JSM 2005 Online Program

Abstract #304297

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	131
Type:	Topic Contributed
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Biometrics Section
Abstract - #304297
Title:	Mixture Modeling for PET Neuroreceptor Studies
Author(s):	Huiping Jiang*+ and Todd Ogden
Companies:	Columbia University and Columbia University
Address:	2195 N Central Road, Fort Lee, NJ, 07024, United States
Keywords:	Mixture Model ; PET ; kinetic model
Abstract:	Standard kinetic modeling is a longstanding and popular method for modeling concentrations over time in PET imaging studies for neuroreceptor binding. Major drawbacks with this general approach are its reliance on the particular choice of model and that the nonlinear least squares algorithm used for fitting such models requires substantial computational expense. Relatively recently, alternatives to kinetic modeling have become popular. Graphical analysis (starting with Logan et al. 1990 and including several variants) is an attractive option because it allows estimation of distribution volume without requiring the specification of a kinetic model. Another nice alternative to kinetic modeling is the basis pursuit modeling method of Gunn et al. (2002) in which each voxel time-activity curve (TAC) is expressed as a weighted sum of basis functions. Overfitting is controlled by applying an L1 penalty to the basis coefficients, and this penalty may be chosen by crossvalidation.

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