Design and Implementation of Automated Clinical Whole Body Parametric PET With Continuous Bed Motion
- Resource Type
- Periodical
- Authors
- Hu, J.; Panin, V.; Smith, A.M.; Spottiswoode, B.; Shah, V.; Von Gall, C.C.A.; Baker, M.; Howe, W.; Kehren, F.; Casey, M.; Bendriem, B.
- Source
- IEEE Transactions on Radiation and Plasma Medical Sciences IEEE Trans. Radiat. Plasma Med. Sci. Radiation and Plasma Medical Sciences, IEEE Transactions on. 4(6):696-707 Nov, 2020
- Subject
- Nuclear Engineering
Engineered Materials, Dielectrics and Plasmas
Bioengineering
Computing and Processing
Fields, Waves and Electromagnetics
Image reconstruction
Positron emission tomography
Biomedical imaging
Expectation-maximization algorithms
Computed tomography
Image resolution
Blood input function
continuous bed motion (CBM)
kinetic modeling
parametric imaging
positron emission tomography (PET)
- Language
- ISSN
- 2469-7311
2469-7303
We described workflows and methodologies for fully automated parametric imaging using clinical positron emission tomography (PET) systems with continuous bed motion (CBM) which aim to enable physicians to practice parametric PET routinely. The key components of our implemented methods include automatic generation of image-derived blood input functions, accurate tracking of slice imaging time during CBM acquisitions, and parametric image formation with advanced algorithms. Locations of the left ventricle and the descending aorta were automatically detected from high resolution anatomical images and registered to dynamic PET images to generate blood input functions. A method to accurately track dynamic scans and calculate time information for whole body CBM parametric PET was implemented based on bed position tags. This approach of calculating time information based on finely sampled bed position tags can be applied to flexible scan modes with various scan speeds over different body regions. We applied the calculated slice time information for whole body parametric imaging using a linear Patlak model. Parametric images were reconstructed with a nested expectation maximization (EM) algorithm. We demonstrated that parametric images generated by our automated workflow can provide quantitative parameters in addition to standardized uptake value images. We presented results for a uni-direction dynamic scan from a Biograph mCT system and a bi-direction dynamic scan from a Biograph Vision system.