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@ARTICLE{Doering:1024832,
      author       = {Doering, Elena and Antonopoulos, Georgios and Hönig, Merle
                      C. and van Eimeren, Thilo and Eickhoff, Simon B. and Patil,
                      Kaustubh and Drzezga, Alexander},
      title        = {{T}he {L}ink between {B}rain age and {A}lzheimer’s
                      {D}isease development using different neuroimaging
                      modalities},
      journal      = {Alzheimer's and dementia},
      volume       = {19},
      number       = {S3},
      issn         = {1552-5260},
      address      = {Hoboken, NJ},
      publisher    = {Wiley},
      reportid     = {FZJ-2024-02498},
      pages        = {e065384},
      year         = {2023},
      abstract     = {Brain age (BA) provides a proxy of general brain health
                      through the prediction of chronological age (CA) from
                      neuroimaging data of healthy individuals. During aging, the
                      adult brain undergoes changes both on the morphological and
                      metabolic level. Here, we compare the link between BA
                      predicted from morphology (structural MRI) or metabolism
                      (18F-FDG-PET) and cognitive function, as well as
                      pathophysiological measures of Alzheimer’s disease (AD) in
                      cognitively normal individuals (CN) and patients with mild
                      cognitive impairment (MCI).},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525) / 5253 - Neuroimaging (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5251 / G:(DE-HGF)POF4-5253},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1002/alz.065384},
      url          = {https://juser.fz-juelich.de/record/1024832},
}