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 preand 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.www.sciedu.ca/jbgc Journal of Biomedical Graphics and Computing, 2013, Vol. 3, No. 4 ISSN 1925-4008 E-ISSN 1925 86 Conclusions: We demonstrate the effectiveness of customization of 3D data analysis tools to obtain specific characterization and quantitative information about different dental therapies.

Optimized 3D co-registration of ultra-low-field and high-field magnetic resonance images

“…Moreover, SWIM could be effectively adapted to images from different modalities to track changes in tissues or in material structures in order to detect the effect of therapeutic treatments or micro-morphology changes [ 30 , 43 ]. Since the implementation of reliable and robust methods of multimodal image co-registration and image fusion [ 44 – 46 ] is central in several medicine-related research and clinical fields [ 42 ], it would be worth exploiting our pipeline in other imaging modalities in the future.…”

“…In addition, SWIM uses a reverse mapping procedure [ 28 ] and a trilinear interpolation [ 29 ] to prevent the generic transformation T from creating empty voxels in the transformed image, altering the NMI value [ 30 ]. These empty voxels could be caused by the discrete sampling of the image space, implying that after a generic transformation T , the new position of each voxel may not coincide with a point on the grid described by the coordinate set.…”

Multimodal‐3D imaging based on μMRI and μCT techniques bridges the gap with histology in visualization of the bone regeneration process

“…Additionally, numerical truncation might force two or more voxels from the original volume to be transformed into the same voxel, thus producing empty voxels in the transformed volume. To avoid empty voxels in the transformed image, which alter the NMI, we implemented a reverse mapping procedure and trilinear interpolation (Sinibaldi et al, ).…”

Fast Room Temperature Very Low Field-Magnetic Resonance Imaging System Compatible with MagnetoEncephaloGraphy Environment

“…The VLF field images of the first head were acquired with the isotropic 3 mm resolution sequence discussed above, T R = 500 ms and NEX = 16 for a total acquisition time of 2.3 h. The high field images of the rabbit were obtained with a 3T scanner (Achieva, Philips) using a knee coil and 3D T 1 -TFE (Ultrafast Gradient Echo) standard clinical sequence for brain anatomical characterization with 1x1x1 mm 3 resolution, 12x12x18 cm 3 FOV, T R = 8.5 ms, T E = 3.9 ms, NEX = 3 and T acq = 6 min. The high field image is down sampled in the image space to match the low field resolution and spatially co-registered using an in-house algorithm [ 31 ]. The second rabbit head was scanned with the same spatial resolution as the first one (both at VLF as well as at HF), but with T R = 300 ms and NEX = 9, for a total acquisition time of 46 min.…”