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Biology subjects

Ducharme, S.

Publications and source records attributed to Ducharme, S..

2 recordsLinked to original sources
bioRxiv2019

DEFORMATION BASED MORPHOMETRY STUDY OF LONGITUDINAL MRI CHANGES IN BEHAVIORAL VARIANT FRONTOTEMPORAL DEMENTIA

ObjectiveTo objectively quantify how cerebral volume loss could assist with clinical diagnosis and clinical trial design in the behavioural variant of frontotemporal dementia (bvFTD).\n\nMethodsWe applied deformation-based morphometric analyses with robust registration to precisely quantify the magnitude and pattern of atrophy in patients with bvFTD as compared to cognitively normal controls (CNCs), to assess the progression of atrophy over one year follow up and to generate clinical trial sample size estimates to detect differences for the structures most sensitive to change. This study included 203 subjects - 70 bvFTD and 133 CNCs - with a total of 482 timepoints from the Frontotemporal Lobar Degeneration Neuroimaging Initiative.\n\nResultsDeformation based morphometry (DBM) revealed significant atrophy in the frontal lobes, insula, medial and anterior temporal regions bilaterally in bvFTD subjects compared to controls with outstanding subcortical involvement. We provide detailed information on regional changes per year. In both cross-sectional analysis and over a one-year follow-up period, ventricle expansion was the most prominent differentiator of bvFTD from controls and a sensitive marker of disease progression.\n\nConclusionsAutomated measurement of ventricular expansion is a sensitive and reliable marker of disease progression in bvFTD to be used in clinical trials for potential disease modifying drugs, as well as possibly to implement in clinical practice. Ventricular expansion measured with DBM provides the lowest published estimated sample size for clinical trial design to detect significant differences over one and two years.

neuroscience↗
bioRxiv2019

MRI and cognitive scores complement each other to accurately predict Alzheimer’s dementia 2 to 7 years before clinical onset

BackgroundPredicting cognitive decline and the eventual onset of dementia in patients with Mild Cognitive Impairment (MCI) is of high value for patient management and potential cohort enrichment in pharmaceutical trials. We used cognitive scores and MRI biomarkers from a single baseline visit to predict the onset of dementia in an MCI population over a nine-year follow-up period.\n\nMethodAll MCI subjects from ADNI1, ADNI2, and ADNI-GO with available baseline cognitive scores and T1w MRI were included in the study (n=756). We built a Naive Bayes classifier for every year over a 9-year follow-up period and tested each one with Leave one out cross validation.\n\nResultsWe reached 87% prediction accuracy at five years follow-up with an AUC>0.85 from two to seven years (peaking at 0.92 at five years). Both cognitive test scores and MR biomarkers were needed to make the prognostic models highly sensitive and specific, especially for longer follow-ups. MRI features are more sensitive, while cognitive features bring specificity to the prediction.\n\nConclusionCombining cognitive scores and MR biomarkers yield accurate prediction years before onset of dementia. Such a tool may be helpful in selecting patients that would most benefit from lifestyle changes, and eventually early treatments that would slow cognitive decline and delay the onset of dementia.

neuroscience↗