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

• Published in: NeuroImage (Orlando, Fla.) Vol. 50; no. 2; pp. 516 - 523
• Main Authors: Leung, Kelvin K., Clarkson, Matthew J., Bartlett, Jonathan W., Clegg, Shona, Jack, Clifford R., Weiner, Michael W., Fox, Nick C., Ourselin, Sébastien
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.04.2010; Elsevier Limited
• Subjects: Aged; Aging; Algorithms; Alzheimer Disease - pathology; Alzheimer's disease; Atrophy; Atrophy - pathology; Automation; Biomedical research; Boundary shift integral; Brain - pathology; Brain research; BSI; Dementia; Humans; Image Interpretation, Computer-Assisted - methods; Intensity normalization; KN-BSI; Magnetic Resonance Imaging - methods; Medical imaging; MRI; NMR; Noise; Nuclear magnetic resonance; Pharmaceutical industry; Quality control; Registration; Scanners; Studies; Atrophy; KN-BSI; MRI; Boundary shift integral; BSI; Alzheimer's disease; Intensity normalization; Alzheimer’s disease
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2009.12.059

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.