alexa COMKAT: compartment model kinetic analysis tool.
Oncology

Oncology

Journal of Cancer Science & Therapy

Author(s): Muzic RF Jr, Cornelius S

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Abstract Compartment models are the basis for most physiologically based quantification of nuclear medicine data. Although some software packages are available for this purpose, many are expensive, run on relatively few types of computers or are of limited capability, and cannot be extended because of the unavailability of source code. Consequently, institutions with modeling expertise often develop software for themselves, which has the disadvantages of lack of standardization and possible replication of effort. Therefore, general-purpose compartment-modeling software distributed with source code would be a welcome resource for the nuclear medicine community. METHODS: We formulated a mathematic framework within which compartment models containing unimolecular and bimolecular (receptor saturation) kinetics can be described. We implemented this framework within MATLAB and call the resultant software COMKAT (Compartment Model Kinetic Analysis Tool). RESULTS: COMKAT simplifies the process of defining and solving standard blood flow, 18F-FDG, and receptor models as well as models of a user's own design. In particular, COMKAT automatically defines and implements state, analytic sensitivity, and Jacobian equations. Given these, COMKAT can perform simulations in which model outputs are solved for specified parameter values, thereby allowing the user to predict how sensitive data are to these parameters. In addition, COMKAT can be used to estimate values for the parameters by fitting model output to experimental data. COMKAT is equipped with command-line and graphic user interfaces from which the user can access these features. Examples of these applications are presented along with validation and performance summaries. CONCLUSION: COMKAT is a useful software tool and is available without cost to researchers, at www.nuclear.uhrad.com/comkat.
This article was published in J Nucl Med and referenced in Journal of Cancer Science & Therapy

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