Predictive value of PET/CT based metabolic information in the modern 3D based radiotherapy treatment of head and neck can-cer patients - single institute study.

Objective: The aim of the study was to evaluate the predictive value of pretreatment positron emission tomography (PET) standardized uptake value (SUVmax), standardized uptake value corrected for lean body mass (SULpeak) value, metabolic tumour volume (MTV) and total lesion glycolysis (TLG) parameters of the primary tumour assessed with PET/computed tomography (CT) in the clinical out-come in patients diagnosed with histopathologically confirmed head and neck squamous cell carcinoma.

Materials And Methods: Retrospective evaluation was performed using PET/CT image datasets of 52 histologically proven head and neck cancer patients in 4 weeks' prior receiving definitive chemo-radiotherapy (CRT). Positron emission tomography /CT was performed before the CRT and 12 weeks after it for response evaluation. Image data was used for target volume delineation and for specify SUVmax, SULpeak, MTV and TLG parameters of the primary tumour. According to the results of the therapeutic response evaluation two patient subgroups were created in relation to the presence or absence of viable tumour. Metabolic data from pre-treatment PET/CT and therapeutic response were correlated using Kruskal-Wallis test.

Results: After completion of the CRT in 24/52 (46%) cases viable residual tumour was detected on restaging PET/CT, while in 28/52 (54%) patients showed complete remission. For the therapeutic success prediction assessment, we could not find any significant correlation with pre-treatment SUVmax and SULpeak values (P>0.44, P>0.33). Total lesion glycolysis provided nearly significant difference (P=0.052) and MTV had shown significant difference (P=0.001) between the two patient subgroups statistically.

Conclusion: Simple metabolic data (SUVmax and SULpeak) from pretreatment fluorine-18-fluorodeoxyglucose (F-FDG) PET/CT were unable to predict therapeutic response, while volumetric information containing MTV and TLG parameters proved to be more useful, thus their inclusion to risk stratification may also have additional value.