The future of early childhood tooth decay detection?
Could 3D AI technology pave the way for significantly faster and more accessible care.
Cutting-edge 3D AI technology can identify early childhood tooth decay as accurately as visual exams, paving the way for significantly faster and more accessible care, according to a new study.
The research, led by the Murdoch Children’s Research Institute (MCRI) and the University of Melbourne, has shown how a scanner – resembling an enlarged electric toothbrush – paired with AI-assisted software, provides a thorough picture of children’s dental health within minutes.
The hand-held, wireless intraoral scanner (IOS) shines a fluorescence light onto the teeth and gums and a tiny camera records how that light reflects back. AI software then pieces the images together to create a detailed 3D model of the mouth. The images can be saved and reviewed either in person or remotely.
The study involved 216 children, aged five, recruited from the Melbourne Infant Study: BCG for Allergy and Infection Reduction (MIS BAIR). The researchers compared their traditional dental exams against the enhanced technology. The research, published in JMIR Public Health and Surveillance, found 38% of children showed signs of dental decay and 18% had enamel defects in both visual and digital scans.
Associate Professor Mihiri Silva said the findings would fill a significant knowledge gap in paediatric dentistry. “It’s crucial to examine baby teeth as they are a key predicator of future health outcomes,” she said.
“Visual examinations are the gold standard in dental care, but we need to find new ways to better detect tooth decay as soon as early signs of decay occur. We wanted to test this 3D technology in children because digital images can open up more tools to prevent decay and monitor changes in plaque buildup.”
MCRI researcher Dr Bree Jones said the team found the digital technology was just as precise at detecting early signs of dental damage as visual check-ups and could compliment current tools. “Intraoral scanners capture thousands of images of the teeth, which AI stitches into a 3D model of the mouth – like assembling a jigsaw puzzle to reveal the whole picture,” she said.
“The 3D AI technology could provide more comprehensive dental assessments for children who are only able to tolerate a brief or limited time at the dentist, helping to avoid fillings. It may also be helpful to parents trying to visualise their children’s dental results and treatment plans and those living in low resource or remote areas with limited access to services.”
Associate Professor Silva’s team is also leading Infant2Child, a long-term study that aims to improve dental health in the first 2,000 days of life.
“We are looking at how we can support prevention in early childhood because parents have told us that they value practical, evidence-based advice, which will be key to promoting good oral health throughout a person’s life,” she said. “We want children to establish good habits early to ultimately keep teeth healthy so children can thrive, and also save families and our healthcare system money.”
The 3D imagery for the study was captured using the TRIOS 4 intraoral scanner (IOS) from developer and manufacturer 3Shape.
Comments are closed here.