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@ARTICLE{Doering:1019312,
      author       = {Doering, Elena and Antonopoulos, Georgios and Hönig, Merle
                      and van Eimeren, Thilo and Daamen, Marcel and Boecker,
                      Henning and Jessen, Frank and Düzel, Emrah and Eickhoff,
                      Simon and Patil, Kaustubh and Drzezga, Alexander},
      title        = {{MRI} or 18 {F}-{FDG} {PET} for {B}rain {A}ge {G}ap
                      {E}stimation: {L}inks to {C}ognition, {P}athology, and
                      {A}lzheimer {D}isease {P}rogression},
      journal      = {Journal of nuclear medicine},
      volume       = {64},
      number       = {12},
      issn         = {0097-9058},
      address      = {New York, NY},
      publisher    = {Soc.},
      reportid     = {FZJ-2023-05286},
      pages        = {},
      year         = {2023},
      abstract     = {Deviations of brain age from chronologic age, known as the
                      brain age gap (BAG), have been linked to neurodegenerative
                      diseases such as Alzheimer disease (AD). Here, we compare
                      the associations of MRI-derived (atrophy) or 18F-FDG
                      PET–derived (brain metabolism) BAG with cognitive
                      performance, neuropathologic burden, and disease progression
                      in cognitively normal individuals (CNs) and individuals with
                      subjective cognitive decline (SCD) or mild cognitive
                      impairment (MCI). Methods: Machine learning pipelines were
                      trained to estimate brain age from 185 matched T1-weighted
                      MRI or 18F-FDG PET scans of CN from the Alzheimer’s
                      Disease Neuroimaging Initiative and validated in external
                      test sets from the Open Access of Imaging and German Center
                      for Neurodegenerative Diseases–Longitudinal Cognitive
                      Impairment and Dementia studies. BAG was correlated with
                      measures of cognitive performance and AD neuropathology in
                      CNs, SCD subjects, and MCI subjects. Finally, BAG was
                      compared between cognitively stable and declining
                      individuals and subsequently used to predict disease
                      progression. Results: MRI (mean absolute error, 2.49 y)
                      and 18F-FDG PET (mean absolute error, 2.60 y) both
                      estimated chronologic age well. At the SCD stage, MRI-based
                      BAG correlated significantly with beta-amyloid1-42 (Aβ1-42)
                      in cerebrospinal fluid, whereas 18F-FDG PET BAG correlated
                      with memory performance. At the MCI stage, both BAGs were
                      associated with memory and executive function performance
                      and cerebrospinal fluid Aβ1-42, but only MRI-derived BAG
                      correlated with phosphorylated-tau181/Aβ1-42. Lastly,
                      MRI-estimated BAG predicted MCI-to-AD progression better
                      than 18F-FDG PET–estimated BAG (areas under the curve,
                      0.73 and 0.60, respectively). Conclusion: Age was reliably
                      estimated from MRI or 18F-FDG PET. MRI BAG reflected
                      cognitive and pathologic markers of AD in SCD and MCI,
                      whereas 18F-FDG PET BAG was sensitive mainly to early
                      cognitive impairment, possibly constituting an independent
                      biomarker of brain age-related changes.},
      cin          = {INM-7 / INM-2},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406 / I:(DE-Juel1)INM-2-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525) / 5252 - Brain Dysfunction and Plasticity
                      (POF4-525) / 5253 - Neuroimaging (POF4-525) / 5254 -
                      Neuroscientific Data Analytics and AI (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5251 / G:(DE-HGF)POF4-5252 /
                      G:(DE-HGF)POF4-5253 / G:(DE-HGF)POF4-5254},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {38050112},
      UT           = {WOS:001179150300007},
      doi          = {10.2967/jnumed.123.265931},
      url          = {https://juser.fz-juelich.de/record/1019312},
}