Ian B. Malone

Magnetic resonance imaging evidence for presymptomatic change in thalamus and caudate in familial Alzheimer's disease.

Amyloid imaging studies of presymptomatic familial Alzheimer’s disease have revealed the striatum and thalamus to be the earliest sites of amyloid deposition. This study aimed to investigate whether there are associated volume and diffusivity changes in these subcortical structures during the presymptomatic and symptomatic stages of familial Alzheimer’s disease. As the thalamus and striatum are involved in neural networks subserving complex cognitive and behavioural functions, we also examined the diffusion characteristics in connecting white matter tracts. A cohort of 20 presenilin 1 mutation carriers underwent volumetric and diffusion tensor magnetic resonance imaging, neuropsychological and clinical assessments; 10 were symptomatic, 10 were presymptomatic and on average 5.6 years younger than their expected age at onset; 20 healthy control subjects were also studied. We conducted region of interest analyses of volume and diffusivity changes in the thalamus, caudate, putamen and hippocampus and examined diffusion behaviour in the white matter tracts of interest (fornix, cingulum and corpus callosum). Voxel-based morphometry and tract-based spatial statistics were also used to provide unbiased whole-brain analyses of group differences in volume and diffusion indices, respectively. We found that reduced volumes of the left thalamus and bilateral caudate were evident at a presymptomatic stage, together with increased fractional anisotropy of bilateral thalamus and left caudate. Although no significant hippocampal volume loss was evident presymptomatically, reduced mean diffusivity was observed in the right hippocampus and reduced mean and axial diffusivity in the right cingulum. In contrast, symptomatic mutation carriers showed increased mean, axial and in particular radial diffusivity, with reduced fractional anisotropy, in all of the white matter tracts of interest. The symptomatic group also showed atrophy and increased mean diffusivity in all of the subcortical grey matter regions of interest, with increased fractional anisotropy in bilateral putamen. We propose that axonal injury may be an early event in presymptomatic Alzheimer’s disease, causing an initial fall in axial and mean diffusivity, which then increases with loss of axonal density. The selective degeneration of long-coursing white matter tracts, with relative preservation of short interneurons, may account for the increase in fractional anisotropy that is seen in the thalamus and caudate presymptomatically. It may be owing to their dense connectivity that imaging changes are seen first in the thalamus and striatum, which then progress to involve other regions in a vulnerable neuronal network.

Accurate automatic estimation of total intracranial volume: a nuisance variable with less nuisance.

Total intracranial volume (TIV/ICV) is an important covariate for volumetric analyses of the brain and brain regions, especially in the study of neurodegenerative diseases, where it can provide a proxy of maximum pre-morbid brain volume. The gold-standard method is manual delineation of brain scans, but this requires careful work by trained operators. We evaluated Statistical Parametric Mapping 12 (SPM12) automated segmentation for TIV measurement in place of manual segmentation and also compared it with SPM8 and FreeSurfer 5.3.0. For T1-weighted MRI acquired from 288 participants in a multi-centre clinical trial in Alzheimers disease we find a high correlation between SPM12 TIV and manual TIV (R2 = 0.940, 95% Confidence Interval (0.924, 0.953)), with a small mean difference (SPM12 40.4 ± 35.4 ml lower than manual, amounting to 2.8% of the overall mean TIV in the study). The correlation with manual measurements (the key aspect when using TIV as a covariate) for SPM12 was significantly higher (p < 0.001) than for either SPM8 (R2 = 0.577 CI (0.500, 0.644)) or FreeSurfer (R2 = 0.801 CI (0.744, 0.843)). These results suggest that SPM12 TIV estimates are an acceptable substitute for labour-intensive manual estimates even in the challenging context of multiple centres and the presence of neurodegenerative pathology. We also briefly discuss some aspects of the statistical modelling approaches to adjust for TIV.

Attenuation Correction Methods Suitable for Brain Imaging with a PET/MRI Scanner: A Comparison of Tissue Atlas and Template Attenuation Map Approaches

Modeled attenuation correction (AC) will be necessary for combined PET/MRI scanners not equipped with transmission scanning hardware. We compared 2 modeled AC approaches that use nonrigid registration with rotating 68Ge rod–based measured AC for 10 subjects scanned with 18F-FDG. Methods: Two MRI and attenuation map pairs were evaluated: tissue atlas–based and measured templates. The tissue atlas approach used a composite of the BrainWeb and Zubal digital phantoms, whereas the measured templates were produced by averaging spatially normalized measured MR image and coregistered attenuation maps. The composite digital phantom was manually edited to include 2 additional tissue classes (paranasal sinuses, and ethmoidal air cells or nasal cavity). In addition, 3 attenuation values for bone were compared. The MRI and attenuation map pairs were used to generate subject-specific attenuation maps via nonrigid registration of the MRI to the MR image of the subject. SPM2 and a B-spline free-form deformation algorithm were used for the nonrigid registration. To determine the accuracy of the modeled AC approaches, radioactivity concentration was assessed on a voxelwise and regional basis. Results: The template approach produced better spatial consistency than the phantom-based atlas, with an average percentage error in radioactivity concentration across the regions, compared with measured AC, of −1.2% ± 1.2% and −1.5% ± 1.9% for B-spline and SPM2 registration, respectively. In comparison, the tissue atlas method with B-spline registration produced average percentage errors of 0.0% ± 3.0%, 0.9% ± 2.9%, and 2.9% ± 2.8% for bone attenuation values of 0.143 cm−1, 0.152 cm−1, and 0.172 cm−1, respectively. The largest errors for the template AC method were found in parts of the frontal cortex (−3%) and the cerebellar vermis (−5%). Intersubject variability was higher with SPM2 than with B-spline. Compared with measured AC, template AC with B-spline and SPM2 achieved a correlation coefficient (R2) of 0.99 and 0.98, respectively, for regional radioactivity concentration. The corresponding R2 for the tissue atlas approach with B-spline registration was 0.98, irrespective of the bone attenuation coefficient. Conclusion: Nonrigid registration of joint MRI and attenuation map templates can produce accurate AC for brain PET scans, particularly with measured templates and B-spline registration. Consequently, these methods are suitable for AC of brain scans acquired on combined PET/MRI systems.

An unbiased longitudinal analysis framework for tracking white matter changes using diffusion tensor imaging with application to Alzheimer's disease

We introduce a novel image-processing framework for tracking longitudinal changes in white matter microstructure using diffusion tensor imaging (DTI). Charting the trajectory of such temporal changes offers new insight into disease progression but to do so accurately faces a number of challenges. Recent developments have highlighted the importance of processing each subjects data at multiple time points in an unbiased way. In this paper, we aim to highlight a different challenge critical to the processing of longitudinal DTI data, namely the approach to image alignment. Standard approaches in the literature align DTI data by registering the corresponding scalar-valued fractional anisotropy (FA) maps. We propose instead a DTI registration algorithm that leverages full tensor information to drive improved alignment. This proposed pipeline is evaluated against the standard FA-based approach using a DTI dataset from an ongoing study of Alzheimers disease (AD). The dataset consists of subjects scanned at two time points and at each time point the DTI acquisition consists of two back-to-back repeats in the same scanning session. The repeated scans allow us to evaluate the specificity of each pipeline, using a test-retest design, and assess precision, using bootstrap-based method. The results show that the tensor-based pipeline achieves both higher specificity and precision than the standard FA-based approach. Tensor-based registration for longitudinal processing of DTI data in clinical studies may be of particular value in studies assessing disease progression.

White matter tract signatures of the progressive aphasias.

The primary progressive aphasias (PPA) are a heterogeneous group of language-led neurodegenerative diseases resulting from large-scale brain network degeneration. White matter (WM) pathways bind networks together, and might therefore hold information about PPA pathogenesis. Here we used diffusion tensor imaging and tract-based spatial statistics to compare WM tract changes between PPA syndromes and with respect to Alzheimers disease and healthy controls in 33 patients with PPA (13 nonfluent/agrammatic PPA); 10 logopenic variant PPA; and 10 semantic variant PPA. Nonfluent/agrammatic PPA was associated with predominantly left-sided and anterior tract alterations including uncinate fasciculus (UF) and subcortical projections; semantic variant PPA with bilateral alterations in inferior longitudinal fasciculus and UF; and logopenic variant PPA with bilateral but predominantly left-sided alterations in inferior longitudinal fasciculus, UF, superior longitudinal fasciculus, and subcortical projections. Tract alterations were more extensive than gray matter alterations, and the extent of alteration across tracts and PPA syndromes varied between diffusivity metrics. These WM signatures of PPA syndromes illustrate the selective vulnerability of brain language networks in these diseases and might have some pathologic specificity.

Profiles of White Matter Tract Pathology in Frontotemporal Dementia

Despite considerable interest in improving clinical and neurobiological characterisation of frontotemporal dementia and in defining the role of brain network disintegration in its pathogenesis, information about white matter pathway alterations in frontotemporal dementia remains limited. Here we investigated white matter tract damage using an unbiased, template‐based diffusion tensor imaging (DTI) protocol in a cohort of 27 patients with the behavioral variant of frontotemporal dementia (bvFTD) representing both major genetic and sporadic forms, in relation both to healthy individuals and to patients with Alzheimers disease. Widespread white matter tract pathology was identified in the bvFTD group compared with both healthy controls and Alzheimers disease group, with prominent involvement of uncinate fasciculus, cingulum bundle and corpus callosum. Relatively discrete and distinctive white matter profiles were associated with genetic subgroups of bvFTD associated with MAPT and C9ORF72 mutations. Comparing diffusivity metrics, optimal overall separation of the bvFTD group from the healthy control group was signalled using radial diffusivity, whereas optimal overall separation of the bvFTD group from the Alzheimers disease group was signalled using fractional anisotropy. Comparing white matter changes with regional grey matter atrophy (delineated using voxel based morphometry) in the bvFTD cohort revealed co‐localisation between modalities particularly in the anterior temporal lobe, however white matter changes extended widely beyond the zones of grey matter atrophy. Our findings demonstrate a distributed signature of white matter alterations that is likely to be core to the pathophysiology of bvFTD and further suggest that this signature is modulated by underlying molecular pathologies. Hum Brain Mapp 35:4163–4179, 2014.

The Importance of Group-Wise Registration in Tract Based Spatial Statistics Study of Neurodegeneration: A Simulation Study in Alzheimer's Disease

Tract-based spatial statistics (TBSS) is a popular method for the analysis of diffusion tensor imaging data. TBSS focuses on differences in white matter voxels with high fractional anisotropy (FA), representing the major fibre tracts, through registering all subjects to a common reference and the creation of a FA skeleton. This work considers the effect of choice of reference in the TBSS pipeline, which can be a standard template, an individual subject from the study, a study-specific template or a group-wise average. While TBSS attempts to overcome registration error by searching the neighbourhood perpendicular to the FA skeleton for the voxel with maximum FA, this projection step may not compensate for large registration errors that might occur in the presence of pathology such as atrophy in neurodegenerative diseases. This makes registration performance and choice of reference an important issue. Substantial work in the field of computational anatomy has shown the use of group-wise averages to reduce biases while avoiding the arbitrary selection of a single individual. Here, we demonstrate the impact of the choice of reference on: (a) specificity (b) sensitivity in a simulation study and (c) a real-world comparison of Alzheimers disease patients to controls. In (a) and (b), simulated deformations and decreases in FA were applied to control subjects to simulate changes of shape and WM integrity similar to what would be seen in AD patients, in order to provide a “ground truth” for evaluating the various methods of TBSS reference. Using a group-wise average atlas as the reference outperformed other references in the TBSS pipeline in all evaluations.

The pattern of atrophy in familial Alzheimer disease Volumetric MRI results from the DIAN study

Objective: To assess regional patterns of gray and white matter atrophy in familial Alzheimer disease (FAD) mutation carriers. Methods: A total of 192 participants with volumetric T1-weighted MRI, genotyping, and clinical diagnosis were available from the Dominantly Inherited Alzheimer Network. Of these, 69 were presymptomatic mutation carriers, 50 were symptomatic carriers (31 with Clinical Dementia Rating [CDR] = 0.5, 19 with CDR > 0.5), and 73 were noncarriers from the same families. Voxel-based morphometry was used to identify cross-sectional group differences in gray matter and white matter volume. Results: Significant differences in gray matter (p < 0.05, family-wise error–corrected) were observed between noncarriers and mildly symptomatic (CDR = 0.5) carriers in the thalamus and putamen, as well as in the temporal lobe, precuneus, and cingulate gyrus; the same pattern, but with more extensive changes, was seen in those with CDR > 0.5. Significant white matter differences between noncarriers and symptomatic carriers were observed in the cingulum and fornix; these form input and output connections to the medial temporal lobe, cingulate, and precuneus. No differences between noncarriers and presymptomatic carriers survived correction for multiple comparisons, but there was a trend for decreased gray matter in the thalamus for carriers closer to their estimated age at onset. There were no significant increases of gray or white matter in asymptomatic or symptomatic carriers compared to noncarriers. Conclusions: Atrophy in FAD is observed early, both in areas commonly associated with sporadic Alzheimer disease and also in the putamen and thalamus, 2 regions associated with early amyloid deposition in FAD mutation carriers.

Vascular and Alzheimer's disease markers independently predict brain atrophy rate in Alzheimer's Disease Neuroimaging Initiative controls

This study assessed relationships among white matter hyperintensities (WMH), cerebrospinal fluid (CSF), Alzheimers disease (AD) pathology markers, and brain volume loss. Subjects included 197 controls, 331 individuals with mild cognitive impairment (MCI), and 146 individuals with AD with serial volumetric 1.5-T MRI. CSF Aβ1-42 (n = 351) and tau (n = 346) were measured. Brain volume change was quantified using the boundary shift integral (BSI). We assessed the association between baseline WMH volume and annualized BSI, adjusting for intracranial volume. We also performed multiple regression analyses in the CSF subset, assessing the relationships of WMH and Aβ1-42 and/or tau with BSI. WMH burden was positively associated with BSI in controls (p = 0.02) but not MCI or AD. In multivariable models, WMH (p = 0.003) and Aβ1-42 (p = 0.001) were independently associated with BSI in controls; in MCI Aβ1-42 (p < 0.001) and tau (p = 0.04) were associated with BSI. There was no evidence of independent effects of WMH or CSF measures on BSI in AD. These data support findings that vascular damage is associated with increased brain atrophy in the context of AD pathology in pre-dementia stages.

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2

Alzheimers 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 Alzheimers disease (AD) and related disorders.