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      Contributions of imprecision in PET‐MRI rigid registration to imprecision in amyloid PET SUVR measurements

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          Abstract

          Quantitative measurement of β‐amyloid from amyloid PET scans typically relies on localizing target and reference regions by image registration to MRI. In this work, we present a series of simulations where 50 small random perturbations of starting location and orientation were applied to each subject's PET scan, and rigid registration using spm_coreg was performed between each perturbed PET scan and its corresponding MRI. We then measured variation in the output PET‐MRI registrations and how this variation affected the resulting SUVR measurements. We performed these experiments using scans of 1196 participants, half using 18F florbetapir and half using 11C PiB. From these experiments, we measured the magnitude of the imprecision in the rigid registration steps used to localize measurement regions, and how this contributes to the overall imprecision in SUVR measurements. Unexpectedly, we found for both tracers that the imprecision in these measurements depends on the degree of amyloid tracer uptake, and thus also indirectly on Alzheimer's disease clinical status. We then examined common choices of reference regions, and we show that SUVR measurements using supratentorial white matter references are relatively resistant to this source of error. We also show that the use of partial volume correction further magnifies the effects of registration imprecision on SUVR measurements. Together, these results suggest that this rigid registration step is an attractive target for future work in improving measurement techniques. Hum Brain Mapp 38:3323–3336, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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          The Mayo Clinic Study of Aging: Design and Sampling, Participation, Baseline Measures and Sample Characteristics

          Background: The objective of this study was to establish a prospective population-based cohort to investigate the prevalence, incidence and risk factors for mild cognitive impairment (MCI) and dementia. Methods: The Olmsted County, Minn., population, aged 70–89 years on October 1, 2004, was enumerated using the Rochester Epidemiology Project. Eligible subjects were randomly selected and invited to participate. Participants underwent a comprehensive in-person evaluation including the Clinical Dementia Rating Scale, a neurological evaluation and neuropsychological testing. A consensus diagnosis of normal cognition, MCI or dementia was made by a panel using previously published criteria. A subsample of subjects was studied via telephone interview. Results: Four hundred and two subjects with dementia were identified from a detailed review of their medical records but were not contacted. At baseline, we successfully evaluated 703 women aged 70–79 years, 769 women aged 80–89 years, 730 men aged 70–79 years and 517 men aged 80–89 years (total n = 2,719). Among the participants, 2,050 subjects were evaluated in person and 669 via telephone. Conclusions: Strengths of the study are that the subjects were randomly selected from a defined population, the majority of the subjects were examined in person, and MCI was defined using published criteria. Here, we report the design and sampling, participation, baseline measures and sample characteristics.
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            Prevalence of mild cognitive impairment is higher in men. The Mayo Clinic Study of Aging.

            We investigated the prevalence of mild cognitive impairment (MCI) in Olmsted County, MN, using in-person evaluations and published criteria. We evaluated an age- and sex-stratified random sample of Olmsted County residents who were 70-89 years old on October 1, 2004, using the Clinical Dementia Rating Scale, a neurologic evaluation, and neuropsychological testing to assess 4 cognitive domains: memory, executive function, language, and visuospatial skills. Information for each participant was reviewed by an adjudication panel and a diagnosis of normal cognition, MCI, or dementia was made using published criteria. Among 1,969 subjects without dementia, 329 subjects had MCI, with a prevalence of 16.0% (95% confidence interval [CI] 14.4-17.5) for any MCI, 11.1% (95% CI 9.8-12.3) for amnestic MCI, and 4.9% (95% CI 4.0-5.8) for nonamnestic MCI. The prevalence of MCI increased with age and was higher in men. The prevalence odds ratio (OR) in men was 1.54 (95% CI 1.21-1.96; adjusted for age, education, and nonparticipation). The prevalence was also higher in subjects who never married and in subjects with an APOE epsilon3epsilon4 or epsilon4epsilon4 genotype. MCI prevalence decreased with increasing number of years of education (p for linear trend <0.0001). Our study suggests that approximately 16% of elderly subjects free of dementia are affected by MCI, and amnestic MCI is the most common type. The higher prevalence of MCI in men may suggest that women transition from normal cognition directly to dementia at a later age but more abruptly.
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              The Alzheimer's Disease Neuroimaging Initiative positron emission tomography core.

              This is a progress report of the Alzheimer's Disease Neuroimaging Initiative (ADNI) positron emission tomography (PET) Core. 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. 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. 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. Copyright 2010 The Alzheimer
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                Author and article information

                Contributors
                schwarz.christopher@mayo.edu
                Journal
                Hum Brain Mapp
                Hum Brain Mapp
                10.1002/(ISSN)1097-0193
                HBM
                Human Brain Mapping
                John Wiley and Sons Inc. (Hoboken )
                1065-9471
                1097-0193
                22 April 2017
                July 2017
                : 38
                : 7 ( doiID: 10.1002/hbm.v38.7 )
                : 3323-3336
                Affiliations
                [ 1 ] Department of Radiology Mayo Clinic and Foundation Rochester Minnesota
                [ 2 ] Department of Neurology Mayo Clinic and Foundation Rochester Minnesota
                [ 3 ] Department of Information Technology Mayo Clinic and Foundation Rochester Minnesota
                Author notes
                [*] [* ]Correspondence to: Christopher G. Schwarz, Ph.D., Mayo Clinic, Diagnostic Radiology, 200 First Street SW, Rochester, MN, 55905. E‐mail: schwarz.christopher@ 123456mayo.edu
                Author information
                http://orcid.org/0000-0002-1466-8357
                Article
                HBM23622
                10.1002/hbm.23622
                5518286
                28432784
                2b45669d-ba9c-4cfa-b363-4dcef564eb9f
                © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

                This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 07 December 2016
                : 06 April 2017
                : 09 April 2017
                Page count
                Figures: 8, Tables: 1, Pages: 14, Words: 8862
                Funding
                Funded by: NIH grants
                Award ID: R01 AG011378, R00 AG37573, R01 AG041851, U01 AG24904, U01 AG06786, P50 AG16574, R01 AG034676
                Funded by: The Alexander Family Professorship of Alzheimer's Disease Research, Mayo Clinic; the GHR Foundation
                Funded by: Elsie and Marvin Dekelboum Family Foundation
                Categories
                Technical Report
                Technical Report
                Custom metadata
                2.0
                hbm23622
                July 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.1.4 mode:remove_FC converted:20.07.2017

                Neurology
                reproducibility of results,alzheimer disease,positron‐emission tomography,image processing,computer‐assisted,amyloid,florbetapir,pittsburgh compound b

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