Korea: To achieve successful restorations, abutment tooth preparation in prosthodontics must adhere to fundamental principles, ensuring adequate reduction and structural stability.
In dental education, consistent and accurate feedback is crucial for students’ clinical improvement. Conventional evaluation methods, reliant on visual inspection, can lead to inconsistencies in grading.
To address this, researchers from Seoul National University, in collaboration with dental faculties in the University of Washington (USA) and University of Bern (Switzerland) developed a human-based digitally assisted evaluation (DAE) system using 3D inspection and metrology software, which has shown promise in improving consistency.
However, limitations remain, prompting researchers and software engineers to develop a novel software-based approach called Software-Based Automated Evaluation (SAE) utilizing computational geometric algorithms.
Purpose and Hypotheses of the Study
The study aimed to propose the concept of SAE for tooth preparation quality assessment and assess its feasibility by comparing it with the human-based DAE. The null hypotheses were that there would be no differences in intra-rater agreement between SAE and DAE and no differences in the scores graded by the two methods.
Results: Robust Operation and Evaluation Criteria
The SAE demonstrated robust operation for all prepared teeth, successfully assessing occlusal reduction and total occlusal convergence. The average amount of occlusal reduction at different cusps ranged from approximately 1.39 mm to 1.88 mm, while the average values of total occlusal convergence were reported as 26.44° in the mesiodistal plane and 18.60° in the buccolingual plane.
The preparation margin area’s average width was measured at 0.36 mm. The SAE assessment showed complete agreement with the results.
Potential Advancement in Dental Evaluation
The software-based automated evaluation (SAE) approach for tooth preparation evaluation offers a promising method for dental education and clinical skill feedback.
With perfect intra-rater agreement and almost perfect inter-rater agreement, SAE demonstrates potential to provide more reliable and precise assessments compared to the human-based digitally assisted evaluation (DAE).
By minimizing possible errors and discrepancies in conventional rating, SAE could play a vital role in improving dental education and enhancing the quality of dental restorations. Further research and implementation are necessary to fully explore the potential benefits of this innovative software-based assessment in the field of dentistry.
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