INTRODUCTION: To observe the early change of metabolic tumor heterogeneity during chemoradiotherapy and to determine its prognostic value for patients with locally advanced non-small cell lung cancer (NSCLC). METHODS: From January 2007 to March 2010, 58 patients with NSCLC were included who were received 18F-fluorodeoxyglucose (18F-FDG) PET/CT before and following 40 Gy radiotherapy with the concurrent cisplatin-based chemotherapy (CCRT). Primary tumor FDG uptake heterogeneity was determined using global and local scale textural features extracted from standardized uptake value (SUV) histogram analysis (coefficient of variation [COV], skewness, kurtosis, area under the curve of the cumulative SUV histogram [AUC-CSH]) and normalized gray-level co-occurrence matrix (contrast, dissimilarity, entropy, homogeneity). SUVmax and metabolic tumor volume (MTV) were also evaluated. Correlations were analyzed between parameters on baseline or during treatments with tumor response, progression-free survival (PFS), and overall survival (OS). RESULTS: Compared with non-responders, responders showed significantly greater pre-treatment COV, contrast and MTV (AUC = 0.781, 0.804, 0.686, respectively). Receiver-operating-characteristic curve analysis showed that early change of tumor textural analysis serves as a response predictor with higher sensitivity (73.2%~92.1%) and specificity (80.0%~83.6%) than baseline parameters. Change in AUC-CSH and dissimilarity during CCRT could also predict response with optimal cut-off values (33.0% and 28.7%, respectively). The patients with greater changes in contrast and AUC-CSH had significantly higher 5-year OS (P = 0.008, P = 0.034) and PFS (P = 0.007, P = 0.039). In multivariate analysis, only change in contrast was found as the independent prognostic factor of PFS (HR 0.476, P = 0.021) and OS (HR 0.519, P = 0.015). CONCLUSIONS: The metabolic tumor heterogeneity change during CCRT characterized by global and local scale textural features may be valuable for predicting treatment response and survival for patients with locally advanced NSCLC.

Introduction

To observe the early change of metabolic tumor heterogeneity during chemoradiotherapy and to determine its prognostic value for patients with locally advanced non-small cell lung cancer (NSCLC).

Methods

From January 2007 to March 2010, 58 patients with NSCLC were included who were received 18F-fluorodeoxyglucose (18F-FDG) PET/CT before and following 40 Gy radiotherapy with the concurrent cisplatin-based chemotherapy (CCRT). Primary tumor FDG uptake heterogeneity was determined using global and local scale textural features extracted from standardized uptake value (SUV) histogram analysis (coefficient of variation [COV], skewness, kurtosis, area under the curve of the cumulative SUV histogram [AUC-CSH]) and normalized gray-level co-occurrence matrix (contrast, dissimilarity, entropy, homogeneity). SUVmax and metabolic tumor volume (MTV) were also evaluated. Correlations were analyzed between parameters on baseline or during treatments with tumor response, progression-free survival (PFS), and overall survival (OS).

Results

Compared with non-responders, responders showed significantly greater pre-treatment COV, contrast and MTV (AUC = 0.781, 0.804, 0.686, respectively). Receiver-operating-characteristic curve analysis showed that early change of tumor textural analysis serves as a response predictor with higher sensitivity (73.2%~92.1%) and specificity (80.0%~83.6%) than baseline parameters. Change in AUC-CSH and dissimilarity during CCRT could also predict response with optimal cut-off values (33.0% and 28.7%, respectively). The patients with greater changes in contrast and AUC-CSH had significantly higher 5-year OS (P = 0.008, P = 0.034) and PFS (P = 0.007, P = 0.039). In multivariate analysis, only change in contrast was found as the independent prognostic factor of PFS (HR 0.476, P = 0.021) and OS (HR 0.519, P = 0.015).

Conclusions

The metabolic tumor heterogeneity change during CCRT characterized by global and local scale textural features may be valuable for predicting treatment response and survival for patients with locally advanced NSCLC.