The international journal of medical robotics + computer assisted surgery : MRCAS · 2026
Global Workflow of a Comanipulation-Based Robotic System for Cervical Spine Surgery.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Koszulinski A, Sandoval J, Wu C-T, Huang S-H, Sahani S K, Wu S-L, Essomba T, Vendeuvre T, Faure J-P, Zeghloul S, Laribi M A
Аннотация
BACKGROUND: Cervical arthrodesis requires precise pedicle screw placement to ensure safety and effectiveness. Traditional planning and execution are time-consuming and prone to variability.
METHODS: We developed a robot-assisted system integrating three components: an AI-based preoperative planning module, adapted from previous work, to generate patient-specific screw trajectory from 3D CT point-clouds; an intraoperative registration and motion compensation system with optical tracking to align the trajectory with patient anatomy in real time; and a comanipulation control strategy enforcing virtual fixtures and depth limits to guide the robotic arm safely. The system was tested on 3D-printed models and cadaveric specimens.
RESULTS: Robotic assistance significantly improved the geometric accuracy of drilling, reducing transverse positional deviations by a factor of two and orientation deviations by a factor of eight compared with freehand procedures. In addition, the average drilling depth overshoot was reduced by 50%. Perforation rates were found to be of the same order as those observed with freehand techniques.
CONCLUSION: The proposed workflow improves trajectory-following accuracy and depth control while preserving intuitive surgeon interaction. These results demonstrate the feasibility of integrating AI-based planning, intraoperative tracking, and collaborative robotics for cervical spine surgery.
METHODS: We developed a robot-assisted system integrating three components: an AI-based preoperative planning module, adapted from previous work, to generate patient-specific screw trajectory from 3D CT point-clouds; an intraoperative registration and motion compensation system with optical tracking to align the trajectory with patient anatomy in real time; and a comanipulation control strategy enforcing virtual fixtures and depth limits to guide the robotic arm safely. The system was tested on 3D-printed models and cadaveric specimens.
RESULTS: Robotic assistance significantly improved the geometric accuracy of drilling, reducing transverse positional deviations by a factor of two and orientation deviations by a factor of eight compared with freehand procedures. In addition, the average drilling depth overshoot was reduced by 50%. Perforation rates were found to be of the same order as those observed with freehand techniques.
CONCLUSION: The proposed workflow improves trajectory-following accuracy and depth control while preserving intuitive surgeon interaction. These results demonstrate the feasibility of integrating AI-based planning, intraoperative tracking, and collaborative robotics for cervical spine surgery.