Prognostic value of CT texture analysis in patients with nonsmall cell lung cancer: Comparison with FDG-PET
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1 Prognostic value of CT texture analysis in patients with nonsmall cell lung cancer: Comparison with FDG-PET Poster No.: C-0784 Congress: ECR 2010 Type: Scientific Exhibit Topic: Chest Authors: B. Ganeshan 1, K. Burnand 2, E. Panayiotou 2, R. Young 1, C. Keywords: DOI: Chatwin 1, K. Miles 1 ; 1 Falmer, Brighton/UK, 2 Brighton/UK CT texture analysis, SUV, Non-small cell lung cancer /ecr2010/C-0784 Any information contained in this pdf file is automatically generated from digital material submitted to EPOS by third parties in the form of scientific presentations. References to any names, marks, products, or services of third parties or hypertext links to thirdparty sites or information are provided solely as a convenience to you and do not in any way constitute or imply ECR's endorsement, sponsorship or recommendation of the third party, information, product or service. ECR is not responsible for the content of these pages and does not make any representations regarding the content or accuracy of material in this file. As per copyright regulations, any unauthorised use of the material or parts thereof as well as commercial reproduction or multiple distribution by any traditional or electronically based reproduction/publication method ist strictly prohibited. You agree to defend, indemnify, and hold ECR harmless from and against any and all claims, damages, costs, and expenses, including attorneys' fees, arising from or related to your use of these pages. Please note: Links to movies, ppt slideshows and any other multimedia files are not available in the pdf version of presentations. Page 1 of 9
2 Purpose Lung cancer is the most common cause of death related to cancer worldwide 1,2 Non-small cell lung carcinoma (NSCLC) is the most common form of lung cancer 3 Computed tomography (CT) is widely used for initial diagnosis and staging NSCLC patients 4 Primary tumour metabolism measured as standardized uptake value (SUV) from fluorodeoxyglucose (FDG)-PET is a recognised prognostic marker of survival in NSCLC 5,6 Tumour heterogeneity is a feature of more aggressive disease status indicating poor prognosis Texture analysis of radiological images (TexRAD) e.g. CT is a novel tool developed to analyse tumour heterogeneity In NSCLC, CT texture measurement of primary tumour heterogeneity demonstrated significant relationship with tumour metabolism and stage 7 This study assesses and compares the ability of CT texture analysis of primary tumour as a prognostic marker of survival in comparison to FDG- PET SUV in NSCLC Methods and Materials Non-contrast CT texture and SUV were retrospectively evaluated in primary tumour (lesion) within FDG PET-CT images from 56 patients with NSCLC Texture analysis comprised band-pass image filtration to highlight image features at different spatial frequencies between # = 0.5 (fine detail) and # = 2.5 (coarse features) with quantification of mean grey-level intensity (MGI), entropy and uniformity in the filtered CT images Quantification of the above parameters were also carried out in unfiltered CT images SUV max was measured using a standard clinical imaging software Receiver operating characteristics (ROC) identified the diagnostic threshold for Texture and SUV to predict patients who died within 30 months of their CT Using the diagnostic threshold, Texture and SUV were related to patient survival using Kaplan-Meier (KM) survival analysis. Filter sigma (#) Filter width (pixels) Filter width (mm) Page 2 of 9
3 Table 1: Filter sigma value & the corresponding width of the filter (pixels and mm) Images for this section: Fig. 1: Highlights the conventional non-contrast CT image of the lung lesion (top-left), followed by the derived lesion texture maps superimposed on the conventional CT image for a NSCLC patient who was alive at 30 months after CT (Patient A) - fine (red), medium (green) and coarse (blue) texture not easily perceptible from the conventional CT image Page 3 of 9
4 Fig. 2: Highlights the conventional non-contrast CT image of the lung lesion (top-left), followed by the derived lesion texture maps superimposed on the conventional CT image for a NSCLC patient who died within 5 months of CT (Patient B) - fine (red), medium (green) and coarse (blue) texture not easily perceptible from the conventional CT image Page 4 of 9
5 Results The median (range) survival of the patients was 29.5 (1-38) months Survival analysis on the 56 patients showed 28 died (50%), of which 27 died within 30 months of their CT and 2 patients were untraceable SUV (diagnostic threshold: > 9.1) did not significantly predict patient survival CT lung lesion texture was a significant predictor of patient survival; particularly medium texture (#=1.0, entropy, diagnostic threshold > 3.0) most significantly separated the patient groups (p<0.001). Parameter Diagnostic threshold (ROC) p (KM survival analysis) SUV max > Fine (#=0.5) entropy Medium (#=1.0) > > * entropy Medium (#=1.0) uniformity <= Medium (#=1.8) uniformity <= Coarse (#=2.0) MGI > Coarse (#=2.5) uniformity <= Table 2: Diagnostic threshold (from ROC analysis) and comparison of the survival curves (from KM survival analysis) for SUV max and texture parameters ( * - indicates the most significant parameter from KM analysis) Images for this section: Page 5 of 9
6 Page 6 of 9
7 Fig. 1: Kaplan-Meier survival curves for NSCLC patients separated by (A) CT lung lesion texture (#=1.0, entropy) and (B) lung lesion SUVmax from PET. Survival curves were significantly different for texture analysis (p=0.0007) and not significant for SUVmax Fig. 2: TexRAD spectrums generated for the 2 NSCLC patients, who were followed up for a minimum period of 30 months. Patient B demonstrated heterogeneous texture within the lung lesion on CT across different filter parameters representing fine, medium and coarse features (higher mean grey-level intensity, entropy and lower uniformity). Particularly medium (#=1.0) entropy for patient B was greater than the diagnostic Page 7 of 9
8 threshold of 3.0 in comparison to patient A. Note: The height of the spectrum 'bar' indicates mean grey-level intensity, colour of each bar indicates degree of uniformity between 0 and 1 (0 - non-uniform and 1 - uniform) and the trend line indicates entropy (a measure that represents heterogeneity) across different filter parameters. Page 8 of 9
9 Conclusion Our study provides preliminary evidence that analysis of lung lesion texture on non-contrast enhanced CT is potentially a superior predictor of survival for patients with NSCLC than FDG uptake (SUV) on PET Future studies need to explore the relationship between texture and pathological findings - providing a biological rationale for its prognostic value and use in clinical practice References 1. Matteis SD, Consonni D, Bertazzi PA. Exposure to occupational carcinogens and lung cancer risk. Evolution of epidemiological estimates of attributable fraction. Acta Biomed 2008; 79(1): WHO. Revised Global Burden of Disease (GBD) 2002 Estimates. 2008; Available from: index.html. 3. Travis WD, Travis LB, Devesa SS. Lung cancer. Cancer 1995; 75(1): Mountain CF. Revisions in the international system for staging lung cancer. Chest 1997;111: Berghmans T, Dusart M, Paesmans M,et al. 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. 2008; 3(1):6-12. Review. 6. Na II, Byun BH, Kang HJ, et al. 18F-fluro-2-deoxy-glucose uptake predicts clinical outcome in patients with gefitinib-treated non-small cell lung cancer. Clin Cancer Res. 2008; 14(7): Ganeshan B, Panayiotou E, Abaleke SC, Young RCD, Chatwin CR, Miles KA. 'TEX-CT Vs PET-CT' as a prognostic tool in Non-Small Cell Lung Carcinoma. In Cancer Imaging, ICIS 2008, Bath, UK Personal Information Page 9 of 9
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