Automated structural imaging analysis detects premanifest Huntington’s disease neurodegeneration within one year
Identifieur interne : 000135 ( Pmc/Corpus ); précédent : 000134; suivant : 000136Automated structural imaging analysis detects premanifest Huntington’s disease neurodegeneration within one year
Auteurs : D. S. Adnan Majid ; Diederick Stoffers ; Sarah Sheldon ; Samar Hamza ; Wesley K. Thompson ; Jody Goldstein ; Jody Corey-Bloom ; Adam R. AronSource :
- Movement disorders : official journal of the Movement Disorder Society [ 0885-3185 ] ; 2011.
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 and controls.
Using a one-year longitudinal design, we analyzedT1-weighted structural scans in 35 preHD individuals and 22 age-matched controls. We used the SIENA software tool (Structural Image Evaluation, using Normalization, of Atrophy) 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 vs. 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 over three 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 74close-to-onset individuals in each arm (treatment vs. placebo) to detect a 50% slowing in yearly atrophy with80% power.
Automated whole-brain analysis of structural MRI can reliably detect preHD disease progression over one 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.
Url:
DOI: 10.1002/mds.23656
PubMed: 21484871
PubMed Central: 3136652
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