% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Doering:1041319,
      author       = {Doering, Elena and Hoenig, Merle C. and Giehl, Kathrin and
                      Dzialas, Verena and Andrassy, Grégory and Bader, Abdelmajid
                      and Bauer, Andreas and Elmenhorst, David and Ermert,
                      Johannes and Frensch, Silke and Jäger, Elena and Jessen,
                      Frank and Krapf, Philipp and Kroll, Tina and Lerche,
                      Christoph and Lothmann, Julia and Matusch, Andreas and
                      Neumaier, Bernd and Onur, Oezguer A. and Ramirez, Alfredo
                      and Richter, Nils and Sand, Frederik and Tellmann, Lutz and
                      Theis, Hendrik and Zeyen, Philip and van Eimeren, Thilo and
                      Drzezga, Alexander and Bischof, Gerard Nisal},
      title        = {“{F}ill {S}tates”: {PET}-derived {M}arkers of the
                      {S}patial {E}xtent of {A}lzheimer {D}isease {P}athology},
      journal      = {Radiology},
      volume       = {314},
      number       = {3},
      issn         = {0033-8419},
      address      = {Oak Brook, Ill.},
      publisher    = {Soc.},
      reportid     = {FZJ-2025-02218},
      pages        = {e241482},
      year         = {2025},
      note         = {Deutsche Forschungsgemeinschaft [DFG] research grant
                      “Brain network dependent propagation of tau-pathology in
                      Alzheimer disease” DR 445/9-1 [AD]). Some co-authors
                      received funding from the DFG (project ID 431549029-SFB
                      1451). Datacollection and sharing for this project was
                      funded by the Alzheimer’s Disease Neuroimaging Initiative
                      (ADNI) (National Institutes of Health grant no. U01
                      AG024904) and U.S. Department of Defense ADNI (award no.
                      W81XWH-12-2-0012).},
      abstract     = {Background: Alzheimer disease (AD) progression can be
                      monitored by tracking intensity changes in PET standardized
                      uptake value (SUV) ratiosof amyloid, tau, and
                      neurodegeneration. The spatial extent (“fill state”) of
                      these three hallmark pathologic abnormalities may serve as
                      criticalpathophysiologic information, pending further
                      investigation.Purpose: To examine the clinical utility and
                      increase the accessibility of PET-derived fill
                      states.Materials and Methods: This secondary analysis of two
                      prospective studies used data from two independent cohorts:
                      the Alzheimer’s DiseaseNeuroimaging Initiative (ADNI) and
                      the Tau Propagation over Time study (T-POT). Each cohort
                      comprised amyloid-negative cognitively normalindividuals
                      (controls) and patients with subjective cognitive decline,
                      mild cognitive impairment, or probable-AD dementia. Fill
                      states of amyloid, tau,and neurodegeneration were computed
                      as the percentages of significantly abnormal voxels relative
                      to controls across PET scans. Fill states and SUVratios were
                      compared across stages (Kruskal-Wallis H test, area under
                      the receiver operating characteristic curve analysis) and
                      tested for associationwith the severity of cognitive
                      impairment (Spearman correlation, multivariate regression
                      analysis). Additionally, a convolutional neural network(CNN)
                      was developed to estimate fill states from patients’ PET
                      scans without requiring controls.Results: The ADNI cohort
                      included 324 individuals (mean age, 72 years ± 6.8 [SD];
                      173 $[53\%]$ female), and the T-POT cohort comprised
                      99individuals (mean age, 66 years ± 8.7; 63 $[64\%]$
                      female). Higher fill states were associated with higher
                      stages of cognitive impairment (P < .001),and tau and
                      neurodegeneration fill states showed higher diagnostic
                      performance for cognitive impairment compared with SUV ratio
                      (P < .05) acrosscohorts. Similarly, all fill states were
                      negatively correlated with cognitive performance (P < .001)
                      and uniquely characterized the degree of cognitiveimpairment
                      even after adjustment for SUV ratio (P < .05). The CNN
                      estimated amyloid and tau accurately, but not
                      neurodegeneration fill states.Conclusion: Fill states
                      provided reliable markers of AD progression, potentially
                      improving early detection, staging, and monitoring of AD in
                      clinicalpractice and trials beyond SUV ratio.},
      cin          = {INM-5 / INM-2 / INM-3 / INM-4},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-5-20090406 / I:(DE-Juel1)INM-2-20090406 /
                      I:(DE-Juel1)INM-3-20090406 / I:(DE-Juel1)INM-4-20090406},
      pnm          = {5253 - Neuroimaging (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5253},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {40131110},
      UT           = {WOS:001464548700015},
      doi          = {10.1148/radiol.241482},
      url          = {https://juser.fz-juelich.de/record/1041319},
}