JMIR Publications

ABSTRACT

Advancements in technology have transformed dentistry, particularly through innovations in computer-aided manufacturing (CAM) and three-dimensional (3D) digital production systems. The correctness of zirconia crown’s marginal and internal fit is crucial to their durability and clinical function. Traditionally, these crowns have been designed using computer-aided design and manufacturing (CAD-CAM) software. However, the introduction of Artificial Intelligence (AI) software offers a potential alternative that may provide more precision and efficiency. By evaluating the performance of AI-driven CAD software against traditional CAD-CAM software, this study aims to provide valuable insights into their effectiveness in producing well-fitting zirconia crowns. Understanding these differences is crucial for dental practitioners to make informed decisions about the best tools to use for creating high-quality prosthetics, ultimately improving patient outcomes. 1. The study will include patients who need zirconia crowns. 2. Mandibular first molars are chosen as the sample teeth due to their typical complexity and variability in preparation. 3. Tooth Preparation: Standardized tooth preparation protocols will be followed to ensure uniformity in preparation dimensions and characteristics across all samples. 4. One crown will be fabricated using AI software and the other with CAD-CAM software. Micro-CT scans and clinical assessments were used to evaluate the crown's marginal and internal fits. 5. Measurements of marginal fit (gap between crown margin and prepared tooth) and internal fit (adaptation of crown to tooth structure) are quantitatively analyzed using specialized software. These measurements are taken at multiple points around the crown margin and within the internal surface to determine precise deviations in micrometers or other appropriate units. The study will investigate and compare the marginal fit and internal fit of zirconia crowns designed using artificial intelligence software versus CAD-CAM software in the field of dental prosthetics. This research will specifically examine commonly used AI software and traditional CAD-CAM software systems deployed in dental laboratories. The study will employ rigorous quantitative methods to measure and evaluate the MF and internal fit of the crowns, utilizing standardized protocols for accuracy and consistency in assessment. Additionally, the scope encompasses an analysis of production workflows associated with each software type, aiming to uncover differences in efficiency and process complexity. Factors such as error rates during design and manufacturing processes, as well as a comprehensive cost-effectiveness assessment, will also be explored.