Partial volume and motion correction in cardiac PET: First results from an in vs ex vivo comparison using animal datasets
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In a previous study on ex vivo, static cardiac datasets, we investigated the benefits of performing partial volume correction (PVC) in cardiac 18F-Fluorodeoxyglucose(FDG) PET datasets. In the present study, we extend the analysis to in vivo cardiac datasets, with the aim of defining which reconstruction technique maximizes quantitative accuracy and, ultimately, makes PET a better diagnostic tool for cardiac pathologies.
In vivo sheep datasets were acquired and reconstructed with/without motion correction and using several reconstruction algorithms (with/without resolution modeling, with/without non-anatomical priors). Corresponding ex vivo scans of the excised sheep hearts were performed on a small-animal PET scanner (Siemens Focus 220, microPET) to provide high-resolution reference data unaffected by respiratory and cardiac motion. A comparison between the in vivo cardiac reconstructions and the corresponding ex vivo ground truth was performed.
The use of an edge-preserving prior (Total Variation (TV) prior in this work) in combination with motion correction reduces the bias in absolute quantification when compared to the standard clinical reconstructions (− 0.83 vs − 3.74 SUV units), when the end-systolic gate is considered. At end-diastole, motion correction improves absolute quantification but the PVC with priors does not improve the similarity to the ground truth more than a regular iterative reconstruction with motion correction and without priors. Relative quantification was not influenced much by the chosen reconstruction algorithm.
The relative ranking of the algorithms suggests superiority of the PVC reconstructions with dual gating in terms of overall absolute quantification and noise properties. A well-tuned edge-preserving prior, such as TV, enhances the noise properties of the resulting images of the heart. The end-systolic gate yields the most accurate quantification of cardiac datasets.
KeywordsCardiac PET Motion correction Partial volume correction Quantification
Positron emission tomography
Partial volume effect
Partial volume correction
Ordered subsets expectation maximization (reconstruction algorithm)
Maximum a posteriori (reconstruction algorithm)
Total variation (prior)
Standard uptake values
The authors wish to thank Charles Watson and Judd Jones for their help with the Siemens data processing.
AT was responsible for the study design, the simulation setup, the reconstructions, and the data collection and analysis, and drafted the manuscript. JD was also responsible for the data collection. JN and KV assisted with the study design, the analysis of data, and the careful revision of the manuscript. JUV, FR, PC, JD, and OG participated in the study design and critically revised the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
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