Comparison of novel multi-level Otsu (MO-PET) and conventional PET segmentation methods for measuring FDG metabolic tumor volume in patients with soft tissue sarcoma

Inki Lee, Hyung Jun Im, Meiyappan Solaiyappan, Steve Y. Cho

Research output: Contribution to journalArticle

Abstract

Background: We have previously developed a novel and highly consistent PET segmentation algorithm using a multi-level Otsu method (MO-PET). The aim of this study was to evaluate the reliability of MO-PET compared to conventional PET segmentation methods for measuring 18F-FDG (FDG) PET metabolic tumor volume (MTV) in patients with soft tissue sarcoma (STS). Clinical and imaging data were obtained from the Cancer Imaging Archive. Forty-eight STS patients with FDG PET/CT and MR prior to therapy were analyzed. MTV of the tumor using MO-PET was compared to other conventional methods (absolute SUV threshold values of 2.0, 2.5, or 3.0 and percentage of tumor SUVmax values of 30, 40, 50, or 60%) and gradient-based method (PET Edge™). The reference volume was defined as an MR-based gross tumor volume (GTV). Spearman, intra-class correlation, and Bland-Altman analysis were performed to evaluate the correlation and agreement of MTV to GTV. Results: MTVs obtained using each conventional SUV parameter, PET Edge™, and MO-PET were highly correlated with the GTV in Spearman and intra-class correlation analysis (p < 0.05). MO-PET and PET Edge™ showed high intra-class correlation coefficient of MTV to GTV (0.93 and 0.84, respectively). The Bland-Altman bias results showed the highest agreement for MTV using MO-PET with GTV (26.0 ± 489.6 cm3) compared to other methods (SUV 2.0 with − 69.3 ± 765.8, 30% SUVmax with − 255.0 ± 876.6, and PET Edge™ with − 26.46 ± 668.82 cm3). Conclusions: PET MTV segmented with MO-PET showed higher correlation and agreement with GTV in comparison to conventional percentage SUVmax and absolute SUV threshold-based PET segmentation methods. MO-PET is comparable to PET Edge™. MO-PET is a reliable and consistent method for measuring tumor MTV.

Original languageEnglish (US)
Article number22
JournalEJNMMI Physics
Volume4
Issue number1
DOIs
StatePublished - Dec 1 2017

Keywords

  • Metabolic tumor volume
  • Positron emission tomography
  • Segmentation
  • Soft tissue sarcoma

ASJC Scopus subject areas

  • Radiation
  • Biomedical Engineering
  • Instrumentation
  • Radiology Nuclear Medicine and imaging

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