The recently developed total-body PET scanner enables high temporal resolution in dynamic imaging. Due to the much improved temporal resolution and large field of view, delay and the dispersion effects in the image-derived input function, which vary for different tissues and organs, may affect accuracy in parametric imaging. In this paper, the delay effect was studied using the early kinetics of an FDG scan, which may be approximated using a 1-tissue compartment model. Dynamic reconstructed frames were acquired using the total-body PET scanner with 1-second frames for the first 30 seconds and 2 seconds for the subsequent 60 seconds. The image-derived input function was acquired from the reconstructed dynamic sequence using volumes of interest in the ascending and descending aorta. Voxel-specific delay times for the plasma input function were also modeled within the 1-tissue compartment model. A total of 4 parametric images were generated. Image-based parametric image generation was achieved with a maximum likelihood estimation method. Parametric images with and without the modeling of delay time in the input function were compared. Additional image denoising techniques including Gaussian denoising and non-local-mean denoising were employed. Quantitative evaluation was achieved by the calculation of the Akaike Information Criterion (AIC). The voxel-specific parameters of the 1-tissue compartment together with the delay time were successfully reconstructed using the proposed method. The estimated delay time showed variations as large as 40 seconds. The non-local-mean filter was shown to be able to reduce the image noise of the generated parametric images. Various image artifacts were observed when no delay time model was included. We have shown that with the use of total-body PET and the increased sensitivity, it is possible to estimate parametric images using the very early stages of the FDG injection. The combined effects of delay and dispersion will be studied in the future.