Comparative Evaluation of the Internal and Marginal Fit of Dental Crowns Designed Using Cad and Ai-Based Software

Abstract

Introduction: Zirconia crowns are becoming increasingly popular in dentistry, primarily because they offer exceptional strength, an appealing appearance, and good biocompatibility. While traditional CAD software helps with crown design, it often requires a great deal of manual tweaking. Recently, artificial intelligence (AI) has emerged as a game-changer in this field, providing automated design capabilities that promise to enhance precision and minimize the need for human input.

Aim: This study set out to compare the fit of zirconia crowns designed using AI-based software (Dentbird) with those created using conventional CAD software (Exocad).

 Materials and Methods: We included ten patients who needed single crowns for their lower molars. Digital impressions were taken, and crowns were designed using both AI and traditional CAD systems. To evaluate the fit, we used a triple-scan protocol and analyzed the results with Geomagic Control X. We performed statistical analysis using SPSS version 21.

Results: The crowns designed with AI software showed a noticeably better fit, both internally and at the margins, compared to those made with conventional CAD software. This improvement was particularly significant in the buccal and distal regions (p < 0.005).

Conclusion: The findings highlight that AI-based crown design software outperformed traditional CAD methods in achieving a better fit. This suggests that AI could significantly enhance clinical accuracy and make digital workflows in prosthodontics more efficient.