A Head-to-Head Comparison of 68Ga-LNC1007 and 2-18F-FDG/68Ga-FAPI-02 PET/CT in Patients With Various Cancers.

Journal: Clinical Nuclear Medicine
Published:
Abstract

Objective: This head-to-head comparison study was designed to investigate the radiotracer uptake and clinical feasibility of using 68Ga-LNC1007, to detect the primary and metastatic lesions in patients with various types of cancer, and to compare the results with those of 2-18F-FDG PET/CT and 68Ga-FAPI-02 PET/CT.

Methods: Sixty-one patients with 10 different kinds of cancers were enrolled in this study. Among them, 50 patients underwent paired 68Ga-LNC1007 and 2-18F-FDG PET/CT, and the other 11 patients underwent paired 68Ga-LNC1007 and 68Ga-FAPI-02 PET/CT. The final diagnosis was based on histopathological results and diagnostic radiology. Immunohistochemistry for FAP and integrin αvβ3 was performed in 24 primary tumors.

Results: 68Ga-LNC1007 PET/CT detected all 55 primary tumors, whereas 2-18F-FDG PET/CT was visually positive for 45 primary tumors (P = 0.002). Furthermore, subgroup analysis showed that 68Ga-LNC1007 PET/CT was superior to 2-18F-FDG PET/CT in diagnosing renal cell carcinomas and hepatocellular carcinomas. For metastatic tumors, 68Ga-LNC1007 PET/CT revealed more PET-positive lesions and higher SUVmax for skeletal metastases and peritoneal metastases compared with 2-18F-FDG. The SUVmax and tumor-to-background ratio of primary tumors on 68Ga-LNC1007 PET/CT were much higher than those on 68Ga-FAPI-02 PET/CT, the same was also observed for metastatic tumors. Immunohistochemical results showed that the SUVmean quantified from 68Ga-LNC1007 PET was correlated with FAP expression level (r = 0.564, P = 0.005).

Conclusions: 68Ga-LNC1007 is a promising new diagnostic PET tracer for imaging of various kinds of malignant lesions. It may be a better alternative to 2-18F-FDG for diagnosing renal cell carcinoma, hepatocellular carcinoma, skeletal metastases, and peritoneal metastases.

Authors
Jie Zang, Rong Lin, Xuejun Wen, Chao Wang, Tianzhi Zhao, Vivianne Jakobsson, Yun Yang, Xiaoming Wu, Zhide Guo, Xiaoyuan Chen, Jingjing Zhang, Weibing Miao