Journal of dentistry · 2024
Occlusal caries detection and monitoring using a 3D intraoral scanner system. An in vivo assessment.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
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Michou Stavroula, Tsakanikou Angeliki, Bakhshandeh Azam, Ekstrand Kim R, Rahiotis Christos, Benetti Ana R
Аннотация
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.
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.