Jonathan B. Chalk

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 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.

AN EVALUATION OF THE TIME DEPENDENCE OF THE ANISOTROPY OF THE WATER DIFFUSION TENSOR IN ACUTE HUMAN ISCHEMIA

We have performed MRI examinations to determine the water diffusion tensor in the brain of six patients who were admitted to the hospital within 12 h after the onset of cerebral ischemic symptoms. The examinations have been carried out immediately after admission, and thereafter at varying intervals up to 90 days post admission. Maps of the trace of the diffusion tensor, the fractional anisotropy and the lattice index, as well as maps of cerebral blood perfusion parameters, were generated to quantitatively assess the character of the water diffusion tensor in the infarcted area. In patients with significant perfusion deficits and substantial lesion volume changes, four of six cases, our measurements show a monotonic and significant decrease in the diffusion anisotropy within the ischemic lesion as a function of time. We propose that retrospective analysis of this quantity, in combination with brain tissue segmentation and cerebral perfusion maps, may be used in future studies to assess the severity of the ischemic event.

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.

4D deformation modeling of cortical disease progression in Alzheimer's dementia

This work describes the development of a model of cerebral atrophic changes associated with the progression of Alzheimers disease (AD). Linear registration, region‐of‐interest analysis, and voxel‐based morphometry methods have all been employed to elucidate the changes observed at discrete intervals during a disease process. In addition to describing the nature of the changes, modeling disease‐related changes via deformations can also provide information on temporal characteristics. In order to continuously model changes associated with AD, deformation maps from 21 patients were averaged across a novel z‐score disease progression dimension based on Mini Mental State Examination (MMSE) scores. The resulting deformation maps are presented via three metrics: local volume loss (atrophy), volume (CSF) increase, and translation (interpreted as representing collapse of cortical structures). Inspection of the maps revealed significant perturbations in the deformation fields corresponding to the entorhinal cortex (EC) and hippocampus, orbitofrontal and parietal cortex, and regions surrounding the sulci and ventricular spaces, with earlier changes predominantly lateralized to the left hemisphere. These changes are consistent with results from post‐mortem studies of AD. Magn Reson Med 46:661–666, 2001.

MR image-based measurement of rates of change in volumes of brain structures. Part II: application to a study of Alzheimer’s disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired T1-weighted brain MR images for a group of Alzheimers disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

MRI based diffusion and perfusion predictive model to estimate stroke evolution

In this study we present a novel automated strategy for predicting infarct evolution, based on MR diffusion and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs) defining the initial diffusion lesion and tissue with abnormal hemodynamic function as defined by the mean transit time (MTT) abnormality were automatically extracted from DWI/PI maps. Quantitative measures of cerebral blood flow (CBF) and volume (CBV) along with ratio measures defined relative to the contralateral hemisphere (r(a)CBF and r(a)CBV) were calculated for the MTT ROIs. A parametric normal classifier algorithm incorporating these measures was used to predict infarct growth. The mean r(a)CBF and r(a)CBV values for eventually infarcted MTT tissue were 0.70 +/- 0.19 and 1.20 +/- 0.36. For recovered tissue the mean values were 0.99 +/- 0.25 and 1.87 +/- 0.71, respectively. There was a significant difference between these two regions for both measures (p < 0.003 and p < 0.001, respectively). Mean absolute measures of CBF (ml/100g/min) and CBV (ml/100g) for the total infarcted territory were 33.9 +/- 9.7 and 4.2 +/- 1.9. For recovered MTT tissue, the mean values were 41.5 +/- 7.2 and 5.3 +/- 1.2, respectively. A significant difference was also found for these regions (p < 0.009 and p < 0.036, respectively). The mean measures of sensitivity, specificity, positive and negative predictive values for modeling infarct evolution for the validation patient data were 0.72 +/- 0.05, 0.97 +/- 0.02, 0.68 +/- 0.07 and 0.97 +/- 0.02. We propose that this automated strategy may allow possible guided therapeutic intervention to stroke patients and evaluation of efficacy of novel stroke compounds in clinical drug trials.

Spasticity and white matter abnormalities in adult phenylketonuria.

A 19 year old male with phenylketonuria (PKU) developed a spastic paparesis 8 months after stopping his restricted phenylalanine diet. CT and MRI showed abnormalities of the deep cerebral white matter, and visual evoked response latencies were prolonged. The spasticity gradually improved over several months after resuming the PKU diet. A repeat MRI scan was unchanged. His brother also had PKU and ceased dietary restrictions, but his only neurological abnormality was a slight increase in the deep tendon reflexes of the lower limbs. CT and MRI of his brain was normal. DNA analysis showed that both brothers were homozygous for the same PKU mutation. These patients demonstrate that reversible neurological signs may develop in patients with classic PKU after ceasing dietary restrictions and that these may be associated with abnormalities seen on neuro-imaging.