Endocrown-based restoration of a structurally compromised tooth using additive manufacturing in a fully digital workflow: A case report

Introduction: The rapid advancement of digital technologies in dentistry has facilitated the effective integration of CAD/CAM systems into restorative treatment protocols. These systems enable both subtractive and additive manufacturing methods to be incorporated into clinical workflows. Endocrowns, preferred for restoring endodontically treated teeth with compromised structural integrity, offer significant advantages in terms of precision and time efficiency when digitally planned and fabricated. Case Description: A 33-year-old male patient presented to the clinic with complaints of acute dental pain. Clinical and radiographic evaluations revealed deep dentinal caries and extensive coronal substance loss in the affected tooth, for which endodontic treatment was indicated. Following root canal therapy, an endocrown restoration was selected to preserve the remaining tooth structure and restore functional integrity. The treatment was carried out entirely using a digital workflow. An intraoral scanner (TRIOS® 3 Color, 3Shape, Denmark) was used to capture the digital impression. The restoration was designed using CAD software (Exocad, Germany) and subsequently fabricated using additive manufacturing technology with a 3D printer (Asiga MAX, Australia) and high-precision dental resin. The restoration was cemented using adhesive techniques in a clinical setting. Discussion: Endocrowns fabricated through a fully digital workflow demonstrate superior accuracy, workflow standardization, and time efficiency compared to conventional methods. Additive manufacturing enables the precise production of complex morphologies, eliminates the need for physical models, reduces material waste, and enhances cost-effectiveness. These restorations exhibit high clinical compatibility and improve patient comfort while reducing operator dependency during production. However, limitations such as high system acquisition costs, the need for technical proficiency, and limited long-term clinical data must be considered for widespread adoption.