Value of Multitracer Imaging in Hepatocellular Carcinomas with Different Metastatic Potential

Abstract Background Hepatocellular carcinoma (HCC) shows marked heterogeneity and varying metastatic potential, challenging prognosis and treatment. This study evaluated multitracer PET imaging with [ 18 F]FDG, [ 18 F]FLT, and [ 18 F]ACE to differentiate HCCs by metastatic behavior and explored its prognostic relevance. Methods Four human HCC cell lines with varying metastatic potential (HepG2, QGY7701, MHCC97-H, MHCC97-L) were assessed for in vitro tracer uptake, proliferation, and invasion. Subcutaneous and spontaneous metastasis models were established in nude mice. Tumor uptake of tracers was quantified via microPET/CT. mRNA expression of MMP9 and VEGFR-2 and survival were analyzed. Fisher’s classifier was applied to compare single-, dual-, and triple-tracer datasets with cross-validation. Results Tracer uptake significantly differed among cell lines ( p < 0.001). The triple-tracer model ([ 18 F]FDG + [ 18 F]FLT + [ 18 F]ACE) yielded the lowest classification error rate (0.074) compared with dual tracers (0.085–0.362). In vivo, [ 18 F]FDG uptake correlated with metastatic potential, MMP9 and VEGFR-2 expression (r = 0.770–0.830, p < 0.05), and inversely with survival (r = − 0.726, p = 0.005). There is a significant difference in FDG uptake values between high-metastatic and low-metastatic cell lines as well as in tumor model.[ 18 F]FLT uptake showed moderate correlation with biomarkers but not with survival, while [ 18 F]ACE had no significant discriminative value. Conclusions A multiparameter (multitracer) classification model had superior ability to discriminate four HCC cell lines with different biological behavior compared with dual tracers or single tracer through in vitro cell uptake experiment. [1⁸F]FDG uptake can distinguish between tumor models with high and low metastatic potential, and [1⁸F]FDG uptake can predict the survival time in metastatic models. [ 18 F]FDG uptake probably be noninvasive prognostic marker, reflecting tumor heterogeneity and correlating with survival and metastasis-related biomarkers. This approach may aid in clinical stratification and personalized management of HCC.