Extraction decision and identification of treatment predictors in Class I malocclusions

Evaluation of four machine learning methods in predicting orthodontic extraction decision from clinical examination data and analysis of feature contribution

Introduction

The study aims to predict tooth extraction decision based on four machine learning methods and analyze the feature contribution, so as to shed light on the important basis for experts of tooth extraction planning, providing reference for orthodontic treatment planning.

Methods

This study collected clinical information of 192 patients with malocclusion diagnosis and treatment plans. This study used four machine learning strategies, including decision tree, random forest, support vector machine (SVM) and multilayer perceptron (MLP) to predict orthodontic extraction decisions on clinical examination data acquired during initial consultant containing Angle classification, skeletal classification, maxillary and mandibular crowding, overjet, overbite, upper and lower incisor inclination, vertical growth pattern, lateral facial profile. Among them, 30% of the samples were randomly selected as testing sets. We used five-fold cross-validation to evaluate the generalization performance of the model and avoid over-fitting. The accuracy of the four models was calculated for the training set and cross-validation set. The confusion matrix was plotted for the testing set, and 6 indicators were calculated to evaluate the performance of the model. For the decision tree and random forest models, we observed the feature contribution.

Results

The accuracy of the four models in the training set ranges from 82% to 90%, and in the cross-validation set, the decision tree and random forest had higher accuracy. In the confusion matrix analysis, decision tree tops the four models with highest accuracy, specificity, precision and F1-score and the other three models tended to classify too many samples as extraction cases. In the feature contribution analysis, crowding, lateral facial profile, and lower incisor inclination ranked at the top in the decision tree model.

Conclusion

Among the machine learning models that only use clinical data for tooth extraction prediction, decision tree has the best overall performance. For tooth extraction decisions, specifically, crowding, lateral facial profile, and lower incisor inclination have the greatest contribution.

Effect of the Proximity of Roots to the Cortical Plate and Inclination of Incisors on External Apical Root Resorption

Background

External apical root resorption (EARR) is an unfavorable side effect of orthodontic treatment. Orthodontic treatment of patients with increased crowding could lead to the proclination of incisors and proximity of roots to the cortical plates.

Aims

The aim of this study was to evaluate the effects of the proximity of the labial and lingual cortical plates and the inclination of incisors on EARR.

Settings and Design

Twenty-six patients (age: 13.39 years) with nonextraction fixed orthodontic treatment were evaluated at pretreatment and posttreatment (52 cone-beam computed tomographies).

Materials and Methods

The maxillary and mandibular incisors (416 teeth) were evaluated for the pretreatment predictors such as the labial and palatal (lingual) cortical plate thickness, width of the mandibular symphysis/maxillary alveolus and cancellous bone, position of the root apex in cancellous/cortical bone, and treatment factors such as distance of root to the labial and palatal (lingual) outer and inner cortical plate and incisor inclination.

Statistical Analysis Used

Statistical analyses were performed with R software at a 0.05 significance level. Each parameter was compared between pretreatment and posttreatment by a paired t-test, and the association to root resorption was performed using a regression model.

Results

Clinically significant (>1 mm) root resorption was observed in 35% of all mandibular incisors and 52% of all maxillary incisors. Width of cancellous bone, position of the root apex in cortical bone, proximity of the root apex to the labial and palatal (lingual) outer cortical plate, lingual inner cortical plate, and proclination of incisors were significant factors associated with EARR.

Conclusions

Proximity to the cortical plates and proclination of incisors are associated with increased EARR.

Machine Learning Algorithms for the Diagnosis of Class III Malocclusions in Children

Artificial intelligence has been applied to medical diagnosis and decision-making but it has not been used for classification of Class III malocclusions in children.

OBJECTIVE

This study aims to propose an innovative machine learning (ML)-based diagnostic model for automatically classifies dental, skeletal and functional Class III malocclusions.

METHODS

The collected data related to 46 cephalometric feature measurements from 4-14-year-old children (n = 666). The data set was divided into a training set and a test set in a 7:3 ratio. Initially, we employed the Recursive Feature Elimination (RFE) algorithm to filter the 46 input parameters, selecting 14 significant features. Subsequently, we constructed 10 ML models and trained these models using the 14 significant features from the training set through ten-fold cross-validation, and evaluated the models' average accuracy in test set. Finally, we conducted an interpretability analysis of the optimal model using the ML model interpretability tool SHapley Additive exPlanations (SHAP).

RESULTS

The top five models ranked by their area under the curve (AUC) values were: GPR (0.879), RBF SVM (0.876), QDA (0.876), Linear SVM (0.875) and L2 logistic (0.869). The DeLong test showed no statistical difference between GPR and the other models (p > 0.05). Therefore GPR was selected as the optimal model. The SHAP feature importance plot revealed that he top five features were SN-GoMe (the ratio of the length of the anterior skull base SN to that of the mandibular base GoMe), U1-NA (maxillary incisor angulation to NA plane), Overjet (the distance between two lines perpendicular to the functional occlusal plane from U1 and L), ANB (the difference between angles SNA and SNB), and AB-NPo (the angle between the AB and N-Pog line).

CONCLUSIONS

Our findings suggest that ML models based on cephalometric data could effectively assist dentists to classify dental, functional and skeletal Class III malocclusions in children. In addition, features such as SN_GoMe, U1_NA and Overjet can as important indicators for predicting the severity of Class III malocclusions.

Evaluation of different machine learning algorithms for extraction decision in orthodontic treatment

INTRODUCTION

The extraction decision significantly affects the treatment process and outcome. Therefore, it is crucial to make this decision with a more objective and standardized method. The objectives of this study were (1) to identify the best-performing model among seven machine learning (ML) models, which will standardize the extraction decision and serve as a guide for inexperienced clinicians, and (2) to determine the important variables for the extraction decision.

METHODS

This study included 1000 patients who received orthodontic treatment with or without extraction (500 extraction and 500 non-extraction). The success criteria of the study were the decisions made by the four experienced orthodontists. Seven ML models were trained using 36 variables; including demographic information, cephalometric and model measurements. First, the extraction decision was performed, and then the extraction type was identified. Accuracy and area under the curve (AUC) of the receiver operating characteristics (ROC) curve were used to measure the success of ML models.

RESULTS

The Stacking Classifier model, which consists of Gradient Boosted Trees, Support Vector Machine, and Random Forest models, showed the highest performance in extraction decision with 91.2% AUC. The most important features determining extraction decision were maxillary and mandibular arch length discrepancy, Wits Appraisal, and ANS-Me length. Likewise, the Stacking Classifier showed the highest performance with 76.3% accuracy in extraction type decisions. The most important variables for the extraction type decision were mandibular arch length discrepancy, Class I molar relationship, cephalometric overbite, Wits Appraisal, and L1-NB distance.

CONCLUSION

The Stacking Classifier model exhibited the best performance for the extraction decision. While ML models showed a high performance in extraction decision, they could not able to achieve the same level of performance in extraction type decision.

Orthodontic Risk Perspectives among Orthodontists during Treatment: A Descriptive Pilot Study in Greece and Slovakia

This study explores orthodontists' perspectives on risks associated with orthodontic treatment, as described by Greek and Slovak orthodontists. Informed by the foundational importance of effective communication of risk perspectives in health sciences, particularly in facilitating valid consent and shared decision-making, this research addresses gaps identified in the literature concerning the consistent communication of potential treatment risks based on demographic and cultural characteristics. This study identifies 15 potential critical risks during orthodontic treatment. These risks include root resorption; temporary undesired changes to the occlusion; sleep difficulties; not achieving an ideal result; development of black triangles between teeth; taking additional X-rays; speech difficulties; using a protective splint during sports; duration of treatment; number of visits; transmission of infectious diseases; and swallowing orthodontic appliances. A questionnaire, distributed electronically to orthodontists in Greece (N1 = 570) and Slovakia (N2 = 210) from September 2022 to December 2022, aimed to assess risk communication practices, taking into consideration socio-demographic factors, such as country, gender, age, and academic-degree-related variations. A total of 168 valid questionnaires (91 from Slovakia and 77 from Greece) were obtained, indicating significant disparities in the risks emphasized and preferred forms of consent. The Greek orthodontists focused more on the risks involved, such as relapse, root resorption, temporal occlusal changes, and failure of desired movement, while the Slovak practitioners tended to be more interested in sleeping difficulties, temporal occlusal changes, and not achieving an ideal result. They also obtained written or digital consent from patients or their parents/guardians more frequently than the Greek team. Male orthodontists discussed specific risks more frequently, including relapse and extractions, whereas females preferred written or digital consent. PhD-trained orthodontists prioritized certain risks, indicating the need for tailored approaches. This study underscores the dynamic nature of risk assessment in orthodontic practice, emphasizing its ethical and strategic dimensions. The findings advocate for tailored risk communication strategies that recognize individual, contextual, and cultural factors, and the need for an orthodontic informed consent protocol for a tailored communication approach for patients to elevate the standard of care in European orthodontics. The reliance on digital tools reflects contemporary trends in enhancing patient understanding, thereby supporting ongoing innovation in orthodontic practices.

AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning-A Comprehensive Review

The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools. This review explores the principles of AI, its applications in orthodontics, and its implementation in clinical practice. A comprehensive literature review was conducted, focusing on AI applications in dental diagnostics, cephalometric evaluation, skeletal age determination, temporomandibular joint (TMJ) evaluation, decision making, and patient telemonitoring. Due to study heterogeneity, no meta-analysis was possible. AI has demonstrated high efficacy in all these areas, but variations in performance and the need for manual supervision suggest caution in clinical settings. The complexity and unpredictability of AI algorithms call for cautious implementation and regular manual validation. Continuous AI learning, proper governance, and addressing privacy and ethical concerns are crucial for successful integration into orthodontic practice.

An artificial neural network approach for rational decision-making in borderline orthodontic cases: A preliminary analytical observational in silico study

INTRODUCTION

Artificial intelligence (AI) technology has transformed the way healthcare functions in the present scenario. In orthodontics, expert systems and machine learning have aided clinicians in making complex, multifactorial decisions. One such scenario is an extraction decision in a borderline case.

OBJECTIVE

The present in silico study was planned with the intention of building an AI model for extraction decisions in borderline orthodontic cases.

DESIGN

An observational analytical study.

SETTING

Department of Orthodontics, Hitkarini Dental College and Hospital, Madhya Pradesh Medical University, Jabalpur, India.

METHODS

An artificial neural network (ANN) model for extraction or non-extraction decisions in borderline orthodontic cases was constructed based on a supervised learning algorithm using the Python (version 3.9) Sci-Kit Learn library and feed-forward backpropagation method. Based on 40 borderline orthodontic cases, 20 experienced clinicians were asked to recommend extraction or non-extraction treatment. The decision of the orthodontist and the diagnostic records, including the selected extraoral and intra-oral features, model analysis and cephalometric analysis parameters, constituted the training dataset of AI. The built-in model was then tested using a testing dataset of 20 borderline cases. After running the model on the testing dataset, the accuracy, F1 score, precision and recall were calculated.

RESULTS

The present AI model showed an accuracy of 97.97% for extraction and non-extraction decision-making. The receiver operating curve (ROC) and cumulative accuracy profile showed a near-perfect model with precision, recall and F1 values of 0.80, 0.84 and 0.82 for non-extraction decisions and 0.90, 0.87 and 0.88 for extraction decisions.

LIMITATION

As the present study was preliminary in nature, the dataset included was too small and population-specific.

CONCLUSION

The present AI model gave accurate results in decision-making capabilities related to extraction and non-extraction treatment modalities in borderline orthodontic cases of the present population.

Non-extraction Orthodontic Treatment in Angle Class I Malocclusion with Severe Crowding, Deep Bite, and Midline Shifting: A Case Report

Crowding is the most common dental case worldwide. This case report describes the diagnosis and management of a 20-year-old woman with severe crowding, deep bite, and midline shifting. The patient presented with the chief complaint of crowding and an unaesthetic smile. Upon examination, the patient had Angle Class I Malocclusion. The severe crowding was treated comprehensively and successfully corrected using fixed orthodontic appliances and without extraction, only interproximal reduction (IPR).

Immediate autotransplantation of a mandibular premolar with complete roots to a fractured tooth site, using platelet-rich fibrin in an orthodontic patient, report of a case

Transplantation of one tooth to another site in the same individual can be considered an attractive alternative to dental implants or fixed prostheses. This study reports the treatment results of a 16-year-old female with severe crowding in upper and lower arches and a fractured mandibular premolar with a poor prognosis. The crowding of the lower left quadrant was relieved by the extraction of the first premolar. This extracted tooth with a complete root was transplanted to the right quadrant with the fractured tooth. Platelet-rich fibrin can stimulate and accelerate periodontal healing. The platelet concentrate of this patient was prepared and applied to the socket wall at the time of surgery. The acceptable occlusion and the excellent 4-year prognosis of the transplanted tooth are presented.

Palatal shape covariation in extraction versus nonextraction borderline patients: A geometric morphometric study

INTRODUCTION

This study aimed to evaluate changes in palatal shape after orthodontic treatment from a borderline sample of extraction and nonextraction patients with a Class I relationship.

METHODS

A borderline sample regarding premolar extractions was obtained through discriminant analysis and comprised 30 nonextraction and 23 extraction patients. The digital dental casts of these patients were digitized with 3 curves and 239 landmarks placed on the hard palate. Procrustes superimposition and principal component analysis were implemented to assess group shape variability patterns.

RESULTS

The success of the discriminant analysis in identifying a borderline sample regarding the extraction modality was validated using geometric morphometrics. Concerning palatal shape, no sexual dimorphism was found (P = 0.78). The first 6 principal components that were statistically significant accounted for 79.2% of the total shape variance. Palatal changes were 61% more pronounced in the extraction group, which exhibited a decrease in palatal length (P = 0.02; 10,000 permutations). In contrast, the nonextraction group showed an increase in the palatal width (P <0.001; 10,000 permutations). Intergroup comparisons indicated that the nonextraction group exhibited longer palates, whereas the extraction group exhibited higher palates (P = 0.02; 10,000 permutations).

CONCLUSIONS

Considerable changes in palatal shape were seen for the nonextraction and extraction treatment group, with the latter exhibiting more pronounced changes, mainly in terms of palatal length. Further investigations are needed to clarify the clinical significance of the palatal shape changes in borderline patients after extraction and nonextraction treatment.

An Anthropological Investigation of the Sociocultural and Economic Forces Shaping Dental Crowding Prevalence

OBJECTIVE

The aim of the current study is to explore country of origin and social race category differences in dental crowding prevalence through an anthropological approach.

DESIGN

Data were collected from individuals within five countries (Australia, China, Japan, South Africa, United States; n = 1008) and seven social race groups in two countries (American Black, American White, Latinx, and Indigenous in the United States, South African Black, South African White, and South African Coloured; n = 654). Statistical significance between groups was assessed with a Kruskal-Wallis test, while a Dunn's post-hoc test identified which groups significantly differed.

RESULTS

Results indicate South Africa is characterized by the lowest frequencies of dental crowding, with Coloured South Africans yielding the highest and Black South Africans displaying the lowest frequencies. Individuals in the United States exhibited relatively high levels of minor dental crowding. American Blacks had lower crowding levels, while the Indigenous group had high levels of severe crowding. Individuals within China and Japan exhibited higher relative prevalence of severe crowding.

CONCLUSIONS

Overall, significant differences exist in dental crowding prevalence across countries and social race categories using an anthropological grading system to assess crowding. These differences are likely impacted by sociocultural (aesthetic preferences) and economic (access to dental care) factors.

Machine Learning Predictive Model as Clinical Decision Support System in Orthodontic Treatment Planning

Diagnosis and treatment planning forms the crux of orthodontics, which orthodontists gain with years of expertise. Machine Learning (ML), having the ability to learn by pattern recognition, can gain this expertise in a very short duration, ensuring reduced error, inter-intra clinician variability and good accuracy. Thus, the aim of this study was to construct an ML predictive model to predict a broader outline of the orthodontic diagnosis and treatment plan. The sample consisted of 700 case records of orthodontically treated patients in the past ten years. The data were split into a training and a test set. There were 33 input variables and 11 output variables. Four ML predictive model layers with seven algorithms were created. The test set was used to check the efficacy of the ML-predicted treatment plan and compared with that of the decision made by the expert orthodontists. The model showed an overall average accuracy of 84%, with the Decision Tree, Random Forest and XGB classifier algorithms showing the highest accuracy ranging from 87-93%. Yet in their infancy stages, Machine Learning models could become a valuable Clinical Decision Support System in orthodontic diagnosis and treatment planning in the future.

Cephalometric predictors for optimal soft tissue profile outcome in adult Asian class I subjects treated via extraction and non-extraction. A retrospective study

OBJECTIVE

The aim of this retrospective study was to identify cephalometric predictors associated with favourable soft tissue profile outcomes after premolars extraction and non-extraction in class I malocclusion subjects.

MATERIALS AND METHODS

A total of 80 subjects, treated with non-extraction and premolars extraction (40 subjects each), were equally divided into favourable (FG) and unfavourable (UFG) groups using subjective and objective soft tissue profile outcome assessment methods. An independent t-test was utilized for the comparison of cephalometric measurements between the non-extraction (NE) and premolars extraction (PME) treatment modalities. Cox proportional hazard algorithm regression analysis was performed to identify cephalometric factors associated with favourable soft tissue outcomes.

RESULTS

The pre-treatment mean age of the NE group was 20.2±2.3 and PME group was 20.2±2.5 years. After dividing the sample of the NE and PME groups according to subjective and objective soft-tissue outcome assessment criteria, FG and UFG consisted of 20 subjects each. Cox proportional hazard algorithm regression analysis found upper incisor to NA angle (95% CI: 1.033, 1.196) to be associated with FG in NE and upper incisor to SN (95% CI: 1.018, 1.206) and ANB angle (95% CI:1.165, 3.608) in PME. There was a statistically significant strong correlation between subjective and objective evaluation methods (P≤0.001).

CONCLUSIONS

Cephalometric analysis is a valuable tool to predict soft-tissue outcomes after NE and PME. Increased upper incisors inclinations at the start of NE treatment result in favourable soft tissue profile outcomes. Slightly convex profile and proclined maxillary incisors are the predictors of favourable soft tissue profile outcome after PME. There was a statistically significant association between subjective and objective evaluation criteria of soft tissue outcomes.

Pretreatment dentoskeletal comparison between individuals treated with extractions in the 1970s and in the new millennium

OBJECTIVE

This retrospective study aimed to compare the occlusal and dentoskeletal initial features of patients treated with four first premolar extractions in the 1970s and after 2000.

MATERIALS AND METHODS

Group 70' was composed by 30 subjects with Class I malocclusion (mean age of 12.8 years, 10 male, 20 female) treated in the 1970s with four first premolar extractions and comprehensive orthodontic treatment. Group NM comprised 30 subjects with Class I malocclusion (mean age of 13.4 years, 13 male, 17 female) treated in the new millennium, similarly to Group 70'. Initial dental models and lateral cephalograms were digitized and measured using OrthoAnalyzerTM 3D software and Dolphin Imaging 11.0 software, respectively. Initial occlusal and dentoskeletal features were analyzed and compared. Intergroup comparison was performed using t tests (p < 0.05). Holm-Bonferroni correction for multiple comparison was applied.

RESULTS

Group NM showed significantly greater maxillary and mandibular effective lengths and greater maxillary and mandibular incisor protrusion in comparison with Group 70'. Group NM presented a significantly greater lower anterior facial height. Group NM also showed significantly smaller nasolabial angle and protruded inferior lip.

CONCLUSION

Patients with Class I malocclusion treated with four first premolar extractions in the new millennium present a greater degree of dental and labial protrusion, increased lower anterior facial height, and more acute nasolabial angle compared with patients treated similarly in the 1970s. Greater dental and labial protrusion determines first premolar extractions in the new millennium.

CLINICAL RELEVANCE

Despite the decrease of tooth extraction frequency, four first premolar extractions may be justified in cases with severe dental and skeletal protrusions.

Temporary deterioration of oral health-related quality of life (OHRQoL) in nonextraction and extraction modalities of comprehensive orthodontic treatment in adolescents

OBJECTIVE

To evaluate the effects of nonextraction and all first premolar extraction modalities of orthodontic treatment on oral health-related quality of life (OHRQoL) among adolescents.

MATERIALS AND METHODS

Sixty-eight adolescents of aged 12-18 years were chosen. Subjects who required nonextraction orthodontic treatment were included in group I, and those who required all first premolar extractions for orthodontic treatment were included in group II. Baseline OHRQoL data (T0) were recorded before the start of treatment. To evaluate the impact of orthodontic treatment on OHRQoL, the Oral Health Impact Profile-14 (OHIP-14) questionnaire was presented to all subjects for retrospective evaluation at 1 month (T1), 3 months (T2), 6 months (T3) and 1 year (T4) after the start of orthodontic treatment and 1 week after completion of orthodontic treatment (T5).

RESULTS

At T1 and T2, the physical pain and physical disability domains of OHIP-14 were impacted significantly by comprehensive orthodontic treatment in both groups (P < .001). The negative impact of orthodontic treatment on OHRQoL was maximum at T1 and then slowly recovered to the pretreatment level at T3 in both groups. Recovery of OHIP-14 scores was relatively faster in group I subjects compared to group II subjects. At T1 and T2, social disability and handicap domains were deteriorated significantly in group II subjects compared to group I subjects (P < .01).

CONCLUSIONS

The severity of OHRQoL deterioration was similar in both modalities of orthodontic treatment, but recovery from negative impacts was relatively slower in the first premolar extraction subjects.

Bimaxillary protrusion and gummy smile treated with clear aligners: Closing premolar extraction spaces with bone screw anchorage

Inadequate posterior anchorage is a serious limitation for aligner treatment involving extraction of four first premolars. Inappropriate axial inclinations may compromise intermaxillary occlusion and stability. OrthoBoneScrew® (OBS) anchorage is designed to augment the Invisalign® clear aligner G6 solution to produce more predictable outcomes as illustrated by the current case report. An 18-year-old female presented with two chief complains: (1) Protrusive, incompetent lips, and (2) excessive gingival exposure when smiling (“gummy smile”). Clinical evaluation revealed bimaxillary protrusion, hypermentalis activity, anterior crowding, and excessive anterior axial inclinations, particularly of the lower incisors (116°). The American Board of Orthodontic (ABO) discrepancy index (DI) was 21. The treatment plan was extraction of all four first premolars, and clear aligner (Invisalign®) therapy anchored with four OBSs: Infra-zygomatic crest (IZC), and between the roots of the upper central and lateral incisors (Incisal) bilaterally. Eighteen months of initial treatment with 45 aligners retracted and intruded the anterior segments in both arches by closing the extraction spaces with supplemental anchorage provided by IZC and Incisal OBSs. The final series of 20 refinement aligners achieved an excellent outcome as evidenced by an ABO cast-radiograph evaluation (CRE) score of 10, and a pink and white (P&W) dental esthetic score of 3. Post-treatment analysis revealed multiple opportunities for improvement. The patient was well satisfied with the final outcome.

Machine Learning for the Diagnosis of Orthodontic Extractions: A Computational Analysis Using Ensemble Learning

Extraction of teeth is an important treatment decision in orthodontic practice. An expert system that is able to arrive at suitable treatment decisions can be valuable to clinicians for verifying treatment plans, minimizing human error, training orthodontists, and improving reliability. In this work, we train a number of machine learning models for this prediction task using data for 287 patients, evaluated independently by five different orthodontists. We demonstrate why ensemble methods are particularly suited for this task. We evaluate the performance of the machine learning models and interpret the training behavior. We show that the results for our model are close to the level of agreement between different orthodontists.

A Full Diagnostic Process for the Orthodontic Treatment Strategy: A Documented Case Report

The need for extractions in orthodontic treatment has always been a controversial topic. However, to date there is not a specific clinical guideline that can help the clinicians deciding to plan an extractive or a non-extractive orthodontic treatment. In this respect, clinicians must deal with patients’ occlusal, functional, periodontal and aesthetics characteristics before planning an orthodontic treatment including extraction. Considering the absence of specific guidelines, the choice to extract teeth or not is complicated, particularly in borderline cases. In this case report, we present a borderline case of a patient with the skeletal Class III pattern and significant crowding in both arches that could be treated with or without extraction, illustrating the diagnostic and decision-making processes that were conducted for the orthodontic treatment strategy.

Intra-observer reliability and agreement of manual and digital orthodontic model analysis

Background and aim

Digital orthodontic model analysis is gaining acceptance in orthodontics, but its reliability is dependent on the digitalisation hardware and software used. We thus investigated intra-observer reliability and agreement / conformity of a particular digital model analysis work-flow in relation to traditional manual plaster model analysis.

Materials and methods

Forty-eight plaster casts of the upper/lower dentition were collected. Virtual models were obtained with orthoX®scan (Dentaurum) and analysed with ivoris®analyze3D (Computer konkret). Manual model analyses were done with a dial caliper (0.1 mm). Common parameters were measured on each plaster cast and its virtual counterpart five times each by an experienced observer. We assessed intra-observer reliability within method (ICC), agreement/conformity between methods (Bland-Altman analyses and Lin's concordance correlation), and changing bias (regression analyses).

Results

Intra-observer reliability was substantial within each method (ICC ≥ 0.7), except for five manual outcomes (12.8 per cent). Bias between methods was statistically significant, but less than 0.5 mm for 87.2 per cent of the outcomes. In general, larger tooth sizes were measured digitally. Total difference maxilla and mandible had wide limits of agreement (-3.25/6.15 and -2.31/4.57 mm), but bias between methods was mostly smaller than intra-observer variation within each method with substantial conformity of manual and digital measurements in general. No changing bias was detected.

Conclusions

Although both work-flows were reliable, the investigated digital work-flow proved to be more reliable and yielded on average larger tooth sizes. Averaged differences between methods were within 0.5 mm for directly measured outcomes but wide ranges are expected for some computed space parameters due to cumulative error.

Treating Bimaxillary Protrusion and Crowding with the Invisalign G6 First Premolar Extraction Solution and Invisalign Aligners

In cases requiring extraction of four first premolars, ensuring maintenance of adequate posterior anchorage and proper inclination of the teeth adjacent to the extraction sites during space closure can be difficult. The Invisalign G6 first premolar extraction solution has been developed to specifically address these problems. This case report describes the treatment of a 30-year-old woman whose main concerns were related to her protrusive and malaligned anterior teeth. Clinical findings revealed, among others, bimaxillary anterior protrusion and moderate-to-severe anterior crowding. A treatment approach involving extraction of the four first premolars was chosen, followed by orthodontic treatment with the Invisalign G6 first premolar extraction solution and Invisalign aligners. At the completion of 19.5 months of aligner treatment, the patient’s anterior teeth were retracted and uprighted, resulting in an improvement in her lip profile. Normal overjet and overbite were also achieved along with alleviation of the anterior crowding. The patient was extremely happy with the treatment results.

Soft tissue changes following extraction vs. nonextraction orthodontic fixed appliance treatment: a systematic review and meta-analysis

The aim of this systematic review was to assess the effect of systematic extraction protocols during orthodontic fixed appliance treatment on the soft tissue profile of human patients. Nine databases were searched until December 2016 for controlled clinical studies including premolar extraction or nonextraction treatment. After elimination of duplicate studies, data extraction, and risk-of-bias assessment according to the Cochrane guidelines, random-effects meta-analyses of mean differences (MD) or standardized mean differences (SMD) and their 95% CIs were performed, followed by subgroup, meta-regression, and sensitivity analyses. Extraction treatment was associated with increased lower lip retraction (24 studies; 1,456 patients; MD = 1.96 mm), upper lip retraction (21 studies; 1,149 patients; MD = 1.26 mm), nasolabial angle (21 studies; 1,089 patients; MD = 4.21°), soft-tissue profile convexity (six studies; 408 patients; MD = 1.24°), and profile pleasantness (three studies; 249 patients; SMD = 0.41). Patient age, extraction protocol, and amount of upper incisor retraction during treatment were significantly associated with the observed extraction effects, while the quality of evidence was very low in all cases due to risk of bias, baseline confounding, inconsistency, and imprecision. Although tooth extractions seem to affect patient profile, existing studies are heterogenous and no consistent predictions of profile response can be made.

Profile changes following extraction orthodontic treatment: A comparison of first versus second premolar extraction

OBJECTIVE

To determine the change in the soft tissue profile following extraction orthodontic treatment with either first or second premolar extractions.

METHODS

This was a retrospective clinical study of 81 consecutive orthodontic patients treated with extraction of four premolars. Patients were divided into two treatment groups according to whether four first premolar teeth (PM1 treatment group, n=48) or four second premolar teeth were removed (PM2 treatment group, n=33) during treatment. Changes in the nasolabial angle and the distance of the upper and lower lips to E-plane were compared pre- and post-treatment. Age, sex, upper lip thickness, facial convexity, facial axis, upper and lower arch crowding at pre-treatment, use of molar anchorage and the amount of retrusion of the maxillary and mandibular incisor teeth during treatment were used as explanatory variables.

RESULTS

When facial convexity and facial axis at pre-treatment, the use of maxillary anchorage and the amount of retrusion of the maxillary and mandibular incisor teeth achieved as a consequence of treatment were taken into account, there was less than one degree (0.67°) difference between the change in the nasolabial angle in the PM1 treatment group compared to the PM2 treatment group (P>0.05). The mean change in the upper lip position relative to E-plane and the mean change in lower lip position relative to E-plane were also similar for the two groups.

CONCLUSION

The change in soft tissue profile following orthodontic treatment was similar regardless of whether first premolar or second premolar teeth were removed.

Vertical skeletal changes after extraction and non-extraction treatment in matched class I patients identified by a discriminant analysis: cephalometric appraisal and Procrustes superimposition

Background

In the long-lasting debate of extraction versus non-extraction treatment, the impact of extractions on the skeletal vertical dimension remains rather unclear. The aim of this retrospective research study was to obtain a bias-free sample of morphologically similar borderline patients treated with or without extraction of the four first premolars and to retrospectively evaluate the vertical changes that occurred.

Methods

A borderline sample of 83 patients, 41 treated with four first premolar extractions and 42 treated without, was obtained by means of discriminant analysis applied to a previously investigated parent sample of 542 class I patients. The pretreatment and posttreatment cephalometric radiographs were analyzed digitally, and seven measurements were assessed for vertical skeletal changes. Also, average tracings between the two treatment groups were evaluated using the Procrustes superimposition method.

Results

The variables of SN to Go-Gn and Y-axis showed adjusted intergroup differences of − 0.91° and − 1.11° (P = 0.04). Comparing the mean intra-group differences of all the variables simultaneously, a significant difference was found between the two treatment groups (overall P value = 0.04). In the extraction group, only the gonial angle showed a significant decrease (P = 0.01) while the overall P value evaluating the intra-group differences between pre- and posttreatment was significant (overall P value < 0.01). In the non-extraction group, the variable of N-ANS/N-Me showed a significant decrease (P = 0.02) and the overall P value evaluating the intra-group differences between pre- and posttreatment was also significant (overall P value < 0.01). Differences in treatment duration were assessed using a log-normal model and showed that extraction treatment lasted significantly longer than non-extraction treatment (P < 0.01).

Conclusions

The borderline group of patients identified by the discriminant analysis exhibited similar morphological characteristics at treatment’s onset; therefore, the posttreatment changes could safely be attributed to the choice of extraction or non-extraction treatment and not to pre-existing differences. Treatment choice had an impact on the patients’ vertical skeletal dimensions. Patients treated with four first premolar extractions showed a slight decrease in the vertical skeletal measurements, whereas non-extraction patient treatment showed a slight increase. The treatment time was also significantly higher in the extraction group.

Attitudes of orthodontists and laypersons towards tooth extractions and additional anchorage devices

Background

This study investigated the attitudes of orthodontists and laypersons towards the choice of extracting second premolars, rather than first premolars, based on tooth condition and the use of additional anchorage devices.

Methods

Questionnaires were sent to two groups: 324 orthodontists who were members of the Thai Association of Orthodontists, and 100 randomly selected Thai laypersons aged above 20 years and who were unrelated to the field of dentistry. Descriptive and chi-square statistics were used to analyze the data.

Results

Questionnaires were returned by 142 orthodontists (43.8%) and completed by 100 laypersons. The larger the size of the caries lesion in the maxillary second premolar was found, the more orthodontists and laypersons both chose to extract a carious maxillary second premolar instead of a healthy maxillary first premolar. For orthodontists, the use of mini-implant anchorage was significantly related to their extraction decision. Orthodontists who were familiar with mini-implants usage would choose to extract the second premolar at a lower size of extent of caries. Besides, when larger sizes of caries lesions in maxillary second premolars were considered, laypersons tended to have greater acceptance of the use of additional anchorage devices in order to keep the healthy maxillary first premolar.

Conclusions

In this study, tooth condition and the use of anchorage devices are currently the main considerations by both orthodontists and laypersons when selecting the teeth to be extracted for orthodontic treatment.

Arch-width changes in extraction vs nonextraction treatments in matched Class I borderline malocclusions

INTRODUCTION

The aims of this study were to identify a sample of borderline Class I extraction and nonextraction patients and to investigate posttreatment changes in arch-width and perimeter measurements.

METHODS

A parent sample of 580 Class I patients was subjected to discriminant analysis, and a borderline subsample of 62 patients, 31 treated with extraction of 4 first premolars and 31 treated without extractions, was obtained. The patients' plaster casts were digitally scanned, and the maxillary and mandibular intercanine and intermolar widths and perimeters were assessed.

RESULTS

The extraction group showed increases in maxillary and mandibular intercanine widths (P <0.001) and decreases in mandibular intermolar width and in maxillary and mandibular perimeters (P <0.001). The nonextraction group showed increases in all 4 arch-width measurements (P ≤0.003), whereas the maxillary and mandibular perimeters were maintained. The posttreatment differences between the 2 groups showed significant differences in the maxillary (P <0.001) and mandibular intermolar widths (P <0.001). Also, the comparison of the arch perimeters between the 2 treatment groups showed adjusted differences of -8.51 mm (P <0.001) and -8.44 mm (P <0.001) for the maxillary and mandibular arches, respectively. The intercanine widths showed no changes between the 2 treatment groups.

CONCLUSIONS

Borderline Class I patients treated with extraction of 4 first premolars had decreased maxillary and mandibular intermolar and perimeter measurements compared with nonextraction patients. The maxillary and mandibular intercanine widths showed no significant difference between the 2 treatment groups.

Improvement in Peer Assessment Rating scores after nonextraction, premolar extraction, and mandibular incisor extraction treatments in patients with Class I malocclusion

INTRODUCTION

Different treatment protocols implemented for correction of Class I malocclusion aim at achieving ideal occlusal characteristics. This study was planned to evaluate the improvement in the occlusal characteristics of Class I patients treated with nonextraction (NE), all first premolar extractions (PME), and mandibular incisor extraction (MIE) as assessed by the percentage of improvement in Peer Assessment Rating (PAR) scores.

METHODS

This retrospective cross-sectional study was conducted on the pretreatment and posttreatment dental casts of 108 subjects with Class I malocclusion. The total sample was divided into 3 equal groups according to the treatment protocol implemented: NE, PME, and MIE. The mean pretreatment and posttreatment PAR scores, and the percentages of improvement were compared among the 3 treatment modalities using Kruskal-Wallis and post-hoc Dunnett T3 tests.

RESULTS

The mean percentages of improvement in the PAR score were 75.8% ± 25.8% in the NE group, 73.1% ± 19.4% in the PME group, and 70.6% ± 24.1% in the MIE group. There was no significant difference (P = 0.351) in the percentages of improvement in PAR scores among the 3 treatment modalities. However, the mean pretreatment and posttreatment PAR scores varied significantly (P <0.001) in the 3 groups. The average pretreatment and posttreatment PAR scores were highest in the MIE group and lowest in the NE group.

CONCLUSIONS

The comparable percentages of improvement in PAR scores among the 3 groups denote that equivalent occlusal corrections were achieved in Class I patients treated with the NE, PME, and MIE protocols.

[Comprehensive assessment of atypical-extraction orthodontic treatment]

OBJECTIVE

To discuss through retrospective study associated factors influencing orthodontists to develop orthodontic treatment plans and to calculate constituent ratio of a typical extraction in orthodontic treatment.

METHODS

Systematic sampling was performed among 7 344 orthodontic patients, who received orthodontic treatment from April 2012 to March 2014 in the Department of Orthodontics, West China Hospital of Stomatology, Sichuan University. The study included statistical data on factors that may influence development of treatment plans. Samples were used to calculate extraction-ratio and atypical-extraction-ratio. Research focused on associated factors influencing development of treatment plans while evaluating correlation significances of each factor. Finally, treatment outcomes of atypical-extraction were compared with those of typical-extraction.

RESULTS

Among studied patients, 55.31% (406/734) received orthodontic extraction treatment. In orthodontic-extraction-treated patients, typical-extraction accounted for 59.11% (240/406), orthodontists-selected atypical-extraction accounted for 23.15% (94/406), and passive atypical-extraction accounted for 17.73% (72/406). With statistical analysis, we inferred associated factors influencing development of treatment plans as follows: sex and age of patients, sex of orthodontists, accurate condition of specific teeth, Angle's classification, and degree of midline deviation. Tooth loss before treatment also directly influences passive atypical-extraction. Statistically significant factors were not obtained. Significant difference of treatment outcome was not observed between atypical-extraction and typical-extraction-orthodontic treatment (P>0.05).

CONCLUSIONS

Above mentioned factors may influence orthodontists to develop treatment plans. However, orthodontists should also consider expected results of treatment strategies to prepare individual treatment plans on the basis of comprehensive analysis. 
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Functional evaluation in orthodontic surgical treatment: long-term stability and predictability

Background

The introduction of electromyographic and kinesiographic technology in orthodontics allows to obtain objective data regarding the functional aspects of the mandibular movements and the masticatory muscular activity. It is then important to be able to correlate the data obtained by instrumental activity with the clinical ones. The aim of this study consists to analyse the post ortodontic surgical stability through instrumental evaluation of the masticatory muscles and mandibular movements.

Method

30 patients undergo electromyographic and kinesiographic evaluations through all the surgical orthodontic iter and were than followed during other 4 years. JMP software was used to analyze and correlate the electromyographic and knesioographic data during treatment and during the follow up.

Results

A linear correlations between some functional objective values collected from the examinations at the beginning and during therapy and the follow up one has been demonstrated.

Conclusion

It is important to submit patients in surgical ortodontic treatment to instrumental analysis which can evidence how masticatory function and mandibular movements are performed. It is also important to highlight some functional values also from the beginning of the treatment because an alteration of such values can be related to a better or worse postsurgical rehabilitation.

Short-term effects of systematic premolar extraction on lip profile, vertical dimension and cephalometric parameters in borderline patients for extraction therapy--a retrospective cohort study

OBJECTIVES

The belief of many orthodontists that premolar extraction therapy leads to a loss of vertical dimension and an aggravated facial profile often predetermines a non-extraction approach. We investigated the short-term effects of systematic premolar extraction in borderline cases for extraction therapy on dentofacial parameters, especially vertical dimension and facial profile.

MATERIALS AND METHODS

Of 50 juvenile borderline cases for extraction treatment with a distinct sagittal overjet of 6-9 mm and dental crowding of >6 mm, 25 had all first premolars extracted, whereas the 25 control patients received non-extraction orthodontic treatment with corresponding fixed and removable appliances. Patient selection by multivariate cluster analysis ensured homogeneity at baseline regarding dentoskeletal parameters. Parameter changes were determined with radiographic cephalograms and compared between the extraction and non-extraction group.

RESULTS

The systematic extraction of premolars in borderline patients with a distinct sagittal overjet and crowding did not significantly influence sagittal or vertical skeletal dimension, while leading to a slightly more concave lip profile due to incisor retraction compared to the non-extraction control group.

CONCLUSIONS

The influence of premolar extractions on facial profile is often overestimated, since only slight changes in lip profile are to be expected. In integrated treatment planning, the extraction decision should not be primarily based on concerns about the aggravation of facial profile and loss of vertical dimension.

CLINICIAL RELEVANCE

The decision, whether to extract healthy premolars in borderline patients for extraction therapy, is difficult to make. Our study clarifies the repercussions on cephalometric dentofacial parameters, facilitating future orthodontic extraction decisions.

Patients' acceptance of corticotomy-assisted orthodontics

OBJECTIVE

To study patients' acceptance of corticotomy-assisted orthodontics as a treatment option.

METHODS

Adult patients seeking orthodontic treatment were asked to complete two sets of questionnaires; the first set included questions about age, sex, and level of education and general questions about orthodontic treatment; and the second set was related to the corticotomy-assisted orthodontics. Before answering the corticotomy questions, a brief description of the clinical procedure was explained and photographs of an actual procedure were shown.

RESULTS

A total of 150 subjects were approached and 129 (86%) agreed to answer the questionnaires (72 male and 57 female patients). Of these, only 3.1% did hear about corticotomy and 7.8% selected corticotomy instead of extraction. Fear from the surgery (53.2%) was the most frequent reason for not selecting corticotomy followed by fear from pain (36.9%). The acceptance of corticotomy between males and females was similar. No relationship was found between the level of education and prior knowledge of the procedure, P=0.857. Prior knowledge about corticotomy was not a factor in selecting it as a treatment option (P=0.556) to reduce the treatment time (P=0.427).

CONCLUSION

The acceptance of corticotomy-assisted orthodontics as a treatment option was low. Fear from the surgery was the main reason for not selecting it. The acceptance of corticotomy-assisted orthodontics was not related to patient's level of education or sex.

Predictors of long-term stability of maxillary dental arch dimensions in patients treated with a transpalatal arch followed by fixed appliances

BACKGROUND

The aim of this retrospective study was to identify which dental and/or cephalometric variables were predictors of long-term maxillary dental arch stability in patients treated with a transpalatal arch (TPA) during the mixed dentition phase followed by full fixed appliances in the permanent dentition.

METHODS

Thirty-six patients, treated with TPA followed up by full fixed appliances, were divided into stable and relapse groups based on the long-term presence or not of relapse. Intercuspid, interpremolar and intermolar widths, arch length and perimeter, crowding, and upper incisor proclination were evaluated before treatment (T 0), post-TPA treatment (T 1), post-fixed appliance treatment (T 2), and a minimum of 3 years after full fixed appliances' removal (T 3). A binary logistic regression was performed thereafter to evaluate the impact of the dental arch and cephalometric measurements at T 1 and the changes between T 0 and T 1 as predictive variables for relapse at T 3.

RESULTS

The proposed model explained 42.7 % of the variance in treatment stability and correctly classified 72.2 % of the sample. Of the seven predictive variables, only upper anterior crowding (p = 0.029) was statistically significant. For every millimeter of decreased crowding at T 1 (after TPA treatment/before starting the fixed orthodontic treatment), there was an increase of 3.57 times in the odds of having stability.

CONCLUSIONS

The best predictor of relapse was maxillary crowding before treatment. The odds of relapse increase by 3.6 times for every millimeter of crowding at baseline.

Treating dental crowding with mandibular incisor extraction in an Angle Class I patient

Mandibular dental crowding often encourages patients to seek orthodontic treatment. The orthodontist should decide between protrusion of incisors or decrease in dental volume so as to achieve proper alignment and leveling. The present study reports the treatment of an Angle Class I malocclusion adolescent female brachyfacial patient with severe mandibular dental crowding, increased curve of Spee and deep overbite. The patient was treated with extraction of a mandibular incisor. This case was presented to the Brazilian Board of Orthodontics and Dentofacial Orthopedics (BBO) as a requirement for the title of certified by the BBO.

Sagittal lip positions in different skeletal malocclusions: a cephalometric analysis

BACKGROUND

The objectives of this paper are to (1) study use of soft tissue analyses advocated by Steiner, Ricketts, Burstone, Sushner and Holdway to develop soft tissue cephalometric norms as baseline data for sagittal lip position in Northeast Chinese adult population, (2) compare the sagittal lip positions in different skeletal malocclusions and (3) compare the sagittal lip positions in Northeast Chinese adults with other reported populations.

METHODS

Lateral cephalometric radiographs of subjects were taken in natural head position. Radiographs were manually traced and five reference lines - Sushner, Steiner, Burstone, Holdway and Ricketts, were used. The linear distance between the tip of the lips and the five reference lines were measured. Statistical analysis was done using the Statistical Package for Social Sciences (SPSS) 21. Descriptive analysis was done for each variable for each subject. Coefficient of variation between lip positions as assessed by reference lines was determined. Post hoc Tukey's test was used for comparison of the mean cephalometric values of three skeletal malocclusions. The level of significance for the analysis was set at p < 0.05.

RESULTS

The findings showed significant difference in the sagittal lip positions in different skeletal malocclusions. There was variation in consistent reference line in each skeletal malocclusion. The S2 line was the most consistent reference line in skeletal class I and class II group. The B line was the most consistent line in skeletal class III. In skeletal class II group, upper lips were the most protrusive and lower lips were retrusive than in skeletal class I and class III groups. In case of skeletal class III group, upper lips were retrusive and lower lips were more protrusive than in skeletal class I and class II groups.

CONCLUSIONS

The sagittal lip positions were found to be associated with the skeletal malocclusion pattern. Northeast Chinese population has protrusive upper and lower lip in comparison to Caucasians. Each skeletal malocclusion group showed different preferable reference lines for analysis of sagittal lip position.

Stability of class II subdivision malocclusion treatment with 3 and 4 premolar extractions

BACKGROUND

The purpose of this study was to compare the occlusal stability of class II subdivision malocclusion treatment with 3 and 4 first premolar extractions. A sample of 156 dental casts from 52 patients with class II subdivision malocclusion was divided into two groups according to the extraction protocol. Group 1 comprised 24 patients treated with 3 premolar extractions and group 2 included 28 patients treated with 4 premolar extractions.

METHODS

Peer assessment rating (PAR) indexes were measured on the dental casts obtained before (T1) and after treatment (T2) and at a mean of 6.9 years after the end of treatment (T3). The groups were matching regarding sex distribution, pretreatment, posttreatment and long-term posttreatment ages, and treatment and long-term posttreatment times. They were also comparable concerning the initial malocclusion severity and the occlusal results at the end of treatment. Stability evaluation was calculated by subtracting the posttreatment from the long-term posttreatment index values (T3 - T2). T tests were used to compare the amount and percentage of long-term posttreatment changes.

RESULTS

There were no intergroup differences regarding the amount and percentage of long-term posttreatment changes.

CONCLUSION

Treatment of class II subdivision malocclusion with 3 and 4 premolar extractions have a similar long-term posttreatment occlusal stability.

Change in the pulp chamber temperature with different stripping techniques

Background

The aim of this study is to evaluate the change in pulp chamber temperature during the stripping technique.

Methods

Seventy-eight proximal surfaces of 39 extracted human teeth were stripped by two techniques: double-sided perforated stripping disk (PSD) and handheld stripper (HS). The teeth were divided into three groups: incisors (group 1), premolars (2), and molars (3). A J type thermocouple was inserted into the pulp chamber for temperature evaluation during the stripping procedure.

Results

Temperature rise was observed in all groups. The average temperature increase for the incisors was 2.58°C (±0.27°C) with PSD and 1.24°C (±0.3°C) with HS; for the premolars, 2.64°C (±0.29°C) with PSD and 0.96°C (±0.39°C) with HS; and for the molars, 2.48°C (±0.38°C) with PSD and 0.92°C (±0.18°C) with HS. There was significant difference (p < 0.001) in pulp temperature variation among the stripping techniques evaluated. Greater variations in the temperature were observed for the stripping technique with PSD for all groups (3.1°C in incisors and premolars, 3.2°C in molars). Stripping performed with HS had minor differences in pulp temperature (1.7°C in incisors, 1.9°C in premolars, and 1.2°C in molars) than those in PSD group. However, the temperature variation was less than the critical threshold (5.5°C) in all groups. The results for teeth group comparison showed no significant difference in the temperature variation.

Conclusions

The stripping technique with PSD produced significant increase in pulp temperature, with no differences between the types of teeth. However, it may not be clinically relevant, and both stripping techniques can be used safely.