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.
Clin Nucl Med. 2013 Sep;38(9):715-20. doi: 10.1097/RLU.0b013e31829f57fa.
The aim of this study was to determine an optimal threshold method for the segmentation of malignant lesions from (18)F-FDG PET/CT images and to evaluate the prognostic value of the total lesion glycolysis in post-surgical patients with epithelial ovarian cancer.
We retrospectively reviewed 47 patients with pathologically proven epithelial ovarian cancer who underwent (18)F-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 SUV(max), WBMTV, WBTLG, and other pathological variables for overall survival were assessed by Cox proportional hazards regression analysis and Kaplan-Meier survival analysis.
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).
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.
本研究旨在确定一种用于（18）F-FDG PET/CT 图像中恶性病变分割的最佳阈值方法，并评估上皮性卵巢癌术后患者总病变糖酵解（total lesion glycolysis，TLG）的预后价值。
我们回顾性分析了 47 例经病理证实的上皮性卵巢癌患者的（18）F-FDG PET/CT 影像学资料，这些患者均在术后进行了检查。随访时间为 26.6±19.8 个月（4~89 个月）。对每位患者，使用 3D 面积生长算法、标准摄取值（standard uptake value，SUV）2.5 和背景方法对每个病灶进行 2 种阈值分割。比较检测率。然后使用最佳阈值方法计算全身代谢肿瘤体积（whole-body metabolic tumor volume，WBMTV）和全身总病变糖酵解（whole-body total lesion glycolysis，WBTLG）。采用 Cox 比例风险回归分析和 Kaplan-Meier 生存分析评估 SUV（max）、WBMTV、WBTLG 和其他病理变量对总生存的预后意义。
47 例患者共确认 142 个转移病灶，这些病灶均经长期临床随访或病理检查证实。阈值 SUV 2.5 法和背景法的检出率分别为 37.32%（53/142）和 96.48%（137/142），两种方法之间存在显著差异（P<0.005）。多因素分析显示，背景法获得的 WBTLG 是与预后相关的独立预测因素（HR 1.043，95%CI 1.01~1.078，P=0.011），而其他因素均无统计学关联。生存分析也表明，WBTLG 增加与生存时间明显缩短相关（P<0.001）。
在这组上皮性卵巢癌术后患者中，背景法较 SUV=2.5 法能分割更多的恶性病灶，且从该方法获得的 WBTLG 可作为独立的预后因素。
