Analysis of prognostic values of various PET metrics in preoperative FDG PET for early stage bronchial carcinoma for progression free and overall survival: significantly increased glycolysis is a predictive factor.

Purpose: To assess various volume based PET quantification metrics including: metabolic tumor volume (MTV) and total lesion glycolysis (TLG) with different thresholds as well as background activity based PET metrics (Background Subtracted Lesion activity (BSL) and Volume (BSV)) as prognostic markers for progression free and overall survival (PFS, OS) in early stage I and II non-small cell lung cancer (NSCLC) after resection. Patients and Methods: 133 patients received an adequate FDG PET/CT scan prior to surgery between January 2003 and December 2010. All PET activity metrics showed a skewed distribution and were log-transformed before calculating the Pearson correlation coefficients (PCC). Survival tree analysis was used to discriminate between high and low risk patients and to select the most important prognostic markers. Akaike information criterion (AIC) was used to compare two uni-variate models. Results: Within the study time 36 patients died from NSCLC and 26 patients from other causes. At the end of follow up 70 patients were alive, with 67 patients being free of disease. All log-transformed PET metrics showed a very strong linear association with a PCC between 0.703-0.962. After multiple testing corrections only one prognostic marker contributed a significant split point in the survival tree analysis. Out of 10 potential predictors including 7 PET metrics BSL>6852 (P = 0.017) was chosen as split point assigning 13 patients into a high risk group. If BSL was removed from the set of predictors TLG42% >4204 (P = 0.023) was chosen as split point. Using a dichotomized BSL or TLG42% variable for an uni-variate Cox model the AIC-difference of both models was smaller than 2, therefore the data do not provide evidence that one of the two prognostic factors is superior. Conclusion: Volume based PET metrics do correlate with PFS and OS and could be used for risk assessment in stage I-II NSCLC. The different PET metrics assessed in this study showed a very high correlation; therefore, it is not surprising that there was no significant difference to predict PFS or OS within this study. Overall, Patients with large and metabolically active tumors should be considered high risk and might need further treatment after resection. Since all analysis steps were done with the same data these results should be validated on new patient data.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 2017 May 10 [Epub ahead of print]

Seraina Steiger, Michael Arvanitakis, Beate Sick, Walter Weder, Sven Hillinger, Irene A Burger

University Hospital Zurich,Nuclear Medicine Department, Switzerland., University Hospital Zurich, Thoracic Surgery, Switzerland., University of Zurich, Department of Biostatistics, Switzerland., University Hospital Zurich, Switzerland.