[Direct integral linear least square regression method for kinetic evaluation of hepatobiliary scintigraphy: theory, basic analysis and comparison with non-linear least square regression method].
In hepatobiliary scintigraphy, kinetic model analysis, which provides kinetic parameters like hepatic extraction or excretion rate, have been done for quantitative evaluation of liver function. In this analysis, unknown model parameters are usually determined using nonlinear least square regression method (NLS method) where iterative calculation and initial estimate for unknown parameters are required. As a simple alternative to NLS method, direct integral linear least square regression method (DILS method), which can determine model parameters by a simple calculation without initial estimate, is proposed, and tested the applicability to analysis of hepatobiliary scintigraphy. In order to see whether DILS method could determine model parameters as good as NLS method, or to determine appropriate weight for DILS method, simulated theoretical data based on prefixed parameters were fitted to 1 compartment model using both DILS method with various weightings and NLS method. The obtained parameter values were then compared with prefixed values which were used for data generation. The effect of various weights on the error of parameter estimate was examined, and inverse of time was found to be the best weight to make the error minimum. When used this weight, DILS method could give close parameter values to those obtained by NLS method and both parameter values were very close to prefixed values. With appropriate weighting, the DILS method could provide reliable parameter estimate which is relatively insensitive to the data noise. In conclusion, the DILS method could be used as a simple alternative to NLS method, providing reliable parameter estimate.
Shuke
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Department of Nuclear Medicine, Kanazawa University School of Medicine.
D001659:Biliary Tract / Q000000981:diagnostic imaging*; D005069:Evaluation Studies as Topic; D008099:Liver / Q000000981:diagnostic imaging*; D008954:Models, Biological; D011877:Radionuclide Imaging; D012044:Regression Analysis