Background and Objectives: With the goal of identifying regions with bicortical bone and avoiding root contact, the present study proposes an innovative technique for the simulation of the insertion of mini orthodontic implants using automatic jaw segmentation. The simulation of mini implants takes place in 3D rendering visualization instead of Multi-Planar Reconstruction (MPR) sections. Materials and Methods: The procedure involves utilizing software that automatically segments the jaw, teeth, and implants, ensuring their visibility in 3D rendering images. These segmented files are utilized as study models to determine the optimum location for simulating orthodontic implants, in particular locations characterized by limited distances between the implant and the roots, as well as locations where the bicortical structures are present. Results: By using this method, we were able to simulate the insertion of mini implants in the maxilla by applying two cumulative requirements: the implant tip needs to be positioned in a bicortical area, and it needs to be situated more than 0.6 mm away from the neighboring teeth’s roots along all of their axes. Additionally, it is possible to replicate the positioning of the mini implant in order to distalize the molars in the mandible while avoiding the mandibular canal and the path of molar migration. Conclusions: The utilization of automated segmentation and visualization techniques in 3D rendering enhances safety measures during the simulation and insertion of orthodontic mini implants, increasing the insertion precision and providing an advantage in the identification of bicortical structures, increasing their stability.

Background/Objectives: Pterygoid implant placement represents a valuable alternative to conventional bone grafting procedures in the rehabilitation of the atrophic posterior maxilla; however, the procedure remains technically demanding because of limited visibility, difficult access, complex pterygomaxillary anatomy, and the need for precise angulation and distal bicortical anchorage. Although digital guidance has increasingly been applied in implant dentistry, a clearly described workflow integrating automatic segmentation, selective virtual trimming of the posterior maxillary anatomy, and direct three-dimensional planning for static-guided pterygoid implant placement remains insufficiently detailed in the literature. The aim of this report was to describe and illustrate such a workflow in a proof-of-concept clinical application. Methods: This work was designed as a methodological proof-of-concept with a single clinical illustration. A CBCT dataset was imported into BlueSkyPlan, where automatic segmentation was used to generate three-dimensional models of the maxilla, teeth, and pterygoid process. The segmented volumes were then selectively trimmed to expose the relevant pterygomaxillary anatomy and to support direct three-dimensional planning of the implant axis in the rendered model. A static surgical guide with combined tooth and mucosal support was subsequently designed, positioned on a printed jaw model derived from the intraoral scan, and assessed by CBCT-based internal verification. Results: In this proof-of-concept application, the workflow enabled three-dimensional visualization of the pterygomaxillary trajectory, supported implant axis planning in the rendered model, and facilitated guide design and radiographic verification of the planned trajectory. The verification step provided an internal methodological consistency check between the planned implant axis and the drill-guided direction visible on CBCT. Conclusions: The present report describes a segmentation-assisted three-dimensional planning workflow for static-guided pterygoid implant placement in a single proof-of-concept clinical application. The workflow should be interpreted as a methodological illustration rather than a quantitative validation study. Further investigations are required to evaluate accuracy, inter-operator reproducibility, and broader clinical applicability.

Background/Objectives: Implant placement in transnasal and paranasal regions of the severely atrophic maxilla is challenged by complex anatomy and proximity to critical structures, particularly the nasolacrimal duct (NLD). While cortical anchorage is considered important for implant stability, structured methods for evaluating anatomical eligibility and anatomical risk during planning remain limited. This proof-of-concept study aimed to describe a segmentation-assisted workflow for anatomical assessment of potential paranasal implant trajectories. Methods: A single-case proof-of-concept workflow was developed using CBCT imaging and multi-component anatomical bone segmentation (MCABS). Segmented anatomical structures were used to selectively visualize cortical pathways within the anterior maxilla. Implant planning was performed using axial, non-tilted trajectories. Particular attention was directed toward visualization of the spatial relationship between the planned implant pathway and the nasolacrimal duct. Workflow feasibility was further explored through study-model fabrication, guided implant insertion, and axis-based verification. Results: The proposed workflow enabled selective visualization of cortical structures and facilitated identification of anatomically favorable implant trajectories within the paranasal region. The relationship between the planned implant pathway and the nasolacrimal duct could be directly assessed using the segmented anatomical model. Guided insertion in the study model demonstrated concordance between planned and executed implant axes, supporting the technical feasibility of the workflow. Conclusions: Within the limitations of a single-case proof-of-concept study, the proposed segmentation-assisted workflow may contribute to preoperative anatomical assessment of potential paranasal implant trajectories and their relationship to adjacent anatomical structures. The workflow should be regarded as a methodological demonstration rather than a validated clinical protocol. Further anatomical, reproducibility, biomechanical, and clinical studies are required before broader clinical adoption can be considered.