Clustering of multi-parametric functional imaging to identify high-risk subvolumes in non-small cell lung cancer

Aniek J. G. Even*, Bart Reymen, Matthew D. La Fontaine, Marco Das, Felix M. Mottaghy, Jose S. A. Belderbos, Dirk De Ruysscher, Philippe Lambin, Wouter van Elmpt

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

18 Citations (Web of Science)

Abstract

Background and purpose: We aimed to identify tumour subregions with characteristic phenotypes based on pre-treatment multi-parametric functional imaging and correlate these subregions to treatment outcome. The subregions were created using imaging of metabolic activity (FDG-PET/CT), hypoxia (HX4-PET/CT) and tumour vasculature (DCE-CT).

Materials and methods: 36 non-small cell lung cancer (NSCLC) patients underwent functional imaging prior to radical radiotherapy. Kinetic analysis was performed on DCE-CT scans to acquire blood flow (BF) and volume (BV) maps. HX4-PET/CT and DCE-CT scans were non-rigidly co-registered to the planning FDG-PET/CT. Two clustering steps were performed on multi-parametric images: first to segment each tumour into homogeneous subregions (i.e. supervoxels) and second to group the supervoxels of all tumours into phenotypic clusters. Patients were split based on the absolute or relative volume of supervoxels in each cluster; overall survival, was compared using a log-rank test.

Results: Unsupervised clustering of supervoxels yielded four independent clusters. One cluster (high hypoxia, high FDG, intermediate BF/BV) related to a high-risk tumour type: patients assigned to this cluster had significantly worse survival compared to patients not in this cluster (p = 0.035).

Conclusions: We designed a subregional analysis for multi-parametric imaging in NSCLC, and showed the potential of subregion classification as a biomarker for prognosis. This methodology allows for a comprehensive data-driven analysis of multi-parametric functional images. (c) 2017 The Author(s). Published by Elsevier Ireland Ltd.

Original languageEnglish
Pages (from-to)379-384
Number of pages6
JournalRadiotherapy and Oncology
Volume125
Issue number3
DOIs
Publication statusPublished - Dec 2017

Keywords

  • Functional imaging
  • Biomarker
  • NSCLC
  • Hypoxia
  • DCE-CT
  • FDG PET/CT
  • INTRATUMOR HETEROGENEITY
  • TUMOR HETEROGENEITY
  • DOSE-ESCALATION
  • NECK-CANCER
  • PET
  • HYPOXIA
  • RADIOTHERAPY
  • SUBREGIONS
  • PERFUSION
  • SURVIVAL

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