Journal of Nuclear Medicine | |
Fat-Constrained 18F-FDG PET Reconstruction in Hybrid PET/MR Imaging | |
Susanne Heinzer1  Osman Ratib1  Christian Wülker1  Peter Börnert1  Steffen Renisch1  Sven Prevrhal1  | |
关键词: PET/MR; fat tissue; Dixon; PET reconstruction; prior information; | |
DOI : 10.2967/jnumed.114.139758 | |
学科分类:医学(综合) | |
来源: Society of Nuclear Medicine | |
【 摘 要 】
Fusion of information from PET and MR imaging can increase the diagnostic value of both modalities. This work sought to improve 18F FDG PET image quality by using MR Dixon fat-constrained images to constrain PET image reconstruction to low-fat regions, with the working hypothesis that fatty tissue metabolism is low in glucose consumption. Methods: A novel constrained PET reconstruction algorithm was implemented via a modification of the system matrix in list-mode time-of-flight ordered-subsets expectation maximization reconstruction, similar to the way time-of-flight weighting is incorporated. To demonstrate its use in PET/MR imaging, we modeled a constraint based on fat/water-separating Dixon MR images that shift activity away from regions of fat tissue during PET image reconstruction. PET and MR imaging scans of a modified National Electrical Manufacturers Association/International Electrotechnical Commission body phantom simulating body fat/water composition and in vivo experiments on 2 oncology patients were performed on a commercial time-of-flight PET/MR imaging system. Results: Fat-constrained PET reconstruction visibly and quantitatively increased resolution and contrast between high-uptake and fatty-tissue regions without significantly affecting the images in nonfat regions. Conclusion: The incorporation of MR tissue information, such as fat, in image reconstruction can improve the quality of PET images. The combination of a variety of potential other MR tissue characteristics with PET represents a further justification for merging MR data with PET data in hybrid systems.
【 授权许可】
Unknown
【 预 览 】
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RO201912010198968ZK.pdf | 1804KB | download |