How to Obtain an Orthodontic Virtual Patient through Superimposition of Three-Dimensional Data: A Systematic Review

Background: This systematic review summarizes the current knowledge on the superimposition of three-dimensional (3D) diagnostic records to realize an orthodontic virtual patient. The aim of this study is to analyze the accuracy of the state-of-the-art digital workflow. Methods: The research was carried out by an electronic and manual query eectuated from ISS (Istituto Superiore di Sanit\ue0 in Rome) on three dierent databases (MEDLINE, Cochrane Library and ISI WEB OF SCIENCE) up to 31st January 2020. The search focused on studies that superimposed at least two dierent 3D records to build up a 3D virtual patient\u2014information about the devices used to acquire 3D data, the software used to match data and the superimposition method applied have been summarized. Results: 1374 titles were retrieved from the electronic search. After title-abstract screening, 65 studies were selected. After full-text analysis, 21 studies were included in the review. Dierent 3D datasets were used: facial skeleton (FS), extraoral soft tissues (ST) and dentition (DENT). The information provided by the 3D data was superimposed in four dierent combinations: FS + DENT (13 papers), FS + ST (5 papers), ST + DENT (2 papers) and all the types (FS + ST + DENT) (1 paper). Conclusions: The surface-based method was most frequently used for 3D objects superimposition (11 papers), followed by the point-based method (6 papers), with or without fiducial markers, and the voxel-based method (1 paper). Most of the papers analyzed the accuracy of the superimposition procedure (15 papers), while the remaining were proof-of-principles (10 papers) or compared dierent methods (3 papers). Further studies should focus on the definition of a gold standard. The patient is going to have a huge advantage from complete digital planning when more information about the spatial relationship of anatomical structures are needed: ectopic, impacted and supernumerary teeth, root resorption and angulations, cleft lip and palate (CL/P), alveolar boundary conditions, periodontally compromised patients, temporary anchorage devices (TADs), maxillary transverse deficiency, airway analyses, obstructive sleep apnea (OSAS), TMJ disorders and orthognathic and cranio-facial surgery

Replacement of the distorted dentition of the cone-beam computed tomography (CBCT) scans for orthognathic surgery planning

Purpose: CBCT imaging does not record dental morphology accurately due to the scattering produced by metallic restorations and the reported magnification. The aim of this study was the development and the evaluation of a new method for the replacement of the distorted dentition of CBCT scans with 3D dental image captured by a digital intraoral camera. Materials and Method: Six dried skulls with orthodontics brackets fixed on the teeth were used in this study. Three intra-oral markers made of dental stone were constructed and attached to orthodontics brackets. The skulls were CBCT scanned and occlusal surfaces were captured using TRIOS ® 3D intraoral scanner. The digital intra-oral scan (IOS) was fused into the CBCT models. This produced a new composite digital model of the skull and dentition. The skulls were scanned again using the commercially accurate Laser Faro® arm to produce the 3D model “gold standard” for the assessment of the accuracy of the developed method. This was assessed by measuring the distance between the occlusal surfaces of the new composite model and the “gold standard” 3D laser scanned model Results: The results showed the errors related to the superimposition of the intra-oral image on the CBCT to replace the distorted dentition were between 0.11 and 0.20 mm. Conclusion: The results of this study suggests that the dentition in the CBCT can be accurately replaced with the digital IOS captured by an intra-oral scanner to create a composite model which will improve the accuracy of the digital orthognathic surgical planning and the fabrication of an occlusal wafer

Assessment of 3D Facial Scan Integration in 3D Digital Workflow Using Radiographic Markers and Iterative Closest Point Algorithm

Introduction: Integration of 3 dimensional (3D) facial scanning into digital smile design workflows has been made available in multiple commercially available systems. Limited data exists on the accuracy of facial scans and accuracy of various methods of merging facial scans with cone beam computed tomography (CBCT) scans.Objective: The purpose of this prospective clinical study was to evaluate the accuracy of 2 methods used to integrate soft tissue facial scans with CBCT scans. It would allow proposal of a novel approach for integrating a 3D facial scan using facial radio-opaque markers in a 3D digital workflow.Material and methods: Fifteen CBCT and 3D face scans were obtained from patients who were undergoing treatment at MUSoD. A DICOM with RO markers and 3 STL data files from the facial scans were obtained for each patient. These files were superimposed using Exocad software. Accuracy of superimpositions was evaluated by measuring distances between RO markers on DICOM and STL data. The obtained dataset was analyzed using the paired t-test. Results: The results showed that the mean values for the 6 subsets, merging through the ICP algorithm, were 1.47-2mm. However, when merged by RO markers, the mean valuewas 0.14mm. Using a paired t-test, the novel RO points method was statistically more accurate than ICP algorithm method (

Comparative linear accuracy of cone beam CT derived 3D images in orthodontic analysis.

Objective . To compare the in vitro reliability and accuracy of linear measurements between cephalometric landmarks on CBCT 3D images with varying basis projection images to direct measurements on human skulls. Methods . Sixteen linear dimensions between anatomical sites marked on 19 human skulls were directly measured. Skulls were imaged with CBCT at three settings: 153, 306, and 612 basis projections. The mean absolute error and modality mean of linear measurements between landmarks on 3D images were compared to the anatomic truth. Results . No difference in mean absolute error between the scan settings was found. The average skull absolute error between marked reference points were less than the distances between unmarked reference sites. Conclusion . CBCT measurements were consistent between scan sequences and for direct measurements between marked reference points. Reducing the number of projections for 3D reconstruction did not lead to reduced dimensional accuracy and potentially provides reduced patient radiation exposure

Comparative linear accuracy and reliability of cone beam CT derived 2-dimensional and 3-dimensional images constructed using an orthodontic volumetric rendering program.

The purpose of this project was to compare the accuracy and reliability of linear measurements made on 2D projections and 3D reconstructions using Dolphin 3D software (Chatsworth, CA) as compared to direct measurements made on human skulls. The linear dimensions between 6 bilateral and 8 mid-sagittal anatomical landmarks on 23 dentate dry human skulls were measured three times by multiple observers using a digital caliper to provide twenty orthodontic linear measurements. The skulls were stabilized and imaged via PSP digital cephalometry as well as CBCT. The PSP cephalograms were imported into Dolphin (Chatsworth, CA, USA) and the 3D volumetric data set was imported into Dolphin 3D (Version 2.3, Chatsworth, CA, USA). Using Dolphin 3D, planar cephalograms as well as 3D volumetric surface reconstructions were (3D CBCT) generated. The linear measurements between landmarks of each three modalities were then computed by a single observer three times. For 2D measurements, a one way ANOVA for each measurement dimension was calculated as well as a post hoc Scheffe multiple comparison test with the anatomic distance as the control group. 3D measurements were compared to anatomic truth using Student\u27s t test (PiÜ50.05). The intraclass correlation coefficient (ICC) and absolute linear and percentage error were determined as indices of intraobserver reliability. Our results show that for 2D mid sagittal measurements that Simulated LC images are accurate and similar to those from PSP images (except for Ba-Na), and for bilateral measurements simulated LC measurements were similar to PSP but less accurate, underestimating dimensions by between 4.7% to 17%.For 3D volumetric renderings, 2/3 rd of CBCT measurements are statistically different from actual measurements, however this possibly is not clinically relevant

Dental measurements and Bolton index reliability and accuracy obtained from 2D digital, 3D segmented CBCT, and 3d intraoral laser scanner

To compare the reliability and accuracy of direct and indirect dental measurements derived from two types of 3D virtual models: generated by intraoral laser scanning (ILS) and segmented cone beam computed tomography (CBCT), comparing these with a 2D digital model. One hundred patients were selected. All patients? records included initial plaster models, an intraoral scan and a CBCT. Patients´ dental arches were scanned with the iTero® intraoral scanner while the CBCTs were segmented to create three-dimensional models. To obtain 2D digital models, plaster models were scanned using a conventional 2D scanner. When digital models had been obtained using these three methods, direct dental measurements were measured and indirect measurements were calculated. Differences between methods were assessed by means of paired t-tests and regression models. Intra and inter-observer error were analyzed using Dahlberg´s d and coefficients of variation. Intraobserver and interobserver error for the ILS model was less than 0.44 mm while for segmented CBCT models, the error was less than 0.97 mm. ILS models provided statistically and clinically acceptable accuracy for all dental measurements, while CBCT models showed a tendency to underestimate measurements in the lower arch, although within the limits of clinical acceptability. ILS and CBCT segmented models are both reliable and accurate for dental measurements. Integration of ILS with CBCT scans would get dental and skeletal information altogether

Clinically applicable artificial intelligence system for dental diagnosis with CBCT

Abstract In this study, a novel AI system based on deep learning methods was evaluated to determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks, pathologies, clinical effectiveness, and safety when used by dentists in a clinical setting. The system consists of 5 modules: ROI-localization-module (segmentation of teeth and jaws), tooth-localization and numeration-module, periodontitis-module, caries-localization-module, and periapical-lesion-localization-module. These modules use CNN based on state-of-the-art architectures. In total, 1346 CBCT scans were used to train the modules. After annotation and model development, the AI system was tested for diagnostic capabilities of the Diagnocat AI system. 24 dentists participated in the clinical evaluation of the system. 30 CBCT scans were examined by two groups of dentists, where one group was aided by Diagnocat and the other was unaided. The results for the overall sensitivity and specificity for aided and unaided groups were calculated as an aggregate of all conditions. The sensitivity values for aided and unaided groups were 0.8537 and 0.7672 while specificity was 0.9672 and 0.9616 respectively. There was a statistically significant difference between the groups (p = 0.032). This study showed that the proposed AI system significantly improved the diagnostic capabilities of dentists