TY - JOUR T1 - Total-Body Parametric Imaging using Kernel and Direct Reconstruction on the uEXPLORER JF - Journal of Nuclear Medicine JO - J Nucl Med SP - 456 LP - 456 VL - 60 IS - supplement 1 AU - Xuezhu Zhang AU - Zhaoheng Xie AU - Eric Berg AU - Martin Judenhofer AU - Weiping Liu AU - Yang Lv AU - Yu Ding AU - Xinyu LV AU - Tianyi Xu AU - Yun Dong AU - Hongcheng Shi AU - Shuguang Chen AU - Pengcheng Hu AU - Jun Bao AU - Hongdi Li AU - Simon Cherry AU - Ramsey Badawi AU - Jinyi Qi Y1 - 2019/05/01 UR - http://jnm.snmjournals.org/content/60/supplement_1/456.abstract N2 - 456Introduction: The EXPLORER consortium has developed the world’s first 2-meter long total-body PET scanner (uEXPLORER) to provide a versatile platform for biomedical research and clinical applications. Its total-body coverage and ultra-high sensitivity provide opportunities for more accurate tracer kinetics analysis in studies of new pharmaceuticals, physiology and pathology. In this work, we demonstrate total-body parametric imaging using kernel and direct reconstruction of the EXPLORER data. Methods: We conducted the first human dynamic total-body PET study using the uEXPLORER scanner. A healthy female subject was recruited (61-yrs old, height 156 cm, weight 56 kg) and gave informed consent under the guidance of the Ethics Board of Zhongshan Hospital (Shanghai, China). A one-hour dynamic scan was performed immediately after an intravenous injection of 6.9 mCi of 18F-FDG in the foot. A total of ~60 billion prompt coincidences were recorded. To exploit the high temporal resolution of the scanner, we divided the dataset into 187 temporal frames: 60×1 sec, 30×2 sec, 20×3 sec, 12×10 sec, 50×30 sec, and 15×120 sec. For quantitative image reconstruction, all corrections (normalization, attenuation, randoms, scatters, and resolution model) were implemented in the forward model. Dynamic data were reconstructed using a 3D TOF list-mode OSEM algorithm and a kernel-based algorithm. We used three composite frames (10-20-30min) to build the kernel matrix. Images were reconstructed into a 239x239x679 matrix with 2.85-mm cubic voxels. The linear Patlak graphical method was analyzed for non-reversible glucose metabolism in different tissues. For comparison, indirect Patlak analysis from reconstructed frames and direct reconstruction using the nested algorithm were conducted for the later 30-min frames. The input function was extracted from the upper aorta region instead of the left ventricle to minimize blurring due to cardiac motion. Results: Images reconstructed by OSEM show good image quality with low noise, even for the 1-second frames. The image quality was further improved by using the kernel method. Total-body Patlak parametric images were obtained by using either indirect estimation or direct reconstruction. In comparison, direct reconstruction improves parametric image quality with better contrast versus background noise tradeoff over the indirect method. Conclusion: This study demonstrated the capability of total-body parametric imaging using the EXPLORER. Furthermore, the results show that the kernel-regularized reconstruction and direct parametric imaging can achieve superior image quality for tracer kinetics studies compared to the conventional indirect OSEM for total-body imaging. Acknowledgements: Support for this work includes NIH grant R01 CA206187. We acknowledge the contributions of all team members from UC Davis, United Imaging Healthcare and Zhongshan Hospital. ER -