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@INPROCEEDINGS{PitarchAbaigar:1053899,
      author       = {Pitarch-Abaigar, Carla and Adap, Sanyukta and Akbari, Hamed
                      and Flinn, Alexandra and Shah, N Jon and Langen, Karl-Josef
                      and Galldiks, Norbert and Pease, Matthew and Gatson, Na
                      Tosha and LaViolette, Peter S and Davatzikos, Christos and
                      Parker, Jason and Lohmann, Philipp and Bakas, Spyridon},
      title        = {{BIOM}-82. {GLIOBLASTOMA} {BEYOND} {THE} {ENHANCING}
                      {TUMOR} {MARGINS}: {A} {LONGITUDINAL} {CASE} {STUDY}
                      {COMPARING} {FET} {PET} {WITH} {MRI}-{BASED} {AI}
                      {INFILTRATION} {MAPS}},
      issn         = {1523-5866},
      reportid     = {FZJ-2026-01597},
      year         = {2025},
      abstract     = {AbstractBACKGROUNDGlioblastoma is the most common malignant
                      brain tumor, with rapid proliferation, diffuse infiltration,
                      and poor prognosis. Imaging plays a central role in its
                      diagnosis, treatment planning, and disease monitoring.
                      Positron Emission Tomography with
                      O-(2-[18F]fluoroethyl)-L-tyrosine (FET PET) depicts
                      metabolically active tumor irrespective of the blood-brain
                      barrier integrity. Here, we compare FET PET with
                      AI-generated infiltration maps (AI-InfM) derived from
                      multiparametric MRI (mpMRI - T1, T1Gd, T2, T2-FLAIR, DSC) to
                      identify viable tumor beyond the enhancing tumor,
                      potentially corresponding to early recurrence
                      sites.METHODSWe identified a patient with a newly-diagnosed
                      glioblastoma in a non resectable eloquent area.
                      Pre-operative scans were acquired at baseline and two
                      follow-up timepoints, during and post-treatment, at
                      six-month intervals. Each scanning session comprised a
                      50-minute dynamic FET PET scan and mpMRI performed at
                      Research Center Juelich, Germany. AI-InfM, based on Support
                      Vector Machines, were trained following within-patient,
                      self-normalized measures of heterogeneity across
                      pre-operative mpMRI of treatment-naïve glioblastoma in a
                      subset of the public UPENN-GBM dataset. AI-InfM were then
                      generated for the identified patient and compared with FET
                      PET visually and quantitatively using clinically-established
                      measures, e.g., tumor-to-brain ratios (TBR).RESULTSAlthough
                      FET PET showed no increased tracer uptake at baseline, the
                      AI-InfM identified a region with elevated signal. This
                      region exhibited increased uptake of FET in the first
                      follow-up scan (TBRmax from 1.9 at baseline to 2.2 at
                      follow-up), supporting the AI-InfM’s early prediction.
                      After completion of adjuvant temozolomide therapy, the third
                      scan denoted the predicted high-risk area with reduced tumor
                      activity across FET PET, AI-InfM, and mpMRI.CONCLUSIONSOur
                      findings indicate potential complementary value of FET PET
                      and mpMRI-derived AI-InfM, for early recurrence
                      identification. This case study underscores the potential to
                      enhance early detection of tumor progression, by virtue of
                      the infiltrative spread in glioblastoma, and warrants
                      continued development and evaluation in a larger
                      multi-institutional cohort.},
      month         = {Nov},
      date          = {2025-11-20},
      organization  = {7th Quadrennial Meeting of the World
                       Federation of Neuro-Oncology Societies,
                       Honolulu (USA), 20 Nov 2025 - 23 Nov
                       2025},
      cin          = {INM-4},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-4-20090406},
      pnm          = {5253 - Neuroimaging (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5253},
      typ          = {PUB:(DE-HGF)1},
      doi          = {10.1093/neuonc/noaf201.0170},
      url          = {https://juser.fz-juelich.de/record/1053899},
}