Literature DB >> 20034579

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

Kelvin K Leung1, Matthew J Clarkson, Jonathan W Bartlett, Shona Clegg, Clifford R Jack, Michael W Weiner, Nick C Fox, Sébastien Ourselin.   

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. Copyright 2010 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Alzheimer’s disease; Atrophy; BSI; Boundary shift integral; Intensity normalization; KN-BSI; MRI

Mesh:

Year:  2009        PMID: 20034579      PMCID: PMC2828361          DOI: 10.1016/j.neuroimage.2009.12.059

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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