As cone-beam computed tomography (CBCT) has gained popularity rapidly in dental imaging applications in the past two decades, radiation dose in CBCT imaging remains a potential, health concern to the patients. It is a common practice in dental CBCT imaging that only a small volume of interest (VOI) containing the teeth of interest is illuminated, thus substantially lowering imaging radiation dose. However, this would yield data with severe truncations along both transverse and longitudinal directions. Although images within the VOI reconstructed from truncated data can be of some practical utility, they often are compromised significantly by truncation artifacts. In this work, we investigate optimization-based reconstruction algorithms for VOI image reconstruction from CBCT data of dental patients containing severe truncations. In an attempt to further reduce imaging dose, we also investigate optimization-based image reconstruction from severely truncated data collected at projection views substantially fewer than those used in clinical dental applications. Results of our study show that appropriately designed optimization-based reconstruction can yield VOI images with reduced truncation artifacts, and that, when reconstructing from only one half, or even one quarter, of clinical data, it can also produce VOI images comparable to that of clinical images.