Prognostic value of baseline FDG-PET/CT-derived quantitative parameters in patients with Peripheral T-cell lymphoma

1422 Background: Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of diseases. Most patients respond to initial therapy, however the response is short and additional treatment strategies are needed. Early identification of patients with grave prognosis is crucial for selecting the appropriate treatment. This study assesses the prognostic value of quantitative pre-treatment FDG-PET/CT parameters in patients with newly diagnosed peripheral T-cell lymphoma. Methods: Twenty nine patients, (17 F, aged 20-79 y), with confirmed PTCL, staged with FDG-PET/CT were retrospectively enrolled in a single medical center. Twenty-three of the 29 patients (79%) had stage III/IV disease. All patients were treated with anthracycline-based chemotherapy. Quantitative parameters including metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured for each patient using a semiautomatic software (Mirada XD, Mirada Medical Ltd). MTV was computed using the 41% maximum standardized uptake value (SUV) threshold Methods: An optimal cut-off value for survival prediction was determined by receiver operating curve (ROC) analysis. Results: The median follow-up was 3.3 years with a 2-year progression free survival (PFS) and overall survival (OS) of 34% and 65%, respectively. The median baseline MTV was 109 cm 3 and TLG was 565. No optimal sensitivity and specificity threshold was found for both MTV and TLG, neither in the whole population nor in the subgroup of patients with advanced disease. Conclusion: In present study in a small number of patients neither MTV nor TLG were predictive outcome parameters. Current results do not support recently published scarce literature data regarding the role of quantitative PET/CT parameters in PTCL. In view of these controversial results further studies in a large number of patients are needed to determine whether quantitative functional PET/CT parameters such as MTV and TLG could be used for precise prediction of outcome in patients with PTCL.