The relationship between temporomandibular joint disk displacement and mandibular asymmetry in skeletal Class III patients

Objective: To investigate the relationship between temporomandibular joint disk displacement (TMJ DD) and facial asymmetry in skeletal Class III patients. Materials and Methods: The subjects comprised 97 skeletal Class III adult patients seeking orthodontic treatment. In addition to the routine lateral and posteroanterior (PA) cephalograms, and regardless of the TMJ status, each subject consented to magnetic resonance imaging (MRI) to evaluate their TMJs. According to MRI readings, subjects were classified into four groups: group 1, bilateral normal disk position; group 2, bilateral DD with or without reduction; group 3, DD more advanced on the right side; and group 4, DD more advanced on the left side. PA and lateral cephalometric variables were analyzed to compare the four groups. Results: When the TMJ DD was more advanced on one side than on the other, the chin point usually deviated to the advanced side. When the TMJ DD status was equal or bilaterally normal, the amount of mandibular deviation was not significant. Conclusions: If a skeletal Class III patient has an asymmetric face, especially in the mandibular region, careful examination is necessary with regard to the status of the TMJ during orthodontic diagnosis and treatment planning. (Angle Orthod. 2011;81:624-631.)

A better statistical method of predicting postsurgery soft tissue response in Class II patients

Objective: To propose a better statistical method of predicting postsurgery soft tissue response in Class II patients. Materials and Methods: The subjects comprise 80 patients who had undergone surgical correction of severe Class II malocclusions. Using 228 predictor and 64 soft tissue response variables, we applied two multivariate methods of forming prediction equations, the conventional ordinary least squares (OLS) method and the partial least squares (PLS) method. After fitting the equation, the bias and a mean absolute prediction error were calculated. To evaluate the predictive performance of the prediction equations, a leave-one-out cross-validation method was used. Results: The multivariate PLS method provided a significantly more accurate prediction than the conventional OLS method. Conclusion: The multivariate PLS method was more satisfactory than the OLS method in accurately predicting the soft tissue profile change after surgical correction of severe Class II malocclusions.OAIID:oai:osos.snu.ac.kr:snu2014-01/102/0000030821/2SEQ:2PERF_CD:SNU2014-01EVAL_ITEM_CD:102USER_ID:0000030821ADJUST_YN:YEMP_ID:A076080DEPT_CD:861CITE_RATE:1.184DEPT_NM:치의학과SCOPUS_YN:YCONFIRM:

A More Accurate Method of Predicting Soft Tissue Changes After Mandibular Setback Surgery

Purpose: To propose a more accurate method to predict the soft tissue changes after orthognathic surgery.Patients and Methods: The subjects included 69 patients who had undergone surgical correction of Class III mandibular prognathism by mandibular setback. Two multivariate methods of forming prediction equations were examined using 134 predictor and 36 soft tissue response variables: the ordinary least-squares (OLS) and the partial least-squares (PLS) methods. After fitting the equation, the bias and a mean absolute prediction error were calculated. To evaluate the predictive performance of the prediction equations, a 10-fold cross-validation method was used.Results: The multivariate PLS method showed significantly better predictive performance than the conventional OLS method. The bias pattern was more favorable and the absolute prediction accuracy was significantly better with the PLS method than with the OLS method.Conclusions: The multivariate PLS method was more satisfactory than the conventional OLS method in accurately predicting the soft tissue profile change after Class III mandibular setback surgery. (C) 2012 American Association of Oral and Maxillofacial Surgeons J Oral Maxillofac Surg 70:e553-e562, 2012This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grants 2011-0026594 and 2011-0028067).OAIID:oai:osos.snu.ac.kr:snu2012-01/102/0000030821/7SEQ:7PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:0000030821ADJUST_YN:YEMP_ID:A076080DEPT_CD:861CITE_RATE:1.64FILENAME:첨부된 내역이 없습니다.DEPT_NM:치의학과EMAIL:[email protected]_YN:YCONFIRM:

A More Accurate Method of Predicting Soft Tissue Changes After Mandibular Setback Surgery

Purpose: To propose a more accurate method to predict the soft tissue changes after orthognathic surgery.Patients and Methods: The subjects included 69 patients who had undergone surgical correction of Class III mandibular prognathism by mandibular setback. Two multivariate methods of forming prediction equations were examined using 134 predictor and 36 soft tissue response variables: the ordinary least-squares (OLS) and the partial least-squares (PLS) methods. After fitting the equation, the bias and a mean absolute prediction error were calculated. To evaluate the predictive performance of the prediction equations, a 10-fold cross-validation method was used.Results: The multivariate PLS method showed significantly better predictive performance than the conventional OLS method. The bias pattern was more favorable and the absolute prediction accuracy was significantly better with the PLS method than with the OLS method.Conclusions: The multivariate PLS method was more satisfactory than the conventional OLS method in accurately predicting the soft tissue profile change after Class III mandibular setback surgery. (C) 2012 American Association of Oral and Maxillofacial Surgeons J Oral Maxillofac Surg 70:e553-e562, 2012This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grants 2011-0026594 and 2011-0028067).OAIID:oai:osos.snu.ac.kr:snu2012-01/102/0000030821/7SEQ:7PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:0000030821ADJUST_YN:YEMP_ID:A076080DEPT_CD:861CITE_RATE:1.64FILENAME:첨부된 내역이 없습니다.DEPT_NM:치의학과EMAIL:[email protected]_YN:YCONFIRM:

How to report reliability in orthodontic research: Part 1

In reporting reliability, duplicate measurements are often needed to determine if measurements are sufficiently in agreement among the observers (interobserver agreement) and/or within the same observer (intraobserver agreement). Some reports are often analyzed inappropriately using paired t tests and/or correlation coefficients. The aim of this article is to highlight the statistical problems of reliability testing using paired t tests and correlation coefficients and to encourage good reliability reporting within orthodontic research. With regard to the complex issue of reliability, a simple and singular statistical approach is not available. However, some methods are better than others. A graphic technique based on the Bland-Altman plot that can be simultaneously applied for both intra- and interobserver reliability will also be discussed.This work was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology(2012-0007545).OAIID:oai:osos.snu.ac.kr:snu2013-01/102/0000030821/5SEQ:5PERF_CD:SNU2013-01EVAL_ITEM_CD:102USER_ID:0000030821ADJUST_YN:YEMP_ID:A076080DEPT_CD:861CITE_RATE:1.381FILENAME:2013 07월 ajodo reliability 1 2012-0007545(pls).pdfDEPT_NM:치의학과EMAIL:[email protected]_YN:YCONFIRM:

How to report reliability in orthodontic research: Part 2

Proper statistical analysis is an absolutely essential tool for both clinicians and researchers attempting to implement evidence-based decisions. When analyzing reliability, statistical graphic representation is the best method. Other previously published error studies of 2-dimensional measurements, such as cephalometric landmarks, have inappropriately applied 1-dimensional approaches, such as linear or angular measurements. The aim of this article is to illustrate a graphic presentation method that can be applied to 2-dimensional data sets. We propose that this technique can show errors in both the x-axis and the y-axis simultaneously and should be used when reporting the reliability of a 2-dimensional data set. Our prediction error analysis of soft-tissue changes after orthognathic surgery will be presented as an example. By using different colors in each ellipse, this method can also identify any between-group differences.This work is supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012-0007545)OAIID:oai:osos.snu.ac.kr:snu2013-01/102/0000030821/6SEQ:6PERF_CD:SNU2013-01EVAL_ITEM_CD:102USER_ID:0000030821ADJUST_YN:YEMP_ID:A076080DEPT_CD:861CITE_RATE:1.458FILENAME:ajodo-s-13-00036.pdfDEPT_NM:치의학과EMAIL:[email protected]_YN:YCONFIRM:

Evaluation of automated cephalometric analysis based on the latest deep learning method

Objectives: To compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks (AI) with previously published AI according to the test style of the worldwide AI challenges at the International Symposium on Biomedical Imaging conferences held by the Institute of Electrical and Electronics Engineers (IEEE ISBI). Materials and Methods: This latest AI was developed by using a total of 1983 cephalograms as training data. In the training procedures, a modification of a contemporary deep learning method, YOLO version 3 algorithm, was applied. Test data consisted of 200 cephalograms. To follow the same test style of the AI challenges at IEEE ISBI, a human examiner manually identified the IEEE ISBI-designated 19 cephalometric landmarks, both in training and test data sets, which were used as references for comparison. Then, the latest AI and another human examiner independently detected the same landmarks in the test data set. The test results were compared by the measures that appeared at IEEE ISBI: the success detection rate (SDR) and the success classification rates (SCR). Results: SDR of the latest AI in the 2-mm range was 75.5% and SCR was 81.5%. These were greater than any other previous AIs. Compared to the human examiners, AI showed a superior success classification rate in some cephalometric analysis measures. Conclusions: This latest AI seems to have superior performance compared to previous AI methods. It also seems to demonstrate cephalometric analysis comparable to human examiners.Y

Do Class III patients have a different growth spurt than the general population?

Introduction: Understanding the timing and length of the growth spurt of Class III prognathic patients is fundamental to the strategy of interceptive orthopedic orthodontics as well as to the timing of orthognathic surgery. Consequently, this study was undertaken to determine whether there are any significant differences in the stature growth pattern of Class III subjects compared with non-Class III subjects and the general population. Methods: Twelve-year longitudinal stature growth data were collected for 402 randomly selected adolescents in the general population, 55 Class III mandibular prognathic patients, and 37 non-Class III patients. The growth data were analyzed by using the traditional linear interpolation method and nonlinear growth functions. The 6 stature growth parameters were measured: age at takeoff, stature at takeoff, velocity at takeoff, age at peak height velocity, stature at peak height velocity, and velocity at peak height velocity. Comparisons in the stature growth parameters and 15 cephalometric variables among the general population, Class III subjects, and non-Class III subjects were made with multivariate analysis. Results: Patients with Class III prognathism did not have different growth parameters compared with Class II subjects or the general population. Conclusions: This study does not allow meaningful conclusions with regard to the relationship of mandibular size and stature growth pattern. The application of nonlinear growth curves vs the traditional linear interpolation method was also discussed.OAIID:oai:osos.snu.ac.kr:snu2012-01/102/0000030821/8SEQ:8PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:0000030821ADJUST_YN:YEMP_ID:A076080DEPT_CD:861CITE_RATE:1.381FILENAME:첨부된 내역이 없습니다.DEPT_NM:치의학과EMAIL:[email protected]_YN:YCONFIRM:

Assessment of reliability in orthodontic literature: A meta-epidemiological study

Objectives: To map the statistical methods applied to assess reliability in orthodontic publications and to identify possible trends over time. Materials and Methods: Original research articles published in 2009 and 2019 in a subset of orthodontic journals were downloaded. Publication characteristics, including publication year, number of authors, single vs multicenter study, geographic origin of the study, statistician involvement, study category, subject category, types of reliability assessment, and statistical methods applied to assess reliability, were recorded. Descriptive statistics, Chi-square tests, and logistic regression analyses were performed to investigate associations between reliability analysis and study characteristics. Results: A total of 768 original research articles were analyzed. The most prevalent study category was observational (69%) with a statistician involved in 16% of studies. Overall, reliability was assessed in 47% of studies, and the most frequent methods applied to assess reliability were intraclass correlation coefficients or kappa statistics (60.4%). The odds of applying appropriate methods were greater in 2019 than in 2009 (odds ratio [OR]: 2.43; 95% confidence interval [CI]: 1.75, 3.37; P , .001). Involvement of a statistician resulted in greater odds of applying appropriate methods compared to no statistician involvement (OR: 1.88; 95% CI: 1.23, 2.87; P , .01). Conclusions: Over the past decade (2009 vs 2019), reliability assessment became more common in the orthodontic literature, and studies applying correct statistical methods to assess reliability significantly increased. This trend was more apparent in studies that involved a statistician, which may highlight the role of the statistician