Treatment response to erlotinib and overall survival in non–small cell lung cancer are associated with a reduction in tumor heterogeneity on fluorine 18 fluorodeoxyglucose PET images.
To determine if first-order and high-order textural features on fluorine 18 (18F) fluorodeoxyglucose (FDG) positron emission tomography (PET) images of non–small cell lung cancer (NSCLC) (a) at baseline, (b) at 6 weeks, or (c) the percentage change between baseline and 6 weeks can predict response or survival in patients treated with erlotinib.
Materials and Methods
Institutional review board approval was obtained for post hoc analysis of data from a prospective single-center study for which informed consent was obtained. The study included 47 patients with NSCLC who underwent 18F-FDG PET/computed tomography (CT) at baseline (n = 47) and 6 weeks (n = 40) after commencing treatment with erlotinib. First-order and high-order primary tumor texture features reflecting image heterogeneity, standardized uptake values, metabolic tumor volume, and total lesion glycolysis were measured for all 18F-FDG PET studies. Response to erlotinib was assessed by using the Response Evaluation Criteria in Solid Tumors (RECIST) on CT images obtained at 12 weeks (n = 32). Associations between PET parameters, overall survival (OS), and RECIST-based treatment response were tested by Cox and logistic regression analyses, respectively.
Median OS was 14.1 months. According to CT RECIST at 12 weeks, there were 21 nonresponders and 11 responders. Response to erlotinib was associated with reduced heterogeneity (first-order standard deviation, P = .01; entropy, P = .001; uniformity, P = .001). At multivariable analysis, high-order contrast at 6 weeks (P = .002) and percentage change in first-order entropy (P = .03) were independently associated with survival. Percentage change in first-order entropy was also independently associated with treatment response (P = .01).
Response to erlotinib is associated with reduced heterogeneity at 18F-FDG PET. Changes in first-order entropy are independently associated with OS and treatment response.
© RSNA, 2015
- 1. . Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma. N Engl J Med 2009;361(10):947–957. Crossref, Medline, Google Scholar
- 2. . Erlotinib in previously treated non-small-cell lung cancer. N Engl J Med 2005;353(2):123–132. Crossref, Medline, Google Scholar
- 3. . Erlotinib as maintenance treatment in advanced non-small-cell lung cancer: a multicentre, randomised, placebo-controlled phase 3 study. Lancet Oncol 2010;11(6):521–529. Crossref, Medline, Google Scholar
- 4. . Is 18F-FDG PET/CT useful for the early prediction of histopathologic response to neoadjuvant erlotinib in patients with non-small cell lung cancer? J Nucl Med 2010;51(9):1344–1348. Crossref, Medline, Google Scholar
- 5. . Early prediction of nonprogression in advanced non-small-cell lung cancer treated with erlotinib by using [(18)F]fluorodeoxyglucose and [(18)F]fluorothymidine positron emission tomography. J Clin Oncol 2011;29(13):1701–1708. Crossref, Medline, Google Scholar
- 6. . (18)F-FDG PET/CT for monitoring treatment responses to the epidermal growth factor receptor inhibitor erlotinib. J Nucl Med 2011;52(11):1684–1689. Crossref, Medline, Google Scholar
- 7. . A phase II study of ¹⁸F-fluorodeoxyglucose PET-CT in non-small cell lung cancer patients receiving erlotinib (Tarceva); objective and symptomatic responses at 6 and 12 weeks. Eur J Cancer 2012;48(1):68–74. Crossref, Medline, Google Scholar
- 8. . Predictive value of early and late residual 18F-fluorodeoxyglucose and 18F-fluorothymidine uptake using different SUV measurements in patients with non-small-cell lung cancer treated with erlotinib. Eur J Nucl Med Mol Imaging 2012;39(7):1117–1127. Crossref, Medline, Google Scholar
- 9. . Prognostic impact of [18F]fluorothymidine and [18F]fluoro-D-glucose baseline uptakes in patients with lung cancer treated first-line with erlotinib. PLoS ONE 2013;8(1):e53081. Crossref, Medline, Google Scholar
- 10. . Changes in 18F-fluorodeoxyglucose and 18F-fluorodeoxythymidine positron emission tomography imaging in patients with non-small cell lung cancer treated with erlotinib. Clin Cancer Res 2011;17(10):3304–3315. Crossref, Medline, Google Scholar
- 11. . Spatial heterogeneity in sarcoma 18F-FDG uptake as a predictor of patient outcome. J Nucl Med 2008;49(12):1973–1979. Crossref, Medline, Google Scholar
- 12. . Exploring feature-based approaches in PET images for predicting cancer treatment outcomes. Pattern Recognit 2009;42(6):1162–1171. Crossref, Medline, Google Scholar
- 13. . Automated radiation targeting in head-and-neck cancer using region-based texture analysis of PET and CT images. Int J Radiat Oncol Biol Phys 2009;75(2):618–625. Crossref, Medline, Google Scholar
- 14. . Coregistered FDG PET/CT-based textural characterization of head and neck cancer for radiation treatment planning. IEEE Trans Med Imaging 2009;28(3):374–383. Crossref, Medline, Google Scholar
- 15. . Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med 2011;52(3):369–378. Crossref, Medline, Google Scholar
- 16. , El Naqa I. Combined PET/CT image characteristics for radiotherapy tumor response in lung cancer. Radiother Oncol 2012;102(2):239–245. Crossref, Medline, Google Scholar
- 17. . Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy? J Nucl Med 2013;54(1):19–26. Crossref, Medline, Google Scholar
- 18. . Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker. Radiology 2011;261(1):165–171. Link, Google Scholar
- 19. . Quantitative imaging in cancer evolution and ecology. Radiology 2013;269(1):8–15. Link, Google Scholar
- 20. . Phantom study on radiotherapy planning using PET/CT: delineation of GTV by evaluating SUV. J Radiat Res (Tokyo) 2010;51(2):157–164. Crossref, Medline, Google Scholar
- 21. . Gray matter textural heterogeneity as a potential in-vivo biomarker of fine structural abnormalities in Asperger syndrome. Pharmacogenomics J 2013;13(1):70–79. Crossref, Medline, Google Scholar
- 22. . Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis. Eur J Nucl Med Mol Imaging 2013;40(1):133–140. Crossref, Medline, Google Scholar
- 23. . Textural features corresponding to textural properties. IEEE Trans Syst Man Cybern 1989;19(5):1264–1274. Crossref, Google Scholar
- 24. . Reproducibility of tumor uptake heterogeneity characterization through textural feature analysis in 18F-FDG PET. J Nucl Med 2012;53(5):693–700. Crossref, Medline, Google Scholar
- 25. . Temporal analysis of intratumoral metabolic heterogeneity characterized by textural features in cervical cancer. Eur J Nucl Med Mol Imaging 2013;40(5):716–727. Crossref, Medline, Google Scholar
- 26. . Texture analysis of aggressive and nonaggressive lung tumor CE CT images. IEEE Trans Biomed Eng 2008;55(7):1822–1830. Crossref, Medline, Google Scholar
- 27. . Fractal analysis of internal and peripheral textures of small peripheral bronchogenic carcinomas in thin-section computed tomography: comparison of bronchioloalveolar cell carcinomas with nonbronchioloalveolar cell carcinomas. J Comput Assist Tomogr 2003;27(1):56–61. Crossref, Medline, Google Scholar
- 28. . Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol 2012;22(4):796–802. Crossref, Medline, Google Scholar
- 29. . 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 2010;10:137–143. Crossref, Medline, Google Scholar
- 30. . Non-small cell lung cancer: histopathologic correlates for texture parameters at CT. Radiology 2013;266(1):326–336. Link, Google Scholar
- 31. . 2-Deoxy-2-[18F] fluoro-D-glucose uptake and correlation to intratumoral heterogeneity. Anticancer Res 2007;27(4B):2155–2159. Medline, Google Scholar
- 32. . Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters. Acta Oncol 2010;49(7):1012–1016. Crossref, Medline, Google Scholar
- 33. . The effect of small tumor volumes on studies of intratumoral heterogeneity of tracer uptake. J Nucl Med 2014;55(1):37–42. Crossref, Medline, Google Scholar
- 34. , Cheze Le Rest C, Pradier O, Visvikis D. Robustness of intratumour 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma. Eur J Nucl Med Mol Imaging 2013;40(11):1662–1671. Crossref, Medline, Google Scholar
Article HistoryReceived June 14, 2014; revision requested July 18; revision received November 12; accepted January 5, 2015; final version accepted February 12.
Published online: Apr 17 2015
Published in print: Sept 2015