Demonstration of virtual imaging trial applications for optimization and education of dento-maxillofacial CBCT imaging

Background

A number of studies have suggested that there is a need for improved understanding of dento-maxillofacial cone beam computed tomography (CBCT) technology, and to establish optimized imaging protocols. While several ex vivo/in vitro studies, along with a few in vivo studies, have addressed this topic, virtual imaging trials could form a powerful alternative but have not yet been introduced within the field of dento-maxillofacial imaging.

Purpose

To introduce and illustrate the potential of utilizing a virtual imaging trial (VIT) platform for dento-maxillofacial CBCT imaging through a number of case studies.

Methods

A framework developed in-house, simulating an existing CBCT scanner, and the necessary digital patient phantoms were prepared for the following potential studies: I) the impact of intracanal material type (Ni-Cr alloy, fiberglass, gutta-percha) and acquisition settings (tube current (mA), tube voltage (kVp)) on root fracture (RF) visibility; II) image artefact levels from candidate new restorative materials, such as graphene; III) the effect of patient rigid motion on image artifacts; IV) the effect of a metal artifact reduction algorithm on RF visibility in a tooth treated endodontically and restored with a metal post. In addition, features not available on the real system, including automatic exposure control and extended tube current and tube voltage ranges, were added to study the impact of these parameters. Patient dose levels were also quantified.

Results

The generated images showed the influence of different restorative materials, dose levels, rigid motion, and image processing on the quality of the final images. Results of these simulated conditions were consistent with findings in the literature. Patient effective dose levels ranged between 22 and 138 $\mu \mathrm{Sv}$ for all simulated scenarios. Images were considered sufficiently realistic according to an experienced oral radiologist. Furthermore, the platform was able to simulate scenarios that are difficult or impossible to replicate physically in a controlled and repeatable way.

Conclusions

A virtual imaging trial platform has the potential to improve the understanding and use of CBCT technology. Improved insight into system performance can lead to optimized imaging protocols, and help to reduce the large variation in system setup and performance currently seen in clinical practice in dento-maxillofacial CBCT imaging.