Browsing by Subject "Group atlas"

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    Joint-label fusion brain atlases for dementia research in Down syndrome
    (Wiley, 2022-05-25) Queder, Nazek; Phelan, Michael J.; Taylor, Lisa; Tustison, Nicholas; Doran, Eric; Hom, Christy; Nguyen, Dana; Lai, Florence; Pulsifer, Margaret; Price, Julie; Kreisl, William C.; Rosas, Herminia D.; Krinsky-McHale, Sharon; Brickman, Adam M.; Yassa, Michael A.; Schupf, Nicole; Silverman, Wayne; Lott, Ira T.; Head, Elizabeth; Mapstone, Mark; Keator, David B.; Alzheimer’s Biomarkers Consortium; Neurology, School of Medicine
    Research suggests a link between Alzheimer's Disease in Down Syndrome (DS) and the overproduction of amyloid plaques. Using Positron Emission Tomography (PET) we can assess the in-vivo regional amyloid load using several available ligands. To measure amyloid distributions in specific brain regions, a brain atlas is used. A popular method of creating a brain atlas is to segment a participant's structural Magnetic Resonance Imaging (MRI) scan. Acquiring an MRI is often challenging in intellectually-imparied populations because of contraindications or data exclusion due to significant motion artifacts or incomplete sequences related to general discomfort. When an MRI cannot be acquired, it is typically replaced with a standardized brain atlas derived from neurotypical populations (i.e. healthy individuals without DS) which may be inappropriate for use in DS. In this project, we create a series of disease and diagnosis-specific (cognitively stable (CS-DS), mild cognitive impairment (MCI-DS), and dementia (DEM-DS)) probabilistic group atlases of participants with DS and evaluate their accuracy of quantifying regional amyloid load compared to the individually-based MRI segmentations. Further, we compare the diagnostic-specific atlases with a probabilistic atlas constructed from similar-aged cognitively-stable neurotypical participants. We hypothesized that regional PET signals will best match the individually-based MRI segmentations by using DS group atlases that aligns with a participant's disorder and disease status (e.g. DS and MCI-DS). Our results vary by brain region but generally show that using a disorder-specific atlas in DS better matches the individually-based MRI segmentations than using an atlas constructed from cognitively-stable neurotypical participants. We found no additional benefit of using diagnose-specific atlases matching disease status. All atlases are made publicly available for the research community.