The effect of using patient-specific guides for total knee replacement without hardware removal in complex...

Post-traumatic knee replacement (PTKR) is frequently complicated by the presence of retained metallic hardware around the joint, which limits the use of intramedullary alignment guides. Consequently, extramedullary jigs are often required, although they may increase radiation exposure and reduce alignment precision. Patient-specific guides (PSGs), generated from medical imaging and produced via 3D printing, offer a potential alternative for improving accuracy in complex surgical scenarios. This study aimed to assess the accuracy of PSGs in PTKR using in-vitro knee models with and without retained hardware.

CT images of arthritic knees were used to generate 3D-printed anatomical models. Metallic plates and screws were subsequently mounted to replicate typical post-traumatic hardware configurations. These phantoms underwent CT scanning for virtual surgical planning, and patient-specific guides (PSGs) were designed based on the reconstructed preoperative models. In-vitro distal femoral and proximal tibial resections were then performed by a surgeon using the corresponding PSGs. After the simulated procedures, all phantoms were re-scanned to quantify PSG positioning accuracy and resection angles.

Knee phantoms with hardware exhibited shape deviations 17-18.5 times greater than those without hardware (p < 0.05). PSG positioning errors averaged 0.68 mm and 2.83° in hardware models, compared to 0.55 mm and 1.32° in non-hardware models. Resection angle errors in hardware phantoms ranged from 2.4° to 3.1°, significantly higher than in the non-hardware group.

Based on the in-vitro experimental findings, PSGs allow PTKR to be performed without the removal of retained hardware while achieving accuracy that exceeds that of traditional extramedullary alignment techniques. Although hardware presence results in a quantifiable reduction in accuracy, PSGs continue to demonstrate improved alignment precision and contribute to enhanced workflow efficiency in the context of complex PTKR.