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
Similar content being viewed by others
References
World Health Organization. The global burden of disease: 2004 update (2008); Available at http://www.who.int/healthinfo/global_burden_disease/GBD_report_2004update_part2.pdf. Accessed February 7, 2011
American Cancer Society (2010) Cancer Facts and Figures 2010. American Cancer Society. Available at http://www.cancer.org/acs/groups/content/@epidemiologysurveilance/documents/document/acspc-026238.pdf. Accessed February 7, 2011
Spiro SG, Tanner NT, Silvestri GA et al (2010) Lung cancer: progress in diagnosis, staging and therapy. Respirology 15:44–50
Dales RE, Stark RM, Raman S (1990) Computed tomography to stage lung cancer. Approaching a controversy using meta-analysis. Am Rev Respir Dis 141:1096–101
Rami-Porta R, Crowley JJ, Goldstraw P (2009) The revised TNM staging system for lung cancer. Annals of Thoracic Cardiovascular Surgery Feb 15:4–9
van Westreenen HL, Westerterp M, Bossuyt PM et al (2004) Systematic review of the staging performance of 18 F-fluorodeoxyglucose positron emission tomography in esophageal cancer. J Clin Oncol 22:3805–12
Wirth A, Foo M, Seymour JF, Macmanus MP, Hicks RJ (2008) Impact of [18f] fluorodeoxyglucose positron emission tomography on staging and management of early-stage follicular non-hodgkin lymphoma. Int J Radiat Oncol Biol Phys 71:213–9
Vermeersch H, Loose D, Ham H, Otte A, Van de Wiele C (2003) Nuclear medicine imaging for the assessment of primary and recurrent head and neck carcinoma using routinely available tracers. Eur J Nucl Med Mol Imaging 30:1689–700
Silvestri GA, Gould MK, Margolis ML, Tanoue LT, McCrory D, Toloza E, Detterbeck F (2007) Noninvasive staging of non-small cell lung cancer: ACCP evidenced-based clinical practice guidelines, 2nd edn. American College of Chest Physicians. Chest 132(3 Suppl):178S–201S
Alongi F, Ragusa P, Montemaggi P et al (2006) Combining independent studies of diagnostic fluorodeoxyglucose positron-emission tomography and computed tomography in mediastinal lymph node staging for non-small cell lung cancer. Tumouri 92:327–33
Berghmans T, Dusart M, Paesmans M et al (2008) Primary tumour standardized uptake value (SUVmax) measured on fluorodeoxyglucose positron emission tomography (FDG-PET) is of prognostic value for survival in non-small cell lung cancer (NSCLC). A systematic review and meta-analysis (MA) by the European Lung Cancer Working Party for the IASLC lung cancer staging project. J Thorac Oncol 3:6–12
Goo JM, Kim HY, Lee JW et al (2008) Is the computer-aided detection scheme for lung nodule also useful in detecting lung cancer? J Comput Assist Tomogr 32:570–5
Souto M, Tahoces PG, Suárez Cuenca JJ et al (2008) Automatic detection of pulmonary nodules on computed tomography: a preliminary study. Radiologia 50:387–92
Goldin JG, Brown MS, Petkovska I (2008) Computer-aided diagnosis in lung nodule assessment. Journal of Thoracic Imaging 23:97–104
Armato SG 3rd, Li F, Giger ML et al (2002) Lung cancer: performance of automated lung nodule detection applied to cancers missed in a CT screening program. Radiology 225:685–92
Armato SG 3rd, Roy AS, Macmahon H et al (2005) Evaluation of automated lung nodule detection on low-dose computed tomography scans from a lung cancer screening program. Acad Radiol 12:337–46
Sluimer I, Schilham A, Prokop M et al (2006) Computer analysis of computed tomography scans of the lung: a survey. IEEE Trans Med Imaging 25:385–405
Ganeshan B, Abaleke S, Young RC et al (2010) Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage. Cancer Imaging 10:137–43
Miles KA, Ganeshan B, Griffiths MR et al (2009) Colorectal cancer: Texture analysis of portal phase hepatic CT images as a potential marker of survival. Radiology 250:444–52
Ganeshan B, Miles KA, Young RCD, Chatwin CR (2007) In search of biologic correlates for liver texture on portal-phase CT. Acad Radiol 14:1058–68
Ganeshan B, Miles KA, Young RCD et al (2007) Hepatic enhancement in colorectal cancer: Texture analysis correlates with hepatic hemodynamics and patient survival. Acad Radiol 14:1520–30
Ganeshan B, Miles KA, Young RCD et al (2007) Hepatic entropy and uniformity: additional parameters that can potentially increase the utility of contrast enhancement during abdominal CT. Clin Radiol 62:761–768
Ganeshan B, Miles KA, Young RCD et al (2009) Texture analysis in non-contrast enhanced CT: Impact of malignancy on texture in apparently disease-free areas of the liver. Eur J Radiol 70:101–10
McNitt-Gray MF, Wyckoff N, Sayre JW et al (1999) The effects of the co-occurrence matrix based texture parameters on the classification of solitary pulmonary nodules imaged on computed tomography. Comput Med Imaging Graph 23:339–48
Kido S, Kuriyama K, Higashiyama M et al (2002) Fractal analysis of small peripheral pulmonary nodules in thin-section CT: evaluation of the lung-nodule interfaces. J Comput Assist Tomogr 26:573–8
Wang H, Guo XH, Jia ZW et al (2010) Multilevel binomial logistic prediction model for malignant pulmonary nodules based on texture features of CT image. Eur J Radiol 74:124–9
Nelson DA, Tan TT, Rabson AB et al (2004) Hypoxia and defective apoptosis drive genomic instability and tumourigenesis. Genes Dev 18:2095–107
Semenza GL (2002) HIF-1 and tumour progression: pathophysiology and therapeutics. Trends Mol Med 8(4 Suppl):S62–7
Ganeshan B, Mandeville H, Burke M, et al (2010) CT of Non-Small Cell Lung Cancer (NSCLC): Histopathological Correlates for Texture Parameters. In Radiological Society of North America (RSNA), Chicago, USA
Keyes JW (1995) SUV: Standard Uptake Value or Silly Useless Value. J Nucl Med 36:1836–39
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.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ganeshan, B., Panayiotou, E., Burnand, K. et al. Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol 22, 796–802 (2012). https://doi.org/10.1007/s00330-011-2319-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00330-011-2319-8