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Instrumentation & Data Analysis: Data Analysis & ManagementCardiac/Small Animal |
1 Molecular and Medical Pharmacology, UCLA, Los Angeles, California; 2 University of Innsbruck, Innsbruck, Austria
604
Objectives: To understand PET measured anti-
Vβ3-integrin 64Cu-RGD peptide kinetics in mice, we have constructed a compartmental model that can describe kinetics in tumor post IV injection.
Methods: We analyzed 64Cu-RGD peptide 60 min dynamic and 24 hr static follow-up PET scans in 8 tumor bearing SCID mice following a 400 µCi bolus dose using a standard 2-compartment (4k) tissue model with input function calculated by drawing an ROI on the reconstructed PET image in the area corresponding to heart left ventricle. 5 blocking (bl) studies were also considered where tracer was blocked with a cold dose (500x excess hot dose). Patlak & Logan analysis suggested that k4 should be fixed at some constant value (4k-fix). We fitted 2k (k3=k4=0), 3k (k4=0), 4k and 4k-fix models to the PET data and used 2 criteria to determine that 4k-fix is the best model: Akaike Information Criteria and ability of each model to predict tumor concentration of tracer 24 hr post injection.
Results: The 4k-fix model was successfully fitted to dynamic tumor data from all studies. Analysis of specific (sp) and nonspecific (nsp) binding using fitted parameter values shows that the 4k-fix model provided expected results when comparing bl and nbl studies, i.e., Vd,sp [(K1xk3)/(k2xk4)] is much higher than Vd,nsp (K1/k2) in nbl studies (2.2±0.6 vs 0.85±0.14) while Vd,sp and Vd,nsp are about the same in bl studies (0.46±0.16 vs 0.56±0.09). Also, the ratio of static measurements (Tumor60 min/Blood10 min) is highly correlated (RS=0.92) to tumor Vd.
Conclusions: Weve developed and validated a compartmental model for use with the novel 64Cu-RGD peptide PET tracer and demonstrated its potential as a tool for analysis and design of preclinical and clinical imaging studies.
Research Support: NCI Grant R25-CA098010, HHMI Training Fellowship
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