Quantitative tooth mobility evaluation based on intraoral scanner measurements

Quantitative evaluation of the proximal contact area gap change characterization under intercuspal occlusion by intraoral 3D scanning: Food impaction with tight proximal contact

OBJECTIVE

This study aimed to present three indicators that represent the proximal contact area gap change under intercuspal occlusion and to see if and how these indicators influence food impaction with tight proximal contact.

MATERIALS AND METHODS

Ninety volunteers were recruited for bite force measurement and intraoral scanning. Three-dimensional surface data and buccal bite data were obtained for 60 impacted and 60 non-impacted teeth. The scanning data were imported into the Geomagic Studio 2013 to measure three indicators, which included the gap change maximum (Δdm, μm), the buccolingual position of Δdm (P), and the gap expanded buccolingual range (S, mm). The difference between two groups of three indicators and their relationship with food impaction with tight proximal contact were analyzed by the t test, the Pearson chi-squared test, the nonparametric Mann-Whitney U test, and the binary logistic regression analysis (a = 0.05).

RESULTS

All indicators (Δdm, P, and S) were statistically different (p < 0.001, p = 0.002, and p < 0.001) in the impacted and non-impacted groups. Food impaction with tight proximal contact was affected by Δdm and S (p < 0.001, p = 0.039), but not by P (p = 0.409).

CONCLUSION

The excessive increase of the gap change maximum and the gap expanded buccolingual range under bite force promoted the occurrence of food impaction with tight proximal contact.

CLINICAL SIGNIFICANCE

The use of intraoral scanning to measure the characteristics of the proximal contact area gap change under bite force may help to deepen our understanding of the pathogenesis of food impaction with tight proximal contact. Importantly it can provide a reference basis for individualizing and quantifying occlusal adjustment treatment.

Advancements in Methods of Classification and Measurement Used to Assess Tooth Mobility: A Narrative Review

Evaluating tooth mobility is clinically significant, not only for diagnosing periodontal tissues but also in determining the overall periodontal treatment plan. Numerous studies related to tooth mobility have been conducted over the years, including the proposal of various classifications as well as the development of electronic devices for objective measurement. However, there is still no consensus on the measurement methods and criteria for assessing tooth mobility. In this study, we provide a comprehensive review of past and current tooth mobility classification and measurement methods. In order to propose a new method to intuitively evaluate tooth mobility based on previous studies, a digital approach capable of recording tooth micromovements induced by dynamic load should be considered.

Assessment of physiological posterior-tooth displacement under habitual occlusal force by intraoral scanning using implant-supported crowns as the reference

STATEMENT OF PROBLEM

Studies that have used digital methods to quantitatively evaluate physiological tooth displacement under occlusal force are sparse.

PURPOSE

The purpose of this clinical study was to measure physiological posterior tooth displacement under occlusal force by intraoral scanning and reverse engineering technology by using implants as the reference.

MATERIAL AND METHODS

A total of 14 participants received 15 implant-supported single mandibular first molar crowns. The surface data of maxillary and mandibular posterior teeth (U1 and L1) and the buccal occlusal data in the maximum intercuspal position (MIP) with habitual occlusal force were obtained by using an intraoral scanner (TRIOS 3, v20.1.2). The U1 and L1 data were segmented into single teeth, which were then aligned to the buccal occlusal data by using the "best-fit alignment" command to build the data under occlusal force (U2 and L2). U1 and L1 data were compared with U2 and L2 data to calculate the centroid and functional cusp vertex displacements and the long axis deflections of the second premolars and second molars, taking the first molar as the reference. The medians, and first quartile (Q₁), third quartile (Q₃) of the above data were reported, and the Shapiro-Wilk and Wilcoxon tests were used to analyze the differences (α=.05).

RESULTS

Under occlusal force, the median (Q₁, Q₃) centroid displacements of posterior teeth ranged from 61 (52, 101) μm to 146 (80, 186) μm; the functional cusp vertex displacements ranged from 82 (62, 117) μm to 146 (98, 189) μm, and the long axis deflections ranged from 0.45 (0.25, 0.87) degrees to 1.03 (0.52, 1.41) degrees. Mandibular second premolars displaced lingually, mesially, and apically; mandibular second molars displaced distally and apically; and maxillary second premolars and second molars displaced lingually and apically.

CONCLUSIONS

A digital method taking implant-supported single crowns as the reference was used to demonstrate physiological posterior-tooth displacement under habitual occlusal force.

Influence of digital implant analog design on the positional trueness of an analog in additively manufactured models: An in-vitro study

BACKGROUND

Limited evidence exists regarding the accuracy of implant analog position in printed models, particularly when implant analogs with varying designs are used.

PURPOSE

To evaluate the effect of digital implant analog (DIA) design on the trueness of their position in additively manufactured digital implant models (DIMs) and to compare with that of a conventional implant analog in a stone cast.

MATERIALS AND METHODS

A dentate maxillary model with a conventional implant analog (Nobel Biocare Implant Replica 4.3 mm CC RP) at left second premolar site was digitized by using a laboratory scanner (3Shape D2000) and a (SB) scan body to generate the master standard tessellation language (STL) file (M0). 12 custom trays were fabricated on M0 file and conventional polyvinylsiloxane impressions of the model were made. All impressions were poured after inserting conventional implant analogs (Nobel RP Implant Replica) (Group A). Model was then digitized with an intraoral scanner (TRIOS 3) and the same SB, and DIMs with three different DIA designs (Nobel Biocare [Group B], Elos [Group C], and NT-trading [Group D]) were generated (Dental System-Model Builder). 12 DIMs of each design were additively manufactured and corresponding DIAs were inserted. All models were digitized by using the same laboratory scanner and SB, and these STLs were transferred to a 3D analysis software (Geomagic Control X), where the STL files of the models were superimposed over M0. Linear and 3D deviations at three selected points on SB (implant-abutment connection, most cervical point on SB, and most coronal point on SB) as well as angular deviations on two planes (buccolingual and mesiodistal) were calculated. Analysis of variance (ANOVA) and Bonferroni corrected t-tests were used to analyze the trueness of implant analog positions (α = 0.05).

RESULTS

The interaction of main effects significantly affected linear (p < 0.001) and angular deviations (p = 0.020). At point 1, group D had higher deviations than groups A and B (p ≤ 0.015). In addition, groups A and D had higher deviations than group B at point 4 (p < 0.001). While group C had similar linear deviations to those of other groups at point 1 and point 4 (p ≥ 0.192), the differences among test groups at point 2 were nonsignificant (p ≥ 0.276). Group B had lower angular deviations than groups C (p = 0.039) and D (p = 0.006) on buccolingual plane.

CONCLUSIONS

Analog design affected the trueness of analog position as proprietary, pressure/friction fit DIA (group B) had higher linear trueness than screw-retained DIA (Group D) and conventional implant analog (group A). In addition, pressure/friction fit DIA had the highest angular trueness among tested DIAs.

Predicting postoperative pain following root canal treatment by using artificial neural network evaluation

This study aimed to evaluate the accuracy of back propagation (BP) artificial neural network model for predicting postoperative pain following root canal treatment (RCT). The BP neural network model was developed using MATLAB 7.0 neural network toolbox, and the functional projective relationship was established between the 13 parameters (including the personal, inflammatory reaction, operative procedure factors) and postoperative pain of the patient after RCT. This neural network model was trained and tested based on data from 300 patients who underwent RCT. Among these cases, 210, 45 and 45 were allocated as the training, data validation and test samples, respectively, to assess the accuracy of prediction. In this present study, the accuracy of this BP neural network model was 95.60% for the prediction of postoperative pain following RCT. To conclude, the BP network model could be used to predict postoperative pain following RCT and showed clinical feasibility and application value.

The Chairside Periodontal Diagnostic Toolkit: Past, Present, and Future

Periodontal diseases comprise a group of globally prevalent, chronic oral inflammatory conditions caused by microbial dysbiosis and the host immune response. These diseases specifically affect the tooth-supporting tissues (i.e., the periodontium) but are also known to contribute to systemic inflammation. If left untreated, periodontal diseases can ultimately progress to tooth loss, lead to compromised oral function, and negatively impact the overall quality of life. Therefore, it is important for the clinician to accurately diagnose these diseases both early and accurately chairside. Currently, the staging and grading of periodontal diseases are based on recording medical and dental histories, thorough oral examination, and multiple clinical and radiographic analyses of the periodontium. There have been numerous attempts to improve, automate, and digitize the collection of this information with varied success. Recent studies focused on the subgingival microbiome and the host immune response suggest there is an untapped potential for non-invasive oral sampling to assist clinicians in the chairside diagnosis and, potentially, prognosis. Here, we review the available toolkit available for diagnosing periodontal diseases, discuss commercially available options, and highlight the need for collaborative research initiatives and state-of-the-art technology development across disciplines to overcome the challenges of rapid periodontal disease diagnosis.

Increased tooth mobility after fixed orthodontic appliance treatment can be selectively utilized for case refinement via positioner therapy - a pilot study

Background

Increased tooth mobility persists after fixed orthodontic appliance removal, which is therapeutically utilized for post-treatment finishing with positioners. As such a fine adjustment is only required for selected teeth, the aim of this pilot study was to investigate tooth mobility in vivo on corrected and uncorrected subgroups under positioner therapy.

Methods

Mobility was measured on upper teeth of 10 patients (mean age 16.8) by applying loadings for 0.1, 1.0 and 10.0 s with a novel device directly after multibracket appliance debonding as much as 2d, 1, 2 and 6 weeks later. Positioners were inserted at day 2. Specimens were divided into Group C (teeth corrected via positioner), Group N (uncorrected teeth adjacent to teeth from group C), and Group U (uncorrected teeth in an anchorage block). Untreated individuals served as controls (n = 10, mean age 22.4). Statistics were performed via Kolmogorov-Smirnov test and Welch’s unequal variances t-test for comparisons between groups. P < 0.05 was considered statistically significant.

Results

After 1 week, tooth mobility in Group U almost resembled controls (13.0–15.7 N), and reached physiological values after 6 weeks (17.4 N vs. 17.3 N in controls). Group C (9.0–13.4 N) and Group N (9.2–14.7 N) maintained increased mobility after 6 weeks. Tooth mobility was generally higher by reason of long loading durations (10.0 s).

Conclusions

Positioner therapy can selectively utilized increased tooth mobility upon orthodontic fixed appliance treatment for case refinements. Here, uncorrected teeth in anchorage blocks are not entailed by unwanted side effects and recover after 6 weeks post treatment. Corrected teeth and their neighbors exhibit enhanced mobility even after 6 weeks, which represents a necessity for the proper correction of tooth position, and concurrently arouses the requirement for an adequate retention protocol.