Assessment of the prognostic value of radiomic features in18f-fmiso pet imaging of hypoxia in postsurgery brain cancer patients: Secondary analysis of imaging data from a single-center study and the multicenter acrin 6684 trial

Mark Muzi, Eric Wolsztynski, James R. Fink, Janet N. O’sullivan, Finbarr O’sullivan, Kenneth A. Krohn, David A. Mankoff

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Hypoxia is associated with resistance to radiotherapy and chemotherapy in malignant gliomas, and it can be imaged by positron emission tomography with18F-fluoromisonidazole (18F-FMISO). Previous results for patients with brain cancer imaged with18F-FMISO at a single center before conventional chemoradiotherapy showed that tumor uptake via T/Bmax (tissue SUVmax/blood SUV) and hypoxic volume (HV) was associated with poor survival. However, in a multicenter clinical trial (ACRIN 6684), traditional uptake parameters were not found to be prognostically significant, but tumor SUVpeak did predict survival at 1 year. The present analysis considered both study cohorts to reconcile key differences and examine the potential utility of adding radiomic features as prognostic variables for outcome prediction on the combined cohort of 72 patients with brain cancer (30 University of Washington and 42 ACRIN 6684). We used both18F-FMISO intensity metrics (T/Bmax, HV, SUV, SUVmax, SUVpeak) and assessed radiomic measures that determined first-order (histogram), second-order, and higher-order radiomic features of18F-FMISO uptake distributions. A multivariate model was developed that included age, HV, and the intensity of18F-FMISO uptake. HV and SUVpeak were both independent predictors of outcome for the combined data set (P <.001) and were also found significant in multivariate prognostic models (P <.002 and P <.001, respectively). Further model selection that included radiomic features showed the additional prognostic value for overall survival of specific higher order texture features, leading to an increase in relative risk prediction performance by a further 5%, when added to the multivariate clinical model..

Original languageEnglish (US)
Pages (from-to)14-22
Number of pages9
JournalTomography (Ann Arbor, Mich.)
Volume6
Issue number1
DOIs
StatePublished - Mar 2020
Externally publishedYes

Keywords

  • ACRIN 6684
  • Brain cancer
  • Fluoromisonidazole
  • PET imaging
  • Radiomics

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Medicine(all)

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