Stephen E. Rose

Dynamics of Gray Matter Loss in Alzheimer's Disease

We detected and mapped a dynamically spreading wave of gray matter loss in the brains of patients with Alzheimers disease (AD). The loss pattern was visualized in four dimensions as it spread over time from temporal and limbic cortices into frontal and occipital brain regions, sparing sensorimotor cortices. The shifting deficits were asymmetric (left hemisphere > right hemisphere) and correlated with progressively declining cognitive status (p< 0.0006). Novel brain mapping methods allowed us to visualize dynamic patterns of atrophy in 52 high-resolution magnetic resonance image scans of 12 patients with AD (age 68.4 ± 1.9 years) and 14 elderly matched controls (age 71.4 ± 0.9 years) scanned longitudinally (two scans; interscan interval 2.1 ± 0.4 years). A cortical pattern matching technique encoded changes in brain shape and tissue distribution across subjects and time. Cortical atrophy occurred in a well defined sequence as the disease progressed, mirroring the sequence of neurofibrillary tangle accumulation observed in cross sections at autopsy. Advancing deficits were visualized as dynamic maps that change over time. Frontal regions, spared early in the disease, showed pervasive deficits later (>15% loss). The maps distinguished different phases of AD and differentiated AD from normal aging. Local gray matter loss rates (5.3 ± 2.3% per year in AD v 0.9 ± 0.9% per year in controls) were faster in the left hemisphere (p < 0.029) than the right. Transient barriers to disease progression appeared at limbic/frontal boundaries. This degenerative sequence, observed in vivo as it developed, provides the first quantitative, dynamic visualization of cortical atrophic rates in normal elderly populations and in those with dementia.

Mapping hippocampal and ventricular change in Alzheimer disease

We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Sixty-two [corrected] high-resolution MRI scans were acquired from 12 AD patients (mean [corrected] age +/- SE at first scan: 68.7 +/- 1.7 [corrected] years) and 14 matched controls (age: 71.4 +/- 0.9 years) [corrected] each scanned twice (1.9 +/- 0.2 [corrected] years apart, when all subjects are pooled [corrected] 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

Loss of connectivity in Alzheimer's disease: an evaluation of white matter tract integrity with colour coded MR diffusion tensor imaging

A NOVEL MRI METHOD diffusion tensor imaging—was used to compare the integrity of several white matter fibre tracts in patients with probable Alzheimers disease. Relative to normal controls, patients with probable Alzheimers disease showed a highly significant reduction in the integrity of the association white matter fibre tracts, such as the splenium of the corpus callosum, superior longitudinal fasciculus, and cingulum. By contrast, pyramidal tract integrity seemed unchanged. This novel finding is consistent with the clinical presentation of probable Alzheimers disease, in which global cognitive decline is a more prominent feature than motor disturbance.

Diffusion- and perfusion-weighted MRI response to thrombolysis in Stroke

Diffusion‐ and perfusion‐weighted magnetic resonance imaging provides important pathophysiological information in acute brain ischemia. We performed a prospective study in 19 sub‐6‐hour stroke patients using serial diffusion‐ and perfusion‐weighted imaging before intravenous thrombolysis, with repeat studies, both subacutely and at outcome. For comparison of ischemic lesion evolution and clinical outcome, we used a historical control group of 21 sub‐6‐hour ischemic stroke patients studied serially with diffusion‐ and perfusion‐weighted imaging. The two groups were well matched for the baseline National Institutes of Health Stroke Scale and magnetic resonance parameters. Perfusion‐weighted imaging–diffusion‐weighted imaging mismatch was present in 16 of 19 patients treated with tissue plasminogen activator, and 16 of 21 controls. Perfusion‐weighted imaging–diffusion‐weighted imaging mismatch patients treated with tissue plaminogen activator had higher recanalization rates and enhanced reperfusion at day 3 (81% vs 47% in controls), and a greater proportion of severely hypoperfused acute mismatch tissue not progressing to infarction (82% vs −25% in controls). Despite similar baseline diffusion‐weighted imaging lesions, infarct expansion was less in the recombinant tissue plaminogen activator group (14cm3 vs 56cm3 in controls). The positive effect of thrombolysis on lesion growth in mismatch patients translated into a greater improvement in baseline to outcome National Institutes of Health Stroke Scale in the group treated with recombinant tissue plaminogen activator, and a significantly larger proportion of patients treated with recombinant tissue plaminogen activator having a clinically meaningful improvement in National Institutes of Health Stroke Scale of ≥7 points. The natural evolution of acute perfusion‐weighted imaging–diffusion‐weighted imaging mismatch tissue may be altered by thrombolysis, with improved stroke outcome. This has implications for the use of diffusion‐ and perfusion‐weighted imaging in selecting and monitoring patients for thrombolytic therapy.

Apparent Fibre Density: a novel measure for the analysis of diffusion-weighted magnetic resonance images.

This article proposes a new measure called Apparent Fibre Density (AFD) for the analysis of high angular resolution diffusion-weighted images using higher-order information provided by fibre orientation distributions (FODs) computed using spherical deconvolution. AFD has the potential to provide specific information regarding differences between populations by identifying not only the location, but also the orientations along which differences exist. In this work, analytical and numerical Monte-Carlo simulations are used to support the use of the FOD amplitude as a quantitative measure (i.e. AFD) for population and longitudinal analysis. To perform robust voxel-based analysis of AFD, we present and evaluate a novel method to modulate the FOD to account for changes in fibre bundle cross-sectional area that occur during spatial normalisation. We then describe a novel approach for statistical analysis of AFD that uses cluster-based inference of differences extended throughout space and orientation. Finally, we demonstrate the capability of the proposed method by performing voxel-based AFD comparisons between a group of Motor Neurone Disease patients and healthy control subjects. A significant decrease in AFD was detected along voxels and orientations corresponding to both the corticospinal tract and corpus callosal fibres that connect the primary motor cortices. In addition to corroborating previous findings in MND, this study demonstrates the clear advantage of using this type of analysis by identifying differences along single fibre bundles in regions containing multiple fibre populations.

Diffusion indices on magnetic resonance imaging and neuropsychological performance in amnestic mild cognitive impairment

Background: Magnetic resonance diffusion tensor imaging (DTI) shows promise in the early detection of microstructural pathophysiological changes in the brain. Objectives: To measure microstructural differences in the brains of participants with amnestic mild cognitive impairment (MCI) compared with an age-matched control group using an optimised DTI technique with fully automated image analysis tools and to investigate the correlation between diffusivity measurements and neuropsychological performance scores across groups. Methods: 34 participants (17 participants with MCI, 17 healthy elderly adults) underwent magnetic resonance imaging (MRI)-based DTI. To control for the effects of anatomical variation, diffusion images of all participants were registered to standard anatomical space. Significant statistical differences in diffusivity measurements between the two groups were determined on a pixel-by-pixel basis using gaussian random field theory. Results: Significantly raised mean diffusivity measurements (p<0.001) were observed in the left and right entorhinal cortices (BA28), posterior occipital–parietal cortex (BA18 and BA19), right parietal supramarginal gyrus (BA40) and right frontal precentral gyri (BA4 and BA6) in participants with MCI. With respect to fractional anisotropy, participants with MCI had significantly reduced measurements (p<0.001) in the limbic parahippocampal subgyral white matter, right thalamus and left posterior cingulate. Pearson’s correlation coefficients calculated across all participants showed significant correlations between neuropsychological assessment scores and regional measurements of mean diffusivity and fractional anisotropy. Conclusions: DTI-based diffusivity measures may offer a sensitive method of detecting subtle microstructural brain changes associated with preclinical Alzheimer’s disease.

Gray and white matter changes in Alzheimer's disease: A diffusion tensor imaging study

To investigate microstructural changes in cortical and white matter pathways in patients with Alzheimers disease using diffusion tensor imaging (DTI).

Correlation of Quantitative EEG in Acute Ischemic Stroke With 30-Day NIHSS Score Comparison With Diffusion and Perfusion MRI

Background and Purpose— Magnetic resonance imaging (MRI) methods such as diffusion- (DWI) and perfusion-weighted (PWI) imaging have been widely studied as surrogate markers to monitor stroke evolution and predict clinical outcome. The utility of quantitative electroencephalography (qEEG) as such a marker in acute stroke has not been intensively studied. The aim of the present study was to correlate ischemic cortical stroke patients’ clinical outcomes with acute qEEG, DWI, and PWI data. Materials and Methods— DWI and PWI data were acquired from 11 patients within 7 and 16 hours after onset of symptoms. Sixty-four channel EEG data were obtained within 2 hours after the initial MRI scan and 1 hour before the second MRI scan. The acute delta change index (aDCI), a measure of the rate of change of average scalp delta power, was compared with the National Institutes of Health Stroke Scale scores (NIHSSS) at 30 days, as were MRI lesion volumes. Results— The aDCI was significantly correlated with the 30-day NIHSSS, as was the initial mean transit time (MTT) abnormality volume (&rgr;=0.80, P <0.01 and &rgr;=0.79, P <0.01, respectively). Modest correlations were obtained between the 15-hour DWI lesion volume and both the aDCI and 30-day NIHSSS (&rgr;=0.62, P <0.05 and &rgr;=0.73, P <0.05, respectively). Conclusions— In this small sample the significant correlation between 30-day NIHSSS and acute qEEG data (aDCI) was equivalent to that between the former and MTT abnormality volume. Both were greater than the modest correlation between acute DWI lesion volume and 30-day NIHSSS. These preliminary results indicate that acute qEEG data might be used to monitor and predict stroke evolution.

Fluid Registration of Diffusion Tensor Images Using Information Theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

Quantitative EEG indices of sub-acute ischaemic stroke correlate with clinical outcomes

OBJECTIVE We investigated the ability of quantitative electroencephalography (QEEG) measures in sub-acute stroke to assist monitoring or prognostication of stroke evolution. QEEG indices and National Institutes of Health Stroke Scale (NIHSS) scores were compared. METHODS Ischaemic cortical stroke patients were studied. Resting, 62-channel EEG and NIHSS score were acquired at 49+/-3h post-symptom onset, and NIHSS administered at 30+/-2 days post-stroke. Mean power was calculated for delta (1-4 Hz), theta (4.1-8 Hz), alpha (8.1-12.5 Hz) and beta (12.6-30 Hz) frequency bands, using a 62-channel electrode array and a 19-channel subset. RESULTS Thirteen patients (6 male, median age 66, range 54-86 years) were studied. Sub-acute delta:alpha power ratio (DAR; r=0.91, P<0.001), relative alpha power (r=-0.82, P<0.01), and NIHSS score (r=0.92, P<0.001) each were significantly correlated with 30-day NIHSS score. The former two significant correlations were upheld in 19-channel EEG data. QEEG measures involving theta or beta power were not significantly correlated with NIHSS scores. CONCLUSIONS QEEG measures such as DAR demonstrate potential to augment bedside assessment of cerebral pathophysiology and prognostication of stroke evolution. A standard, 19-channel array seems adequate for these purposes. Future studies in larger samples should investigate the potential effects on these measures of sleep state and possible causes of artefacts. SIGNIFICANCE QEEG measures from a standard number of electrodes, if available rapidly and robust to potential artefacts, may inform future management of stroke patients.