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Intraoral digital scans: Part 2—influence of ambient scanning light conditions on the mesh quality of different intraoral scanners

Intraoral digital scans: Part 2—influence of ambient scanning light conditions on the mesh quality of different intraoral scanners



Intraoral digital scans: Part 2—influence of ambient scanning light conditions on the mesh quality of different intraoral scanners




Journal of Prosthetic Dentistry, 2020-11-01, Volume 124, Issue 5, Pages 575-580, Copyright © 2019 Editorial Council for the Journal of Prosthetic Dentistry


Abstract

Statement of problem

Digital scans should be able to accurately reproduce the different complex geometries of the patient's mouth. Mesh quality of the digitized mouth is an important factor that influences the capabilities of the geometry reproduction of an intraoral scanner (IOS). However, the mesh quality capabilities of IOSs and the relationship with different ambient light scanning conditions are unclear.

Purpose

The purpose of this in vitro study was to measure the impact of various light conditions on the mesh quality of different IOSs.

Material and methods

Three IOSs were evaluated—iTero Element, CEREC Omnicam, and TRIOS 3—with 4 lighting conditions—chair light, 10 000 lux; room light, 1003 lux; natural light, 500 lux; and no light, 0 lux. Ten digital scans per group were made of a mandibular typodont. The mesh quality of digital scans was analyzed by using the iso2mesh MATLAB package. Two-way ANOVA and Kruskal-Wallis 1-way ANOVA statistical tests were used to analyze the data (á=.05).

Results

Significant differences in mesh quality values were found among the different IOSs under the same lighting conditions and among the different lighting conditions using the same IOS. TRIOS 3 showed the highest consistency and mesh quality mean values across all scanning lighting conditions tested. CEREC Omnicam had the lowest mean mesh quality values across all scanning lighting conditions. iTero Element displayed some consistency in the mesh quality values depending on the scanning lighting conditions: chair light and room light conditions presented good consistency in mesh quality, indicating better mesh quality, and natural light and no light conditions displayed differing consistency in mesh quality values. Nevertheless, no light condition led to the minimal mean mesh quality across all IOS groups.

Conclusions

Differences in the mesh quality between different IOSs should be expected. The photographic scanning techniques evaluated presented higher mesh quality mean values than the video-based scanning technology tested. Moreover, changes in lighting condition significantly affect mesh quality. TRIOS 3 showed the highest consistency in terms of the mean mesh quality, indicating better photographic system in comparison with iTero Element.

Clinical Implications

Ambient lighting condition is an important factor that affects the mesh quality values or the geometries reproduction capabilities of an intraoral scanner. Depending on the scanner selected and the goal of the digital scan procedure, different lighting conditions are recommended to improve the outcome of the digital scan.

The integration of intraoral scanners (IOSs) with computer-aided design and computer-aided manufacturing (CAD-CAM) technologies has enabled a fully digital workflow for dental restorative treatment. Beyond the operational features of an IOS system, including the speed of use, the need for powder, the size of the intraoral wand and tips, and the cost, important fundamentals such as the technology used, the mesh quality of the obtained data, and the accuracy (trueness and precision) of the system should also be considered.

The relationship between the technology used by an IOS and the accuracy of its acquisition procedure has been studied, as well as factors that could impact the accuracy of a digital scan, including handling and the learning curve, calibration, scanning protocol, ambient light scanning conditions, surface characteristics, mobile tissue, reflective restorations, and/or the presence of saliva. However, the authors are unaware of information regarding the mesh quality differences between the different IOS dental systems, which could influence the capabilities of the scanner to accurately reproduce the different complex geometries of the patient's mouth and its relationship with ambient lighting conditions.

IOSs are noncontact optical technologies that can be classified as photographic and videographic systems. Regardless of the type of imaging technology used by an IOS, all cameras require the projection of light that is then recorded as individual images or video and compiled by the software after recognition of the points of interest (POIs). The first 2 coordinates (x and y) of each point are evaluated on the image, and the third coordinate (z) is then calculated by estimating the distance of the specified point from the optical instrument through triangulation.

The multiple sets of points or point clouds generated through the optical sensors are subsequently registered (aligned with respect to each other) and are converted into a surface model represented as a triangle mesh. The algorithms used by the IOS software can generate files of varying mesh densities that can be adaptively defined based on the curvature of the region in the mouth; high curvature regions often have highly dense meshing, while relatively flat regions have lower triangle mesh density. The capabilities of the reproduction geometries of an IOS system are determined by its mesh quality.

The purpose of the present study was to measure the impact of various ambient scanning lighting conditions on the mesh quality of 3 different IOS systems. Two independent factors, the lighting condition and the IOS system, were used to compare mesh quality. The null hypotheses were no difference would be found on the mesh quality of the digital scans among the 3 different IOSs under the 4 different ambient scanning lighting conditions evaluated and that no difference would be found on the mesh quality of digital scans under the same light condition among the 3 IOSs analyzed.


Material and methods

A dental mannequin (Nissim Type 2; Nissim) with a maxillary and mandibular dentate typodont (Hard gingiva jaw model MIS2010-L-HD-M-32; Nissim) was used ( Fig. 1 ). A prosthodontist (M.R.-L.) with 8 years of experience using IOSs recorded different mandibular scans with 3 IOSs following the recommended scanning protocol from each manufacturer. To replicate the clinical environment, the interincisal opening was standardized to 50 mm. In addition, the mannequin was fixed on the head support of a dental chair, and the IOSs were always positioned on the left side of the dental chair. Three IOSs were evaluated ( Table 1 ) at 4 ambient lighting settings ( Table 2 ).

A, Dental simulator model with interincisal opening of 50 mm. B, Mandibular typodont with first right premolar missing.
Figure 1
A, Dental simulator model with interincisal opening of 50 mm. B, Mandibular typodont with first right premolar missing.

Table 1
Characteristics of intraoral scanning systems evaluated
Group Open/Close System Technology Powdering Color Image Image Type
IOS-1, iTero Element (Cadent LTD) Open Parallel confocal microscopy technique
Illuminates the surface of the object with three beams of different colored light (red, green, or blue) which combine to provide white light.
No Yes Photographic
IOS-2, Omnicam (CEREC-Dentsply Sirona) Open Active triangulation (multicolor stripe projection). No Yes Videographic
IOS-3, TRIOS 3 (3Shape A/S) Open Confocal microscopy technology. Ultrafast optical sectioning.
Light source provides an illumination pattern to cause a light oscillation on the object.
No Yes Photographic

Table 2
Summary of different light conditions settings evaluated
Light Condition Chair Light 10 000 Lux 4100 K Room Light 1003 Lux 4100 K Windows 500 Lux
CL Yes Yes No
RL No Yes No
NL No No Yes
ZL No No No
CL, chair light; NL, natural light; RL, room light; ZL, no light.

For the CL group, a room with a dental chair (A-dec 500; A-dec) and no windows was selected. The LED light of the chair had an intensity of 15 000 lux and 4100 K oriented 45 degrees at a distance of 58 cm to the mannequin. The room had 6 fluorescent tubes of 54 W, 5000 lumens (GE F54W-T5-841-ECO, Ecolux High Output fluorescent tube; Ecolux Lighting Pvt, Ltd), with a white spectrum color temperature (4100 K) ceiling light. The ambient light condition of 10 000 lux was determined by using a light meter (Digital Light Meter LX1330B; Dr. Meter).

For the RL group, the light of the chair was turned off, and only the ceiling light of the same room was used, with no windows or natural light. The illuminance of the room was 1003 lux, which was measured by using the same light meter. For the ZL group, the same room was used where the light chair and ceiling light were turned off. For the NL group, a room was used with natural light of 500 lux measured by using the same light meter obtained through windows.

Ten digital scans were made for each group in an ambient light scanning setting for a total of 120 digital scans. The mesh quality of the reconstructed model was analyzed by using the iso2mesh MATLAB package.

Element shape metrics were used to measure the quality of the generated mesh. The Joe-Liu quality metric was used to measure the quality which was defined as follows:




η


=





2


×




2




×




3




S











0





i





j


<


2






l




ij




2






,


where



S


represented the area of a triangle and





l




ij




denoted the edge length between the i-th and the j-th vertices in the triangle. The range of the Joe-Liu quality was from 0 to 1. A value close to 1 represented higher mesh quality (1 means equilateral triangle), while a value close to 0 means nearly degenerated element.

The statistical aggregates were computed to evaluate the mesh quality and effect of the IOSs and ambient scanning light conditions. The mean values of mesh quality of each scan were computed for conducting statistical tests. The normality of the data set was tested by using the Kolmogorov-Smirnov test. Because of the nonnormality of the data, the data were transformed by using the ARTool before a 2-way ANOVA. To investigate further, the Kruskal-Wallis 1-way ANOVA was performed per ambient scanning light condition for each IOS and per IOS for each scanning light condition individually.


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