Dr. Donald Alton Tyndall, DDS, MSPH, PhD, ABOMR, FICD
Dr. Don Tyndall is Professor in the Division of Diagnostic Sciences at the UNC Adams School of Dentistry. Dr. Tyndall graduated from UNC-CH in 1973 with majors in Biology and Ancient History. He received his D.D.S. in 1980 from the UNC School of Dentistry, his M.S.P.H. in Environmental Sciences and Engineering in 1984 specializing in Health Physics and his Ph.D. in 1988 in Health Physics from the UNC Gillings School of Global Public Health.
Dr. Tyndall was the Director of Radiology for the School of Dentistry from 1988 to 2019. He was the creator of the UNC Adams School of Dentistry’s graduate program in Oral and Maxillofacial Radiology and served as its director from 1993-2006. Currently he is serving as Director of the Oral & Maxillofacial Radiology Predoctoral Program. He is a Diplomate of the American Board of Oral and Maxillofacial Radiology and was a Director and past President from 1995-1999. Dr. Tyndall has twice served as the Councillor for Scientific Affairs and Public Policy on the Executive Council of the American Academy of Oral and Maxillofacial Radiology (AAOMR). From 2000-2006 he served on the Radiology Review Committee of the Commission on Dental Accreditation. Dr. Tyndall served as President of the AAOMR in 2022-2023. In addition, he is a Fellow in the International College of Dentists and the American College of Dentists.
Dr. Tyndall currently serves on the Editorial Board of the Journal of the American Dental Association and is a member of the Journal of Endodontics Scientific Advisory Board as an expert in artificial Intelligence. He has also served as consultant to several dental imaging companies specializing in artificial intelligence, dental MRI, and intraoral tomosynthesis.
His research interests include artificial intelligence for radiologic diagnosis in 2D and 3D imaging, development of a novel multisource carbon nanotube x-ray system for cone beam CT units, 2D and 3D caries detection, applications of CBCT, MRI and stationary intraoral tomosynthesis (sIOT) in dentistry. His work as author or co-author has been published in over 130 journal articles.
This presentation will be focused towards endodontics. It will review current technologies and how to best use them in endodontics. It will also provide information, on four emerging technologies: Artificial intelligence using convolutional neural networks, dedicated dental MRI (ddMRI), stationary intraoral tomosynthesis (sIOT) and second generation 2CBCT sources.
Artificial Intelligence : Attention will be given to the role of AI as an adjunctive technology for the interpretation of 2D and 3D images. The discussion will center on “How good is AI?” and “How much does AI help?” An update on the current state of AI as applied to 2D and 3D imaging will be offered.
DdMRI: DdMRI refers to MRI systems developed exclusively for dental and maxillofacial purposes. Potential ddMRI applications will be presented along with the current state of ddMRI will with example images.
sIOT: SIOT is designed to overcome limitations in intraoral radiography using a novel multisource intraoral system based on CNT technology relatively free of metal artifacts and overlapping. SIOT technology will be addressed along with applications and examples.
Second Generation CBCT Sources: Work on a second generation CBCT x-ray source is underway using multiple CNT arrays and multispectral imaging. Potential improvements include, true HU, reduced metal artifacts and improved soft tissue contrast. Second generation CBCT source technology will be presented along with sample images.
At the end of this course the participant should be able to:
1. Discuss the advantages of AI as applied to 2D and 3D radiologic interpretation.
2. List potential applications of ddMRI for the interpretation of dentoalveolar and maxillofacial disease and abnormalities.
3. Describe sIOT technology and potential improvements over conventional intraoral imaging.
4. List the technological changes in second generation CBCT x-ray sources and potential improvements over current CBCT systems