Combinative evaluation of primary tumor and lymph nodes in predicting pelvic lymphatic metastasis in early-stage cervical cancer: A multiparametric PET-CT study

Abstract Purpose The purpose of this study is to investigate the value of combining tumor and pelvic lymph node (PLN) characteristics on PET-CT in predicting PLN metastasis of patients with early-stage cervical cancer, specifically to further reduce the false-negative cases of diagnosis. Methods The [18F] FDG PET-CT imaging data of 394 patients who were newly diagnosed with cervical cancer (FIGO stage, Ia-IIa) were retrospectively studied. We measured size, total lesion glycolysis (TLG) of tumor, metabolic tumor volume (MTV), maximum and mean standardized uptake value (SUVmax, SUVmean) of tumor and lymph node (LN). Diagnostic efficiency was evaluated using receiver operator characteristic (ROC) curve. We also investigated additional CT diagnosis information in PET-negative cases. Results Our results indicated both lymph node and tumor parameters were independent risk factors for lymphatic metastasis in early-stage cervical cancer. The diagnosis based on above meaningful parameters, we name it ‘combination diagnosis’, offered significantly higher predictive value than that based on SUV measurement alone, which the values of AUC were 0.842 and 0.784 respectively (P  Conclusions We proposed a combination diagnosis method that can better predict PLN metastasis for patients with early-stage cervical cancer. In PET-negative cases, combination diagnosis of TLG of tumor and CT indicators also produced improved prediction by reducing false-negative cases of diagnosis. This combination diagnosis approach has significant implications in cervical cancer patient management and treatment planning.