Evaluating two respiratory correction methods for abdominal PET/MRI imaging.

EJNMMI Phys

Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, China.

Published: January 2022

Background: To evaluate two respiratory correction methods for abdominal PET/MRI images and further to analyse the effects on standard uptake values (SUVs) of respiratory motion correction, 17 patients with 25 abdominal lesions on F-FDG PET/CT were scanned with PET/MRI. PET images were reconstructed using end-expiratory respiratory gating and multi-bin respiratory gating. Meanwhile, full data and the first 3 min and 20 s of data acquired both without respiratory gating were reconstructed for evaluation. Five parameters, including the SUV and SUV in the lesions, the SUV and standard deviation (SD) in the background, and the signal-to-noise ratio (SNR), were calculated and used for statistical comparisons. The differences in multi-bin respiratory gating and reconstruction of full data, relative to the reconstruction of the first 3 min and 20 s of data acquired, were calculated.

Results: Compared with PET/CT, the longer scanning time of abdominal PET/MRI makes respiratory motion correction necessary. The multi-bin respiratory gating correction could reduce the PET image blur and increase the SUV (11.98%) and SUV (13.12%) of the lesions significantly (p = 0.00), which was much more effective than end-expiratory respiratory gating for abdominal PET/MRI. The added value of SUV caused by respiratory motion correction has no significant difference compared with that caused by count loss with the correction (p = 0.39), which was rarely reported by previous studies.

Conclusion: Based on the current parameters, the method of multi-bin respiratory gating was more effective for respiratory motion correction in abdominal PET/MRI in comparisons with the method of end-respiratory gating. However, the increased noise in gated images, due to the fact that PET data get discarded, is partly responsible for the increase in SUV.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804027PMC
http://dx.doi.org/10.1186/s40658-022-00430-wDOI Listing

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