Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage

Ganeshan, Balaji, Abaleke, Sandra, Young, Rupert, Chatwin, Chris and Miles, Kenneth A. (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 (1). pp. 137-143. ISSN 1470-7330

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Abstract

The aim was to undertake an initial study of the relationship between texture features in computed tomography (CT) images of non-small cell lung cancer (NSCLC) and tumour glucose metabolism and stage. This retrospective pilot study comprised 17 patients with 18 pathologically confirmed NSCLC. Non-contrast-enhanced CT images of the primary pulmonary lesions underwent texture analysis in 2 stages as follows: (a) image filtration using Laplacian of Gaussian filter to differentially highlight fine to coarse textures, followed by (b) texture quantification using mean grey intensity (MGI), entropy (E) and uniformity (U) parameters. Texture parameters were compared with tumour fluorodeoxyglucose (FDG) uptake (standardised uptake value (SUV)) and stage as determined by the clinical report of the CT and FDG-positron emission tomography imaging. Tumour SUVs ranged between 2.8 and 10.4. The number of NSCLC with tumour stages I, II, III and IV were 4, 4, 4 and 6, respectively. Coarse texture features correlated with tumour SUV (E: r = 0.51, p = 0.03; U: r = -0.52, p = 0.03), whereas fine texture features correlated with tumour stage (MGI: r(s) = 0.71, p = 0.001; E: r(s) = 0.55, p = 0.02; U: r(s) = -0.49, p = 0.04). Fine texture predicted tumour stage with a kappa of 0.7, demonstrating 100% sensitivity and 87.5% specificity for detecting tumours above stage II (p = 0.0001). This study provides initial evidence for a relationship between texture features in NSCLC on non-contrast-enhanced CT and tumour metabolism and stage. Texture analysis warrants further investigation as a potential method for obtaining prognostic information for patients with NSCLC undergoing CT.

Item Type: Article
Schools and Departments: Brighton and Sussex Medical School > Clinical and Laboratory Investigation
School of Engineering and Informatics > Engineering and Design
School of Mathematical and Physical Sciences > Mathematics
Brighton and Sussex Medical School > Clinical and Experimental Medicine
Subjects: R Medicine > R Medicine (General) > R855 Medical technology
R Medicine > R Medicine (General) > R895 Medical physics. Medical radiology. Nuclear medicine
R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology Including cancer and carcinogens
Depositing User: Grecia GarciaGarcia
Date Deposited: 10 Aug 2011 09:25
Last Modified: 01 Sep 2017 10:14
URI: http://sro.sussex.ac.uk/id/eprint/7173
Google Scholar:6 Citations
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