A digital workflow to predict facial aesthetics in patients with maxillofacial trauma with implant retained prostheses

Purpose:To introduce a digital workflow for the prediction of facial aesthetics, especially in patients with dentation deformity caused by maxillofacial trauma.Methods: Cone-beam computed tomography (CBCT) and three-dimensional facial scans of patients with radiographic prostheses were collected. The aforementioned data were uploaded to ProPlan CMF software and merged to generate a virtual patient with craniofacial hard tissue, realistic facial soft tissue, and remaining dentition. The radiographic prostheses were scanned to form a digital cast, which was fitted with its CBCT image to create the virtual prostheses. Postoperative facial soft tissue was simulated according to the movement of the virtual prostheses. An appropriate virtual diagnostic prosthesis plan was selected by the patient and dentist. Subsequently, prosthetically driven implant guide and restoration were designed and fabricated.Conclusions: A virtual patient was successfully constructed. A 4-mm protrusion of the virtual prosthesis was chosen. Subsequently, implant surgery was performed, and dental prostheses were fabricated based on this location. The fusion of the postoperative facial scan and preoperative facial prediction was found to be coincident. This technique can effectively predict facial aesthetic features of patients with maxillofacial trauma, facilitate communication with patients, reduce chairside time, and guide the multidisciplinary design of implant placement and restoration fabrication.