Automated structural imaging analysis detects premanifest Huntington's disease neurodegeneration within 1 year |
| |
| Authors: | DS Adnan Majid BS Diederick Stoffers PhD Sarah Sheldon BS Samar Hamza BS Wesley K Thompson PhD Jody Goldstein BS Jody Corey‐Bloom MD PhD Adam R Aron PhD |
| |
| Institution: | 1. Department of Psychology, University of California, San Diego (UCSD), San Diego, California, USA;2. Neurosciences Graduate Program, University of California, San Diego (UCSD), San Diego, California, USA;3. Netherlands Institute for Neuroscience, Amsterdam, The Netherlands;4. Department of Neurosciences, University of California, San Diego (UCSD), San Diego, California, USA;5. Department of Psychiatry, University of California, San Diego (UCSD), San Diego, California, USA |
| |
| Abstract: | Intense efforts are underway to evaluate neuroimaging measures as biomarkers for neurodegeneration in premanifest Huntington's disease (preHD). We used a completely automated longitudinal analysis method to compare structural scans in preHD individuals and controls. Using a 1‐year longitudinal design, we analyzed T1‐weighted structural scans in 35 preHD individuals and 22 age‐matched controls. We used the SIENA (Structural Image Evaluation, using Normalization, of Atrophy) software tool to yield overall percentage brain volume change (PBVC) and voxel‐level changes in atrophy. We calculated sample sizes for a hypothetical disease‐modifying (neuroprotection) study. We found significantly greater yearly atrophy in preHD individuals versus controls (mean PBVC controls, ?0.149%; preHD, ?0.388%; P = .031, Cohen's d = .617). For a preHD subgroup closest to disease onset, yearly atrophy was more than 3 times that of controls (mean PBVC close‐to‐onset preHD, ?0.510%; P = .019, Cohen's d = .920). This atrophy was evident at the voxel level in periventricular regions, consistent with well‐established preHD basal ganglia atrophy. We estimated that a neuroprotection study using SIENA would only need 74 close‐to‐onset individuals in each arm (treatment vs placebo) to detect a 50% slowing in yearly atrophy with 80% power. Automated whole‐brain analysis of structural MRI can reliably detect preHD disease progression in 1 year. These results were attained with a readily available imaging analysis tool, SIENA, which is observer independent, automated, and robust with respect to image quality, slice thickness, and different pulse sequences. This MRI biomarker approach could be used to evaluate neuroprotection in preHD. © 2011 Movement Disorder Society |
| |
| Keywords: | MRI biomarker premanifest HD longitudinal atrophy |
|
|
