A new AI system is redefining the prediction and prevention of childhood caries.
Jointly developed by the Faculty of Dentistry of the University of Hong Kong, the Chinese Academy of Sciences, Qingdao Stomatological Hospital and Qingdao Women and Children’s Hospital, the AI ??system “Spatial-MiC” successfully achieved high-precision prediction of the risk of early childhood caries (ECC) by analyzing the microbial characteristics of each tooth.
The prediction accuracy was as high as 93% two months before symptoms appeared, and the current caries detection accuracy was as high as 98%.
The uniqueness of this system lies in that it breaks through the traditional method of uniform evaluation of the entire mouth of teeth, but goes deep into the microbial ecosystem of a single tooth to identify its unique bacterial combination and change trend.
In a nearly one-year study, the researchers collected a total of 2,504 dental plaque samples from 89 children aged 3 to 5 years, and combined 16S rRNA sequencing and shotgun metagenomics technology to deeply describe the microbial composition and functional characteristics of different tooth positions.
The study found that in a healthy mouth, there is a stable microbial gradient from front to back of the teeth, and different areas support different bacterial communities due to factors such as saliva flow and tooth anatomical structure.
In the early stages of caries development, this natural balance is broken, and the bacterial flora of the front teeth may migrate to the back teeth, and vice versa, and this migration often occurs before clinical symptoms appear.
The breakthrough of Spatial-MiC lies in its “spatial perception modeling” capability. The system not only evaluates the microbial information of the target tooth, but also integrates it with the microbial environment of the surrounding teeth for analysis, thereby making more accurate situational predictions.
This approach is significantly better than traditional risk assessment tools, making preventive interventions more refined and personalized.
This achievement is of great significance to public health. About 70% of five-year-old children in China are affected by early caries, which not only causes pain and infection, but also may affect children’s nutritional intake and language development.
At present, most dental interventions adopt a “unified strategy” and lack the fine identification of risks of a single tooth.
The emergence of Spatial-MiC provides technical support for “policy according to teeth”, which may completely change the preventive dental care model.
In the future, the research team plans to further expand the scope of system verification and explore the applicability of different populations and regions.
At the same time, they are also developing point-of-care diagnostic devices that can be integrated into dental clinical practice, allowing dentists to obtain microbial data and perform AI risk assessments in real time at the chairside.
By deeply integrating AI technology with microbiology, Spatial-MiC provides an unprecedented and precise tool for children’s oral health care, which is expected to reduce the occurrence of caries, reduce the need for invasive treatment, improve long-term oral health and reduce the burden on the medical system.
This is not only a leap forward in children’s dental technology, but also marks the arrival of a new era of smarter, more proactive and more personalized oral care.