NDLI: Automated 3D Mapping of Hippocampal Atrophy and its Clinical Correlates in 400 Subjects with Alzheimer’s Disease, Mild Cognitive Impairment, and Elderly Controls

Content Provider	PubMed Central
Author	Morra, Jonathan H. Tu, Zhuowen Apostolova, Liana G. Green, Amity E. Avedissian, Christina Madsen, Sarah K. Parikshak, Neelroop Hua, Xue Toga, Arthur W. Jack, Clifford R. Schuff, Norbert Weiner, Michael W. Thompson, Paul M.
Abstract	We used a new method we developed for automated hippocampal segmentation, called the auto context model (ACM), to analyze brain MRI scans of 400 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). After training the classifier on 21 hand-labeled expert segmentations, we created binary maps of the hippocampus for three age- and sex-matched groups: 100 subjects with Alzheimer’s disease (AD), 200 with mild cognitive impairment (MCI) and 100 elderly controls (mean age: 75.84; SD: 6.64). Hippocampal traces were converted to parametric surface meshes and a radial atrophy mapping technique was used to compute average surface models and local statistics of atrophy. Surface-based statistical maps visualized links between regional atrophy and diagnosis (MCI versus controls: p = 0.008; MCI versus AD: p = 0.001), mini-mental state exam (MMSE) scores, and global and sum-of-boxes clinical dementia rating scores (CDR; all p < 0.0001, corrected). Right but not left hippocampal atrophy was associated with geriatric depression scores (p = 0.004, corrected); hippocampal atrophy was not associated with subsequent decline in MMSE and CDR scores, educational level, ApoE genotype, systolic or diastolic blood pressure measures, or homocysteine. We gradually reduced sample sizes and used false discovery rate curves to examine the method’s power to detect associations with diagnosis and cognition in smaller samples. 40 subjects were sufficient to discriminate AD from normal and correlate atrophy with CDR scores; 104, 200 and 304 subjects, respectively, were required to correlate MMSE with atrophy, to distinguish MCI from normal, and MCI from AD.
Related Links	http://dx.doi.org/10.1002/hbm.20708
Ending Page	2788
Page Count	23
Starting Page	2766
File Format	PDF
ISSN	10659471
e-ISSN	10970193
Journal	Human brain mapping
Issue Number	9
Volume Number	30
Language	English
Publisher Date	2009-09-01
Access Restriction	Open
Subject Keyword	Anatomy Radiological and Ultrasound Technology Radiology Nuclear Medicine and imaging Neurology Clinical Neurology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Anatomy Neurology Radiology, Nuclear Medicine and Imaging Neurology (clinical) Radiological and Ultrasound Technology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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