Linked Life Data

19277975

Source:http://linkedlifedata.com/resource/pubmed/id/19277975

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2009-9-21
pubmed:abstractText
Noninvasive MRI biomarkers for Alzheimer's disease (AD) may enable earlier clinical diagnosis and the monitoring of therapeutic effectiveness. To assess potential neuroimaging biomarkers, the Alzheimer's Disease Neuroimaging Initiative is following normal controls (NC) and individuals with mild cognitive impairment (MCI) or AD. We applied high-throughput image analyses procedures to these data to demonstrate the feasibility of detecting subtle structural changes in prodromal AD. Raw DICOM scans (139 NC, 175 MCI, and 84 AD) were downloaded for analysis. Volumetric segmentation and cortical surface reconstruction produced continuous cortical surface maps and region-of-interest (ROI) measures. The MCI cohort was subdivided into single- (SMCI) and multiple-domain MCI (MMCI) based on neuropsychological performance. Repeated measures analyses of covariance were used to examine group and hemispheric effects while controlling for age, sex, and, for volumetric measures, intracranial vault. ROI analyses showed group differences for ventricular, temporal, posterior and rostral anterior cingulate, posterior parietal, and frontal regions. SMCI and NC differed within temporal, rostral posterior cingulate, inferior parietal, precuneus, and caudal midfrontal regions. With MMCI and AD, greater differences were evident in these regions and additional frontal and retrosplenial cortices; evidence for non-AD pathology in MMCI also was suggested. Mesial temporal right-dominant asymmetries were evident and did not interact with diagnosis. Our findings demonstrate that high-throughput methods provide numerous measures to detect subtle effects of prodromal AD, suggesting early and later stages of the preclinical state in this cross-sectional sample. These methods will enable a more complete longitudinal characterization and allow us to identify changes that are predictive of conversion to AD.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1097-0193
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
30
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
3238-53
pubmed:dateRevised
2010-12-3
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Structural MRI biomarkers for preclinical and mild Alzheimer's disease.
pubmed:affiliation
Department of Psychiatry, University of California, San Diego, La Jolla, California 92093-0841, USA. fennema@ucsd.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural