Today, neuronavigation is widely used in daily clinical routine to perform safe and efficient surgery. Augmented reality (AR) interfaces can provide anatomical models and preoperative planning contextually blended with the real surgical scenario, overcoming the limitations of traditional neuronavigators. This study aims to demonstrate the reliability of a new-concept AR headset in navigating complex craniotomies. Moreover, we aim to prove the efficacy of a patient-specific template-based methodology for fast, non-invasive, and fully automatic planning-to-patient registration. The AR platform navigation performance was assessed with an in-vitro study whose goal was twofold: to measure the real-to-virtual 3D target visualization error (TVE), and assess the navigation accuracy through a user study involving 10 subjects in tracing a complex craniotomy. The feasibility of the template-based registration was preliminarily tested on a volunteer. The TVE mean and standard deviation were 1.3 and 0.6 mm. The results of the user study, over 30 traced craniotomies, showed that 97% of the trajectory length was traced within an error margin of 1.5 mm, and 92% within a margin of 1 mm. The in-vivo test confirmed the feasibility and reliability of the patient-specific template for registration. The proposed AR headset allows ergonomic and intuitive fruition of preoperative planning, and it can represent a valid option to support neurosurgical tasks.
Evaluation of a Wearable AR Platform for Guiding Complex Craniotomies in Neurosurgery
Condino, Sara;Montemurro, Nicola;Cattari, Nadia;D’Amato, Renzo;Ferrari, Vincenzo;Cutolo, Fabrizio
2021-01-01
Abstract
Today, neuronavigation is widely used in daily clinical routine to perform safe and efficient surgery. Augmented reality (AR) interfaces can provide anatomical models and preoperative planning contextually blended with the real surgical scenario, overcoming the limitations of traditional neuronavigators. This study aims to demonstrate the reliability of a new-concept AR headset in navigating complex craniotomies. Moreover, we aim to prove the efficacy of a patient-specific template-based methodology for fast, non-invasive, and fully automatic planning-to-patient registration. The AR platform navigation performance was assessed with an in-vitro study whose goal was twofold: to measure the real-to-virtual 3D target visualization error (TVE), and assess the navigation accuracy through a user study involving 10 subjects in tracing a complex craniotomy. The feasibility of the template-based registration was preliminarily tested on a volunteer. The TVE mean and standard deviation were 1.3 and 0.6 mm. The results of the user study, over 30 traced craniotomies, showed that 97% of the trajectory length was traced within an error margin of 1.5 mm, and 92% within a margin of 1 mm. The in-vivo test confirmed the feasibility and reliability of the patient-specific template for registration. The proposed AR headset allows ergonomic and intuitive fruition of preoperative planning, and it can represent a valid option to support neurosurgical tasks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
