In my extensive experience with navigation and robotics in hip and knee arthroplasty, I find it valuable to delineate between the two approaches and address the specific considerations for each joint.

Starting with hip replacement, my involvement in the development of the Mako robot provides me with a unique perspective. Having conducted robotic hip replacements with Mako and navigated hips with various systems like Stryker Mako, Brainlab, Intellijoint, and Naviswiss, I’ve concluded that robotics may not offer significant benefits in hip replacement. The simplicity of bony preparation on the socket side and the sphere-like nature of the implant placement make manual reaming and navigation more practical. The femur side, in particular, sees minimal impact from the robot, making navigation the preferred choice.

Conversely, knee replacement presents a distinct scenario where implant placement and bony preparation are critical due to the three degrees of freedom in the femoral component. In this context, robotics, with its focus on dimensional and positional accuracy, plays a crucial role. Dimensional accuracy becomes vital for press-fit implants, while positional accuracy significantly influences clinical outcomes, particularly in terms of flexion and extension gaps.

To delve into the rationale for using robotics in knee replacement, it’s essential to understand the importance of two types of accuracy: dimensional and positional. Dimensional accuracy pertains to the precision of preparing specific dimensions, crucial when utilizing press-fit implants. On the other hand, positional accuracy is paramount for achieving accurate clinical outcomes, particularly concerning flexion and extension gaps. Robotics aids in achieving both types of accuracy.

However, there’s an ongoing debate on the philosophy of knee replacement—whether it is primarily a bony or soft tissue operation. Many robotic surgeons lean towards considering it a bony operation, emphasizing gaps and varus/valgus alignment. Despite this trend, the assumption that equal gaps translate to equal soft tissue tension is not foolproof, as errors in robotic accuracy may compromise this correlation.

The soft tissue tensioning aspect becomes crucial in knee replacement, and currently, only a few technologies, such as eLIBRA (no longer available), OrthoSensor, and BalanceBot, offer the capability to measure tension directly. Without these technologies, surgeons rely on manual assessment based on their tactile feel, which may not be as precise.

In the broader perspective, while robotics has brought positive advancements, there’s a need for critical research on three main fronts:

  1. Correlation of Surgical Plan with Clinical Outcome: Establishing a consensus on the ideal placement of the implant remains elusive, and research is needed to correlate various surgical plans (kinematic alignment, mechanical alignment, reverse kinematic alignment, gap balancing) with clinical outcomes.

  2. Measurement of Ligament Tension: Defining the optimal ligament tension, especially focusing on the medial collateral ligament (MCL), and developing technology capable of measuring soft tissue tension directly, not just gaps, is essential.

  3. AI Algorithm and Machine Learning: The development of artificial intelligence algorithms and machine learning models that can analyze surgical plans, ligament tension, and clinical outcomes to optimize future surgical plans, creating a feedback loop for continuous improvement.

While acknowledging the positive impact of robotics, these research areas are pivotal for refining and maximizing the benefits of knee replacement procedures. Ultimately, the goal is to enhance precision, improve patient outcomes, and bridge the gap between surgical planning and real-world results in knee arthroplasty, and I leave you with this final question: “Why to me hip replacements run marathons and my knee replacements don’t?”