OBJECTIVES: To evaluate the role of FDG PET/CT in the preoperative N-staging of high-risk clinical stage I endometrial cancer. The correlation between the metabolic characteristics of endometrial tumor uptake as predictors of a) lymph-node (LN) metastases and b) recurrence, was also evaluated. METHODS: Seventy-six high-risk (G2 with deep myometrial invasion, G3, serous/clear-cell carcinoma) clinical stage I endometrial cancer patients underwent preoperative PET/CT scan followed by total hysterectomy, bilateral salpingo-oophorectomy and lymphadenectomy. PET/CT images were analyzed and correlated to histological findings. Maximal and mean standardized uptake value (SUVmax, SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG, defined as the product between SUVmean and MTV) of endometrial lesions were calculated and correlated to: a) presence of LN metastases, b) recurrences. RESULTS: PET/CT resulted positive at LNs in 12/76 patients: 11/12 truly positive, 1/12 falsely positive. Conversely PET/CT was negative in 64/76 patients: 61/64 truly negative and 3/64 falsely negative. On pt-based analysis, sensitivity, specificity, accuracy, positive and negative predictive value of PET/CT in detecting LN metastases were 78.6%, 98.4%, 94.7%, 91.7%, 95.3%, respectively. A significant association was found between the presence of LN metastases and SUVmax (p=0.038), MTV (p=0.007), TLG (p=0.003) of the primary tumor. No correlations were found between the metabolic parameters and relapse (median follow-up 25.4months). CONCLUSIONS: In high-risk clinical stage I endometrial cancer FDG PET/CT demonstrated moderate sensitivity, high specificity and accuracy for the nodal status assessment. SUVmax, MTV and TLG of the primary tumor are significantly correlated to LN metastases, while none of these parameters is predictor of recurrence.
OBJECTIVES: To evaluate the role of FDG PET/CT in the preoperative N-staging of high-risk clinical stage I endometrial cancer. The correlation between the metabolic characteristics of endometrial tumor uptake as predictors of a) lymph-node (LN) metastases and b) recurrence, was also evaluated. METHODS: Seventy-six high-risk (G2 with deep myometrial invasion, G3, serous/clear-cell carcinoma) clinical stage I endometrial cancerpatients underwent preoperative PET/CT scan followed by total hysterectomy, bilateral salpingo-oophorectomy and lymphadenectomy. PET/CT images were analyzed and correlated to histological findings. Maximal and mean standardized uptake value (SUVmax, SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG, defined as the product between SUVmean and MTV) of endometrial lesions were calculated and correlated to: a) presence of LN metastases, b) recurrences. RESULTS: PET/CT resulted positive at LNs in 12/76 patients: 11/12 truly positive, 1/12 falsely positive. Conversely PET/CT was negative in 64/76 patients: 61/64 truly negative and 3/64 falsely negative. On pt-based analysis, sensitivity, specificity, accuracy, positive and negative predictive value of PET/CT in detecting LN metastases were 78.6%, 98.4%, 94.7%, 91.7%, 95.3%, respectively. A significant association was found between the presence of LN metastases and SUVmax (p=0.038), MTV (p=0.007), TLG (p=0.003) of the primary tumor. No correlations were found between the metabolic parameters and relapse (median follow-up 25.4months). CONCLUSIONS: In high-risk clinical stage I endometrial cancer FDG PET/CT demonstrated moderate sensitivity, high specificity and accuracy for the nodal status assessment. SUVmax, MTV and TLG of the primary tumor are significantly correlated to LN metastases, while none of these parameters is predictor of recurrence.
Authors: Casper Reijnen; Joanna IntHout; Leon F A G Massuger; Fleur Strobbe; Heidi V N Küsters-Vandevelde; Ingfrid S Haldorsen; Marc P L M Snijders; Johanna M A Pijnenborg Journal: Oncologist Date: 2019-06-11
Authors: Mostafa Atri; Zheng Zhang; Farrokh Dehdashti; Susanna I Lee; Helga Marques; Shamshad Ali; Wui-Jin Koh; Robert S Mannel; Paul DiSilvestro; Stephanie A King; Michael Pearl; XunClare Zhou; Marie Plante; Katherine M Moxley; Michael Gold Journal: Radiology Date: 2017-01-03 Impact factor: 11.105
Authors: Giorgio Bogani; Sean C Dowdy; William A Cliby; Fabio Ghezzi; Diego Rossetti; Andrea Mariani Journal: J Obstet Gynaecol Res Date: 2014-02 Impact factor: 1.730
Authors: Alessandra Musto; Gaia Grassetto; Maria Cristina Marzola; Sotirios Chondrogiannis; Anna Margherita Maffione; Lucia Rampin; David Fuster; Francesco Giammarile; Patrick M Colletti; Domenico Rubello Journal: Yonsei Med J Date: 2014-11 Impact factor: 2.759