Non-invasive imaging prediction of tumor hypoxia: A novel developed and externally validated CT and FDG-PET-based radiomic signatures

Sebastian Sanduleanu*, Arthur Jochems, Taman Upadhaya, Aniek J. G. Even, Ralph T. H. Leijenaar, Frank J. W. M. Dankers, Remy Klaassen, Henry C. Woodruff, Mathieu Hatt, Hans J. A. M. Kaanders, Olga Hamming-Vrieze, Hanneke W. M. van Laarhoven, Rathan M. Subramiam, Shao Hui Huang, Brian O'Sullivan, Scott Bratman, Ludwig J. Dubois, Razvan L. Miclea, Dario Di Perri, Xavier GeetsMireia Crispin-Ortuzar, Aditya Apte, Joseph O. Deasy, Jung Hun Oh, Nancy Y. Lee, John L. Humm, Heiko Schoder, Dirk De Ruysscher, Frank Hoebers, Philippe Lambin

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Pages (from-to)97-105
Number of pages9
JournalRadiotherapy and Oncology
Volume153
DOIs
Publication statusPublished - Dec 2020

Keywords

  • Radiomics
  • Tumor hypoxia
  • UPTAKE DISTRIBUTIONS
  • CANCER PATIENTS
  • LUNG-TUMORS
  • RADIOTHERAPY
  • HEAD
  • DISCRETIZATION
  • REPEATABILITY
  • ANGIOGENESIS
  • METHODOLOGY
  • INFORMATION

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