The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimer's 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

INTRODUCTION Our goal was to develop cut-points for amyloid PET, tau PET, FDG PET, and MRI cortical thickness. METHODS We examined five methods for determining cut-points. RESULTS The reliable worsening method produced a cut-point only for amyloid PET. The specificity, sensitivity, and accuracy of clinically impaired versus young clinically normal (CN) methods labeled the most people positive and all gave similar cut-points for tau PET, FDG PET and cortical thickness. Cut-points defined using the accuracy of clinically impaired versus age-matched CN method labeled fewer people positive. DISCUSSION In the future, we will employ a single cut-point for amyloid PET (SUVR 1.42, centiloid 19) based on the reliable worsening cut-point method. We will base lenient cut-points for tau PET, FDG PET and cortical thickness on the accuracy of clinically impaired vs young CN method and base conservative cut-points on the accuracy of clinically impaired vs age-matched CN method.

The purpose of this study was to use serial imaging to gain insight into the sequence of pathologic events in Alzheimer's disease, and the clinical features associated with this sequence. We measured change in amyloid deposition over time using serial 11C Pittsburgh compound B (PIB) positron emission tomography and progression of neurodegeneration using serial structural magnetic resonance imaging. We studied 21 healthy cognitively normal subjects, 32 with amnestic mild cognitive impairment and 8 with Alzheimer's disease. Subjects were drawn from two sources—ongoing longitudinal registries at Mayo Clinic, and the Alzheimer's disease Neuroimaging Initiative (ADNI). All subjects underwent clinical assessments, MRI and PIB studies at two time points, approximately one year apart. PIB retention was quantified in global cortical to cerebellar ratio units and brain atrophy in units of cm3 by measuring ventricular expansion. The annual change in global PIB retention did not differ by clinical group (P = 0.90), and although small (median 0.042 ratio units/year overall) was greater than zero among all subjects (P < 0.001). Ventricular expansion rates differed by clinical group (P < 0.001) and increased in the following order: cognitively normal (1.3 cm3/year) <  amnestic mild cognitive impairment (2.5 cm3/year) <  Alzheimer's disease (7.7 cm3/year). Among all subjects there was no correlation between PIB change and concurrent change on CDR-SB (r = −0.01, P = 0.97) but some evidence of a weak correlation with MMSE (r =−0.22, P = 0.09). In contrast, greater rates of ventricular expansion were clearly correlated with worsening concurrent change on CDR-SB (r = 0.42, P < 0.01) and MMSE (r =−0.52, P < 0.01). Our data are consistent with a model of typical late onset Alzheimer's disease that has two main features: (i) dissociation between the rate of amyloid deposition and the rate of neurodegeneration late in life, with amyloid deposition proceeding at a constant slow rate while neurodegeneration accelerates and (ii) clinical symptoms are coupled to neurodegeneration not amyloid deposition. Significant plaque deposition occurs prior to clinical decline. The presence of brain amyloidosis alone is not sufficient to produce cognitive decline, rather, the neurodegenerative component of Alzheimer's disease pathology is the direct substrate of cognitive impairment and the rate of cognitive decline is driven by the rate of neurodegeneration. Neurodegeneration (atrophy on MRI) both precedes and parallels cognitive decline. This model implies a complimentary role for MRI and PIB imaging in Alzheimer's disease, with each reflecting one of the major pathologies, amyloid dysmetabolism and neurodegeneration.

Objectives-To correlate different methods of measuring rates of brain atrophy from serial MRI with corresponding clinical change in normal elderly subjects, patients with mild cognitive impairment (MCI), and probable Alzheimer's disease (AD).Methods-One-hundred sixty subjects were recruited from the Mayo Clinic AD Research Center and AD Patient Registry studies. At baseline 55 subjects were cognitively normal, 41 met criteria for MCI, and 64 met criteria for AD. Each subject went under an MRI examination of the brain at the time of the baseline clinical assessment and then again at the time of a follow-up clinical assessment, 1-5 years later. The annualized changes in volume of four structures were measured from the serial MRI studies -hippocampus, entorhinal cortex, whole brain, and ventricle. Rates of change on several cognitive tests/rating scales were also assessed. Subjects who were classified as normal or MCI at baseline could either remain stable or could convert to a lower functioning group. AD subjects were dichotomized into slow versus fast progressors.Results-All four atrophy rates were greater among normal subjects who converted to MCI or AD than those who remained stable; greater among MCI subjects who converted to AD than those who remained stable, and greater among fast than slow AD progressors. In general, atrophy on MRI was detected more consistently than decline on specific cognitive tests/rating scales._ With one exception, no differences were found among the four MRI rate measures in the strength of the correlation with clinical deterioration at different stages of the disease.Conclusions-These data support the use of rates of change from serial MR imaging studies in addition to standard clinical/psychometric measures as surrogate markers of disease progression in AD. Estimated sample sizes required to power a therapeutic trial in MCI were an order of magnitude less for MRI than for change measures based cognitive tests/rating scales.Psychometric tests and severity rating scales are the de facto gold standard for assessing disease progression in Alzheimer's disease (AD). Change measures from serial imaging studies have been proposed as an adjunctive surrogate marker of disease progression in AD with the expectation that imaging may provide better sensitivity and precision than standard clinical and psychometric measures(1-4). Various serial imaging approaches have been proposed including different structural magnetic resonance imaging (MRI) atrophy rate measures and also serial measures of glucose metabolism with positron emission tomography (PET). NIH Public Access Author ManuscriptNeurology. Author manuscript; available in PMC 2009 August 21. Published in final edited form as:Neurology. 2004 February 24; 62(4): 591-600. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript 5-9) The fact that different serial imaging approaches have been proposed for largely the same objective raises obvious questions. Which imaging approach is best? Do some imaging measures of p...

Objective A workgroup commissioned by the Alzheimer’s Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer’s disease (AD). We performed a preliminary assessment of these guidelines. Methods We employed Pittsburgh compound B positron emission tomography (PET) imaging as our biomarker of cerebral amyloidosis and 18fluorodeoxyglucose PET imaging and hippocampal volume as biomarkers of neurodegeneration. A group of 42 clinically diagnosed AD subjects was used to create imaging biomarker cut-points. A group of 450 cognitively normal (CN) subjects from a population based sample was used to develop cognitive cut-points and to assess population frequencies of the different preclinical AD stages using different cut-point criteria. Results The new criteria subdivide the preclinical phase of AD into stages 1–3. To classify our CN subjects, two additional categories were needed. Stage 0 denotes subjects with normal AD biomarkers and no evidence of subtle cognitive impairment. Suspected Non-AD Pathophysiology (SNAP) denotes subjects with normal amyloid PET imaging, but abnormal neurodegeneration biomarker studies. At fixed cut-points corresponding to 90% sensitivity for diagnosing AD and the 10th percentile of CN cognitive scores, 43% of our sample was classified as stage 0; 16% stage 1; 12 % stage 2; 3% stage 3; and 23% SNAP. Interpretation This cross-sectional evaluation of the NIA-AA criteria for preclinical AD indicates that the 1–3 staging criteria coupled with stage 0 and SNAP categories classify 97% of CN subjects from a population-based sample, leaving just 3% unclassified. Future longitudinal validation of the criteria will be important.

Subsystems within the default mode network are differentially affected in Alzheimer’s disease. Jones et al. present an in-depth analysis of changes within these subsystems and relate them to biomarker profiles across the Alzheimer’s disease spectrum. Results support a cascading network failure model of Alzheimer’s disease.

See Hansson and Mormino (doi:) for a scientific commentary on this article.Where should measurements be taken to best capture tau accumulation in ageing and Alzheimer’s disease? Jack et al. report that in clinically symptomatic stages of Alzheimer’s disease, tau accumulation occurs throughout the brain, rather than only in specific areas. Rate measurements from simple meta-regions of interest may be sufficient to capture progressive within-person tau accumulation.

Task-free functional magnetic resonance imaging (TF-fMRI) has great potential for advancing the understanding and treatment of neurologic illness. However, as with all measures of neural activity, variability is a hallmark of intrinsic connectivity networks (ICNs) identified by TF-fMRI. This variability has hampered efforts to define a robust metric of connectivity suitable as a biomarker for neurologic illness. We hypothesized that some of this variability rather than representing noise in the measurement process, is related to a fundamental feature of connectivity within ICNs, which is their non-stationary nature. To test this hypothesis, we used a large (n = 892) population-based sample of older subjects to construct a well characterized atlas of 68 functional regions, which were categorized based on independent component analysis network of origin, anatomical locations, and a functional meta-analysis. These regions were then used to construct dynamic graphical representations of brain connectivity within a sliding time window for each subject. This allowed us to demonstrate the non-stationary nature of the brain’s modular organization and assign each region to a “meta-modular” group. Using this grouping, we then compared dwell time in strong sub-network configurations of the default mode network (DMN) between 28 subjects with Alzheimer’s dementia and 56 cognitively normal elderly subjects matched 1∶2 on age, gender, and education. We found that differences in connectivity we and others have previously observed in Alzheimer’s disease can be explained by differences in dwell time in DMN sub-network configurations, rather than steady state connectivity magnitude. DMN dwell time in specific modular configurations may also underlie the TF-fMRI findings that have been described in mild cognitive impairment and cognitively normal subjects who are at risk for Alzheimer’s dementia.