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Neuroimaging Core

eagle-i ID

http://eagle-i.itmat.upenn.edu/i/0000017e-7368-a9db-49d6-a5b680000000

Resource Type

  1. Support service

Properties

  1. Resource Description
    The Penn ADRC Neuroimaging Core will consolidate expertise in advanced neuroimaging methods and applications to support the acquisition and analysis of state-of-the-art multimodal MRI of brain structure and function, molecular brain imaging using PET, retinal angiography using optical coherence tomography (OCTA). The Neuroimaging Core will oversee the acquisition and analysis of standard MRI and PET scans used in defining preclinical AD based on amyloid, tau, and neurodegeneration (“A/T/(N)”) staging and for quantifying ischemic lesions in the brain. Additional unique features of the Neuroimaging Core include the use of ultra- high-field (7T) MRI both in vivo and for post-mortem imaging of intact hemispheres, the development methods for accurate image-guided sampling of post-mortem brain tissue allowing spatial linkage between digital pathology and in vivo morphometry, the development of data infrastructure linking imaging and non-imaging databases, novel MRI and OCT methods for quantifying brain structure and vascular function in ADRC research, and infrastructure to support the translation of novel PET tracers to clinical research in AD/ADRD. The Neuroimaging Core will also share imaging data collected at the Penn ADRC with the National Alzheimer's Coordinating Center (NACC) at the University of Washington and SCAN U24.
  2. Contact
    Detre, John A., MD
  3. Service Provided by
    Alzheimer’s Disease Research Center
  4. Website(s)
    https://www.med.upenn.edu/adrc/cores.html
 
RDFRDF
 
Provenance Metadata About This Resource Record
  1. workflow state
    Published
  2. contributor
    ggrant (Gregory Grant)
  3. created
    2022-01-19T12:36:44.943-05:00
  4. creator
    ggrant (Gregory Grant)
  5. modified
    2022-01-19T12:36:51.530-05:00
Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016