Use of Tracer Kinetic Model-Driven Biomarkers for Monitoring Antiangiogenic Therapy of Hepatocellular Carcinoma in First-Pass Perfusion CT

摘要

Development of vascularly targeted anti-cancer therapies has led to an interest in determining the in vivo effectiveness of anti-tumor agents in patients. As the antiangiogenic agents may have significant effects without causing tumor shrinkage, their microcirculatory characteristics have the potential to be response biomarkers. Perfusion CT (PCT) studies can quantify the microcirculatory status of liver tumors, and can be used for assessing the effectiveness of antiangiogenic therapy. Our purpose in this study was to compare five different tracer kinetic models for the analysis of first-pass hepatic PCT data, to investigate whether kinetic parameters differ in significance among different kinetic models, and to select the best single prognostic biomarker with respect to the prediction of 6- month progression-free survival (PFS) of patients with advanced hepatocellular carcinoma (HCC). The first-pass PCT was performed at baseline and on days 10 to 12 after initiation of antiangiogenic treatment. The PCT data were analyzed retrospectively by the Tofts-Kety (TK), extended TK (ETK), two-compartment exchange (2CX), adiabatic approximation to tissue homogeneity (AATH), and distributed parameter (DP) models. Kinetic parameters consisted of blood flow(BF), blood volume (BV), mean transit time (MTT), and permeability-surface area product (PS), mean values of which within HCC were compared between baseline and post-treatment by the Wilcoxon signed-rank test. Baseline mean kinetic parameters within HCC and relative percent changes (%changes) in the mean and standard deviation (SD) from baseline to post-treatment were also compared in terms of PFS discrimination by use of Spearman correlation analysis. After treatment, the changes in the kinetic parameter values were significantly different among models. The results suggested that the %change of SD for BV is an effective prognosis biomarker, potentially reflecting that treatment-induced change of vascular heterogeneity plays a role in the assessment of the HCC response. Based on the predictive ranking of a single biomarker, the AATH model was the best predictor of 6-month PFS in the first-pass PCT analysis.