Tooth morphology, internal fit, occlusion, and proximal contacts of dental crowns designed by deep learning-based dental software: A comparative study.

Cho, Jun-Ho; Çakmak, Gülce; Yi, Yuseung; Yoon, Hyung-In; Yilmaz, Burak; Schimmel, Martin (2024). Tooth morphology, internal fit, occlusion, and proximal contacts of dental crowns designed by deep learning-based dental software: A comparative study. Journal of dentistry, 141(104830), p. 104830. Elsevier Science 10.1016/j.jdent.2023.104830

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OBJECTIVES

This study compared the tooth morphology, internal fit, occlusion, and proximal contact of dental crowns automatically generated via two deep learning (DL)-based dental software systems with those manually designed by an experience dental technician using conventional software.

METHODS

Thirty partial arch scans of prepared posterior teeth were used. The crowns were designed using two DL-based methods (AA and AD) and a technician-based method (NC). The crown design outcomes were three-dimensionally compared, focusing on tooth morphology, internal fit, occlusion, and proximal contacts, by calculating the geometric relationship. Statistical analysis utilized the independent t-test, Mann-Whitney test, one-way ANOVA, and Kruskal-Wallis test with post hoc pairwise comparisons (α=.05).

RESULTS

The AA and AD groups, with the NC group as a reference, exhibited no significant tooth morphology discrepancies across entire external or occlusal surfaces. The AD group exhibited higher root mean square and positive average values on the axial surface (P<0.05). The AD and NC groups exhibited a better internal fit than the AA group (P<.001). The cusp angles were similar across all groups (P=.065). The NC group yielded more occlusal contact points than the AD group (P=.006). Occlusal and proximal contact intensities varied among the groups (both P<.001).

CONCLUSIONS

Crowns designed by using both DL-based software programs exhibited similar morphologies on the occlusal and axial surfaces; however, they differed in internal fit, occlusion, and proximal contact. Their overall performance was clinically comparable to that of the technician-based method in terms of the internal fit and number of occlusal contact points.

CLINICAL SIGNIFICANCE

DL-based dental software for crown design can streamline the digital workflow in restorative dentistry, ensuring clinically-acceptable outcomes on tooth morphology, internal fit, occlusion, and proximal contact. It can minimize the necessity of additional design optimization by dental technician.

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