Key result
A motion correction algorithm using projection consistency conditions significantly improved myocardial blood flow estimate accuracy in simulated cardiac PET-CT, reducing median errors from 33% to 4.5%.
Why the study?
Patient body motion causes large deviations in myocardial blood flow determination, and accurate correction for whole-body motion remains largely unsolved in cardiac PET imaging.
Population
Digital NCAT phantoms and a cardiac torso phantom
Comparison
Projection consistency condition-based CT-to-PET alignment motion correction vs uncorrected motion
Design
Simulation and phantom proof-of-concept study
Authors
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Does not support clinical adoption; hypothesis-generating for motion correction in simulated cardiac PET-CT.
A novel motion correction algorithm using projection consistency conditions significantly improves the accuracy of myocardial blood flow estimates in dynamic cardiac PET-CT.
Hunter et al. (2019) studied Patient body motion in cardiac PET imaging. Motion correction algorithm using projection consistency conditions vs. Uncorrected imaging was evaluated on Accuracy of myocardial blood flow (MBF) estimates. A motion correction algorithm using projection consistency conditions significantly improved myocardial blood flow estimate accuracy in simulated cardiac PET-CT, reducing median errors from 33% to 4.5%.
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