Abstract
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 MethodsInstitutional 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.
ResultsMedian 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).
ConclusionResponse to erlotinib is associated with reduced heterogeneity at 18F-FDG PET. Changes in first-order entropy are independently associated with OS and treatment response.
Original language | English |
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Pages (from-to) | 883-893 |
Number of pages | 11 |
Journal | Radiology |
Volume | 276 |
Issue number | 3 |
Early online date | 17 Aug 2015 |
DOIs | |
Publication status | Published - 1 Sept 2015 |