Kexin Li1, Hongzan Sun2, Qiyong Guo1. 1. Department of Radiology, Shengjing Hospital of China Medical University, Sanhao Street No36, Heping District, Shenyang, Liaoning, 110004, PR China. 2. Department of Radiology, Shengjing Hospital of China Medical University, Sanhao Street No36, Heping District, Shenyang, Liaoning, 110004, PR China. Electronic address: sunhongzan@126.com.
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 < 0.05). In PET-negative cases, we also found that tumor TLG, suspicious LN in lymphatic drainage pathway, long/short axis of LN ≤ 2, heterogeneity of LN significantly associated with PLN metastasis. ROC analysis showed combination diagnosis of all these parameters above produced an AUC value of 0.859 (P < 0.05, 95% CI, 0.811-0.899), which was significantly higher than either using tumor TLG alone (AUC = 0.622, Z = 3.919, P < 0.05) or indices derived from CT alone (AUC = 0.727, 0.668, 0.695. Z = 3.620, 5.356, 3.696, P < 0.05). 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.
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 < 0.05). In PET-negative cases, we also found that tumor TLG, suspicious LN in lymphatic drainage pathway, long/short axis of LN ≤ 2, heterogeneity of LN significantly associated with PLN metastasis. ROC analysis showed combination diagnosis of all these parameters above produced an AUC value of 0.859 (P < 0.05, 95% CI, 0.811-0.899), which was significantly higher than either using tumor TLG alone (AUC = 0.622, Z = 3.919, P < 0.05) or indices derived from CT alone (AUC = 0.727, 0.668, 0.695. Z = 3.620, 5.356, 3.696, P < 0.05). 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 cancerpatient management and treatment planning.
Authors: Ester P Olthof; Maaike A van der Aa; Judit A Adam; Lukas J A Stalpers; Hans H B Wenzel; Jacobus van der Velden; Constantijne H Mom Journal: Int J Clin Oncol Date: 2021-07-09 Impact factor: 3.402
Authors: Matthias Weissinger; Florin-Andrei Taran; Sergios Gatidis; Stefan Kommoss; Konstantin Nikolaou; Samine Sahbai; Christian la Fougère; Sara Yvonne Brucker; Helmut Dittmann Journal: J Nucl Med Date: 2021-01-28 Impact factor: 10.057