LL-MAROCO: A Large Language Model-Assisted Robotic System for Oral and Craniomaxillofacial Osteotomy - Lai Jiang; Liangjing Shao; Jinyang Wu; Xiaofeng Xu; Xinrong Chen; Shilei Zhang (Bioengineering, 2025)
Oral and craniomaxillofacial bone deformities necessitate treatment through osteotomy. Robot-assisted osteotomy appears promising in oral and craniomaxillofacial surgery, but it lacks sufficient intelligence and comprehensive integration of navigation tracking with surgical planning. This study aims to develop an intelligent surgical robot, based on the large language model ChatGPT-4, to enable autonomous planning for oral and craniomaxillofacial osteotomies. An autonomous surgical planning system driven by ChatGPT-4 was developed. Surgical plans were autonomously generated based on expert-defined prompts and surgical objectives. A deep learning framework was employed to match navigation-generated visual data with textual planning outputs. The generated plans were subsequently converted into executable instructions for robotic surgery. System precision, execution accuracy, and usability were experimentally validated through common osteotomies. An anonymous Likert scale assessed operational efficiency. The proposed system achieved a trajectory planning accuracy of 0.24 mm and an average robotic execution accuracy of 1.46 mm. The completion rates for two representative procedures, Le Fort I osteotomy and genioplasty, were 87% and 92%, respectively. Survey results confirmed process feasibility. The integration of a large language model with surgical robot advances intelligent, precise, and safe oral and craniomaxillofacial osteotomy procedures.