Prognostic value of 18F-FDG PET image-based parameters in oesophageal cancer and impact of tumour delineation methodology

  • Mathieu Hatt
  • Dimitris Visvikis
  • Nidal M. Albarghach
  • Florent Tixier
  • Olivier Pradier
  • Catherine Cheze-le Rest
Original Article

Abstract

Purpose

18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) image-derived parameters, such as standardized uptake value (SUV), functional tumour length (TL) and tumour volume (TV) or total lesion glycolysis (TLG), may be useful for determining prognosis in patients with oesophageal carcinoma. The objectives of this work were to investigate the prognostic value of these indices in oesophageal cancer patients undergoing combined chemoradiotherapy treatment and the impact of TV delineation strategies.

Methods

A total of 45 patients were retrospectively analysed. Tumours were delineated on pretreatment 18F-FDG scans using adaptive threshold and automatic (fuzzy locally adaptive Bayesian, FLAB) methodologies. The maximum standardized uptake value (SUVmax), SUVpeak, SUVmean, TL, TV and TLG were computed. The prognostic value of each parameter for overall survival was investigated using Kaplan-Meier and Cox regression models for univariate and multivariate analyses, respectively.

Results

Large differences were observed between methodologies (from −140 to +50% for TV). SUV measurements were not significant prognostic factors for overall survival, whereas TV, TL and TLG were, irrespective of the segmentation strategy. After multivariate analysis including standard tumour staging, only TV (p < 0.002) and TL (p = 0.042) determined using FLAB were independent prognostic factors.

Conclusion

Whereas no SUV measurement was a significant prognostic factor, TV, TL and TLG were significant prognostic factors for overall survival, irrespective of the delineation methodology. Only functional TV and TL derived using FLAB were independent prognostic factors, highlighting the need for accurate and robust PET tumour delineation tools for oncology applications.

Keywords

PET Tumour volume Tumour segmentation Oesophageal cancer Survival 

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Mathieu Hatt
    • 1
  • Dimitris Visvikis
    • 1
  • Nidal M. Albarghach
    • 1
    • 3
  • Florent Tixier
    • 1
  • Olivier Pradier
    • 1
    • 3
  • Catherine Cheze-le Rest
    • 1
    • 2
  1. 1.INSERM, U650 LaTIMCHU MorvanBrestFrance
  2. 2.Academic Department of Nuclear MedicineCHU MorvanBrestFrance
  3. 3.Department of RadiotherapyCHU MorvanBrestFrance

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