Hany Mohamed Aly Ahmed, Arwa Al-Maswary, Mohamed Habaebi, Abdulkadir Tasdelen, Mohammed AbdullahSalim Al Husaini, Hoda Elnawawy, Muaiyed Mahmoud Buzayan, Noor Azlin Yahya, Aeman Elkezza, Hithem Ahmed, Paul Dummer
{"title":"Artificial Intelligence in the Study of Root and Canal Anatomy: A Comprehensive Review on Applications, Advantages, Challenges and Future Directions.","authors":"Hany Mohamed Aly Ahmed, Arwa Al-Maswary, Mohamed Habaebi, Abdulkadir Tasdelen, Mohammed AbdullahSalim Al Husaini, Hoda Elnawawy, Muaiyed Mahmoud Buzayan, Noor Azlin Yahya, Aeman Elkezza, Hithem Ahmed, Paul Dummer","doi":"10.14744/eej.2025.37232","DOIUrl":null,"url":null,"abstract":"<p><p>A thorough understanding of tooth anatomy is essential for all endodontic therapies. Over the last two decades, technological advances in 3D imaging have revealed the complexities of root and canal anatomy. Recently, artificial intelligence (AI) models have been developed and are being applied to a range of fields within medicine and dentistry. There is an emerging trend for the application of this technology in 2D and 3D imaging tools to study the anatomical features of roots and canals. This narrative review provides a comprehensive analysis of AI applications in the study of root and canal anatomy and their implications for education, research and clinical practice. The analysis reveals that AI applications for the study and teaching of root and canal anatomy are promising; however, more investigations are warranted with larger datasets to provide more accurate deep learning models. Students, researchers and clinicians should understand the inherent limitations of AI data generated from 2D and 3D imaging devices. Future studies are needed to assess what effect deep learning models have on the diagnostic and operative clinical skills of students and dental practitioners when managing teeth with different levels of anatomical complexities.</p>","PeriodicalId":11860,"journal":{"name":"European Endodontic Journal","volume":"10 5","pages":"343-364"},"PeriodicalIF":2.0000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Endodontic Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14744/eej.2025.37232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
A thorough understanding of tooth anatomy is essential for all endodontic therapies. Over the last two decades, technological advances in 3D imaging have revealed the complexities of root and canal anatomy. Recently, artificial intelligence (AI) models have been developed and are being applied to a range of fields within medicine and dentistry. There is an emerging trend for the application of this technology in 2D and 3D imaging tools to study the anatomical features of roots and canals. This narrative review provides a comprehensive analysis of AI applications in the study of root and canal anatomy and their implications for education, research and clinical practice. The analysis reveals that AI applications for the study and teaching of root and canal anatomy are promising; however, more investigations are warranted with larger datasets to provide more accurate deep learning models. Students, researchers and clinicians should understand the inherent limitations of AI data generated from 2D and 3D imaging devices. Future studies are needed to assess what effect deep learning models have on the diagnostic and operative clinical skills of students and dental practitioners when managing teeth with different levels of anatomical complexities.