A Robotic System for Implant Modification in Single-stage Cranioplasty
This addresses the need for more precise and efficient implant modification in craniomaxillofacial surgery, offering a domain-specific incremental improvement over current practices.
The paper tackles the problem of inaccurate and time-consuming manual resizing of craniofacial implants during single-stage cranioplasty by introducing a robotic system that uses 3D scanning and automated cutting to determine and modify implant contours intraoperatively, resulting in a 56% improvement in accuracy over manual methods and 42% over an existing projection technique.
Craniomaxillofacial reconstruction with patient-specific customized craniofacial implants (CCIs) is most commonly performed for large-sized skeletal defects. Because the exact size of skull resection may not be known prior to the surgery, in the single-stage cranioplasty, a large CCI is prefabricated and resized intraoperatively with a manual-cutting process provided by a surgeon. The manual resizing, however, may be inaccurate and significantly add to the operating time. This paper introduces a fast and non-contact approach for intraoperatively determining the exact contour of the skull resection and automatically resizing the implant to fit the resection area. Our approach includes four steps: First, a patient's defect information is acquired by a 3D scanner. Second, the scanned defect is aligned to the CCI by registering the scanned defect to the reconstructed CT model. Third, a cutting toolpath is generated from the contour of the scanned defect. Lastly, the large CCI is resized by a cutting robot to fit the resection area according to the given toolpath. To evaluate the resizing performance of our method, six different resection shapes were used in the cutting experiments. We compared the performance of our method to the performances of surgeon's manual resizing and an existing technique which collects the defect contour with an optical tracking system and projects the contour on the CCI to guide the manual modification. The results show that our proposed method improves the resizing accuracy by 56% compared to the surgeon's manual modification and 42% compared to the projection method.