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ObjectiveTo study longitudinal relationships between type 2 diabetes mellitus (T2DM), cortical thickness, and cognitive function in older people with normal cognition, mild cognitive impairment, and Alzheimer disease (AD).MethodsThe sample was derived from the Alzheimer's Disease Neuroimaging Initiative cohort who underwent brain MRI and cognitive tests annually for 5 years. Presence of T2DM was based on fasting blood glucose ≥7.0mml/L or the use of glucose-lowering agents. We used latent growth curve modeling to explore longitudinal relationships between T2DM, cortical thickness, and cognitive function, adjusting for relevant covariates and testing for interactions.ResultsThere were 124 people with T2DM (mean age 75.5 years, SD 6.2) and 693 without T2DM (mean age 75.1 years, SD 6.9) with at least 1 MRI available. AD and lower cortical thickness at study entry was associated with a lower chance of having a MRI available at each follow-up phase (all p < 0.001). T2DM was associated with lower baseline cortical thickness (p = 0.01). We found no direct effect of T2DM on decline in cortical thickness or cognitive function, but there was an indirect pathway linking T2DM and cognitive decline via baseline cortical thickness (β = −0.17, p = 0.022). There was an interaction between T2DM and education whereby the negative effect of T2DM on baseline cortical thickness was reduced in those with greater education (β = 0.34, p = 0.037). These associations changed minimally when adjusted for baseline cognitive diagnosis.ConclusionsIn an older cohort with low cerebrovascular disease burden, T2DM contributes to cognitive decline via neurodegeneration. Prior brain and cognitive reserve may protect against this effect.

It is unclear whether self- or informant-based subjective cognition better distinguishes emotional factors from early-stage Alzheimer's disease (AD).Healthy members (n = 447) of the Arizona apolipoprotein E (APOE) cohort and their informants completed the self and informant paired Multidimensional Assessment of Neurodegenerative Symptoms questionnaire (MANS).Decline on the MANS was endorsed by 30.6% of members and 26.2% of informants. Self- and informant-based decliners had higher scores of psychological distress and slightly lower cognitive scores than nondecliners. Over the next 6.7 years, 20 developed mild cognitive impairment (MCI). Converters were older at entry than nonconverters (63.8 [7.0] vs 58.8 [7.3] years, P = .003), 85% were APOE ε4 carriers (P.0001), and they self-endorsed decline earlier than informants (58.9 [39.2] vs 28.0 [40.4] months before MCI; P = .002).Self- and informant-based subjective decline correlated with greater psychological distress and slightly lower cognitive performance. Those with incident MCI generally self-endorsed decline earlier than informants.

BACKGROUND Diffuse intrinsic brainstem gliomas (DIBSGs) in children remain difficult tumors to treat and have a very poor prognosis. Intensifying both chemotherapy and radiation programs have been attempted without success. Positron emission tomography (PET) has been used to differentiate benign from malignant tumors and may predict outcome. OBJECTIVES To determine whether PET can characterize a specific metabolic pattern of DIBSGs and correlate this with patient survival. METHODS We conducted a retrospective review of patients with DIBSGs and PET scans at diagnosis. Data for ¹⁸[F] fluorodeoxyglucose (FDG) and ¹¹C-methionine (CMET) PET scans were collected. Treatment and survival were reviewed. RESULTS We identified 30 patients with DIBSGs, 25 of whom had FDG and/or CMET PET scans. Scans showed both focal and generalized metabolic activity, and the patterns showed no correlation with survival. Patients with both FDG and CMET positive scans had a mean survival of 380 days, whereas those negative for both isotopes had a mean survival of 446 days. CONCLUSIONS There was no specific PET pattern identified in this DIBSG cohort but a trend toward improved survival was noted with absence of FDG and CMET metabolism. Metabolically active areas may suggest potential sites for biopsy. We believe that biopsy is essential for improving therapy for this patient population.

Here we report the first multi-center clinical trial in Alzheimer's disease (AD) using fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) measures of brain glucose metabolism as the primary outcome. We contrasted effects of 12 months treatment with the PPARγ agonist Rosiglitazone XR versus placebo in 80 mild to moderate AD patients. Secondary objectives included testing for reduction in the progression of brain atrophy and improvement in cognition. Active treatment was associated with a sustained but not statistically significant trend from the first month for higher mean values in Kiindex and CMRgluindex, novel quantitative indices related to the combined forward rate constant for [18F]FDG uptake and to the rate of cerebral glucose utilization, respectively. However, neither these nor another analytical approach recently validated using data from the Alzheimer's Disease Neuroimaging Initiative indicated that active treatment decreased the progression of decline in brain glucose metabolism. Rates of brain atrophy were similar between active and placebo groups and measures of cognition also did not suggest clear group differences. Our study demonstrates the feasibility of using [18F]FDG-PET as part of a multi-center therapeutics trial. It suggests that Rosiglitazone is associated with an early increase in whole brain glucose metabolism, but not with any biological or clinical evidence for slowing progression over a 1 year follow up in the symptomatic stages of AD.

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 1,000 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.

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.

Background This is a progress report of the Alzheimer's Disease Neuroimaging Initiative (ADNI) positron emission tomography (PET) Core. Methods The Core has supervised the acquisition, quality control, and analysis of longitudinal [ 18 F]fluorodeoxyglucose PET (FDG-PET) data in approximately half of the ADNI cohort. In an "add on" study, approximately 100 subjects also underwent scanning with [ 11 C] Pittsburgh compound B PET for amyloid imaging. The Core developed quality control procedures and standardized image acquisition by developing an imaging protocol that has been widely adopted in academic and pharmaceutical industry studies. Data processing provides users with scans that have identical orientation and resolution characteristics despite acquisition on multiple scanner models. The Core labs have used many different approaches to characterize differences between subject groups (Alzheimer's disease, mild cognitive impairment, controls), to examine longitudinal change over time in glucose metabolism and amyloid deposition, and to assess the use of FDG-PET as a potential outcome measure in clinical trials. Results ADNI data indicate that FDG-PET increases statistical power over traditional cognitive measures, might aid subject selection, and could substantially reduce the sample size in a clinical trial. Pittsburgh compound B PET data showed expected group differences, and identified subjects with significant annual increases in amyloid load across the subject groups. The next activities of the PET core in ADNI will entail developing standardized protocols for amyloid imaging using the [ 18 F]-labeled amyloid imaging agent AV45, which can be delivered to virtually all ADNI sites. Conclusions ADNI has demonstrated the feasibility and utility of multicenter PET studies and is helping to clarify the role of biomarkers in the study of aging and dementia.

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.

Study Objectives: To test the hypothesis that healthy adults reporting dream-enactment behavior (DEB+) have reduced cerebral metabolic rate for glucose (CMRgl) in regions preferentially affected in patients with dementia with Lewy bodies (DLB). Design: Automated brain-mapping algorithms were used to compare regional fluorodeoxyglucose (FDG) positron emission tomography (PET) measurements from previously evaluated DEB cases and controls. Setting: Tertiary-care academic medical centers. Participants: Seventeen cognitively normal patients with DEB+ and 17 control subjects (DEB-) who were individually matched for age (59 ± 11 years), education level (16 ± 4 years), sex (67% women), body mass index (26 ± 4.8 kg/m 2 ), first-degree relative with dementia (85%), and proportion of apolipoprotein E (APOE) e4 carriers (13 e4 carriers, 4 noncarriers). Interventions: FDG-PET. Measurements and Results: DEB was associated with significantly lower CMRgI in several brain regions known to be preferentially affected in both DLB and Alzheimer disease (parietal, temporal, and posterior cingulate cortexes) and in several other regions, including the anterior cingulate cortex (p

AMYLOID PETMEASUREMENTS AND EVALUATE AMYLOID-MODIFYING TREATMENTS USING A CEREBRALWHITE MATTER REFERENCE REGION-OF-INTEREST Kewei Chen, Auttawut Roontiva, Pradeep Thiyyagura, Wendy Lee, Xiaofen Liu, Napatkamon Ayutyanont, Hillary Protas, Susan Landau, Ji Luo, Robert Bauer, III,, Cole Reschke, Dan Bandy, Robert Koeppe, Adam S. Fleisher, Richard J. Caselli, William Jagust, Michael Walter Weiner, Eric M. Reiman, Banner Alzheimer’s Institute, Arizona State University, Arizona Alzheimer’s Consortium, Phoenix, Arizona, United States; 2 Banner Alzheimer’s Institute, Arizona Alzheimer’s Consortium, Phoenix, Arizona, United States; Banner Alzheimer’s Institute, Arizona Alzheimer’s Consortium, Phoenix, Arizona, United States; 4 Banner Alzheimer’s Institute, Arizona Alzheimer’s Consortium, Phoenix, Arizona, United States; 5 University of California, Berkeley, Berkeley, California, United States; Banner Alzheimer’s Institute, Arizona Alzheimer’s Consortium, Phoenix, Arizona, United States; Banner Alzheimers Institute, Arizona Alzheimer’s Consortium, Phoenix, Arizona, United States; University of Michigan, Ann Arbor, Michigan, United States; Banner Alzheimer’s Institute, Eli Lilly & Co, Arizona Alzheimer’s Consortium, Phoenix, Arizona, United States; 10 Mayo Clinic, Arizona Alzheimer’s Consortium, Scottsdale, Arizona, United States; 11 Center for Imaging of Neurodegenerative Diseases, VAMedical Center and UCSF, San Francisco, California, United States; Banner Alzheimer’s Institute, University of Arizona, Translational Genomics Research Institute, Phoenix, Arizona, United States. Contact e-mail: kewei.chen@bannerhealth.com

P1-358 FLORBETAPIR PET, FDG-PETAND MRI IN PEOPLE WITH DOWN SYNDROME WITH AND WITHOUT SYMPTOMATIC ALZHEIMER’S DISEASE Marwan Sabbagh, Kewei Chen, Jospeh Rogers, Carolyn Liebsack, Dan Bandy, Christine Belden, Adam Fleischer, Pradeep Thiyyagura, Xioafen Liu, Stephanie Parks, Sandra Jacobson, Michael MalekAhmadi, Eric Reiman, Banner Sun Health Research Institute, Sun City, Arizona, United States; Banner Alzheimer’s Institute, Phoenix, Arizona, United States; Banner Sun Health Research Institute, Sun City, Arizona, United States; Banner Research Institute, Sun City, Arizona, United States. Contact e-mail: marwan.sabbagh@bannerhealth.com

Memory distortions and illusions have been thoroughly documented in psychological studies, but little is known about the neuroanatomical correlates of true and false memories. Vivid but illusory memories can be induced by asking people whether they recall or recognize words that were not previously presented, but are semantically related to other previously presented words. We used positron emission tomography to compare brain regions involved in veridical recognition of printed words that were heard several minutes earlier and illusory recognition of printed words that had not been heard earlier. Veridical and illusory recognition were each associated with blood flow increases in a left medial temporal region previously implicated in episodic memory; veridical recognition was distinguished by additional blood flow increases in a left temporoparietal region previously implicated in the retention of auditory/phonological information. This study reveals similarities and differences in the way the brain processes accurate and illusory memories.

Objective: To investigate predictors of missing data in a longitudinal study of Alzheimer disease (AD). Methods: The Alzheimer9s Disease Neuroimaging Initiative (ADNI) is a clinic-based, multicenter, longitudinal study with blood, CSF, PET, and MRI scans repeatedly measured in 229 participants with normal cognition (NC), 397 with mild cognitive impairment (MCI), and 193 with mild AD during 2005–2007. We used univariate and multivariable logistic regression models to examine the associations between baseline demographic/clinical features and loss of biomarker follow-ups in ADNI. Results: CSF studies tended to recruit and retain patients with MCI with more AD-like features, including lower levels of baseline CSF Aβ 42 . Depression was the major predictor for MCI dropouts, while family history of AD kept more patients with AD enrolled in PET and MRI studies. Poor cognitive performance was associated with loss of follow-up in most biomarker studies, even among NC participants. The presence of vascular risk factors seemed more critical than cognitive function for predicting dropouts in AD. Conclusion: The missing data are not missing completely at random in ADNI and likely conditional on certain features in addition to cognitive function. Missing data predictors vary across biomarkers and even MCI and AD groups do not share the same missing data pattern. Understanding the missing data structure may help in the design of future longitudinal studies and clinical trials in AD.

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 (p1 × 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.

Here we report the first multi-center clinical trial in Alzheimer's disease (AD) using fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) measures of brain glucose metabolism as the primary outcome. We contrasted effects of 12 months treatment with the PPARγ agonist Rosiglitazone XR versus placebo in 80 mild to moderate AD patients. Secondary objectives included testing for reduction in the progression of brain atrophy and improvement in cognition. Active treatment was associated with a sustained but not statistically significant trend from the first month for higher mean values in Kiindex and CMRgluindex, novel quantitative indices related to the combined forward rate constant for [18F]FDG uptake and to the rate of cerebral glucose utilization, respectively. However, neither these nor another analytical approach recently validated using data from the Alzheimer's Disease Neuroimaging Initiative indicated that active treatment decreased the progression of decline in brain glucose metabolism. Rates of brain atrophy were similar between active and placebo groups and measures of cognition also did not suggest clear group differences. Our study demonstrates the feasibility of using [18F]FDG-PET as part of a multi-center therapeutics trial. It suggests that Rosiglitazone is associated with an early increase in whole brain glucose metabolism, but not with any biological or clinical evidence for slowing progression over a 1 year follow up in the symptomatic stages of AD.

The standardized uptake value ratio (SUVR) provides a semi-quantitative index of fibrillar amyloid deposition, a neuropathological feature of Alzheimer's disease (AD), in Pittsburgh Compound B (PIB) PET studies. As accurately identifying individual probable AD patients and subjects at increased risk for AD is of clinical use, we developed the classification model based on SUVR of several ADassociated brain regions to distinguish normal subjects with different APOE genotypes, the major AD genetic risk factor, and probable AD patients. After normalizing PIB PET scans to standard brain template coordinate space, SUVR was computed for 8 brain regions: frontal, posterior cingulate-precuneus, lateral temporal, lateral parietal, and basal ganglia, medial temporal, occipital, and a mean cortical region (consisting of frontal, posterior cingulate-precuneus and lateral temporal region). These regions were defined using anatomical automated labeling toolbox in SPM5. 70% of the subjects were randomly partitioned for training, with remaining 30% for testing. The Artificial Neural Network (ANN) is then applied to the SUVR data to classify the subjects into three groups: low risk (APOE non-carriers), high risk (APOE carriers) and certain (probable AD patients). The process of data partitioning and ANN training/testing was repeated 3 times. ANN was found to classify the subjects into these three groups with the average accuracy of 100% and 95.2% in training and testing respectively. ANN is a promising multivariate-based alternative to discriminate among normal subjects with different APOE genotypes and probable AD patients and is potentially useful in evaluating the change in risk profile of the individual subject.

Eric M. Reiman, Kewei Chen, Napatkamon Ayutyanont, Wendy Lee, Dan Bandy, Cole Reschke, Gene E. Alexander, Michael W. Weiner, Robert A. Koeppe, Norman L. Foster, William J. Jagust, Banner Alzheimer’s Institute, Arizona Alzheimer’s Consortium, Translational Genomics Research Institute, Phoenix, AZ, USA; University of Arizona, Tucson, AZ, USA; Banner Alzheimer’s Institute, Phoenix, AZ, USA; Arizona Alzheimer’s Consortium, Phoenix, AZ, USA; University of California, San Francisco, CA, USA; University of Michigan, Ann Arbor, MI, USA; University of Utah, Salt Lake City, UT, USA; University of California, Berkeley, CA, USA. Contact e-mail: Eric.Reiman@bannerhealth.com

BACKGROUNDWe introduced a hypometabolic convergence index (HCI) to characterize in a single measurement the extent to which a person's fluorodeoxyglucose positron emission tomogram (FDG PET) corresponds to that in Alzheimer's disease (AD). Apolipoprotein E ε4 (APOE ε4) gene dose is associated with three levels of risk for late-onset AD. We explored the association between gene dose and HCI in cognitively normal ε4 homozygotes, heterozygotes, and non-carriers.METHODSAn algorithm was used to characterize and compare AD-related HCIs in cognitively normal individuals, including 36 ε4 homozygotes, 46 heterozygotes, and 78 non-carriers.RESULTSThese three groups differed significantly in their HCIs (ANOVA, p = 0.004), and there was a significant association between HCIs and gene dose (linear trend, p = 0.001).CONCLUSIONSThe HCI is associated with three levels of genetic risk for late-onset AD. This supports the possibility of using a single FDG PET measurement to help in the preclinical detection and tracking of AD.