Application of fluoroscopic stereophotogrammetric analysis in the detection of aseptic loosening of prostheses

Objective·To verify the accuracy and clinical feasibility of fluoroscopic stereophotogrammetric analysis (FSA) technology based on two dimension (2D)-three dimension (3D) registration for early migration detection of aseptic loosening of joint prostheses.Methods·2D-3D registration algorithms centering on the light source and projected object respectively in FSA technology were verified under various working conditions through image synthesis experiments, and the feasibility of clinical application was verified through real model experiments. The image synthesis experiment established a perspective projection environment with the same parameters as the real environment in a virtual environment, the 2D perspective images of the 3D model (bone or prosthesis) during the six degrees of freedom transformation were recorded, and the six degrees of freedom transformation of the 3D model was restored by using different 2D-3D registration algorithms. The error of each registration algorithm was calculated. For real model validation, the migration between bone and prosthesis after joint replacement surgery was simulated with a high precision bone prosthesis migration simulator. The 3D model of the bone or prosthesis was reconstructed by using computed tomograph (CT) images and optical scanning, and the 2D perspective images before and after prosthesis migration were captured by using a fluoroscopy device. The migration of the prosthesis was restored by using FSA technology based on 2D-3D registration, and the error of FSA technology was calculated.Results·The accuracy of the 2D-3D registration algorithm centering on the light source was higher than that of the algorithm centering on the projected object under different working conditions. When the initial registration conditions were favorable, the algorithm centering on the light source reduced the rotation error compared to the algorithm centering on the projected object, with a statistical difference (P=0.021), and the displacement error decreases, with a significant statistical difference (P=0.000). Moreover, algorithms centering on the light sources required lower similarity and fewer registration times to meet clinical application requirements.Conclusion·The accuracy of FSA technology based on 2D-3D registration in early migration detection of artificial joint prostheses meets clinical application requirements. This technology can warn of late aseptic loosening of prostheses by detecting early migration of prostheses after joint replacement surgery, and is expected to be applied to clinical practice through further research.