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Detecting early erosive tooth wear using an intraoral scanner system. | LitMetric
Objectives : To assess the feasibility of detecting and monitoring early erosive tooth wear using a 3D intraoral scanner (IOS) aided by specific software.Methods : Extracted sound permanent teeth were assembled in two shortened artificial dental arches and scanned at different intervals with an IOS (3Shape TRIOS® 3) before and after an erosion/abrasion protocol (i.e. 1 h up to 24 h immersion in citric acid solution and subsequent brushing). The 3D models obtained at consecutive time points were superimposed with the baseline model using dedicated software (3Shape TRIOS® Patient Monitoring, version 2.1.1.0) and reference surface alignment. Surface profile differences between the baseline 3D model and the respective models from different time points were expressed as tooth substance loss. Non-parametric tests were used to assess the significance of tooth substance loss at different time points. Spearman's correlation was applied between the tooth substance loss at the end of each erosion/abrasion cycle and the immersion time in acid.Results : Significant tooth substance loss (0.08 mm, IQR = 0.05) was detected by the software after 3 h of erosive-abrasive challenge (p = 0.045). The overall median loss increased gradually from baseline to 24 h showing a strong correlation with the immersion time in acid (r = 0.971, p < 0.01).Conclusions : The use of an IOS aided by specific software showed good performance for early detection and monitoring of tooth wear in vitro and has promising potential for in vivo application.Clinical Significance : Detection and monitoring of early erosive tooth wear can be reliably aided by intraoral scanning supported by specific software. The measurement error and uncertainty involved in this method should be taken into consideration when interpreting the tooth substance loss measurements. Furthermore, presuming the difficulty in defining reference surfaces in vivo, clinical validation is needed to determine the system's in vivo performance.
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