Augmented reality navigation for minimally invasive knee surgery using enhanced arthroscopy. (April 2021)

• Record Type: Journal Article
• Authors: Chen, Fang; Cui, Xiwen; Han, Boxuan; Liu, Jia; Zhang, Xinran; Liao, Hongen
• Is Part Of: Computer methods and programs in biomedicine. Volume 201(2021)
• Publication Date: 2021-04
• Subjects: Knee surgery -- Augmented reality -- Arthroscopic image -- Enhanced information; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2021.105952
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Α novel in-situ AR navigation based on the enhanced arthroscopic information is developed to solve the existed problems of in-situ AR navigation. This system uses tissue properties-based model deformation method to update the 3D preoperative knee model. Preclinical experiments on knee phantom and in-vitro swine knee demonstrate the effectiveness the proposed in-situ AR navigation. Abstract: Purpose: During the minimally invasive knee surgery, surgeons insert surgical instruments and arthroscopy through small incisions, and implement treatment assisted by 2D arthroscopic images. However, this 2D arthroscopic navigation faces several problems. Firstly, the guidance information is displayed on a screen away from the surgical area, which makes hand/eye coordination difficult. Secondly, the small incision limits the surgeons to view the internal knee structures only from an arthroscopic camera. In addition, arthroscopic images commonly appear obscure visions. Methods: To solve these problems, we proposed a novel in-situ augmented reality navigation system with the enhanced arthroscopic information. Firstly, intraoperative anatomical locations were obtained by using arthroscopic images and arthroscopy calibration. Secondly, tissue properties-based model deformation method was proposed to update the 3D preoperative knee model with anatomical location information. Then, the updated model was further rendered with glasses-free real 3D display for achieving the global in-situ augmented reality view. In addition, virtual arthroscopic images were generated from the updated preoperative model to provide the anatomical information of the operation area. Results: Experimental results demonstrated that virtual arthroscopic images could reflect the correct structure information with a mean error of 0.32 mm. Compared with 2D arthroscopic navigation, the proposed augmented reality navigation reduced the targeting errors by 2.10 mm and 2.70 mm for the experiments of knee phantom and in-vitro swine knee, respectively. Conclusion: Our navigation method is helpful for minimally invasive knee surgery since it can provide the global in-situ information and detail anatomical information.