Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5 Άγιος Νικόλαος
Κρήτη 72100
00302841026182
00306932607174
alsfakia@gmail.com

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Πέμπτη 11 Φεβρουαρίου 2016

Pretreatment 18FDG-PET Textural Features in Locally Advanced Non-Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235

Background: In a secondary analysis of ACRIN 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on positron emission tomography with 18F-fluorodeoxyglucose (FDG-PET) was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Methods: Patients with locally advanced NSCLC underwent 18FDG-PET prior to treatment. A gradient-based segmentation tool was used to contour each patient's primary tumor. MTV, maximum standardized uptake value (SUV), and 43 textural features were extracted for each tumor. To address overfitting and high collinearity among PET features, the Least Absolute Shrinkage and Selection Operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan-Meier curves and log-rank testing were used to compare outcomes among patient groups. Results: 201 patients met inclusion criteria. The LASSO procedure identified one textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm3, and the optimal SumMean cutpoint for tumors above 93.3 cm3 was 0.018. This grouped patients into three categories: low tumor MTV (n = 155, median OS 22.6 months), high tumor MTV and high SumMean (n = 23, median OS 20.0 months), and high tumor MTV and low SumMean (n = 23, median OS 6.2 months; logrank P < 0.001). Conclusion: We have described an appropriate methodology to evaluate the prognostic value of textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted.



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