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Principal Investigator  
Principal Investigator's Name: Paul Unschuld
Institution: University of Zurich
Department: Geriatric Psychiatry
Country:
Proposed Analysis: We aim to assess the relationship between PET spatial resolution and diagnostic specificity of a machine learning algorithm for AD and related biomarker-phenotypes. We would test different spatial resolutions of the PET-data, by filtering the PET-image with a Gaussian. In a second step the voxels will be re-sampled to larger sizes as would be expected with the reduced resolution. We would like to test for predictive validity of various spatial PET resolutions for diagnosis (AD-MCI-HC), and AD related phenotypes, as assessed by the ADNI Biomarker Core and available in the Data Archive: Homocysteine; Isoprostanes species; CSF tau, sAPPβ levels, BACE levels, enzyme activities of Plasma Aβ 40 and Aβ 42. For the computational analysis involved in this project, we will have access to the Monch computation cluster: https://www.cscs.ch/computers/moench/. This data will allow for estimating usefulness of a portable, low cost cranial PET system in AD-diagnostics, which is currently under development at Swiss federal Institute of Technology (ETH Zurich), and University of Zurich.
Additional Investigators  
Investigator's Name: Jan Klohs
Proposed Analysis: The primary objective of the study is to estimate cervical (C1-C6) spinal cord volumes from structural 3D T1-weighted MRI data of aged cognitively normal subjects, and patients diagnosed with mild cognitive impairment, and Alzheimer`s disease dementia. Specifically, we will investigate a) the rate of cervical spinal cord atrophy in the different cohorts, and b) the correlation between cervical spinal cord atrophy rates with cerebral amyloid-β and tau load taken from PET images. The planned analysis will reveal if cervical spinal cord atrophy is progressively involved in Alzheimer`s disease pathogenesis and if cerebral amyloid-β and tau load are related to cervical SC atrophy.
Investigator's Name: Aida Fall
Proposed Analysis: This project is part of a PhD-thesis of Mrs. A. Fall. The specific aim is to determine differences in patterns of cognitive brain network connectivity in healthy individuals versus persons with subjective memory complaints. Secondary analysis will investigate local network effects of pathological protein aggregates Abeta and tau, as measured by PiB and AV1451 SUVR. State of the art software will be used, such as Matlab, SPM based toolboxes (CONN), and Free/PET-Surfer.