with cerebral perfusion and structure in Alzheimer's disease and mild cognitive impairment.

Patients with Alzheimer's disease have reduced cerebral blood flow measured by arterial spin labelling magnetic resonance imaging, but it is unclear how this is related to amyloid-β pathology. Using 182 subjects from the Alzheimer's Disease Neuroimaging Initiative we tested associations of amyloid-β with regional cerebral blood flow in healthy controls (n = 51), early (n = 66) and late (n = 41) mild cognitive impairment, and Alzheimer's disease with dementia (n = 24). Based on the theory that Alzheimer's disease starts with amyloid-β accumulation and progresses with symptoms and secondary pathologies in different trajectories, we tested if cerebral blood flow differed between amyloid-β-negative controls and -positive subjects in different diagnostic groups, and if amyloid-β had different associations with cerebral blood flow and grey matter volume.

Reduced FDG-PET brain metabolism and executive function predict clinical progression in elderly healthy subjects.

Brain changes reminiscent of Alzheimer disease (AD) have been previously reported in a substantial portion of elderly cognitive healthy (HC) subjects. The major aim was to evaluate the accuracy of MRI assessed regional gray matter (GM) volume, 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), and neuropsychological test scores to identify those HC subjects who subsequently convert to mild cognitive impairment (MCI) or AD dementia. We obtained in 54 healthy control (HC) subjects a priori defined region of interest (ROI) values of medial temporal and parietal FDG-PET and medial temporal GM volume.

Numerical modeling of susceptibility-related MR signal dephasing with vessel size measurement: phantom validation at 3T.

Purpose: MRI is used to obtain quantitative oxygenation and blood volume information from the susceptibility-related MR signal dephasing induced by blood vessels. However, analytical models that fit the MR signal are usually not accurate over the range of small blood vessels. Moreover, recent studies have demonstrated limitations in the simultaneous assessment of oxygenation and blood volume.

Locally linear embedding (LLE) for MRI based Alzheimer's disease classification.

Modern machine learning algorithms are increasingly being used in neuroimaging studies, such as the prediction of Alzheimer's disease (AD) from structural MRI. However, finding a good representation for multivariate brain MRI features in which their essential structure is revealed and easily extractable has been difficult. We report a successful application of a machine learning framework that significantly improved the use of brain MRI for predictions.