Functional Mapping of Regional Liver Asialoglycoprotein Receptor Amount from Single Blood Sample and SPECT

摘要

id="p-1">The objective of this study was to validate a method for estimating regional liver asialoglycoprotein (ASGP) receptor amount from single blood samples using static SPECT with 99mTc-diethylenetriaminepentaacetic acid galactosyl human serum albumin (99mTc-GSA). >Methods: Based on a 2-compartment nonlinear model, regional ASGP receptor amount could be calculated from total liver ASGP receptor amount (Ro) and regional GSA uptake at a specific time. Because Ro could be estimated from single blood samples using an empiric formula, regional GSA uptake obtained as a SPECT voxel count could be converted to regional ASGP receptor amount by solving a nonlinear model equation. To validate this method, data from 62 patients with chronic liver disease underwent dynamic SPECT (30 rotations per 30 min) and simultaneous multiblood sampling and were analyzed by this method. Ro was calculated as the sum of voxel values of parametric receptor images generated from plasma concentration of GSA at 20 min and of static SPECT images generated by merging dynamic SPECT data (12-20 min). Ro was also estimated by fitting time-activity curves (4-30 min) of plasma and whole liver to the nonlinear model using the nonlinear regression method. Ro obtained from the receptor image was compared with that from curve fitting in relation to the results of hepatic function tests (indocyanine green test, hepaplastin test, and branched-chain amino acids/tyrosine plasma concentration ratio) and Childa€?s classification. >Results: Ros from the 2 methods showed a significant linear correlation (r2 = 0.938; P 0.0001; slope = 0.90; y-intercept = 1.5). Both Ros had significant correlations with the results of hepatic function tests (P 0.001) and differed significantly among the 3 groups of Childa€?s classification (P 0.0001). >Conclusion: The present method could provide a quantitative ASGP receptor image without dynamic data acquisition. This approach could be useful for quantitative evaluation of regional liver function and estimation of residual liver function in hepatectomy.