title: Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma.
abstract: BACKGROUND
  Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror tumor uptake heterogeneity; some of them may be associated with tumor progression.
  
  
  METHODS
  Fourteen patients with HGG and suspected of PSP underwent FET-PET imaging. A set of 19 conventional and textural FET-PET features were evaluated and subjected to unsupervised consensus clustering. The final diagnosis of true progression vs. PSP was based on follow-up MRI using RANO criteria.
  
  
  RESULTS
  Three robust clusters have been identified based on 10 predominantly textural FET-PET features. None of the patients with PSP fell into cluster 2, which was associated with high values for textural FET-PET markers of uptake heterogeneity. Three out of 4 patients with PSP were assigned to cluster 3 that was largely associated with low values of textural FET-PET features. By comparison, tumor-to-normal brain ratio (TNRmax) at the optimal cutoff 2.1 was less predictive of PSP (negative predictive value 57% for detecting true progression, p=0.07 vs. 75% with cluster 3, p=0.04).
  
  
  CONCLUSIONS
  Clustering based on textural O-(2-[18F]fluoroethyl)-L-tyrosine PET features may provide valuable information in assessing the elusive phenomenon of pseudoprogression.
authors.affiliation: Division of Clinical Neurooncology, Department of Neurology, University of Bonn Medical Center, Germany.|Stem Cell Pathologies Group, Institute of Reconstructive Neurobiology, University of Bonn Medical Center, Germany.
authors.forename: Sied
authors.initials: S
authors.lastname: Kebir
authors.affiliation: Department of Nuclear Medicine, University of Bonn Medical Center, Germany.
authors.forename: Zain
authors.initials: Z
authors.lastname: Khurshid
authors.affiliation: Department of Nuclear Medicine, University of Bonn Medical Center, Germany.
authors.forename: Florian C
authors.initials: FC
authors.lastname: Gaertner
authors.affiliation: Department of Nuclear Medicine, University of Bonn Medical Center, Germany.
authors.forename: Markus
authors.initials: M
authors.lastname: Essler
authors.affiliation: Neuroradiology, Department of Radiology, University of Bonn Medical Center, Germany.
authors.forename: Elke
authors.initials: E
authors.lastname: Hattingen
authors.affiliation: Institute of Medical Biometry, Informatics and Epidemiology, University of Bonn Medical Center, Germany.
authors.forename: Rolf
authors.initials: R
authors.lastname: Fimmers
authors.affiliation: Stem Cell Pathologies Group, Institute of Reconstructive Neurobiology, University of Bonn Medical Center, Germany.|DKFZ -Division of Translational Oncology/Neurooncology, German Cancer Consortium (DKTK) & University Hospital Essen, Germany.
authors.forename: Björn
authors.initials: B
authors.lastname: Scheffler
authors.affiliation: Division of Clinical Neurooncology, Department of Neurology, University of Bonn Medical Center, Germany.
authors.forename: Ulrich
authors.initials: U
authors.lastname: Herrlinger
authors.affiliation: Department of Nuclear Medicine, University of Bonn Medical Center, Germany.
authors.forename: Ralph A
authors.initials: RA
authors.lastname: Bundschuh
authors.affiliation: Division of Clinical Neurooncology, Department of Neurology, University of Bonn Medical Center, Germany.|Stem Cell Pathologies Group, Institute of Reconstructive Neurobiology, University of Bonn Medical Center, Germany.|Clinical Cooperation Unit Neurooncology, MediClin Robert Janker Klinik, Bonn, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Glas
mesh_terms: D000328:Adult; D000368:Aged; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000401:mortality / Q000473:pathology / Q000628:therapy; D016000:Cluster Analysis; D018450:Disease Progression; D018572:Disease-Free Survival; D005260:Female; D005910:Glioma / Q000000981:diagnostic imaging* / Q000401:mortality / Q000473:pathology / Q000628:therapy; D006801:Humans; D053208:Kaplan-Meier Estimate; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D010865:Pilot Projects; D000072078:Positron Emission Tomography Computed Tomography / Q000379:methods*; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D019275:Radiopharmaceuticals / Q000008:administration & dosage*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D013997:Time Factors; D016896:Treatment Outcome; D014443:Tyrosine / Q000008:administration & dosage / Q000031:analogs & derivatives*; D000069558:Unsupervised Machine Learning
chemical_list: D019275:Radiopharmaceuticals; C545932:(18F)fluoroethyltyrosine; D014443:Tyrosine
keywords: FET-PET; glioblastoma; heterogeneity; pseudoprogression; textural