Manja Lehmann

Fast free-form deformation using graphics processing units

A large number of algorithms have been developed to perform non-rigid registration and it is a tool commonly used in medical image analysis. The free-form deformation algorithm is a well-established technique, but is extremely time consuming. In this paper we present a parallel-friendly formulation of the algorithm suitable for graphics processing unit execution. Using our approach we perform registration of T1-weighted MR images in less than 1 min and show the same level of accuracy as a classical serial implementation when performing segmentation propagation. This technology could be of significant utility in time-critical applications such as image-guided interventions, or in the processing of large data sets.

Posterior cortical atrophy

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome that is characterised by progressive decline in visuospatial, visuoperceptual, literacy, and praxic skills. The progressive neurodegeneration affecting parietal, occipital, and occipitotemporal cortices that underlies PCA is attributable to Alzheimers disease in most patients. However, alternative underlying causes, including dementia with Lewy bodies, corticobasal degeneration, and prion disease, have also been identified, and not all patients with PCA have atrophy on clinical imaging. This heterogeneity has led to inconsistencies in diagnosis and terminology and difficulties in comparing studies from different centres, and has restricted the generalisability of findings from clinical trials and investigations of factors that drive phenotypic variability. Important challenges remain, including the identification of factors associated not only with the selective vulnerability of posterior cortical regions but also with the young age of onset of PCA. Greater awareness of the syndrome and agreement over the correspondence between syndrome-level and disease-level classifications are needed to improve diagnostic accuracy, clinical management, and the design of research studies.

Head size, age and gender adjustment in MRI studies: a necessary nuisance?

Imaging studies of cerebral volumes often adjust for factors such as age that may confound between-subject comparisons. However the use of nuisance covariates in imaging studies is inconsistent, which can make interpreting results across studies difficult. Using magnetic resonance images of 78 healthy controls we assessed the effects of age, gender, head size and scanner upgrade on region of interest (ROI) volumetry, cortical thickness and voxel-based morphometric (VBM) measures. We found numerous significant associations between these variables and volumetric measures: cerebral volumes and cortical thicknesses decreased with increasing age, men had larger volumes and smaller thicknesses than women, and increasing head size was associated with larger volumes. The relationships between most ROIs and head size volumes were non-linear. With age, gender, head size and upgrade in one model we found that volumes and thicknesses decreased with increasing age, women had larger volumes than men (VBM, whole-brain and white matter volumes), increasing head size was associated with larger volumes but not cortical thickness, and scanner upgrade had an effect on thickness and some volume measures. The effects of gender on cortical thickness when adjusting for head size, age and upgrade showed some non-significant effect (women>men), whereas the independent effect of head size showed little pattern. We conclude that age and head size should be considered in ROI volume studies, age, gender and upgrade should be considered for cortical thickness studies and all variables require consideration for VBM analyses. Division of all volumes by head size is unlikely to be adequate owing to their non-proportional relationship.

Diverging patterns of amyloid deposition and hypometabolism in clinical variants of probable Alzheimer’s disease

The factors driving clinical heterogeneity in Alzheimers disease are not well understood. This study assessed the relationship between amyloid deposition, glucose metabolism and clinical phenotype in Alzheimers disease, and investigated how these relate to the involvement of functional networks. The study included 17 patients with early-onset Alzheimers disease (age at onset <65 years), 12 patients with logopenic variant primary progressive aphasia and 13 patients with posterior cortical atrophy [whole Alzheimers disease group: age = 61.5 years (standard deviation 6.5 years), 55% male]. Thirty healthy control subjects [age = 70.8 (3.3) years, 47% male] were also included. Subjects underwent positron emission tomography with (11)C-labelled Pittsburgh compound B and (18)F-labelled fluorodeoxyglucose. All patients met National Institute on Ageing-Alzheimers Association criteria for probable Alzheimers disease and showed evidence of amyloid deposition on (11)C-labelled Pittsburgh compound B positron emission tomography. We hypothesized that hypometabolism patterns would differ across variants, reflecting involvement of specific functional networks, whereas amyloid patterns would be diffuse and similar across variants. We tested these hypotheses using three complimentary approaches: (i) mass-univariate voxel-wise group comparison of (18)F-labelled fluorodeoxyglucose and (11)C-labelled Pittsburgh compound B; (ii) generation of covariance maps across all subjects with Alzheimers disease from seed regions of interest specifically atrophied in each variant, and comparison of these maps to functional network templates; and (iii) extraction of (11)C-labelled Pittsburgh compound B and (18)F-labelled fluorodeoxyglucose values from functional network templates. Alzheimers disease clinical groups showed syndrome-specific (18)F-labelled fluorodeoxyglucose patterns, with greater parieto-occipital involvement in posterior cortical atrophy, and asymmetric involvement of left temporoparietal regions in logopenic variant primary progressive aphasia. In contrast, all Alzheimers disease variants showed diffuse patterns of (11)C-labelled Pittsburgh compound B binding, with posterior cortical atrophy additionally showing elevated uptake in occipital cortex compared with early-onset Alzheimers disease. The seed region of interest covariance analysis revealed distinct (18)F-labelled fluorodeoxyglucose correlation patterns that greatly overlapped with the right executive-control network for the early-onset Alzheimers disease region of interest, the left language network for the logopenic variant primary progressive aphasia region of interest, and the higher visual network for the posterior cortical atrophy region of interest. In contrast, (11)C-labelled Pittsburgh compound B covariance maps for each region of interest were diffuse. Finally, (18)F-labelled fluorodeoxyglucose was similarly reduced in all Alzheimers disease variants in the dorsal and left ventral default mode network, whereas significant differences were found in the right ventral default mode, right executive-control (both lower in early-onset Alzheimers disease and posterior cortical atrophy than logopenic variant primary progressive aphasia) and higher-order visual network (lower in posterior cortical atrophy than in early-onset Alzheimers disease and logopenic variant primary progressive aphasia), with a trend towards lower (18)F-labelled fluorodeoxyglucose also found in the left language network in logopenic variant primary progressive aphasia. There were no differences in (11)C-labelled Pittsburgh compound B binding between syndromes in any of the networks. Our data suggest that Alzheimers disease syndromes are associated with degeneration of specific functional networks, and that fibrillar amyloid-β deposition explains at most a small amount of the clinico-anatomic heterogeneity in Alzheimers disease.

Cortical thickness and voxel-based morphometry in posterior cortical atrophy and typical Alzheimer's disease

A significant minority of Alzheimers disease patients present with posterior cortical atrophy (PCA). PCA is characterized by visuospatial and visuoperceptual deficits, and relatively preserved memory, whereas patients with typical Alzheimers disease (tAD) mostly present with early episodic memory deficits. We used two unbiased image analysis techniques to assess atrophy patterns in 48 PCA, 30 tAD, and 50 healthy controls. FreeSurfer was used to measure cortical thickness, and volumetric grey matter differences were assessed using voxel-based morphometry (VBM). Both PCA and tAD showed widespread reductions compared with controls using both techniques. Direct comparison of PCA and tAD revealed thinner cortex predominantly in the right superior parietal lobe in the PCA group compared with tAD, whereas the tAD group showed thinning in the left entorhinal cortex compared with PCA. Similar results were obtained in the VBM analysis. These distinct patterns of atrophy may have diagnostic utility. In a clinical context, a relatively spared medial temporal lobe in the presence of posterior parietal atrophy may imply PCA, and should not discount AD.

Visual assessment of posterior atrophy development of a MRI rating scale

ObjectiveTo develop a visual rating scale for posterior atrophy (PA) assessment and to analyse whether this scale aids in the discrimination between Alzheimer’s disease (AD) and other dementias.MethodsMagnetic resonance imaging of 118 memory clinic patients were analysed for PA (range 0–3), medial temporal lobe atrophy (MTA) (range 0–4) and global cortical atrophy (range 0–3) by different raters. Weighted-kappas were calculated for inter- and intra-rater agreement. Relationships between PA and MTA with the MMSE and age were estimated with linear-regression analysis.ResultsIntra-rater agreement ranged between 0.93 and 0.95 and inter-rater agreement between 0.65 and 0.84. Mean PA scores were higher in AD compared to controls (1.6 ± 0.9 and 0.6 ± 0.7, p < 0.01), and other dementias (0.8 ± 0.8, p < 0.01). PA was not associated with age compared to MTA (B = 1.1 (0.8) versus B = 3.1 (0.7), p < 0.01)). PA and MTA were independently negatively associated with the MMSE (B = −1.6 (0.5), p < 0.01 versus B = −1.4 (0.5), p < 0.01).ConclusionThis robust and reproducible scale for PA assessment conveys independent information in a clinical setting and may be useful in the discrimination of AD from other dementias.

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.

Existing Pittsburgh Compound-B positron emission tomography thresholds are too high: statistical and pathological evaluation

Amyloid-β, a hallmark of Alzheimers disease, begins accumulating up to two decades before the onset of dementia, and can be detected in vivo applying amyloid-β positron emission tomography tracers such as carbon-11-labelled Pittsburgh compound-B. A variety of thresholds have been applied in the literature to define Pittsburgh compound-B positron emission tomography positivity, but the ability of these thresholds to detect early amyloid-β deposition is unknown, and validation studies comparing Pittsburgh compound-B thresholds to post-mortem amyloid burden are lacking. In this study we first derived thresholds for amyloid positron emission tomography positivity using Pittsburgh compound-B positron emission tomography in 154 cognitively normal older adults with four complementary approaches: (i) reference values from a young control group aged between 20 and 30 years; (ii) a Gaussian mixture model that assigned each subject a probability of being amyloid-β-positive or amyloid-β-negative based on Pittsburgh compound-B index uptake; (iii) a k-means cluster approach that clustered subjects into amyloid-β-positive or amyloid-β-negative based on Pittsburgh compound-B uptake in different brain regions (features); and (iv) an iterative voxel-based analysis that further explored the spatial pattern of early amyloid-β positron emission tomography signal. Next, we tested the sensitivity and specificity of the derived thresholds in 50 individuals who underwent Pittsburgh compound-B positron emission tomography during life and brain autopsy (mean time positron emission tomography to autopsy 3.1 ± 1.8 years). Amyloid at autopsy was classified using Consortium to Establish a Registry for Alzheimers Disease (CERAD) criteria, unadjusted for age. The analytic approaches yielded low thresholds (standard uptake value ratiolow = 1.21, distribution volume ratiolow = 1.08) that represent the earliest detectable Pittsburgh compound-B signal, as well as high thresholds (standard uptake value ratiohigh = 1.40, distribution volume ratiohigh = 1.20) that are more conservative in defining Pittsburgh compound-B positron emission tomography positivity. In voxel-wise contrasts, elevated Pittsburgh compound-B retention was first noted in the medial frontal cortex, then the precuneus, lateral frontal and parietal lobes, and finally the lateral temporal lobe. When compared to post-mortem amyloid burden, low proposed thresholds were more sensitive than high thresholds (sensitivities: distribution volume ratiolow 81.0%, standard uptake value ratiolow 83.3%; distribution volume ratiohigh 61.9%, standard uptake value ratiohigh 62.5%) for CERAD moderate-to-frequent neuritic plaques, with similar specificity (distribution volume ratiolow 95.8%; standard uptake value ratiolow, distribution volume ratiohigh and standard uptake value ratiohigh 100.0%). A receiver operator characteristic analysis identified optimal distribution volume ratio (1.06) and standard uptake value ratio (1.20) thresholds that were nearly identical to the a priori distribution volume ratiolow and standard uptake value ratiolow. In summary, we found that frequently applied thresholds for Pittsburgh compound-B positivity (typically at or above distribution volume ratiohigh and standard uptake value ratiohigh) are overly stringent in defining amyloid positivity. Lower thresholds in this study resulted in higher sensitivity while not compromising specificity.

Reduced cortical thickness in the posterior cingulate gyrus is characteristic of both typical and atypical Alzheimer's disease.

Alzheimers disease (AD) and frontotemporal lobar degeneration (FTLD) can be difficult to differentiate clinically due to overlapping symptoms. Subject classification in research studies is often based on clinical rather than pathological criteria which may mean some subjects are misdiagnosed and misclassified. Recently, methods measuring cortical thickness using magnetic resonance imaging have been suggested to be effective in differentiating between clinically-defined AD and frontotemporal dementia (FTD) in addition to showing disease-related patterns of atrophy. In this study we used FreeSurfer, a freely-available and automated software tool, to measure cortical thickness in 28 pathologically-confirmed AD patients, of which 11 had a typical amnestic presentation and 17 an atypical presentation during life, 23 pathologically-confirmed FTLD subjects, and 25 healthy controls. Patients with AD pathology, irrespective of clinical diagnosis, showed reduced cortical thickness bilaterally in the medial temporal lobe, posterior cingulate gyrus, precuneus, posterior parietal lobe, and frontal pole compared with controls. We further showed that lower cortical thickness in the posterior cingulate gyrus, parietal lobe, and frontal pole is suggestive of AD pathology in patients with behavioral or language deficits. In contrast, lower cortical thickness in the anterior temporal lobe and frontal lobe is indicative of the presence of FTLD pathology in patients with a clinical presentation of FTD. Reduced cortical thickness in the posterior cingulate gyrus is characteristic of AD pathology in patients with typical and atypical clinical presentations of AD, and may assist a clinical distinction of AD pathology from FTLD pathology.

Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer’s disease

Although previous studies have emphasized the vulnerability of the default mode network (DMN) in Alzheimer’s disease (AD), little is known about the involvement of other functional networks and their relationship to clinical phenotype. To test whether clinicoanatomic heterogeneity in AD is driven by the involvement of specific networks, network connectivity was assessed in healthy subjects by seeding regions commonly and specifically atrophied in three clinical AD variants: early-onset AD (age at onset, <65 y; memory and executive deficits), logopenic variant primary progressive aphasia (language deficits), and posterior cortical atrophy (visuospatial deficits). Four-millimeter seed regions of interest were used to obtain intrinsic connectivity maps in 131 healthy controls (age, 65.5 ± 3.5 y). Atrophy patterns in independent cohorts of AD variant patients and their correspondence to connectivity networks in controls were also assessed. The connectivity maps of commonly atrophied regions of interest support posterior DMN and precuneus network involvement across AD variants, whereas seeding regions specifically atrophied in each AD variant revealed distinct, syndrome-specific connectivity patterns. Goodness-of-fit analysis of each connectivity map with network templates showed the highest correspondence between the early-onset AD seed connectivity map and anterior salience and right executive-control networks, the logopenic aphasia seed connectivity map and the language network, and the posterior cortical atrophy seed connectivity map and the higher visual network. Connectivity maps derived from controls matched regions commonly and specifically atrophied in the patients. Our findings indicate that the posterior DMN and precuneus network are commonly affected in AD variants, whereas syndrome-specific neurodegenerative patterns are driven by the involvement of specific networks outside the DMN.