Angela Y. Wang

The Alzheimer's Disease Neuroimaging Initiative 2 PET Core: 2015

This article reviews the work done in the Alzheimers Disease Neuroimaging Initiative positron emission tomography (ADNI PET) core over the past 5 years, largely concerning techniques, methods, and results related to amyloid imaging in ADNI.

Realizing the potential of positron emission tomography with 18F-fluorodeoxyglucose to improve the treatment of Alzheimer’s disease

Positron emission tomography (PET) with 18F‐fluorodeoxyglucose (FDG‐PET) thus far rarely has been used to advance the development of new treatments for Alzheimers disease (AD). Now that FDG‐PET with standard acquisition protocols for dementia is widely available, change in cerebral glucose metabolism is a feasible outcome variable for clinical drug trials. Individual analysis of FDG‐PET results also might prove valuable. FDG‐PET can detect metabolic changes very early in the course of AD and identify subjects for earlier treatment. FDG‐PET reliably distinguishes AD from frontotemporal dementia so that only those most likely to benefit are enrolled in trials. Finally, objectively identifying phenotypic variations of AD with FDG‐PET might have pathogenic and prognostic implications that can be used for personalized treatment approaches. The judicious use of FDG‐PET is needed to accelerate the evaluation of promising new drugs and more rationally target treatments for dementing diseases.

Genetic, structural and functional imaging biomarkers for early detection of conversion from MCI to AD

With the advent of advanced imaging techniques, genotyping, and methods to assess clinical and biological progression, there is a growing need for a unified framework that could exploit information available from multiple sources to aid diagnosis and the identification of early signs of Alzheimers disease (AD). We propose a modeling strategy using supervised feature extraction to optimally combine high-dimensional imaging modalities with several other low-dimensional disease risk factors. The motivation is to discover new imaging biomarkers and use them in conjunction with other known biomarkers for prognosis of individuals at high risk of developing AD. Our framework also has the ability to assess the relative importance of imaging modalities for predicting AD conversion. We evaluate the proposed methodology on the Alzheimers Disease Neuroimaging Initiative (ADNI) database to predict conversion of individuals with mild cognitive impairment (MCI) to AD, only using information available at baseline.

Amyloid Deposition and Cognition in Older Adults: The Effects of Premorbid Intellect

Although amyloid deposition remains a marker of the development of Alzheimers disease, results linking amyloid and cognition have been equivocal. Twenty-five community-dwelling non-demented older adults were examined with (18)F-flutemetamol, an amyloid imaging agent, and a cognitive battery, including an estimate of premorbid intellect and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). In the first model, (18)F-flutemetamol uptake significantly correlated with the Delayed Memory Index of the RBANS (r = -.51, p = .02) and premorbid intellect (r = .43, p = .03). In the second model, the relationship between (18)F-flutemetamol and cognition was notably stronger when controlling for premorbid intellect (e.g., three of the five RBANS Indexes and its Total score significantly correlated with (18)F-flutemetamol, rs = -.41 to -.58). Associations were found between amyloid-binding (18)F-flutemetamol and cognitive functioning in non-demented older adults. These associations were greatest with delayed memory and stronger when premorbid intellect was considered, suggesting that cognitive reserve partly compensates for the symptomatic expression of amyloid pathology in community-dwelling elderly.

Automatic classification of Alzheimer’s Disease vs. Frontotemporal dementia: A spatial decision tree approach with FDG-PET

We introduce a novel approach for the automatic classification of FDG-PET scans of subjects with Alzheimers disease (AD) and Frontotemporal dementia (FTD). Unlike previous work in the literature which focuses on principal component analysis and predefined regions of interest, we propose the combined use of information gain and spatial proximity to group cortical pixels into empirically determined regions that can best separate the two diseases. These regions are then used as attributes in a decision tree learning framework. We demonstrate that the proposed method provides better classification accuracy compared to other methods on a group of 48 autopsy confirmed AD and FTD patients.

Regression-to-pons normalization of FDG-PET improves discrimination of Alzheimer's disease from healthy aging

that both conditions have both gray matter and white matter pathologies and these conditions contribute to the neuropsychological characteristics and prognosis. We investigate the difference of cortical and temporal lobe gray and white matter atrophy in AD and SIVD with automatic and manual volumetry. Methods: Fifteen normal controls, fifteen probable AD patients, and fourteen demented patients met the MRI criteria of Erkinjuntti’s subcortical ischemic vascular dementia (SIVD) with neurological signs and symptoms were recruited. They underwent high-resolution T1-weighted volumetric MRI for the volumetry. Manual measurements of the gray and white matter volume in temporal lobe were performed by one rater with ANALYZE software and segmented gray matter image by using statistical parametric mapping 5(SPM5). For cortical gray matter and whole brain white matter (WBWM) volume measurement voxel-based morphometry analysis with SPM5 were used. All volumes were normalized to total intracranial volume for the statistical analysis. Results: Age, gender, and education level were not different among three groups. The Mini-Mental Status Examination (MMSE) and Clinical Dementia Rating (CDR) score were not different between AD and SIVD. Cortical gray matter (CGM) volume was smaller in SIVD but WBWM volume was smaller in AD patients. In temporal lobe, gray matter volume was significantly lower in AD patients on both sides compared to that of normal controls. But there were no differences of gray and white matter volumes between AD and SIVD. The MMSE and CDR score were significantly correlated with CGM volume than the temporal gray matter volume. No relationships were detected between MMSE score and WBWM volume or CDR score and WBWM volume. Conclusions: These findings suggest that subcortical ischemic white matter damage may affect CGM atrophy more than temporal lobe atrophy. CGM atrophy is more important than the WBWM atrophy for the general cognition and severity of dementia.

P2-101: Judgment of line orientation and FDG-PET parietal metabolism

patients with delusion and their age-sex-severity matched probable AD patients without delusion were underwent fluorodeoxy-glucose positron emission tomography (FDG-PET) scanning. Paranoid delusion was defined using Korean version of Behavior Rating Scale for Dementia (Youn et al., 2008). The mean differences in the regional cerebral glucose metabolism between paranoid and non-paranoid groups were estimated based on the results of voxel-by-voxel comparison using statistical parametric mapping (SPM2) and partial least square (PLS, McIntosh and Lobaugh, 2004). To identify the functional connectivity, seed-voxel PLS analysis was performed. Results: Neuropsychiatric symptoms other than paranoid delusion were not significantly different between AD patients with and without delusion. Paranoid delusion ( ) group had significantly decreased cerebral glucose metabolism in temporal area including left hippocampus (BA36, ,y,z -32,-24,-6), right parahippocampal gyrus (BA36, ,y,z 20,-40,12) and right inferior frontal gyrus (BA 47, ,y,z 58,38,-8) than paranoid delusion (-) group (p 0.05, uncorrected for SPM, p 0.01 for PLS). Seed-voxel PLS analysis using peak metabolic rates in the hippocampus and inferior frontal gyrus as seeds identified four different connectivity patterns (LV1-4). Paranoid delusion ( ) group was significantly correlated with LV 1 and LV 4, whereas paranoid delusion (-) group was significantly correlated with LV 2 and LV 3 (p 0.001). Conclusions: This study showed that altered functional connectivity of frontal and temporal lobe was important for the development of paranoid delusion in AD.

IC-P3-179: Quantifying metabolic asymmetry in Alzheimer's disease using both MR and PET imaging

been modeled previously and include pool-specific T1 and T2 values (T1,F, T1,S, T2,F, T2,S) and volume fractions (fF, fS) as free parameters, allowing their estimation from multi-flip angle SPGR and SSFP data. For in vivo demonstration, whole-brain data were acquired of 4 healthy volunteers on a 1.5T Siemens Sonata clinical scanner. Imaging parameters were: 22cm2 16cm field of view, 256x160x118 matrix, SPGR: TE/TR 3.1ms/6.5ms, angles 2° through 18° in 2° increments; SSFP: TE/TR 2.3ms/4.6ms, angles 6° though 70° in 8° increments. Results: Images through the T1,F, T1,S, T2,F, T2,S and myelin fraction maps are shown in Fig. 1. Mean values obtained from different brain regions are shown in Fig. 2 and agree well with previous literature reports.

IC-P2-098: Frequency of hemispheric metabolic asymmetry in probable Alzheimer's disease

Norman L. Foster, Angela Y. Wang, James A. Levy, Robert A. Koeppe, William J. Jagust, Kewei Chen, Eric M. Reiman, Michael W. Weiner, University of Utah, Salt Lake City, UT, USA; University of Michigan, Ann Arbor, MI, USA; University of California, Berkeley, Berkeley, CA, USA; Banner Alzheimer’s Institute, Phoenix, AZ, USA; University of California, San Francisco, San Francisco, CA, USA. Contact e-mail: norman.foster@hsc.utah.edu