Diagnostic Performance of Dynamic Whole-Body Patlak [(18)F]FDG-PET/CT in Patients with Indeterminate Lung Lesions and Lymph Nodes

动态全身 Patlak [(18)F]FDG-PET/CT 在肺部病变和淋巴结性质不明患者中的诊断性能

阅读:1

Abstract

BACKGROUND: Static [(18)F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic performance of additional dynamic whole-body PET. METHODS: A total of 34 consecutive patients with indeterminate pulmonary lesions were enrolled in this prospective trial. All patients underwent static (60 min p.i.) and dynamic (0-60 min p.i.) whole-body [(18)F]FDG-PET/CT (300 MBq) using the multi-bed-multi-timepoint technique (Siemens mCT FlowMotion). Histology and follow-up served as ground truth. Kinetic modeling factors were calculated using a two-compartment linear Patlak model (FDG influx rate constant = Ki, metabolic rate = MR-FDG, distribution volume = DV-FDG) and compared to SUV using ROC analysis. RESULTS: MR-FDG(mean) provided the best discriminatory power between benign and malignant lung lesions with an AUC of 0.887. The AUC of DV-FDG(mean) (0.818) and SUV(mean) (0.827) was non-significantly lower. For LNM, the AUCs for MR-FDG(mean) (0.987) and SUV(mean) (0.993) were comparable. Moreover, the DV-FDG(mean) in liver metastases was three times higher than in bone or lung metastases. CONCLUSIONS: Metabolic rate quantification was shown to be a reliable method to detect malignant lung tumors, LNM, and distant metastases at least as accurately as the established SUV or dual-time-point PET scans.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。