Loading clinical trials...
Loading clinical trials...
Showing 1-3 of 3 trials
NCT07162753
This study explores how artificial intelligence (AI) can be used in orthodontics, which is the area of dentistry that focuses on correcting jaw and bite problems. AI is a computer technology that can learn from large amounts of data and then make predictions or decisions. It is already being tested in medicine and dentistry to help doctors and dentists diagnose conditions. For this study, the AI system was trained using photographs and X-rays from patients in Turkey. The system learned to recognize specific orthodontic skeletal malocclusions. After the training stage, the AI was tested in two groups: one group included Turkish patients whose records were not used in training, and the other group included patients from different ethnic backgrounds who were treated at a clinic in Belgium. This design allows researchers to see if the AI works equally well for people of different backgrounds. Only photographs and X-rays taken before orthodontic treatment are used in the study, and all data are anonymized so that no personal information is shared. The images must meet certain quality standards. For example the head must be in natural position, with no beards, scars, or previous orthodontic treatment that might affect the image. Patients who do not meet these criteria are not included. The AI program analyzes the profile photographs, prepares them for evaluation by adjusting and standardizing the images, and then tries to decide each patient has which malocclusion. The results from Turkish patients and patients from other ethnic groups are compared to see if the system makes fair and accurate decisions for everyone. The purpose of this study is not to test a new treatment, but to understand how well AI can recognize orthodontic problems in different populations. This information is important because AI systems are increasingly being used in healthcare, and they need to be fair and accurate for all patients, not just those from one group. By participating, patients help researchers learn whether AI in orthodontics is reliable across diverse communities. This knowledge can guide future improvements in AI technology, ensuring that it supports orthodontists in providing safe, equal, and effective care for everyone.
NCT06504498
This study aimed to evaluate the effectiveness, pain, and satisfaction levels between patients treated with different thicknesses of clear aligners among Class I maxillary mild crowding cases. Two types of clear aligners with thicknesses of 0.5 and 0.75 mm were used. The null hypotheses were as follows: There is no clinical difference in effectiveness, pain, and satisfaction levels between different thickness of clear aligners. The alternate hypotheses were as follows: The thicker the clear aligner, the greater orthodontic force applied to tooth which affects the amount of orthodontic tooth movement, pain, and satisfaction levels of patients. The primary aim was to evaluate pre- and post-treatment changes in amount of orthodontic tooth movement. Maxillary cephalometric parameters were measured on lateral cephalograms and maxillary dental parameters were measured using OrthoAnalyzer, and compared before and after treatment. Visual Analogue Scale and Patient Satisfaction Evaluation Form were used in order to assess the pain and satisfaction levels of patients. Pain and satisfaction levels were measured before the aligner insertion (T0), at the 4th hour (T1), 2nd day (T2), 1st week (T3), 1st month (T4) and at the end of the treatment (T5).
NCT02866929
Numerous treatment protocols geared towards accelerating orthodontic treatment have emerged in the past few years as an appealing alternative for patients and practitioners. In the context of a thin biotype, these approaches pose a burden that could precipitate periodontal detrimental changes. Therefore, case selection and the implementation of periodontal biotype enhancing strategies become a relevant consideration to ensure long-term successful treatment outcomes. This study focuses on the biological and clinical value of the use of a porcine naturally cross-linked collagen matrix known as Mucograft®. Within the scope of Surgically Accelerated Orthodontic Treatment (SAOT) the structural and material features of Mucograft® provide: 1) A protective effect to the thin biotype upon rapid orthodontic protusive/proinclination movements and 2) Mucograft® enhances the therapeutic window effect that supports an increase on tooth movement rate. The designs of this randomized controlled clinical trial includes a cohort of 40 subjects distributed on the following groups I) Ortho tx, II) Ortho tx + Decortication, III) Ortho tx + Decortication + Mucograft®, and IV) Ortho tx + Mucograft®. Comparing clinical, tomographic and digital impression derived measurements will capture the clinical phenotype; while the biologic phenotype will be derived from evaluating crevicular fluid levels of tooth movement mediators such as Interleukin 1-β and Interleukin-1RA. The significance and innovative value of this proposal stems from the use of Mucograft® as an ideal collagen-based biotype enhancer when performed along with the corticotomy. This approach could prove to be effective to further increase the therapeutic window that allows accelerating orthodontic treatment and, at the same time, could decrease the recession risk in movements of proclination of antero-inferior incisors. Besides, the use of a collagen scaffold alone could potentially trigger a comparable orthodontic acceleratory outcome that could be evaluated as an alternative to decortication.