Robotic-Assisted and Computer-Navigated Arthroplasty

Technology-assisted arthroplasty uses computer navigation or a surgical robot to plan and execute bone preparation and component positioning more precisely than manual jigs allow. The shared premise is that tighter control of alignment, component position and soft-tissue balance should improve durability and function - a premise that has been only partly borne out by clinical evidence.

• Mechanical alignment (MA) — the traditional gold standard: restore a neutral hip-knee-ankle (HKA) mechanical axis of 0° (within ±3°) with the femoral and tibial cuts perpendicular to their mechanical axes. Durable and reproducible, but it ignores the patient's native joint-line obliquity and often needs soft-tissue releases to balance.
• Kinematic alignment (KA) — restore the patient's pre-arthritic native alignment and joint-line obliquity by resurfacing the worn condyles (matching resection to cartilage/bone loss); aims to recreate native kinematics with fewer releases, but can place components in outlier positions in some knees.
• Restricted kinematic alignment (rKA) — KA kept within safe boundaries (e.g. each component and the overall HKA within about ±5° of neutral) to avoid extremes.
• Functional alignment (FA) — the robotics-era hybrid: virtually plan component position, then adjust it within defined limits to balance the soft-tissue gaps through range BEFORE cutting bone (the Young Insall-Award RCT showed far fewer releases, 16% vs 65%, with comparable 2-year scores).
• CPAK (Coronal Plane Alignment of the Knee) — classifies knees by arithmetic HKA (limb alignment) and joint-line obliquity into phenotypes (Types I–IX) to individualise the target; the Young RCT found the FA benefit concentrated in CPAK Type I (neutral) knees.

"Walk me through a robotic knee" is a common viva — the steps that distinguish it from a manual case:

1. Plan — for an image-based system, a pre-operative CT builds a patient-specific 3D model with implant size/position; an imageless system plans intra-operatively.
2. Pin and register — insert bone-anchored tracker arrays (femur and tibia) and register the patient's anatomy to the model by capturing bony landmarks/surface points (registration accuracy is the key operator-dependent error).
3. Capture alignment and gaps — record the limb/HKA alignment and assess the flexion and extension gaps and laxity through range under varus/valgus stress.
4. Virtually plan and BALANCE before cutting — adjust component position, size and rotation on screen to optimise alignment and balance the gaps — the step unique to robotics: you balance the plan to the soft tissues before any bone is cut, which is exactly how functional alignment is delivered and how releases are minimised.
5. Execute within the boundary — make the resections with the tool constrained to the haptic/robotic boundary (the semi-active arm stops cutting outside the plan).
6. Trial and refine — reassess the gaps with trial components, fine-tune the plan if needed, then implant.

The differentiator over manual or plain navigation is quantified, dynamic gap-balancing with the ability to adjust the plan before resecting bone.

A defensible exam stance: robotic and navigated arthroplasty are accurate, safe, and enabling technologies whose precision is established but whose clinical superiority is not yet proven. They are reasonable for surgeons who value reproducibility and wish to execute individualised alignment, but they are not a prerequisite for an excellent arthroplasty, and current evidence does not mandate their use.