Occlusal caries detection and monitoring using a 3D intraoral scanner system. An in vivo assessment.

OBJECTIVE

To assess the agreement in detecting and monitoring occlusal caries over thirty months using conventional visual and radiographic assessment and an intraoral scanner system which supports automated caries scoring.

METHODS

Ninety-one young participants aged 12-19 years were included in the study. All occlusal surfaces were examined visually, radiographically (when indicated), and scanned with the TRIOS 4 intraoral scanner. TRIOS Patient Monitoring software (vers. 2.3, 3Shape TRIOS A/S, Denmark) was used for automated caries detection on the 3D digital models.

RESULTS

Fifty-five of the study participants were re-examined after 30-months. Significant differences regarding caries detection were found between the conventional methods and the automated caries scoring system (p < 0.01), with moderate positive percent agreement (49-61%) and high negative percent agreement (87-98%). All methods reported significant caries progression over the follow-up period (p < 0.01). However, the automated system showed significantly more caries progression than the other methods (p < 0.01).

CONCLUSIONS

The software for automated caries detection and classification showed moderate positive agreement and strong negative agreement with the conventional methods considering both the baseline and the follow-up assessments. The automated caries scoring system detected significantly fewer caries lesions and tended to underestimate the caries severity. All methods indicated significant caries progression over the follow-up period, while the automated system detected more caries progression.

CLINICAL SIGNIFICANCE: The TRIOS system supporting automated occlusal caries detection and classification can assist in detecting and monitoring occlusal caries on permanent teeth as a complementary tool to the conventional methods. However, the operator should be aware that the automated system shows a tendency to underestimate the caries presence and lesion severity.