Software tools for the quantitative evaluation of dental treatment effects from µCT scans

Abstract

Background: The 3D images of dental specimens were obtained by means of micro-Computed Tomography (µCT) before and after therapeutic intervention. A suite of software tools has been developed to assess the efficacy of dental treatment as revealed by µCT scans. Endodontic root canal and restorative therapy were selected as model procedures to test and optimize the developed tools. Non destructive µCT imaging allows repeated scans of the same tooth and might provide quantitative information about specimen modifications over time. Preliminary literature has suggested that anatomical characterization and detailed evaluation of dental therapies would considerably benefit from the coupling between detailed 3D imaging and custom software. However, the main drawbacks reside in time consuming pipeline for scanner-time of the specimens and absence of efficient software for accurate data analysis and direct comparison of a set of 3D dental structures.

Methods: The software we present here implements co-registration procedures together with an algorithm for the 3D quantitative characterization of teeth hollow spaces and interfaces. The software is targeted to the individualized analysis of the single specimen in an effort to help dentists to quantify the outcome of the surgical intervention performed on teeth. The approach aims to automatically highlight the differences between pre- and post-treatment structures for further anatomical and statistical analysis. Of note, the two different treatments analyzed exploit two different perspectives. As a matter of facts, endodontic therapy aims at the modification of the root canal structure (axe, volume and surface), whereas the restorative treatment focus is on the whole tooth structure.

Results: The developed co-registration algorithm allows finding correct superposition in both data sets, despite the pre- and post-structure can be markedly different, especially after the application of dental adhesive composite in the restorative treatment. Tools for characterization of canal volume and surface are robust with respect to the presence of branches and allow the complete characterization of the endodontic treatments. Modification of the tooth structure after restorative treatments is highlighted after the co-registration procedure in automatic way and allows the user to quantify the volume of voids due to the shrinkage of the material at the interface and eventually the presence of internal cracks or other morphological modification of the tooth structure.

Conclusions: We demonstrate the effectiveness of customization of 3D data analysis tools to obtain specific characterization and quantitative information about different dental therapies.