Purpose: The aim of this study was to determine an optimal threshold method for the segmentation of malignant lesions from 18F-FDG PET/CT images and to evaluate the prognostic value of the total lesion glycolysis in post-surgical patients with epithelial ovarian cancer.
Methods: We retrospectively reviewed 47 patients with pathologically proven epithelial ovarian cancer who underwent 18F-FDG PET/CT imaging after surgery. The follow-up time was 26.6 ± 19.8 months (ranged from 4 to 89 months). For each patient, every lesion was segmented by 2 thresholds with 3D-area growing algorithm, standard uptake value (SUV) 2.5, and background method. The detection rates were compared. The optimal threshold method was then used to calculate whole-body metabolic tumor volume (WBMTV) and whole-body total lesion glycolysis (WBTLG). The prognostic significance of SUVmax, WBMTV, WBTLG, and other pathological variables for overall survival were assessed by Cox proportional hazards regression analysis and Kaplan-Meier survival analysis.
Results: A total of 142 metastatic lesions of 47 patients were confirmed by long-term clinical follow-up or pathological findings. The detection rates of the threshold SUV 2.5 and background methods were 37.32% (53/142) and 96.48% (137/142), respectively, which showed significant difference between the 2 methods (P < 0.005). In multivariate analysis, WBTLG, obtained from the background method, was an independent predictive factor associated with the prognosis (HR 1.043, 95% CI 1.01-1.078, P = 0.011), and none of the other factors had statistical association. Survival analysis also showed that the survival time was clearly shortened with WBTLG increasing (P < 0.001).
Conclusions: In this group of post-surgery patients with epithelial ovarian cancer, the background method could segment much more malignant lesions than SUV = 2.5 method, and WBTLG, obtained from this method, could be used as an independent prognostic factor.
From the Department of Nuclear Medicine, Union Hospital, Tongji Medical College of Huazhong University of Science and Technology, Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
Received for publication May 6, 2013; and revision accepted May 19, 2013.
Conflicts of interest and sources of funding: none declared.
Reprints: Xiaoli Lan, MD, PhD, 1277, Jiefang Ave., Wuhan, Hubei Province, 430022, China. E-mail: LXL730724@hotmail.com.