Comparison of FDG PET metabolic tumour volume versus ADC histogram: prognostic value of tumour treatment response and survival in patients with locally advanced uterine cervical cancer.

OBJECTIVE

To evaluate the prognostic utility of volume-based parameters of fluorine-18 fludeoxyglucose positron emission tomography (F-FDG PET) and apparent diffusion coefficient (ADC) histogram analysis for tumour response to therapy and event-free survival (EFS) in patients with uterine cervical cancer receiving chemoradiotherapy.

METHODS

The study included 21 patients diagnosed with locally advanced uterine cervical cancer who underwent pre-treatment MRI and F-FDG PET and were treated with concurrent chemoradiotherapy. F-FDG parameters: maximum and mean standardized uptake value; metabolic tumour volume (MTV); total lesion glycolysis (TLG); ADC parameters: maximum, mean and minimum values; percentile ADC values (10-90%); skewness and kurtosis of ADC were measured and compared between the responder and non-responder groups using a Wilcoxon rank-sum test. The Cox regression analysis and Kaplan-Meier survival curves were performed for EFS analysis.

RESULTS

MTV and TLG of the primary tumour were significantly higher in the non-responder group than in the responder group (p = 0.04 and p = 0.01). Applying Cox regression multivariate analysis, MTV [hazard ratio (HR), 4.725; p = 0.036], TLG (HR, 4.725; p = 0.036) and 10-percentile ADC (HR, 5.207; p = 0.048) showed a statistically significant association with EFS. With the optimal cut-off value, the EFS rates above the cut-off value for MTV and TLG were significantly lower than that below the cut-off value (p = 0.002 and p = 0.002).

CONCLUSION

Pre-treatment volume-based quantitative parameters of F-FDG PET may have better potential than ADC histogram for predicting treatment response and EFS in patients with locally advanced cervical cancer. Advances in knowledge: In this study, pre-treatment volume-based quantitative parameters of F-FDG PET had better potential than ADC histogram for predicting treatment response and survival in patients with locally advanced cervical cancer.