TY - JOUR T1 - <strong>Fast Whole-Body Parametric Imaging for Early Dynamics of FDG using Total-body PET</strong> JF - Journal of Nuclear Medicine JO - J Nucl Med SP - 517 LP - 517 VL - 60 IS - supplement 1 AU - Tao Feng AU - Yizhang Zhao AU - Hongcheng Shi AU - Hongdi Li AU - Ramsey Badawi AU - Patricia Price AU - Terry Jones AU - Simon Cherry Y1 - 2019/05/01 UR - http://jnm.snmjournals.org/content/60/supplement_1/517.abstract N2 - 517Introduction: Parametric imaging has been shown to provide better quantitation compared with SUV imaging in PET. However, the extended scan time makes it difficult to be utilized in clinical practice. With the increased sensitivity from the recently developed total body PET scanner [1], faster scans with higher temporal resolution become possible for dynamic analysis. In this paper, we focus on the study of the K1 parameter using compartment modeling, and on developing a method to acquire whole-body FDG-PET parametric images using only the first 90 seconds of the post-injection scan data with the total-body PET system. A volunteer with an injection dose of 6.3 mCi was scanned using the total-body PET scanner with IRB approval. During the early dynamic process, only the parameters of the first tissue compartment of FDG tracer can be accurately estimated. Dynamic projections were acquired with time interval of 1 second for the first 30 seconds and 2 seconds for the following minute. Image-derived input function was acquired from the reconstructed dynamic sequences in the descending aorta region. The whole-blood correction was achieved using population-based values [2]. Due to the high temporal resolution used in this study, a voxel-specific delay time for the plasma input function was also modeled within the 1-tissue compartment model. With the addition of voxel-specific delay time, a total number of 4 unknown parametric images were estimated including K1, k2, and the plasma fraction. A nested parametric image reconstruction method [3] was developed by using the 1-tissue compartment model solution. Six nested iterations were used within each image reconstruction iteration. A total number of 3 image iterations with 20 subsets were used for the image reconstruction. Qualitative and quantitative evaluation of the model fitting was achieved by visually checking the tissue activity curves for different organs and the calculation of the coefficient of determination (R2) for individual voxels. The voxel-specific parameters of the one-tissue compartment together with the delay time were successfully reconstructed using the proposed parametric reconstruction method. The parameters estimated using our method was able to predict the time-activity curves of the early dynamics of different organs. The time delay effects for different organs were also clearly visible in the reconstructed time delay image with delay variations as large as 40 seconds. A large delay time was observed in the liver region which was likely caused due to the dual blood supply from both the arteries and the portal veins [4], and the algorithm approximated the portal veins input function with the arterial input function by a time delay. The estimated R2 showed that for most voxels, our method provided reasonable estimation considering the high noise presented in the dynamic frames. The right arm (injection location) showed low fitting accuracy, which was likely caused by the imperfect scatter correction due to very high activity concentration during the tracer injection process. We have demonstrated that with the use of ultra-high sensitivity total body PET scanner, it is possible to provide ultra-high temporal resolution and achieve parametric image reconstruction using only the early stage of the scan (within the first two minutes), making it much easier to incorporate parametric imaging into the daily clinical route. We have also shown that with the much improved temporal resolution due to improved sensitivity, the organ-dependent delay time becomes an important factor to consider in the analysis of early-stage dynamics. Future works include additional validations using longer scan time with full modeling of FDG and the modeling of dual input function in the liver region. While our method was based on the analysis of FDG dynamics, it is not limited to FDG tracer dynamics. It can also be applied for tracers that can be modeled or approximated by a one-tissue compartment model, such as 82Rb or 15O for blood flow measurement. ER -