Learning curve of digital intraoral scanning – an in vivo study

Róth, Ivett; Czigola, Alexandra; Joós-Kovács, Gellért Levente; Dalos, Magdolna; Hermann, Péter; Borbély, Judit

doi:10.1186/s12903-020-01278-1

Cited by 46 publications

(24 citation statements)

References 38 publications

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“…The inclusion criteria for patients included age over eighteen years, full dentition (except for the third molar), good oral hygiene, healthy hard/soft tissue (no caries or extraction socket), and normocclusion (Angle I). The exclusion criteria were orthodontic treatment in progress, dental implants, any prosthetic treatment (inlays/onlays, crowns or bridges), and periodontal disorders (gingivitis or periodontitis) [ 14 ].…”

Section: Methodsmentioning

confidence: 99%

“…IOS devices are a way for dentists to partake in a digital workflow; however, a certain degree of experience is required to operate an IOS [ 13 ]. Hence, IOSs have a learning curve; thus, the members of the dental team need to spend time in training to effectively apply these devices in clinical practice [ 3 , 14 ]. Dr. Francois Duret demonstrated the first CAD/CAM system at the France Dental Association's International Congress in 1985.…”

Section: Introductionmentioning

confidence: 99%

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Digital intraoral scanner devices: a validation study based on common evaluation criteria

et al. 2022

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Background The evolution of intraoral scanners (IOSs) is rapid, and new IOSs appear on the market with different properties depending on the manufacturers. There is no uniform rating system based on a defined set of aspects that has reported in the literature that can be used to compare these devices. This validation study aimed to compare different IOSs based on objective and comprehensive parameters. Methods In this study, 12 different IOSs were examined. The IOSs that were tested in this study in order of their delivery included the 3Shape Trios 3 Pod®, Planmeca Emerald®, Straumann DWIO®, GC Aadva®, iTero Element 2®, CEREC Primescan®, Medit i500®, 3Shape Trios 4 Move®, Carestream CS3600®, 3Shape Trios 4 Pod®, Carestream CS3700®, and Planmeca Emerald S®. IOSs were evaluated in four different ways: (a)summary chart, (b)comparative assessment, (c)data based on in vitro measurements and (d)accuracy measurements. A scoring system was created to enable an objective rating of IOSs. Results The differences among IOSs were demonstrated in point scores (summary chart[max. 10 points] + weight of IOSs[max. 2.5 points] + circumference of IOSs[max. 2.5 points] + in vitro scanning time[max. 2.5 points] + pauses in data capture[max. 2.5 points] + accuracy[max. 10 points] = summary[max. 30 points]). Trios 4 Pod achieved the greatest cumulative score (23.37 points), furthermore it earned the highest points for summary chart and scanning speed. Regarding scanning continuity, the best-performing IOSs, which tied at identical point scores, were the Trios 3 and 4 Pod, Trios 4 Move, iTero Element 2, CS3600 and CS3700. The most accurate IOS was the CEREC Primescan, although it earned the lowest points of the comparative assessment (heaviest IOS). GC Aadva scored 5.73 points of a maximum of 30 points, which was the poorest result in this study. Conclusion The scoring system reflects the differences among IOS devices based on the evaluated objective parameters and can be used to help clinicians select the right IOS device. The new generations of IOSs have more special properties, and their accuracy is higher than the previous versions. Trial registration The permission for this study was granted by University Ethics Committee of Semmelweis University (SE RKEB number:108/2019).

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digital intraoral scanner devices: a validation study based on common evaluation criteria

et al. 2022

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“…Among them, TRIOS 3 uses the ultrafast optical sectioning technique based on the confocal laser principle; so, it is one of the most popular oral scanners clinically. Clinicians should go through a proper learning curve [4] and focus on one or two IOS devices in dental practice.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Different Head Movements of Intraoral Scanner in Full Arch of Both Maxilla and Mandible

et al. 2021

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This in vitro study aimed to compare the accuracy of maxilla and mandible full-arch scans from an intraoral scanner via one scan path with six different head movements. Standard maxilla and mandible models via holder were set in a dental chair to simulate position and posture. The reference models’ standard tessellation language (STL) files were formatted via desktop scanner, and operative models’ files were obtained via IOS TRIOS 3 Pod as superimposed by Exocad CAD software. The same scan path with six head movements (Linear, Circle, Wave, 8-figure, S-figure, and A-P) were designed to scan 10 times per jaw, and a total of 120 scan files were then compared with reference files. The data were recorded and deviations of both occlusal and B-L sides were compared, with statistical analysis being performed by one-way analysis of variance (ANOVA) and post hoc comparisons with Tukey test. The trueness of optical impression for full-arch via one path with six head movements differed from maxilla and mandible and depended on the different movements (p < 0.05). In the same path, peak deviation was found at the turning points for left central incisor, left first premolar, left second molar, and right second molar in maxilla, and for right first premolar, second molar, and left second molar in the mandible. The 8-figure movement showed the highest deviation (0.128 ± 0.086 mm) in the maxilla and (0.105 ± 0.069 mm) in the mandible. The Linear movement presented the lowest deviation (0.096 ± 0.07 mm) in the maxilla while the Circle movement presented the lowest deviation (0.073 ± 0.041 mm) in the mandible, with the 8-figure movement showing the worst precision among six movements. In the maxilla, the S- and 8-figure movements were not recommended, while the Linear and Circle movements showed high trueness. In the mandible, the 8-figure movement was not recommended, while the other five presented similar lower deviations.

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“…In addition, there are many cases in which the tooth root morphology of the second molars rather than the first molars is irregular, increasing the likelihood of errors. Furthermore, intraoral scanning inaccuracy of second molars may also lead to errors [ 19 , 20 ]. However, as digital technologies in orthodontic treatment including virtual setup and indirect bonding using 3D printing have become popular, the second molars are included in orthodontic treatment from the beginning of the treatment stages.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of deep learning-based integrated tooth models by merging intraoral scans and CBCT scans for 3D evaluation of root position during orthodontic treatment

2022

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Objective This study aimed to evaluate the accuracy of deep learning-based integrated tooth models (ITMs) by merging intraoral scans and cone-beam computed tomography (CBCT) scans for three-dimensional (3D) evaluation of root position during orthodontic treatment and to compare the fabrication process of integrated tooth models (ITMs) with manual method. Material and methods Intraoral scans and corresponding CBCT scans before and after treatment were obtained from 15 patients who completed orthodontic treatment with premolar extraction. A total of 600 ITMs were generated using deep learning technology and manual methods by merging the intraoral scans and CBCT scans at pretreatment. Posttreatment intraoral scans were integrated into the tooth model, and the resulting estimated root positions were compared with the actual root position at posttreatment CBCT. Discrepancies between the estimated and actual root position including average surface differences, arch widths, inter-root distances, and root axis angles were obtained in both the deep learning and manual method, and these measurements were compared between the two methods. Results The average surface differences of estimated and actual ITMs in the manual method were 0.02 mm and 0.03 mm for the maxillary and mandibular arches, respectively. In the deep learning method, the discrepancies were 0.07 mm and 0.08 mm for the maxillary and mandibular arches, respectively. For the measurements of arch widths, inter-root distances, and root axis angles, there were no significant differences between estimated and actual models both in the manual and in the deep learning methods, except for some measurements. Comparing the two methods, only three measurements showed significant differences. The procedure times taken to obtain the measurements were longer in the manual method than in the deep learning method. Conclusion Both deep learning and manual methods showed similar accuracy in the integration of intraoral scans and CBCT images. Considering time and efficiency, the deep learning automatic method for ITMs is highly recommended for clinical practice.

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Learning curve of digital intraoral scanning – an in vivo study

Cited by 46 publications

References 38 publications

Digital intraoral scanner devices: a validation study based on common evaluation criteria

Digital intraoral scanner devices: a validation study based on common evaluation criteria

Accuracy of Different Head Movements of Intraoral Scanner in Full Arch of Both Maxilla and Mandible

Accuracy of deep learning-based integrated tooth models by merging intraoral scans and CBCT scans for 3D evaluation of root position during orthodontic treatment

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