European Radiology

, Volume 22, Issue 4, pp 796–802 | Cite as

Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival

  • Balaji Ganeshan
  • Elleny Panayiotou
  • Kate Burnand
  • Sabina Dizdarevic
  • Ken Miles
Chest

Abstract

Purpose

To establish the potential for tumour heterogeneity in non-small cell lung cancer (NSCLC) as assessed by CT texture analysis (CTTA) to provide an independent marker of survival for patients with NSCLC.

Materials and methods

Tumour heterogeneity was assessed by CTTA of unenhanced images of primary pulmonary lesions from 54 patients undergoing 18F-fluorodeoxyglucose (FDG) PET-CT for staging of NSCLC. CTTA comprised image filtration to extract fine, medium and coarse features with quantification of the distribution of pixel values (uniformity) within the filtered images. Receiver operating characteristics identified thresholds for PET and CTTA parameters that were related to patient survival using Kaplan-Meier analysis.

Results

The median (range) survival was 29.5 (1–38) months. 24, 10, 14 and 6 patients had tumour stages I, II, III and IV respectively. PET stage and tumour heterogeneity assessed by CTTA were significant independent predictors of survival (PET stage: Odds ratio 3.85, 95% confidence limits 0.9–8.09, P = 0.002; CTTA: Odds ratio 56.4, 95% confidence limits 4.79–666, p = 0.001). SUV was not a significantly associated with survival.

Conclusion

Assessment of tumour heterogeneity by CTTA of non-contrast enhanced images has the potential for to provide a novel, independent predictor of survival for patients with NSCLC.

Key Points

Computed tomography is a routine staging procedure in non-small cell lung cancer

CT texture analysis (CTTA) can quantify heterogeneity within these lung tumours

CTTA seems to offer a novel independent predictor of survival for NSCLC

CTTA could contribute to disease risk-stratification for patients with NSCLC

Keywords

Lung cancer Survival Computed tomography Positron emission tomography Texture analysis 

Notes

Acknowledgement

B.G. and K.M. have a commercial interest in the tumour structural analysis software described in MS.

The authors acknowledge the statistical input given by Dr. Matthew Hankins, Senior Lecturer in Clinical Research Methodology, Division of Primary Care & Public Health & Institute of Postgraduate Medicine, Brighton & Sussex Medical School, Falmer BN1 9PH.

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Copyright information

© European Society of Radiology 2011

Authors and Affiliations

  • Balaji Ganeshan
    • 1
  • Elleny Panayiotou
    • 2
  • Kate Burnand
    • 2
  • Sabina Dizdarevic
    • 3
  • Ken Miles
    • 1
  1. 1.Clinical Imaging Sciences Centre, Division of Clinical & Laboratory InvestigationBrighton & Sussex Medical SchoolBrightonUK
  2. 2.Brighton & Sussex University Hospitals NHS TrustBrightonUK
  3. 3.Department of Nuclear Medicine, Royal Sussex County HospitalBrighton & Sussex University Hospitals NHS TrustBrightonUK

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