Studying ventricular abnormalities in mild cognitive impairment with hyperbolic Ricci flow and tensor-based morphometry.

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD.

Correlations between FDG PET glucose uptake-MRI gray matter volume scores and apolipoprotein E ε4 gene dose in cognitively normal adults: a cross-validation study using voxel-based multi-modal partial least squares.

We previously introduced a voxel-based, multi-modal application of the partial least square algorithm (MMPLS) to characterize the linkage between patterns in a person's complementary complex datasets without the need to correct for multiple regional comparisons. Here we used it to demonstrate a strong correlation between MMPLS scores to characterize the linkage between the covarying patterns of fluorodeoxyglucose positron emission tomography (FDG PET) measurements of regional glucose metabolism and magnetic resonance imaging (MRI) measurements of regional gray matter associated with apolipoprotein E (APOE) ε4 gene dose (i.e., three levels of genetic risk for late-onset Alzheimer's disease (AD)) in cognitively normal, late-middle-aged persons. Coregistered and spatially normalized FDG PET and MRI images from 70% of the subjects (27 ε4 homozygotes, 36 ε4 heterozygotes and 67 ε4 non-carriers) were used in a hypothesis-generating MMPLS analysis to characterize the covarying pattern of regional gray matter volume and cerebral glucose metabolism most strongly correlated with APOE-ε4 gene dose. Coregistered and spatially normalized FDG PET and MRI images from the remaining 30% of the subjects were used in a hypothesis-testing MMPLS analysis to generate FDG PET-MRI gray matter MMPLS scores blind to their APOE genotype and characterize their relationship to APOE-ε4 gene dose. The hypothesis-generating analysis revealed covarying regional gray matter volume and cerebral glucose metabolism patterns that resembled those in traditional univariate analyses of AD and APOE-ε4 gene dose and PET-MRI scores that were strongly correlated with APOE-ε4 gene dose (p<1 × 10(-16)). The hypothesis-testing analysis results showed strong correlations between FDG PET-MRI gray matter scores and APOE-ε4 gene dose (p = 8.7 × 10(-4)). Our findings support the possibility of using the MMPLS to analyze complementary datasets from the same person in the presymptomatic detection and tracking of AD.

Characterizing Alzheimer's disease using a hypometabolic convergence index.

This article introduces a hypometabolic convergence index (HCI) for the assessment of Alzheimer's disease (AD); compares it to other biological, cognitive and clinical measures; and demonstrates its promise to predict clinical decline in mild cognitive impairment (MCI) patients using data from the AD Neuroimaging Initiative (ADNI). The HCI is intended to reflect in a single measurement the extent to which the pattern and magnitude of cerebral hypometabolism in an individual's fluorodeoxyglucose positron emission tomography (FDG-PET) image correspond to that in probable AD patients, and is generated using a fully automated voxel-based image-analysis algorithm. HCIs, magnetic resonance imaging (MRI) hippocampal volume measurements, cerebrospinal fluid (CSF) assays, memory test scores, and clinical ratings were compared in 47 probable AD patients, 21 MCI patients who converted to probable AD within the next 18months, 76 MCI patients who did not, and 47 normal controls (NCs) in terms of their ability to characterize clinical disease severity and predict conversion rates from MCI to probable AD. HCIs were significantly different in the probable AD, MCI converter, MCI stable and NC groups (p=9e-17) and correlated with clinical disease severity. Using retrospectively characterized threshold criteria, MCI patients with either higher HCIs or smaller hippocampal volumes had the highest hazard ratios (HRs) for 18-month progression to probable AD (7.38 and 6.34, respectively), and those with both had an even higher HR (36.72). In conclusion, the HCI, alone or in combination with certain other biomarker measurements, has the potential to help characterize AD and predict subsequent rates of clinical decline. More generally, our conversion index strategy could be applied to a range of imaging modalities and voxel-based image-analysis algorithms.

Higher serum total cholesterol levels in late middle age are associated with glucose hypometabolism in brain regions affected by Alzheimer's disease and normal aging.

Epidemiological studies suggest that higher midlife serum total cholesterol levels are associated with an increased risk of Alzheimer's disease (AD). Using fluorodeoxyglucose positron emission tomography (PET) in the study of cognitively normal late middle-aged people, we demonstrated an association between apolipoprotein E (APOE) epsilon4 gene dose, the major genetic risk factor for late-onset AD, and lower measurements of the cerebral metabolic rate for glucose (CMRgl) in AD-affected brain regions, we proposed using PET as a pre-symptomatic endophenotype to evaluate other putative AD risk modifiers, and we then used it to support an aggregate cholesterol-related genetic risk score in the risk of AD. In the present study, we used PET to investigate the association between serum total cholesterol levels and cerebral metabolic rate for glucose metabolism (CMRgl) in 117 cognitively normal late middle-aged APOE epsilon4 homozygotes, heterozygotes and non-carriers. Higher serum total cholesterol levels were associated with lower CMRgl bilaterally in precuneus, parietotemporal and prefrontal regions previously found to be preferentially affected by AD, and in additional frontal regions previously found to be preferentially affected by normal aging. The associations were greater in APOE epsilon4 carriers than non-carriers in some of the AD-affected brain regions. We postulate that higher midlife serum total cholesterol levels accelerate brain processes associated with normal aging and conspire with other risk factors in the predisposition to AD. We propose using PET in proof-of-concept randomized controlled trials to rapidly evaluate the effects of midlife cholesterol-lowering treatments on the brain changes associated with normal aging and AD.

Twelve-month metabolic declines in probable Alzheimer's disease and amnestic mild cognitive impairment assessed using an empirically pre-defined statistical region-of-interest: findings from the Alzheimer's Disease Neuroimaging Initiative.

Alzheimer's disease (AD) is characterized by specific and progressive reductions in fluorodeoxyglucose positron emission tomography (FDG PET) measurements of the cerebral metabolic rate for glucose (CMRgl), some of which may precede the onset of symptoms. In this report, we describe twelve-month CMRgl declines in 69 probable AD patients, 154 amnestic mild cognitive impairment (MCI) patients, and 79 cognitively normal controls (NCs) from the AD Neuroimaging Initiative (ADNI) using statistical parametric mapping (SPM). We introduce the use of an empirically pre-defined statistical region-of-interest (sROI) to characterize CMRgl declines with optimal power and freedom from multiple comparisons, and we estimate the number of patients needed to characterize AD-slowing treatment effects in multi-center randomized clinical trials (RCTs). The AD and MCI groups each had significant twelve-month CMRgl declines bilaterally in posterior cingulate, medial and lateral parietal, medial and lateral temporal, frontal and occipital cortex, which were significantly greater than those in the NC group and correlated with measures of clinical decline. Using sROIs defined based on training sets of baseline and follow-up images to assess CMRgl declines in independent test sets from each patient group, we estimate the need for 66 AD patients or 217 MCI patients per treatment group to detect a 25% AD-slowing treatment effect in a twelve-month, multi-center RCT with 80% power and two-tailed alpha=0.05, roughly one-tenth the number of the patients needed to study MCI patients using clinical endpoints. Our findings support the use of FDG PET, brain-mapping algorithms and empirically pre-defined sROIs in RCTs of AD-slowing treatments.

Categorical and correlational analyses of baseline fluorodeoxyglucose positron emission tomography images from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

In mostly small single-center studies, Alzheimer's disease (AD) is associated with characteristic and progressive reductions in fluorodeoxyglucose positron emission tomography (PET) measurements of the regional cerebral metabolic rate for glucose (CMRgl). The AD Neuroimaging Initiative (ADNI) is acquiring FDG PET, volumetric magnetic resonance imaging, and other biomarker measurements in a large longitudinal multi-center study of initially mildly affected probable AD (pAD) patients, amnestic mild cognitive impairment (aMCI) patients, who are at increased AD risk, and cognitively normal controls (NC), and we are responsible for analyzing the PET images using statistical parametric mapping (SPM). Here we compare baseline CMRgl measurements from 74 pAD patients and 142 aMCI patients to those from 82 NC, we correlate CMRgl with categorical and continuous measures of clinical disease severity, and we compare apolipoprotein E (APOE) varepsilon4 carriers to non-carriers in each of these subject groups. In comparison with NC, the pAD and aMCI groups each had significantly lower CMRgl bilaterally in posterior cingulate, precuneus, parietotemporal and frontal cortex. Similar reductions were observed when categories of disease severity or lower Mini-Mental State Exam (MMSE) scores were correlated with lower CMRgl. However, when analyses were restricted to the pAD patients, lower MMSE scores were significantly correlated with lower left frontal and temporal CMRgl. These findings from a large, multi-site study support previous single-site findings, supports the characteristic pattern of baseline CMRgl reductions in AD and aMCI patients, as well as preferential anterior CMRgl reductions after the onset of AD dementia.

Improved power for characterizing longitudinal amyloid-ß PET changes and evaluating amyloid-modifying treatments with a cerebral white matter reference region.

UNLABELLED: In this article, we describe an image analysis strategy with improved power for tracking longitudinal amyloid-ß (Aß) PET changes and evaluating Aß-modifying treatments. METHODS: Our aims were to compare the power of template-based cerebellar, pontine, and cerebral white matter reference regions to track 24-mo florbetapir standardized uptake value (SUV) ratio (SUVR) changes; to relate those changes to 24-mo clinical declines; and to evaluate Aß-modifying treatments in Aß-positive (Aß+) and Aß-negative (Aß-) patients with probable Alzheimer dementia (pAD), in patients with mild cognitive impairment (MCI), in cognitively normal controls (NCs), and in cognitively normal apolipoprotein E4 (APOE4) carriers and noncarriers. We used baseline and follow-up (∼24 mo) florbetapir PET scans from 332 Aß+ and Aß- subjects participating in the multicenter Alzheimer's Disease Neuroimaging Initiative. Each of the proposed analyses included 31 pAD patients, 187 MCI patients, and 114 NCs. Cerebral-to-white matter, cerebellar, and pontine SUVRs were characterized in terms of their longitudinal variability; their power to track longitudinal fibrillar Aß increases in Aß+ and Aß- subgroups and cognitively normal APOE4 carriers and noncarriers; the sample sizes needed to detect attenuated accumulation of or clearance of fibrillar Aß accumulation in randomized clinical trials; and their ability to relate 24-mo fibrillar Aß increases to clinical declines. RESULTS: As predicted, cerebral-to-white matter SUVR changes were significantly less variable and had significantly greater power to detect 24-mo fibrillar Aß increases and evaluate Aß-modifying treatment effects in Aß+ pAD, MCI, and NC subjects and cognitively normal APOE4 carriers. They were also distinguished by the ability to detect significant associations between 24-mo Aß increases and clinical declines. CONCLUSION: A cerebral white matter reference region may improve the power to track longitudinal fibrillar Aß increases, to characterize their relationship to longitudinal clinical declines, and to evaluate Aß-modifying treatments in randomized clinical trials.

Assessing the reliability to detect cerebral hypometabolism in probable Alzheimer's disease and amnestic mild cognitive impairment.

Fluorodeoxyglucose positron emission tomography (FDG-PET) studies report characteristic patterns of cerebral hypometabolism in probable Alzheimer's disease (pAD) and amnestic mild cognitive impairment (aMCI). This study aims to characterize the consistency of regional hypometabolism in pAD and aMCI patients enrolled in the AD neuroimaging initiative (ADNI) using statistical parametric mapping (SPM) and bootstrap resampling, and to compare bootstrap-based reliability index to the commonly used type-I error approach with or without correction for multiple comparisons. Batched SPM5 was run for each of 1000 bootstrap iterations to compare FDG-PET images from 74 pAD and 142 aMCI patients, respectively, to 82 normal controls. Maps of the hypometabolic voxels detected for at least a specific percentage of times over the 1000 runs were examined and compared to an overlap of the hypometabolic maps obtained from 3 randomly partitioned independent sub-datasets. The results from the bootstrap derived reliability of regional hypometabolism in the overall data set were similar to that observed in each of the three non-overlapping sub-sets using family-wise error. Strong but non-linear association was found between the bootstrap-based reliability index and the type-I error. For threshold p=0.0005, pAD was associated with extensive hypometabolic voxels in the posterior cingulate/precuneus and parietotemporal regions with reliability between 90% and 100%. Bootstrap analysis provides an alternative to the parametric family-wise error approach used to examine consistency of hypometabolic brain voxels in pAD and aMCI patients. These results provide a foundation for the use of bootstrap analysis characterize statistical ROIs or search regions in both cross-sectional and longitudinal FDG-PET studies. This approach offers promise in the early detection and tracking of AD, the evaluation of AD-modifying treatments, and other biologically or clinical important measurements using brain images and voxel-based data analysis techniques.

Hypometabolism in Alzheimer-affected brain regions in cognitively healthy Latino individuals carrying the apolipoprotein E epsilon4 allele.

OBJECTIVE: To investigate with fluorodeoxyglucose positron emission tomography whether regional reductions in the cerebral metabolic rate for glucose (CMRgl) previously found in cognitively healthy late-middle-aged apolipoprotein E (APOE) epsilon4 carriers extend to members of the Latino Mexican American community. DESIGN: Prospective cohort study. SETTING: Banner Alzheimer's Institute, Phoenix, Arizona. PATIENTS OR OTHER PARTICIPANTS: Eleven APOE epsilon4 carriers and 16 noncarriers from Arizona's Latino community (mean [SD] age, 54.6 [6.4] years) matched for sex, mean age, and educational level and who were predominantly of self-designated Mexican origin. MAIN OUTCOME MEASURE: A brain mapping algorithm was used to compare cross-sectional regional CMRgl in Latino APOE epsilon4 carriers vs noncarriers. RESULTS: Participant groups had similar distributions for age, sex, education, family history of dementia, clinical ratings, and neuropsychological test scores. Latino APOE epsilon4 carriers had lower CMRgl than the noncarriers in the posterior cingulate, precuneus, and parietal regions previously found to be preferentially affected in patients with Alzheimer disease (AD) and cognitively healthy non-Latino APOE epsilon4 carriers. Additionally, the Latino APOE epsilon4 carriers had lower CMRgl in the middle and anterior cingulate cortex, hippocampus, and thalamus. CONCLUSIONS: This study provides support for the relationship between APOE epsilon4 and risk of AD in Latino individuals. It illustrates the role of positron emission tomography as a presymptomatic endophenotype for the assessment of AD risk factors and supports the inclusion of Latino APOE epsilon4 carriers in proof-of-concept studies using fluorodeoxyglucose PET to evaluate promising presymptomatic treatments in cognitively healthy carriers of this common AD susceptibility gene.