An illustration of the use of model-based bootstrapping for evaluation of uncertainty in kinetic information derived from dynamic PET
Mankoff, David A.
Institute of Electrical and Electronics Engineers (IEEE)
Kinetic mapping via mixture analysis,  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.. 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.
Cancer , Medical image processing , Mixture models , Positron emission tomography , Statistical analysis , 4-D PET data , Kinetic mapping , PET flow-metabolism imaging study , Dynamic PET imaging , Bootstrapped data , Model-based bootstrapping , Kinetic information , Mixture analysis , Comprehensive voxel-level analysis , Fitted mixture model , Statistical copies , Breast cancer patient , Image domain , Projection domain , Data models , Kinetic theory , Imaging , Analytical models , Numerical models , Standards , Uncertainty , Spatial autocorrelation , Model-based bootstrap , Standard errors , Simulation
Gu, F., Wu, Q., O’Sullivan, F., Huang, J., Muzi, M. and Mankoff, D. A. (2019) 'An Illustration of the Use of Model-Based Bootstrapping for Evaluation of Uncertainty in Kinetic Information Derived from Dynamic PET', 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Manchester, United Kingdom, 26 Oct.-2 Nov. doi: 10.1109/NSS/MIC42101.2019.9059736
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