ABSTRACTS PRESENTADOS AL 11th INTERNATIONAL SYMPOSIUM "RADIONUCLIDES IN NEPHRO-UROLOGY", REALIZADO EN MONTEREY, CALIFORNIA, 13-17 MAYO 2001.

Charles D. Russell, Eva V. Dubovsky, Andrew T. Taylor Jr.
University of Alabama at Birmingham, AL, and Emory University, Atlanta, GA

Introduction: Nonlinear Bayesian regression permits curve fitting to a group of subjects simultaneously, rather than individually. We evaluated this approach for interpreting plasma clearance curves.

Methods: Tc99m-DTPA plasma clearance curves were analyzed from 79 subjects. The data typically comprised 7-9 samples obtained from 5-10 to 180 - 249 min after injection. A two- compartment model was fitted by Bayesian regression to yield the compartmental hyperparameters V1, L21 and, L12 corresponding respectively to the volume of that compartment that includes blood plasma, and the transfer rates from compartment 1 to 2 and from 2 to 1. This also yielded a clearance estimate for each subject.

Results: Estimates for the hyperparameters were ,. Conventional methods led to fitting failures in 2 of the 79 subjects but there were no failures with the Bayesian model. These hyperparameters were used to calculate GFR for each subject from a single plasma sample with root mean square error 7.8 ml/min, not significantly different from the widely used Christensen-Groth formula (1986). This model requires only 3 parameters, while the Christensen-Groth method requires 6.

Conclusion. A Bayesian two-compartment model was applied to the plasma clearance of Tc99m-DTPA. Fewer fitting failures were encountered than with conventional methods, providing a means of dealing with problem data. The two-compartment model with Bayesian hyperparameters can be used directly to calculate clearance from a single plasma sample.