학술논문

Semiautomated Assessment of the Anterior Cingulate Cortex in Alzheimer's Disease
Document Type
Disease/Disorder overview
Source
Journal of Neuroimaging. May-June 2019, Vol. 29 Issue 3, p376, 7 p.
Subject
Brain
Alzheimer's disease
Pharmaceutical industry
Language
English
ISSN
1051-2284
Abstract
BACKGROUND AND PURPOSE The anterior cingulate cortex (ACC) is involved in several cognitive processes including executive function. Degenerative changes of ACC are consistently seen in Alzheimer's disease (AD). However, volumetric changes specific to the ACC in AD are not clear because of the difficulty in segmenting this region. The objectives of the current study were to develop a precise and high-throughput approach for measuring ACC volumes and to correlate the relationship between ACC volume and cognitive function in AD. METHODS Structural T.sub.1-weighted magnetic resonance images of AD patients (n = 47) and age-matched controls (n = 47) at baseline and at 24 months were obtained from the Alzheimer's disease neuroimaging initiative (ADNI) database and studied using a custom-designed semiautomated segmentation protocol. RESULTS ACC volumes obtained using the semiautomated protocol were highly correlated to values obtained from manual segmentation (r = .98) and the semiautomated protocol was considerably faster. When comparing AD and control subjects, no significant differences were observed in baseline ACC volumes or in change in ACC volumes over 24 months using the two segmentation methods. However, a change in ACC volume over 24 months did not correlate with a change in mini-mental state examination scores. CONCLUSIONS Our results indicate that the proposed semiautomated segmentation protocol is reliable for determining ACC volume in neurodegenerative conditions including AD. Article Note: Acknowledgments: This project was supported by funds from Natural Science and Engineering Research Council of Canada-Discovery Grant to N.R. Data used in the preparation of this article were obtained from the Alzheimer's disease neuroimaging initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at http://adni.loni.usc.edu/wpcontent/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. Data collection and sharing for this project was funded by ADNI, NIH (U01-AG024904), and DOD (award W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; Hoffmann-La Roche Ltd and its affiliated Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy R & D; Johnson & Johnson Pharmaceutical R & D; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The CIHR provides funds to support ADNI clinical sites in Canada. The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. Conflicts of Interest: The authors declare no conflicts of interest.