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Background: Predicting the progression of cognitive decline in Alzheimer's disease (AD) is important for treatment selection and patient counseling. Structural MRI markers such as hippocampus or basal forebrain volumes might represent useful instruments for the prediction of cognitive decline. The primary objective was to determine the predictive value of hippocampus and basal forebrain volumes for global and domain specific cognitive decline in AD dementia during cholinergic treatment.Methods: We used MRI and cognitive data from 124 patients with the clinical diagnosis of AD dementia, derived from the ADNI-1 cohort, who were on standard of care cholinesterase inhibitor treatment during a follow-up period between 0.4 and 3.1 years. We used linear mixed effects models with cognitive function as outcome to assess the main effects as well as two-way interactions between baseline volumes and time controlling for age, sex, and total intracranial volume. This model accounts for individual variation in follow-up times.Results: Basal forebrain volume, but not hippocampus volume, was a significant predictor of rates of global cognitive decline. Larger volumes were associated with smaller rates of cognitive decline. Left hippocampus volume had a modest association with rates of episodic memory decline. Baseline performance in global cognition and memory was significantly associated with hippocampus and basal forebrain volumes; in addition, basal forebrain volume was associated with baseline performance in executive function.Conclusions: Our findings indicate that in AD dementia patients, basal forebrain volume may be a useful marker to predict subsequent cognitive decline during cholinergic treatment.

Hintergrund: Die intensive Erforschung neuer Biomarker zur Diagnostik der Alzheimer Erkrankung (AD) hat zu einem Paradigmenwechsel in der Diagnostik von ehemals phänomenologischen zu biomarkerbasierten Kriterien geführt. Diese neuen Biomarker aus z.B. MRT (Magnetresonanztomographie) oder Liquoranalysen[zum vollständigen Text gelangen Sie über die oben angegebene URL], 16. Deutscher Kongress für Versorgungsforschung (DKVF)

BACKGROUND: Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI). METHODS: We applied a Support Vector Machine (SVM) classifier to DTI and volumetric magnetic resonance imaging data from 35 amyloid-β42 negative MCI subjects (MCI-Aβ42-), 35 positive MCI subjects (MCI-Aβ42+), and 25 healthy controls (HC) retrieved from the European DTI Study on Dementia. The SVM was applied to DTI-derived fractional anisotropy, mean diffusivity (MD), and mode of anisotropy (MO) maps. For comparison, we studied classification based on gray matter (GM) and WM volume. RESULTS: We obtained accuracies of up to 68% for MO and 63% for GM volume when it came to distinguishing between MCI-Aβ42- and MCI-Aβ42+. When it came to separating MCI-Aβ42+ from HC we achieved an accuracy of up to 77% for MD and a significantly lower accuracy of 68% for GM volume. The accuracy of multimodal classification was not higher than the accuracy of the best single modality. CONCLUSIONS: Our results suggest that DTI data provide better prediction accuracy than GM volume in predementia AD

Diffusion tensor imaging (DTI) allows the simultaneous measurement of several diffusion indices that provide complementary information on the substrate of white matter alterations in neurodegenerative diseases. These indices include fractional anisotropy (FA) as measure of fiber tract integrity, and the mode of anisotropy (Mode) reflecting differences in the shape of the diffusion tensor. We used a multivariate approach based on joint independent component analysis of FA and Mode in a large sample of 138 subjects with Alzheimer's disease (AD) dementia, 37 subjects with cerebrospinal fluid biomarker positive mild cognitive impairment (MCI-AD), and 153 healthy elderly controls from the European DTI Study on Dementia to comprehensively study alterations of microstructural white matter integrity in AD dementia and predementia AD. We found a parallel decrease of FA and Mode in intracortically projecting fiber tracts, and a parallel increase of FA and Mode in the corticospinal tract in AD patients compared to controls. Subjects with MCI-AD showed a similar, but spatially more restricted pattern of diffusion changes. Our findings suggest an early axonal degeneration in intracortical projecting fiber tracts in dementia and predementia stages of AD. An increase of Mode, parallel to an increase of FA, in the corticospinal tract suggests a more linear shape of diffusion due to loss of crossing fibers along relatively preserved cortico-petal and cortico-fugal fiber tracts in AD. Supporting this interpretation, we found three populations of fiber tracts, namely cortico-petal and cortico-fugal, commissural, and intrahemispherically projecting fiber tracts, in the peak area of parallel FA and Mode increase.

In this multicenter study, we investigated a possible association between the APOE ε4 allele and white matter (WM) integrity in Alzheimer's disease (AD) using diffusion tensor imaging (DTI).We analyzed fractional anisotropy (FA) and mean diffusivity (MD) as indices of WM integrity in 70 AD patients (35 APOE ε4 carriers, 35 noncarriers) and 56 healthy control (HC) subjects (28 APOE ε4 carriers, 28 noncarriers). APOE ε4 carriers and noncarriers were matched for age and gender within each diagnostic group.We found significant effects of diagnosis (Pcorrected.05 [FWE]; i.e., smaller FA values and larger MD values in AD patients compared with HCs) and significant effects (P.001) of APOE ε4 carrier status on MD in HCs but not in AD subjects.The results indicate that APOE ε4 has a moderate effect on WM integrity in HCs, but no effect on WM integrity in manifest AD.

The basal forebrain cholinergic system (BFCS) is the major source of acetylcholine for the cerebral cortex in humans. The aim was to analyze the pattern of BFCS and cortical atrophy in MCI patients to find evidence for a parallel atrophy along corticotopic organization of BFCS projections. BFCS volume and cortical thickness were analyzed using high-definition 3D structural magnetic resonance imaging data from 1.5-T and 3.0-T scanners of 64 MCI individuals and 62 cognitively healthy elderly controls from the European DTI study in dementia. BFCS volume reduction was correlated with thinning of cortical areas with known BFCS projections, such as Ch2 and parahippocampal gyrus in the MCI group, but not in the control group. Additionally, we found correlations between BFCS and cortex atrophy beyond the known corticotopic projections, such as between Ch4p and the cingulate gyrus. BFCS volume reduction was associated with regional thinning of cortical areas that included, but was not restricted to, the pattern of corticotopic projections of the BFCS as derived from animal studies. Our in vivo results may indicate the existence of more extended projections from the BFCS to the cerebral cortex in humans than that known from prior studies with animals.

Histopathological studies in Alzheimer's disease (AD) suggest severe and region-specific neurodegeneration of the basal forebrain cholinergic system (BFCS). Here, we studied the between-center reliability and diagnostic accuracy of MRI-based BFCS volumetry in a large multicenter data set, including participants with prodromal (n = 41) or clinically manifest AD (n = 134) and 148 cognitively healthy controls. Atrophy was determined using voxel-based and region-of-interest based analyses of high-dimensionally normalized MRI scans using a newly created map of the BFCS based on postmortem in cranio MRI and histology. The AD group showed significant volume reductions of all subregions of the BFCS, which were most pronounced in the posterior nucleus basalis Meynert (NbM). The mild cognitive impairment-AD group showed pronounced volume reductions in the posterior NbM, but preserved volumes of anterior-medial regions. Diagnostic accuracy of posterior NbM volume was superior to hippocampus volume in both groups, despite higher multicenter variability of the BFCS measurements. The data of our study suggest that BFCS morphometry may provide an emerging biomarker in AD.

Diffusion tensor imaging (DTI) detects microstructural changes of the cerebral white matter in Alzheimer's disease (AD). The use of DTI for the diagnosis of AD in a multicenter setting has not yet been investigated. We used voxel-based analysis of fractional anisotropy, mean diffusivity, and grey matter volumes from multimodal magnetic resonance imaging data of 137 AD patients and 143 healthy elderly controls collected across 9 different scanners. We compared different univariate analysis approaches to model the effect of scanner, including a linear model across all scans with a scanner covariate, a random effects model with scanner as a random variable as well as a voxel-based meta-analysis. We found significant reduction of fractional anisotropy and significant increase of mean diffusivity in core areas of AD pathology including corpus callosum, medial and lateral temporal lobes, as well as fornix, cingulate gyrus, precuneus, and prefrontal lobe white matter. Grey matter atrophy was most pronounced in medial and lateral temporal lobe as well as parietal and prefrontal association cortex. The effects of group were spatially more restricted with random effects modeling of scanner effects compared to simple pooled analysis. All three analysis approaches yielded similar accuracy of group separation in block-wise cross-validated logistic regression. Our results suggest similar effects of center on group separation based on different analysis approaches and confirm a typical pattern of cortical and subcortical microstructural changes in AD using a large multimodal multicenter data set.

Background: Hippocampal grey matter (GM) atrophy predicts conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Pilot data suggests that mean diffusivity (MD) in the hippocampus, as measured with diffusion tensor imaging (DTI), may be a more accurate predictor of conversion than hippocampus volume. In addition, previous studies suggest that volume of the cholinergic basal forebrain may reach a diagnostic accuracy superior to hippocampal volume in MCI. Objective: The present study investigated whether increased MD and decreased volume of the hippocampus, the basal forebrain and other AD-typical regions predicted time to conversion from MCI to AD dementia. Methods: 79 MCI patients with DTI and T1-weighted magnetic resonance imaging (MRI) were retrospectively included from the European DTI Study in Dementia (EDSD) dataset. Of these participants, 35 converted to AD dementia after 6-46 months (mean: 21 months). We used Cox regression to estimate the relative conversion risk predicted by MD values and GM volumes, controlling for age, gender, education and center. Results: Decreased GM volume in all investigated regions predicted an increased risk for conversion. Additionally, increased MD in the right basal forebrain predicted increased conversion risk. Reduced volume of the right hippocampus was the only significant predictor in a stepwise model combining all predictor variables. Conclusion: Volume reduction of the hippocampus, the basal forebrain and other AD-related regions was predictive of increased risk for conversion from MCI to AD. In this study, volume was superior to MD in predicting conversion.

Diffusion tensor imaging (DTI) detects white matter damage in neuro-psychiatric disorders, but data on reliability of DTI measures across more than two scanners are still missing. In this study we assessed multicenter reproducibility of DTI acquisitions based on a physical phantom as well as brain scans across 16 scanners. In addition, we performed DTI scans in a group of 26 patients with clinically probable Alzheimer's disease (AD) and 12 healthy elderly controls at one single center. We determined the variability of fractional anisotropy (FA) measures using manually placed regions of interest as well as automated tract based spatial statistics and deformation based analysis. The coefficient of variation (CV) of FA was 6.9% for the physical phantom data. The mean CV across the multicenter brain scans was 14% for tract based statistics, and 29% for deformation based analysis. The degree of variation was higher in less organized fiber tracts. Our findings suggest that a clinical and physical phantom study involving more than two scanners is indispensable to detect potential sources of bias and to reliably estimate effect size in multicenter diagnostic trials using DTI.

Cross-sectional studies using diffusion tensor imaging (DTI) suggest decline of the integrity of intracortically projecting fiber tracts with aging and in neurodegenerative diseases, such as Alzheimer's disease (AD). Longitudinal studies on the change of fiber tract integrity in normal and pathological aging are still rare. Here, we prospectively studied 11 healthy elderly subjects and 14 subjects with amnestic mild cognitive impairment (MCI), a clinical risk group for AD, using high-resolution DTI and MRI at baseline and after 13 to 16 months follow-up. Fractional anisotropy (FA), a DTI measure of fiber tract integrity, was compared across time points and groups using a repeated measures linear model and tract based spatial statistics. Additionally, we determined rates of grey matter and white matter atrophy using automated deformation based morphometry. Healthy elderly subjects showed decline of FA in intracortical projecting fiber tracts, such as corpus callosum, superior longitudinal fasciculus, uncinate fasciculus, inferior fronto-occipital fasciculus, and cingulate bundle (p < 0.05, corrected for multiple comparisons). MCI subjects showed significant FA decline predominantly in the anterior corpus callosum (p < 0.05, corrected for multiple comparisons). Grey and white matter atrophy involved prefrontal, parietal, and temporal lobe areas in controls and prefrontal, cingulate, and parietal lobe areas in MCI subjects and agreed with the pattern of fiber tract changes. Our findings indicate that DTI allows detection of microstructural changes in subcortical fiber tracts over time that are related to aging as well as to early stages of AD type neurodegeneration. The underlying mechanisms for these changes are unknown.