Linked Life Data

15488407

Source:http://linkedlifedata.com/resource/pubmed/id/15488407

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2004-10-18
pubmed:abstractText
Manual segmentation of the hippocampus is the gold standard in volumetric hippocampal magnetic resonance imaging (MRI) analysis; however, this is difficult to achieve reproducibly. This study explores whether application of local registration and calculation of the hippocampal boundary shift integral (HBSI) can reduce random variation compared with manual measures. Hippocampi were outlined on the baseline and registered-repeat MRIs of 32 clinically diagnosed Alzheimer's disease (AD) patients and 47 matched controls (37-86 years) with a wide range of scanning intervals (175-1173 days). The scans were globally registered using 9 degrees of freedom and subsequently locally registered using 6 degrees of freedom and HBSI was then calculated automatically. HBSI significantly reduced the mean rate (P < 0.01) and variation in controls (P < 0.001) and increased group separation between AD cases and controls. When comparing HBSI atrophy rates with manually derived atrophy rates at 90% sensitivity, specificities were 98% and 81%, respectively. From logistic regression models, a 1% increase in HBSI atrophy rates was associated with an 11-fold (CI 3, 36) increase in the odds of a diagnosis of AD. For manually derived atrophy rates, the equivalent odds ratio was 3 (CI 2,4). We conclude that HBSI-derived atrophy rates reduce operator time and error, and are at least as effective as the manual equivalent as a diagnostic marker and are a potential marker of progression in longitudinal studies and trials.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1053-8119
pubmed:author
pubmed:issnType
Print
pubmed:volume
23
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
574-81
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Differentiating AD from aging using semiautomated measurement of hippocampal atrophy rates.
pubmed:affiliation
Dementia Research Centre, Institute of Neurology, University College London, 8-11 Queen Square, WCIN 3BG, London, UK. j.barnes@dementia.ion.ucl.ac.uk
pubmed:publicationType
Journal Article, Clinical Trial, Research Support, Non-U.S. Gov't