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In this work, we investigate and characterize optimization-based image reconstruction from list-mode TOFPET data collected by using a digital TOF-PET scanner with reduced detectors, while seeking possibly to maintain the image quality and volume coverage. In particular, we focused on two patterns of sparse configurations, in both of which the total number of crystals is reduced to 50% of the corresponding clinical TOF-PET scanner. The reconstruction problem from data of the two sparse configurations is formulated as the solution to an image-TV-constrained, data-KLminimization optimization problem, and the image is reconstructed by use of an algorithm tailored from a Chambolle and Pock (CP) algorithm through solving the optimization problem. The characteristics of each sparse configuration was investigated by assessing the corresponding reconstructions visually and quantitatively. Results of the study …