Abstract
Kinetic mapping via mixture analysis[8], [10] involves comprehensive voxel-level analysis of dynamic PET data. Bootstrapping from the fitted mixture model gives the ability to directly simulate statistical copies of the 4-D PET data, and following suitable analysis, subsequent simulations of the associated kinetic maps. This gives the ability to numerically evaluate uncertainties in inferences associated with kinetic information. We provide a simple introduction to the concept of the model-based bootstrap and an illustration of the use of the approach for kinetic mapping from dynamic PET using results from recent work in Huang et al.[4]. The illustration is from a PET flow-metabolism imaging study in a breast cancer patient. It involves separate dynamic PET imaging following injections of O-15 H2O and F-18 FDG. The bootstrapped data is created in the image domain rather than the projection domain, so there is no reconstruction requirement involved.
| 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 |
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| 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
- Mixture models
- Model-based bootstrap
- Simulation
- Spatial autocorrelation
- Standard errors
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