Abstract
Restoring native hip biomechanics is crucial to the success of THA. This is reflected both in terms of complications after surgery such as instability, leg length inequality, pain and limp; and in terms of patient satisfaction. The challenge that remains is that of achieving optimal implant sizing and positioning so as to restore, as closely as possible, the native hip biomechanics specific to the hip joint being replaced. This would optimise function and reduce complications, particularly, instability. (Mirza et al., 2010). Ideally, this skill should also be reproducible irrespective of the surgeon's experience, volume of surgery and learning curve.
The general consensus is that the most substantial limiting factor in a THA is the surgeon's performance and as a result, human errors and unintended complications are not completely avoidable (Tarwala and Dorr, 2011). The more challenging aspects include acetabular component version, sizing and femoral component sizing, offset and position in the femoral canal. This variability has led to interest in technologies for planning THA, and technologies that help in the execution of the procedure. Advances in surgical technology have led to the development of computer navigation and robotic systems, which assist in pre-operative planning and optimise intra-operative implant positioning.
The evolution of surgical technology in lower limb arthroplasty has led to the development of computer navigation and robotics, which are designed to minimise human error and improve implant positioning compared to pre-operative templating using plain radiographs. It is now possible to use pre-operative computerised tomography (image-based navigation) and/or anatomical landmarks (non-imaged-based navigation) to create three-dimensional images of each patient's unique anatomy. These reconstructions are then used to guide bone resection, implant positioning and lower limb alignment.
The second-generation RIO Robotic Arm Interactive Orthopaedic system (MAKO Surgical) uses pre-operative computerised tomography to build a computer-aided design (CAD) model of the patient's hip. The surgeon can then plan and execute optimal sizing and positioning of the prostheses to achieve the required bone coverage, minimise bone resection, restore joint anatomy and restore lower limb biomechanics. The MAKO robotic software processes this information to calculate the volume of bone requiring resection and creates a three-dimensional haptic window for the RIO-robotic arm to resect. The RIO-robotic arm has tactile and audio feedback to resect bone to a high degree of accuracy and preserve as much bone stock as possible.
We have used this technology in the hip to accurately reproduce the anteversion, closure and center of rotation that was planned for each hip. Whilst the precise safe target varies from patient to patient, the ability to reproduce native biomechanics, to gain fixation as planned and to get almost perfect length and offset are a great advantage. Complications such as instability and leg length inequality are thus dramatically reduced.
