Browsing by Author "Kreisl, William C."

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    FDG-PET patterns associated with underlying pathology in corticobasal syndrome
    (American Academy of Neurology, 2019) Pardini, Matteo; Huey, Edward D.; Spina, Salvatore; Kreisl, William C.; Morbelli, Silvia; Wassermann, Eric M.; Nobili, Flavio; Ghetti, Bernardino; Grafman, Jordan; Pathology and Laboratory Medicine, School of Medicine
    Objective: To evaluate brain 18Fluorodeoxyglucose PET (FDG-PET) differences among patients with a clinical diagnosis of corticobasal syndrome (CBS) and distinct underling primary pathologies. Methods: We studied 29 patients with a diagnosis of CBS who underwent FDG-PET scan and postmortem neuropathologic examination. Patients were divided into subgroups on the basis of primary pathologic diagnosis: CBS-corticobasal degeneration (CBS-CBD) (14 patients), CBS-Alzheimer disease (CBS-AD) (10 patients), and CBS-progressive supranuclear palsy (CBS-PSP) (5 patients). Thirteen age-matched healthy patients who underwent FDG-PET were the control group (HC). FDG-PET scans were compared between the subgroups and the HC using SPM-12, with a threshold of p FWE < 0.05. Results: There were no differences in Mattis Dementia Rating Scale or finger tapping scores between CBS groups. Compared to HC, the patients with CBS presented significant hypometabolism in frontoparietal regions, including the perirolandic area, basal ganglia, and thalamus of the clinically more affected hemisphere. Patients with CBS-CBD showed a similar pattern with a more marked, bilateral involvement of the basal ganglia. Patients with CBS-AD presented with posterior, asymmetric hypometabolism, including the lateral parietal and temporal lobes and the posterior cingulate. Finally, patients with CBS-PSP disclosed a more anterior hypometabolic pattern, including the medial frontal regions and the anterior cingulate. A conjunction analysis revealed that the primary motor cortex was the only common area of hypometabolism in all groups, irrespective of pathologic diagnosis. Discussion and conclusions: In patients with CBS, different underling pathologies are associated with different patterns of hypometabolism. Our data suggest that FDG-PET scans could help in the etiologic diagnosis of CBS.
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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.