Prof. Ziad Salameh
DDS, MSc, PhD, FICD
• Specialist in Prosthodontics and expert in dental biomaterials and digital dentistry, holding a DDS, Master’s degrees, and a PhD
in Biomaterials from Saint Joseph University and the University of Siena.
• Professor at the Lebanese University, Director of the Research Center and the Center of Excellence in “3D Printing, Digitalization
& AI”.
• Visiting Professor at the University of Siena and Gulf Medical University (UAE), with more than 85 PubMed-indexed scientific
publications.
• Ambassador and Board Member of the Digital Dentistry Society, and an international speaker in digital prosthodontics and
advanced dental technologies.
Mira Orabi, Karin Simonian
Introduction
Introduction
The integration of digital technologies into prosthetic and restorative dentistry has profoundly transformed contemporary clinical workflows. Recent developments in intraoral scanning, CAD/CAM systems, additive manufacturing, and adhesive protocols have enhanced the precision, efficiency, and predictability of restorative rehabilitation while minimizing material waste [1]. More recently, artificial intelligence (AI) has emerged as a promising innovation and a cornerstone within digital dentistry, it has shifted the CAD systems into higher design quality while reducing fabrication time [1].
Usually, conventional CAD software workflows require extensive manual intervention from the dental technicians or clinicians to optimize marginal detection, occlusal morphology, and proximal contacts [2]. Although these conventional workflows have remarkable flexibility and customization, the workflow remains highly operator-dependent and can often be time consuming [3].
Nowadays, AI assisted CAD platforms aim to simplify and accelerate restorative design by automating various stages of the digital workflow. They have the potential to automatically detect the margins, generate anatomically coherent restorations by thorough analysis of the adjacent and opposing dentition. The integration of generative AI has reduced the need for manual modifications and operator intervention thus improving efficiency and predictability [4].
Artificial Intelligence has been the foundation for some CAD software, like Atomica and Dentbird. With AI, the design process has been significantly improved in terms of time, quality and overall outcome. In addition, DentalTwin has introduced a new concept in digital dentistry based on full automation in AI based designs. With their new product released, DentaBridge, definitive crown and bridge design is now possible under few clicks in a limited period of time [5].
This clinical case describes a fully digital workflow involving the fabrication of a 3D-printed custom post-and-core, posterior onlay, and definitive crowns, integrating Dentabridge from DentalTwin for the design of the definitive crown restorations.
Case Description
Case Description
A patient presented with esthetic concerns related to discoloration of the maxillary left central incisor, in addition to functional concerns involving posterior teeth. Clinical examination revealed pulpal necrosis of tooth 21, extensive coronal tooth structure loss in tooth 25 with vital pulp tissue, and a favorable amount of remaining tooth structure in tooth 26 that had previously undergone endodontic treatment (Fig. 1A, B).
Clinincal Case
Clinical Case
The treatment plan involved endodontic treatment for tooth 21 and 25, followed by 3D printed custom post-and-core and full-coverage crowns with a 3D printed onlay restoration for tooth 26. Intracanal preparation was performed for teeth 21 and 25 to receive custom post-and-core restorations.
A size 000 retraction cord was placed to deflect the soft tissues, and an intraoral scan was taken (Primescan Connect, Dentsply Sirona, Germany) (Fig. 2, 3).
The generated STL files were imported into CAD software (exocad DentalCAD, Darmstadt, Germany), where the design for the custom post and core was carried out for teeth 21 and 25 and design for onlay for tooth 26 (Fig. 4).
The restorations were fabricated using additive manufacturing technology with a 3D printer (Pro 2, SprintRay, USA) using a hybrid ceramic material (Ceramic Crown, SprintRay, USA) (Fig. 5-7).
Adhesive cementation protocol was carried out for the post and core and onlay by applying a silane coupling agent (Bis-Silane, Bisco, USA) on the fitting surface of the restorations. Tooth surfaces were treated using a phosphoric acid 35% (Select HV ETCH, Bisco) for 15 seconds, rinsed thoroughly for 1 min then dried with air and paper points, then bonding agent was applied (All-Bond Universal, Bisco) and light cured (Valo X, Ultradent, USA) for 20 seconds. The post and cores and the onlay were subsequently cemented using dual-cure resin cement (Duolink, Bisco) under adhesive isolation protocols (Fig. 8).
After post and core placement for teeth 21 and 25, completion of the definitive tooth preparation was carried out, and a second digital scan was acquired (Primescan, Dentsply Sirona) (Fig. 9).
The STL files were imported into both Exocad (exocad DentalCAD) and DentalTwin (DentalTwin, Kombo Medical Solutions, Germany) software platforms for the design of the definitive crowns.
With Exocad, margin detection and refinement of the design were performed manually, requiring multiple adjustments to optimize proximal contacts, occlusion, marginal adaptation, and emergence profile. For DentalTwin designs, the STL files were uploaded to DentaBridge portal followed by teeth selection. The design parameters were set, and the restoration type was defined. The definitive crown designs were generated within approximately 8 minutes through a fully AI-automated workflow, requiring no adjustments from the operator (Fig. 10). The designs obtained from both platforms are showed in figure 11.
The definitive restorations obtained from DentalTwin platform were then fabricated using a 3D printer (Pro 2, SprintRay) with a hybrid ceramic material (Ceramic Crown, SprintRay) (Fig. 12A). Following post-processing procedures, finishing was performed using polishing instruments (1540, Laboratoy Kit for 3D printed restoration, associate Prof Gülce Cakmak, Jota).
The restorations were sandblasted with 50-µm aluminum oxide particles to enhance micromechanical retention. Extrinsic characterization and staining were carried out using a staining system (Ideas Dentales, Mexico) to achieve harmonious integration with the patient’s natural dentition. Finally, the restorations were polished using a goat-hair wheel (1540, Laboratoy Kit for 3D printed restoration, associate Prof Gülce Cakmak, Jota) to obtain a high-gloss surface finish and optimized esthetic outcome (Fig. 12B).
Clinical try-in demonstrated excellent marginal adaptation and proximal contact accuracy, with only minimal occlusal refinements required prior to definitive cementation. The intaglio surfaces underwent airborne-particle abrasion followed by applying silane coupling agent (Bis-Silane, Bisco). Then, adhesive cementation was performed using dual-cure resin cement (Duolink, Bisco). Final occlusal verification demonstrated functional harmony in both centric and eccentric movements (Fig. 13-15).
Postoperative evaluation revealed excellent esthetic integration, marginal adaptation, and functional rehabilitation within the patient’s natural dentition.
Discussion
Discussion
The evolution of digital dentistry has progressively shifted restorative workflows toward greater automation, precision, and efficiency. In the present clinical case, full automation of AI-based CAD Software (DentaBridge) demonstrated significant advantages during the definitive restorative design phase by enabling rapid AI-powered generation of anatomically coherent restorations with minimal manual intervention.
Compared with conventional CAD workflows, the AI-based software reduced design time while maintaining accurate proximal contacts, occlusal integration, and esthetic harmony.
A major strength of DentaBridge was its ability to analyze the surrounding dentition and automatically generate anatomically adapted restorations, minimizing repeated manual modifications. Clinically, the restorations demonstrated excellent fit during try-in and required minimal chairside adjustment before cementation. Integrated within a fully digital pipeline — from intraoral scanning through additive manufacturing and characterization — DentaBridge highlighted the capacity of AI-powered CAD systems to streamline restorative procedures, reduce operator-dependent variability, and enhance the efficiency and predictability of contemporary digital prosthodontics.
“DentaBridge highlighted the capacity of AI-powered CAD systems to enhance the efficiency and predictability of contemporary digital prosthodontics.”
Conclusion
Conclusion
Automated AI-powered CAD platforms will provide a seamless process for daily clinical routines. Such workflow plays a critical role in decreasing operator involvement in the designing procedure, while ensuring precision and high quality, bringing chairside dentistry to a new standard.
References
1) Wang Y, Li Y, Xu M, Liu F. Comparative analysis of full crown morphology designed by arti-ficial intelligence and dental technicians. J Dent. 2025 Dec;163:106131. doi: 10.1016/j.jdent.2025.106131. Epub 2025 Sep 23. PMID: 40998103.
2) Dönmez MB, Demirel M, Diken Türksayar AA, Yilmaz B. Influence of printing parameters on the fabrication and fit accuracy of additively manufactured resin-based definitive three-unit fixed partial dentures. J Dent. 2025 Oct;161:105937. doi: 10.1016/j.jdent.2025.105937. Epub 2025 Jun 25. PMID: 40578787.
3) Kong HJ, Kim YL: Application of artificial intelligence in dental crown prosthesis: a scoping review. BMC Oral Health. 2024, 24:937.
4) Al Hendi KD, Alyami MH, Alkahtany M, Dwivedi A, Alsaqour HG. Artificial intelligence in prosthodontics. Bioinformation. 2024 Mar 31;20(3):238.
5) Shu Z, Tian M, Wei H. AI-driven crown generation: A comparative analysis of point cloud completion models for mandibular first molar restoration. J Dent. 2026 May;168:106581. doi: 10.1016/j.jdent.2026.106581. Epub 2026 Feb 16. PMID: 41707826.