Back to 2025 Abstracts

---

Development and Evaluation of a Cooperative Robotic System for the Bilateral Sagittal Split Osteotomy Using an In-Plane Motion Constraint
Jesse Haworth, MSE ¹; Manish Sahu, PhD ²; Katherine J. Zhu, BS ³; Jacob Hammond ¹, Hisashi Ishida, MS ²; Adnan Munawar, PhD ²;Edgar Soto, MD ³; Robin Yang, MD, DDS ³; Russell H. Taylor, PhD ^2
1Department of Mechanical Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD ² Department of Computer Science, Johns Hopkins University Whiting School of Engineering, Baltimore, MD ³Department of Plastic and Reconstructive Surgery, Johns Hopkins University School of Medicine, Baltimore, MD

Background
In bilateral sagittal split osteotomy (BSSO), there is a high risk of neurosensory disturbance and injury due to the complexity of the anatomical space and limited visualization. Robot-assisted surgery can provide stable, tremor-free control of the surgical tool during the procedure. We aimed to develop and validate a cooperatively controlled robot system to enhance the precision of BSSO.
Methods
We designed a cooperatively controlled robot system using the Galen robotic platform. This system had two modes: haptic guidance to align the surgical saw to the planned osteotomy plane and an active constraint to restrict deviations from the osteotomy plane. A medical student, resident, and attending each performed both a freehand and a robot-assisted osteotomy on 3D printed mandible models from six patients. The cut volume from the difference between pre- and postoperative CT scans was computed. The distance from each cut voxel to the planned plane was used to the determine accuracy and precision of the osteotomy. The NASA Task Load Index (TLX) survey assessed the mental workload of both types of operations.
Results
When cutting freehand, the student's osteotomies had the highest deviation from the planned plane (2.16 +/- 0.98 mm) compared to the resident (1.74 +/- 0.95 mm) and the attending (1.64 +/- 0.85 mm). The robot-assisted cuts resulted in significantly lower deviations from the planned plane, indicating accuracy, and lower standard deviations, indicating precision (student: 0.71 +/- 0.53 mm, p=0.0015; resident: 0.53 +/- 0.35 mm, p=0.0010; attending: 0.63 +/- 0.24 mm, p=0.0024). The NASA TLX survey showed that the robot-assisted system made the mental, temporal, and physical demands of BSSO easier for the attending and the resident, whereas the student found both freehand and robot-assisted procedures to be difficult.
Conclusions
A cooperatively controlled robotic system can significantly enhance the precision of the surgical cutting in BSSO. All participants were able to improve performance with robotic assistance, effectively narrowing the skill gap.