To develop and disseminate a free open source tool for computation of 3D surface-to-surface distances between pairs of 3D virtual models of anatomy obtained from cone beam computed tomography (CBCT). This work presents a comprehensive 3D quantitative tool that bridges the gap between methodology made by computer scientists and dental research scientists, making it available to a bigger audience that does not need to have deep computer knowledge to operate the tool, and provide an automated tool to evaluate anatomic changes to reduce operator bias and landmark identification errors.
Class III orthognathic patients and Class II treated patients were used to validate the tool. Evaluation of surgical accuracy was tested based on the postoperative maxillary-mandibular bone surface. Pre- and post- treatment models were registered on the anterior cranial-base. For every vertex of the preoperative maxilla-mandible model, our tool measured the Euclidean distance between that vertex and its closest projection on the postoperative maxilla-mandible bone surface. Results were displayed via distance color maps.
3DMeshMetric allowed the successful quantitative 3D evaluation of post-treatment craniofacial skeletal and growth changes. Using CBCT scanning method, we can reconstruct hard tissue morphology and perform a high sampling quantitative analysis based in 3D-based methodologies to calculate and display measurements. Three-dimensional color maps and semi-transparency overlays allow quantitative assessment of treatment changes.
This work demonstrates a three-fold improvement for the dental research community, by 1) computing highly sampled automated surface-to-surface measurements between a pair of virtual shape models of anatomy obtained from CBCT to reduce operator bias 2) offering an input-to-end solution that will facilitate the access to complicated computer processing methodologies to all users without computer expertise and 3) offering free open source software solutions free of charge, available to a wider public.