Using standard X-ray images to create 3D digital bone models and patient-matched guides for aiding implant positioning and sizing in total knee arthroplasty. Issue 1 (23rd March 2021) - Massé, Vincent; Ghate, Raju S.
Abstract: X-Atlas™ is a new imaging technology intended to advance the state of the art in patient-specific instrumentation. It uses standard AP and lateral radiographs instead of CT or MRI scans to create 3D bone models, which can be used to perform pre-operative surgical planning and fabricate TKA personalized guides. The aim of this study was to validate X-Atlas™ and evaluate the accuracy of personalized guides created with this imaging technology. Its ability to predict implant size was also determined. The accuracy of the X-Atlas™ imaging technology was evaluated by comparing the landmarks of X-Atlas™ 3D Bone models to MRI-reconstructed bone models. The accuracy of PSI guides created with X-Atlas™ (X-PSI™ guides) was evaluated during a validation study (16 specimen knees) and a clinical study (50 patients; Health Canada #CSU2015-12K). Optical navigation was used to measure positioning accuracy. In addition, the ability of X-Atlas™ to predict implant size was assessed. The accuracy of the X-Atlas™ imaging technology was below 0.87 and 1.28 mm for the femoral and tibial landmarks, respectively. The accuracy of X-PSI™ guides to reproduce the pre-operative planned HKA was within ± 3° in 100% and 86.1% of cases, for the laboratory and clinical study respectively, which was significantly better than historical data for conventional instrumentation. X-Atlas™ was able to predict implant size to ± 1 size in 95.6% and 100%, for the femur and tibia component respectively. The X-Atlas™ imaging technology demonstrated excellent accuracy for reconstructing a 3D bone model. The results show that PSI guides created with X-Atlas™ (X-PSI™ guides) provide greater implant positioning accuracy than conventional instrumentation, without the requirement of advanced imaging. Furthermore, the X-Atlas™ imaging technology could effectively predict implant sizing, potentially reducing the number of instrument trays and improving surgical efficiency.