A Novel Tool to Create Digital Twin Temporal Bone Models for Virtual and 3D-Printing: Proof-of-Concept and Evaluation

OBJECTIVE: To develop a haptic software tool for creating digital twin models for virtual or physical interaction based on cone beam (CB) computed tomography (CT) temporal bone imaging and to evaluate the quality of resulting 3D-printed models. BACKGROUND: Temporal bone surgery involves drilling near critical structures with anatomic variation. Patient-specific models for rehearsal and surgical planning might be clinically valuable but require processing of clinical imaging data into accurate "digital twins". This processing remains a major obstacle to widespread clinical adoption. METHODS: This technical proof-of-concept study utilized clinical CBCT of a cadaver head. The imaging data were processed using the VES-tool, a custom-developed visualization engine that uses haptic interaction for guided processing with tools for segmentation of anatomical structures, hole patching, and cleaning. Resulting digital twins were 3D-printed for mastoidectomy by 2 surgeons. The models were evaluated with the Mowry questionnaire by primary surgeons and, using video-based assessment, by 5 additional experts. RESULTS: The VES-tool was iteratively developed to guide processing into digital twin models with features supporting interactive segmentation. The resulting 3D-printed models were rated at 48 and 50 points by the 2 primary surgeons, respectively, exceeding the established 40-point cutoff for educational benefit. Video-based panelists rated models lower (average 31.8 points), although 3 of 5 scored the models above the modified 30-point cutoff for video-based rating. CONCLUSIONS: VES-tool effectively converts clinical imaging into high-quality digital twins rated as highly useful for surgical practice. This pipeline facilitates patient-specific surgical rehearsal and the creation of diverse anatomic libraries for otosurgical training.