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An internet-based "kinetic imaging system" (KIS) for MicroPET.
Sung-Cheng Huang1, David Truong, Hsiao-Ming Wu
1Department of Molecular and Medical Pharmacology, UCLA David Geffen School of Medicine, University of California in Los Angeles, CA 90095, USA. hhuang@mednet.ucla.edu
Molecular Imaging and Biology
|September 1, 2005
Summary
The Kinetic Imaging System (KIS) simplifies MicroPET study design and analysis. This software aids researchers in understanding complex parameters for better experimental planning and data interpretation.
Area of Science:
- Medical Imaging
- Pharmacokinetics
- Computational Biology
Background:
- MicroPET studies require careful selection of numerous interdependent experimental parameters.
- Optimizing these parameters for MicroPET studies is complex and challenging.
Purpose of the Study:
- To develop an integrated software system, the Kinetic Imaging System (KIS), to assist in planning, design, and data analysis of MicroPET studies.
- To provide a user-friendly platform for education, virtual experimentation, and image analysis of MicroPET data.
Main Methods:
- Developed the Kinetic Imaging System (KIS) with four modules: Dictionary, Virtual Experimentation, Image Analysis, and Model Fitting.
- KIS integrates didactic information, computer simulations using a 3D digital mouse phantom, image manipulation, and model-fitting capabilities.
- The system is accessible via the Web or as a stand-alone application.
Main Results:
- KIS enables users to virtually experiment with biochemical/pharmacokinetic parameters and their effects on tissue tracer kinetics.
- Users can evaluate radiotracer characteristics, administration methods, dose levels, imaging sequences, and resolution-to-noise tradeoffs.
- The system facilitates the evaluation of MicroPET experimental design options.
Conclusions:
- The Kinetic Imaging System (KIS) simplifies the learning and application of tracer kinetics for MicroPET studies.
- KIS empowers biology and pharmaceutical scientists to optimize MicroPET experimental design and data analysis through virtual experimentation.