Coronary artery 18F-NaF PET analysis with the use of an elastic motion correction software
18F-Sodium Fluoride Positron Emission Tomography (18F-NaF PET) is a novel molecular imaging modality with promise for use as a risk stratification tool in cardiovascular disease. There are limitations in the analysis of small and rapidly moving coronary arteries using traditional PET technology. We aimed to validate the use of a motion correction algorithm (eMoco) on coronary 18F-NaF PET outcome parameters.
Patients admitted with an acute coronary syndrome underwent 18F-NaF PET and computed tomography coronary angiography. 18F-NaF PET data were analyzed using a diastolic reconstruction, an ungated reconstruction and the eMoco reconstruction.
Twenty patients underwent 18F-NaF PET imaging and 17 patients had at least one positive lesion that could be used to compare PET reconstruction datasets. eMoco improved noise (the coefficient of variation of the blood pool radiotracer activity) compared to the diastolic dataset (0.09 [0.07 to 0.12] vs 0.14[0.11 to 0.17], p < .001) and marginally improved coronary lesion maximum tissue-to-background ratios compared to the ungated dataset (1.33 [1.05 to 1.48]vs 1.29 [1.04 to 1.40], p = .011).
In this pilot dataset, the eMoco reconstruction algorithm for motion correction appears to have potential in improving coronary analysis of 18F-NaF PET by reducing noise and increasing maximum counts. Further testing in a larger patient dataset is warranted.
KeywordsCAD PET Image reconstruction
Positron emission tomography
Elastic motion correction
Computed tomographic coronary angiography
Attenuation correction computed tomography
Acute coronary syndrome
Region of interest
Standardized uptake value
Tissue to background
The authors would like to acknowledge the contribution of the WA PET service staff for performing participant imaging and scan reconstructions, with particular acknowledgement of Andrea Giacomet and Simone Culleton for their assistance in the project.
Inki Hong and Judson Jones are employees of Siemens Medical Solutions. Authors J Bellinge, K Majeed, S Carr, R Francis, and C Schultz have no relevant conflicts of interest.
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