[Optimal lower limb alignment and soft tissue balancing strategy for robot-assisted total knee arthroplasty]

Area of Science:

• Orthopedic Surgery
• Robotics in Medicine
• Biomechanical Engineering

Background:

• Patient satisfaction and long-term prosthetic survival after total knee arthroplasty (TKA) depend on lower limb alignment and soft tissue balance.
• While robot-assisted TKA (rTKA) offers precise osteotomy and soft tissue balancing, traditional mechanical alignment has not shown significant functional improvements.

Purpose of the Study:

• To evaluate the potential of novel TKA alignment principles, kinematic alignment (KA) and functional alignment (FA), in conjunction with rTKA.
• To explore how these alignment strategies, aided by objective tools like pressure sensors, can optimize soft tissue balance and clinical outcomes.

Main Methods:

• Utilizing robot-assisted TKA (rTKA) to achieve precise osteotomies and implement advanced alignment strategies (KA/FA).
• Employing objective soft tissue balance assessment tools, such as pressure sensors, to guide and validate alignment.
• Comparing outcomes of rTKA with KA/FA against traditional methods.

Main Results:

• KA and FA principles better accommodate individual knee morphology and kinematics compared to classic alignment.
• Objective tools like pressure sensors demonstrate improved soft tissue balance with KA and FA.
• rTKA enables more accurate and reproducible achievement of non-neutral alignment goals (KA/FA).

Conclusions:

• Robot-assisted TKA guided by kinematic or functional alignment principles shows promise for improving clinical results.
• The combination of advanced alignment strategies and robotic precision is expected to enhance soft tissue balance.
• These approaches are anticipated to significantly increase patient satisfaction rates following total knee arthroplasty.