Media

Loss of permanent teeth is usually caused by dental diseases or trauma and is common in the global population, especially among the elderly due to aging and relatively poorer oral health.

Failure to replace a missing tooth not only affects facial aesthetic and chewing function, but it may also lead to jawbone loss and shifting to teeth, which may cause malocclusion and bite irregularities that could have a significant impact on the health of the remaining teeth, gums, jaw muscles and jaw points.

Artificial teeth, also known as bridges and dentures, are prosthetic devices used to replace missing teeth. It is essential for the false teeth to resemble the patient’s original tooth so that the patient can retain his or her original appearance, chewing function, oral and physical health.

Currently, the process of designing and creating dentures is highly time-consuming as the existing computerised design process requires tedious manual inputs, teeth occlusion information collection as well as multiple denture fitting procedures due to limited accuracy of exciting technologies.

Researchers from the Faculty of Dentistry at the University of Hong Kong (HKU) and the Department of Computer Science of Chu Hai College of Higher Education, collaborated to develop a new approach using artificial intelligence to automate the design of individualised dentures, in order to enhance the treatment efficiency and improve patient experience.

The AI technology used in the process was based on 3D Generative Adversarial Network (3D-GAN) algorithm and tested on 175 participants recruited at HKU. The study shows that AI technology could reconstruct the shape of a natural healthy tooth and automate the process of false teeth design with high accuracy.

“The 3D GAN algorithm was selected due to its superior performance on 3D object reconstruction compared to other AI algorithms. In the preliminary study, 3D GAN was able to rebuild similar shapes to the original teeth for 60% of the cases. It is expected to mature with more AI training data,” co-Investigator, Dr Reinhard Chau explained.

The new approach only requires the digital model of a patient’s dentition to function. It can learn the features of an individual’s teeth from the rest of the dentition and generate a false tooth that looks like the missing tooth.

“This will facilitate the treatment workflow for dentists in replacing a missing tooth, as the preparation and fitting process will require minimal time, and a patient will not need to stay at the clinic for long hours,” said Principal Investigator Dr Walter Lam.

The study entitled “Artificial intelligence-designed single molar dental prostheses: A protocol of prospective experimental study” is published in the journal PLoS ONE. The preliminary results of the study were presented in the recent International Association of Dental Research (IADR) General Session. The study won the IADR Neal Garrett Clinical Research Prize and First runner-up in the 2022 IADR-SEA Hatton Award - Senior Category.

The research team members
HKU Faculty of Dentistry
Principal Investigator: Dr Walter Lam, Clinical Assistant Professor in Prosthodontics and Founding Member of HKU Musketeers Foundation Institute of Data Science
Co-investigators:
- Dr Reinhard Chau, Research Assistant in Restorative Dental Sciences and Applied Oral Sciences & Community Dental Care
- Professor Colman McGrath, Clinical Professor in Dental Public Health
- Dr Khaing Myat Thu, Senior Research Assistant in Restorative Dental Sciences

Chu Hai College of Higher Education
Co-investigator:
Professor Richard Hsung, Associate Professor in Department of Computer Science

The Journal “Artificial intelligence-designed single molar dental prostheses: A protocol of prospective experimental study”:
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0268535

For media enquiries:
Ms Melody Tang, Senior Communications Officer of the Faculty of Dentistry, HKU,
Tel: 2859 0494 / 9155 0980, Email: melodytang@hku.hk