CV
Prof. Simona Tecco is enabled as Full Professor in Dentistry (A.S.N. MIUR 2023).
She is Associate Professor at the University Vita-Salute San Raffaele, Milano (Italy).
In 1999, She was graduated in Dentistry at the University G.D 'Annunzio, Chieti/Pescara, and obtained
the Orthodontic Specialization Degree at the University “Cattolica del Sacro Cuore” in Rome, in 2006.
She obtained the PhD degree in “Dental Science” in 2003, with “excellent”, and a second PhD degree in “Physiology of mastication and dental materials” taken at the University of Torino. On 2015 She was graduated at the Master in “Orthodontics”, University Tor Vergata, Rome. She is actually Teacher in Orthognatodontics at the University Vita-Salute San Raffaele, Milan.
She is component of the Editorial Board of various Journals. She is an active member of Digital Dentistry Society, and Certified Speaker.
She is author of many researchers and articles in the field of Orthodontics, Pediatric Dentistry, Gnathology.
Predictability Analysis of Orthodontic Treatment with Aligners in Open Bite, Deep Bite, Cross bite Correction
In recent decades, aligner therapy has become common practice. Initially, they were only used in simple orthodontic cases, such misalignment. Nowadays, thanks to the introduction of new materials, attachments, and software, aligners are also used in the treatment of severe malocclusions such as open bite, deep bite, and cross bite. To plan the treatment, the clinician follows a particular operative scheme consisting of several steps, including the elaboration of the clinical case virtually. Unlike fixed multi-brackets therapy, which is based on a reactive action, aligners allow the clinician to observe, in advance, each step that will be performed in the treatment by the aligners, to predict the result. In the scientific world, clinicians have been asking questions about the efficacy and accuracy of digital programming, but to date there are few studies to create a protocol on the predictability of the outcome. The purpose of this retrospective observational study is to assess the predictability of aligners in open bite, deep bite or cross bite correction by comparing post-treatment intraoral scans with the programmed final position. The results of the study will be presented.
Learning objectives
- Learn to plan orthodontic treatment with aligners by foreseeing appropriate overcorrections
- Learn to plan orthodontic treatment with aligners involving the use of specific auxiliary tools
- Understand the technical limitations of aligner treatment
Applications that use Artificial İntelligence in Orthodontics and Gnathology
The main applications using artificial intelligence in orthodontics and gnathology will be presented. Subsequently, the advantages that these applications bring to clinical practice will be illustrated. Some examples of clinical cases will then be illustrated. Furthermore, the scientific literature on this aspect will be highlighted. Currently there are more and more scientific articles that illustrate the clinical applications of artificial intelligence in medicine, and they emphasize the integration of artificial intelligence into orthodontics and its potential to revolutionize treatment monitoring, evaluation, and patient outcomes. But among these we will illustrate those that focus on the real contribution of these applications to the therapeutic result (i.e., that evaluate their efficiency and effectiveness therapeutic). In particular, the difference between the advantages perceived by the operator and the patient, and the true advantages brought by these applications to the therapeutic result (in terms of efficacy and effectiveness), will be highlighted. Finally, a list of all these aspects will be drawn up which will be useful as a "take home message" for the public.
Learning objectives
- Inviting to reflect about the difference between the advantages perceived by the operator and the patient, and the true advantages brought by these applications to the therapeutic result (in terms of efficacy and effectiveness)
- Learning several approaches to using artificial intelligence in orthodontics
- Improving treatment planning, and monitoring in the field of digital orthodontics