UCLA Tracer Kinetic Model Fitting (TKMF) Program

The Tracer Kinetic Model Fitting (TKMF) Program is a server-based tracer kinetic analysis software program that is accessible through the Internet. It provides the general capability of tracer kinetic model fitting to PET/SPECT generated kinetics that characterize local tissue functions in nuclear medicine. With simple user interactions, the program automatically fits a set of kinetic tissue data (e.g., measured with PET/SPECT and obtained with ROI analysis) with a user selected tracer kinetic model.

The program is accessible through the web with any Java-enabled Internet browser on any computer platform (Mac, PC, or Unix/Linux based workstations). It allows both the blood time activity curve (input function) and tissue time activity curve to be uploaded from user’s computer to a working area in the server. After model fitting, the results, including the model predicted kinetic curve and the values of the model parameters, are displayed on the browser and can be printed or downloaded to the user’s local computer. The program is thus a server-based application program accessible by users on the Internet.

Many features (such as, user-defined initial conditions, weightings, and convergence criteria) are incorporated in the program that allows flexibility in performing the model fitting. Currently, the program supports model fittings to FDG, O-15 water, FWIN, EXP, EXPM, POLY, O2, PATLAK, LOGAN and FDOPA. A general exponential model (with 2 exponential components) for estimating macro-parameters is also available. The number of models supported will be expanded gradually to include many models commonly used in nuclear medicine. A capability to allow kinetic fitting with user-defined models and for parametric image generation will be added in the near future.

The program also allows users to upload image files for image analysis.



Official Website

Source Code (requires registration online or by email)

Tutorials: Description, Technical Info, Supported Models, Problem Report

Reference: UCLA Computational Core Group


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