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PMID: 20034579 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Robust atrophy rate measurement in Alzheimer's disease using multi-site serial MRI: tissue-specific intensity normalization and parameter selection.

NeuroImage ·Vol. 50 ·No. 2 ·2010-04-01 ·Pages 516-23

Leung KK, Clarkson MJ, Bartlett JW, Clegg S, Jack CR, Weiner MW, Fox NC, Ourselin S, Alzheimer's Disease Neuroimaging Initiative

Abstract

We describe an improved method of measuring brain atrophy rates from serial MRI for multi-site imaging studies of Alzheimer's disease (AD). The method (referred to as KN-BSI) improves an existing brain atrophy measurement technique-the boundary shift integral (classic-BSI), by performing tissue-specific intensity normalization and parameter selection. We applied KN-BSI to measure brain atrophy rates of 200 normal and 141 AD subjects using baseline and 1-year MRI scans downloaded from the Alzheimer's Disease Neuroimaging Initiative database. Baseline and repeat images were reviewed as pairs by expert raters and given quality scores. Including all image pairs, regardless of quality score, mean KN-BSI atrophy rates were 0.09% higher (95% CI 0.03% to 0.16%, p=0.007) than classic-BSI rates in controls and 0.07% higher (-0.01% to 0.16%, p=0.07) higher in ADs. The SD of the KN-BSI rates was 22% lower (15% to 29%, p<0.001) in controls and 13% lower (6% to 20%, p=0.001) in ADs, compared to classic-BSI. Using these results, the estimated sample size (needed per treatment arm) for a hypothetical trial of a treatment for AD (80% power, 5% significance to detect a 25% reduction in atrophy rate) would be reduced from 120 to 81 (a 32% reduction, 95% CI=18% to 45%, p<0.001) when using KN-BSI instead of classic-BSI. We concluded that KN-BSI offers more robust brain atrophy measurement than classic-BSI and substantially reduces sample sizes needed in clinical trials.

Keywords
Alzheimer’s disease Atrophy BSI Boundary shift integral Intensity normalization KN-BSI MRI
MeSH Terms
Aged Alzheimer Disease/pathology Atrophy/pathology Brain/pathology Humans Image Interpretation, Computer-Assisted/methods Magnetic Resonance Imaging/methods
Authors & Affiliations
9 authors, click to expand affiliations / ORCID
Leung Kelvin K
Dementia Research Centre (DRC), Institute of Neurology, University College London, London, UK. [email protected]
Clarkson Matthew J
Bartlett Jonathan W
Clegg Shona
Jack Clifford R
Weiner Michael W
Fox Nick C
Ourselin Sébastien
Alzheimer's Disease Neuroimaging Initiative
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Article Info
Journal
NeuroImage
Abbr.
Neuroimage
ISSN
1095-9572
Published
2010-04-01
Epub
2009-00-23
Pages
516-23
Language
English
Region
United States
NLM ID
9215515
PMCID
PMC2828361
Subset
IM
Grants
NIA NIH HHS · RC2 AG036535 · United States
Medical Research Council · G0601846 · United Kingdom
NIA NIH HHS · U01 AG024904 · United States
NIA NIH HHS · U19 AG010483 · United States
NIA NIH HHS · RC2 AG036535-01 · United States
NIA NIH HHS · U01 AG024904-05S6 · United States
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