Abstract
The multiple injection dynamic Positron Emission Tomography (PET) scanning is used in the clinical management of certain groups of cancer patients and in medical research. The analysis of such studies can be approached in one of two ways: analyze individual injections separately to recover tracer kinetic information, or concatenate data from separate injections and carry out a combined analysis. Separate analysis offers some simplicity but may not be as efficient statistically. The mixture technique is readily implemented in a separated or combined analysis mode. We evaluate these approaches in a 1-D simulation setting matched to the mathematical complexity of PET. These simulations are largely guided by experience with breast cancer flow-metabolism mismatch studies using 15O-Water (H2O) and 18F-Fluorodeoxyglucose (FDG). An efficient implementation in the R (an open-source environment) is used to implement simulations. The simulations evaluate mean square error (MSE) characteristics, for separate and combined analysis, both as a function of dose. The relationship between MSE characteristics of the underlying source distribution is described and the combined analysis is found to reduce MSE by between 18.1% and 33.85%. The quantitative advantages of combined approach have been demonstrated.
| Original language | English |
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| Title of host publication | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728141640 |
| DOIs | |
| Publication status | Published - Oct 2019 |
| Event | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019 - Manchester, United Kingdom Duration: 26 Oct 2019 → 2 Nov 2019 |
Publication series
| Name | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019 |
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Conference
| Conference | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019 |
|---|---|
| Country/Territory | United Kingdom |
| City | Manchester |
| Period | 26/10/19 → 2/11/19 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Combined Kinetic Modelling
- Mixture analysis
- Multiple Injections
- Simulation
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