Danielle Harvey

The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods

The Alzheimers Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimers disease. Magnetic resonance imaging (MRI), (18F)‐fluorodeoxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquiredat multiple time points. All data will be cross‐linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications thatguided protocol development. A major effort was devoted toevaluating 3D T1‐weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced‐scale clinical trial. The protocol selected for the ADNI study includes: back‐to‐back 3D magnetization prepared rapid gradient echo (MP‐RAGE) scans; B1‐calibration scans when applicable; and an axial proton density‐T2 dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom‐based monitoring of all scanners could be used as a model for other multisite trials. J. Magn. Reson. Imaging 2008.

The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

The Alzheimers Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimers disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects;

Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization.

67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β‐amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau‐mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [18F]‐fluorodeoxyglucose‐PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β‐amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI‐like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease‐modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2‐year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI‐2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

Measures of brain morphology and infarction in the framingham heart study: establishing what is normal

Background: Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally. Objective: To characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures. Methods: A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials. Results: The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimers Disease Assessment Scale–Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Aβ-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures. Conclusion: The Alzheimers Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.

Comparing predictors of conversion and decline in mild cognitive impairment

Numerous anatomical and brain imaging studies find substantial differences in brain structure between men and women across the span of human aging. The ability to extend the results of many of these studies to the general population is limited, however, due to the generally small sample size and restrictive health criteria of these studies. Moreover, little attention has been paid to the possible impact of brain infarction on age-related differences in regional brain volumes. Given the current lack of normative data on gender and aging related differences in regional brain morphology, particularly with regard to the impact of brain infarctions, we chose to quantify brain MRIs from more than 2200 male and female participants of the Framingham Heart Study who ranged in age from 34 to 97 years. We believe that MRI analysis of the Framingham Heart Study more closely represents the general population enabling more accurate estimates of regional brain changes that occur as the consequence of normal aging. As predicted, men had significantly larger brain volumes than women, but these differences were generally not significant after correcting for gender related differences in head size. Age explained approximately 50% of total cerebral brain volume differences, but age-related differences were generally small prior to age 50, declining substantially thereafter. Frontal lobe volumes showed the greatest decline with age (approximately 12%), whereas smaller differences were found for the temporal lobes (approximately 9%). Age-related differences in occipital and parietal lobe were modest. Age-related gender differences were generally small, except for the frontal lobe where men had significantly smaller lobar brain volumes throughout the age range studied. The prevalence of MRI infarction was common after age 50, increased linearly with age and was associated with significantly larger white matter hyperintensity (WMH) volumes beyond that associated with age-related differences in these measures. Amongst men, the presence of MRI infarction was associated with significant age-related reductions in total brain volume. Finally, statistically significant associations were found between the volume of MRI infarcts in cubic centimeters and all brain measures with the exception of parietal lobe volume for individuals where the volume of MRI infarctions was measured. These data serve to define age and gender differences in brain morphology for the Framingham Heart Study. To the degree participants of the Framingham Heart Study are representative the general population, these data can serve as norms for comparison with morphological brain changes associated with aging and disease. In this regard, these cross-sectional quantitative estimates suggest that age-related tissue loss differs quantitatively and qualitatively across brain regions with only minor differences between men and women. In addition, MRI evidence of cerebrovascular disease is common to the aging process and associated with smaller regional brain volumes for a given age, particularly for men. We believe quantitative MRI studies of the Framingham community enables exploration of numerous issues ranging from understanding normal neurobiology of brain aging to assessing the impact of various health factors, particularly those related to cerebrovascular disease, that appear important to maintaining brain health for the general population.

White matter lesions impair frontal lobe function regardless of their location

Objective: A variety of measurements have been individually linked to decline in mild cognitive impairment (MCI), but the identification of optimal markers for predicting disease progression remains unresolved. The goal of this study was to evaluate the prognostic ability of genetic, CSF, neuroimaging, and cognitive measurements obtained in the same participants. Methods: APOE ε4 allele frequency, CSF proteins (Aβ1-42, total tau, hyperphosphorylated tau [p-tau181p]), glucose metabolism (FDG-PET), hippocampal volume, and episodic memory performance were evaluated at baseline in patients with amnestic MCI (n = 85), using data from a large multisite study (Alzheimers Disease Neuroimaging Initiative). Patients were classified as normal or abnormal on each predictor variable based on externally derived cutoffs, and then variables were evaluated as predictors of subsequent conversion to Alzheimer disease (AD) and cognitive decline (Alzheimers Disease Assessment Scale–Cognitive Subscale) during a variable follow-up period (1.9 ± 0.4 years). Results: Patients with MCI converted to AD at an annual rate of 17.2%. Subjects with MCI who had abnormal results on both FDG-PET and episodic memory were 11.7 times more likely to convert to AD than subjects who had normal results on both measures (p ≤ 0.02). In addition, the CSF ratio p-tau181p/Aβ1-42 (β = 1.10 ± 0.53; p = 0.04) and, marginally, FDG-PET predicted cognitive decline. Conclusions: Baseline FDG-PET and episodic memory predict conversion to AD, whereas p-tau181p/Aβ1-42 and, marginally, FDG-PET predict longitudinal cognitive decline. Complementary information provided by these biomarkers may aid in future selection of patients for clinical trials or identification of patients likely to benefit from a therapeutic intervention.

Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI

Objective: To analyze the effect of white matter lesions in different brain regions on regional cortical glucose metabolism, regional cortical atrophy, and cognitive function in a sample with a broad range of cerebrovascular disease and cognitive function. Methods: Subjects (n = 78) were recruited for a study of subcortical ischemic vascular disease (SIVD) and Alzheimer disease (AD) contributions to dementia. A new method was developed to define volumes of interest from high-resolution three-dimensional T1-weighted MR images. Volumetric measures of MRI segmented white matter signal hyperintensities (WMH) in five different brain regions were related to regional PET glucose metabolism (rCMRglc) in cerebral cortex, MRI measures of regional cortical atrophy, and neuropsychological assessment of executive and memory function. Results: WMH was significantly higher in the prefrontal region compared to the other brain regions. In all subjects, higher frontal and parietal WMH were associated with reduced frontal rCMRglc, whereas occipitotemporal WMH was only marginally associated with frontal rCMRglc. These associations were stronger and more widely distributed in nondemented subjects where reduced frontal rCMRglc was correlated with WMH for all regions measured. In contrast, there was no relationship between WMH in any brain region and rCMRglc in either parietal or occipitotemporal regions. WMHs in all brain regions were associated with low executive scores in nondemented subjects. Conclusions: The frontal lobes are most severely affected by SIVD. WMHs are more abundant in the frontal region. Regardless of where in the brain these WMHs are located, they are associated with frontal hypometabolism and executive dysfunction.

Anatomical Mapping of White Matter Hyperintensities (WMH): Exploring the Relationships Between Periventricular WMH, Deep WMH, and Total WMH Burden

The Functional Activities Questionnaire (FAQ) and Alzheimers Disease Assessment Scale-cognitive subscale (ADAS-cog) are frequently used indices of cognitive decline in Alzheimers disease (AD). The goal of this study was to compare FDG-PET and clinical measurements in a large sample of elderly subjects with memory disturbance. We examined relationships between glucose metabolism in FDG-PET regions of interest (FDG-ROIs), and ADAS-cog and FAQ scores in AD and mild cognitive impairment (MCI) patients enrolled in the Alzheimers Disease Neuroimaging Initiative (ADNI). Low glucose metabolism at baseline predicted subsequent ADAS-cog and FAQ decline. In addition, longitudinal glucose metabolism decline was associated with concurrent ADAS-cog and FAQ decline. Finally, a power analysis revealed that FDG-ROI values have greater statistical power than ADAS-cog to detect attenuation of cognitive decline in AD and MCI patients. Glucose metabolism is a sensitive measure of change in cognition and functional ability in AD and MCI, and has value in predicting future cognitive decline.

Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD

Background and Purpose— MRI segmentation and mapping techniques were used to assess evidence in support of categorical distinctions between periventricular white matter hyperintensities (PVWMH) and deep WMH (DWMH). Qualitative MRI studies generally identify 2 categories of WMH on the basis of anatomical localization. Separate pathophysiologies and behavioral consequences are often attributed to these 2 classes of WMH. However, evidence to support these empirical distinctions has not been rigorously sought. Methods— MRI analysis of 55 subjects included quantification of WMH volume, mapping onto a common anatomical image, and spatial localization of each WMH voxel. WMH locations were then divided into PVWMH and DWMH on the basis of distance from the lateral ventricles and correlations, with total WMH volume determined. Periventricular distance histograms of WMH voxels were also calculated. Results— PVWMH and DWMH were highly correlated with total WMH (R2>0.95) and with each other (R2>0.87). Mapping of all WMH revealed smooth expansion from around central cerebrospinal fluid spaces into more distal cerebral white matter with increasing WMH volume. Conclusion— PVWMH, DWMH, and total WMH are highly correlated with each other. Moreover, spatial analysis failed to identify distinct subpopulations for PVWMH and DWMH. These results suggest that categorical distinctions between PVWMH and DWMH may be arbitrary, and conclusions regarding individual relationships between causal factors or behavior for PVWMH and DWMH may more accurately reflect total WMH volume relationships.

Longitudinal volumetric MRI change and rate of cognitive decline

Objective: To analyze the extent and spatial distribution of white matter hyperintensities (WMH) in brain regions from cognitively normal older individuals (CN) and patients with mild cognitive impairment (MCI) and Alzheimer disease (AD). Methods: We studied 26 mild AD, 28 MCI, and 33 CN. MRI analysis included quantification of WMH volume, nonlinear mapping onto a common anatomic image, and spatial localization of each WMH voxel to create an anatomically precise frequency distribution map. Areas of greatest frequency of WMH from the WMH composite map were used to identify 10 anatomic regions involving periventricular areas and the corpus callosum (CC) for group comparisons. Results: Total WMH volumes were associated with age, extent of concurrent vascular risk factors, and diagnosis. After correcting for age, total WMH volumes remained significantly associated with diagnosis and extent of vascular risk. Regional WMH analyses revealed significant differences in WMH across regions that also differed significantly according to diagnosis. In post-hoc analyses, significant differences were seen between CN and AD in posterior periventricular regions and the splenium of the CC. MCI subjects had intermediate values at all regions. Repeated measures analysis including vascular risk factors in the model found a significant relationship between periventricular WMH and vascular risk that differed by region, but regional differences according to diagnosis remained significant and there was no interaction between diagnosis and vascular risk. Conclusions: Differences in white matter hyperintensities (WMH) associated with increasing cognitive impairment appear related to both extent and spatial location. Multiple regression analysis of regional WMH, vascular risk factors, and diagnosis suggest that these spatial differences may result from the additive effects of vascular and degenerative injury. Posterior periventricular and corpus callosum extension of WMH associated with mild cognitive impairment and Alzheimer disease indicate involvement of strategic white matter bundles that may contribute to the cognitive deficits seen with these syndromes.