Dynamic alignment in total knee arthroplasty: Balancing motion, not just bone – A narrative review
J. S. R. G. Saran, Megha Naikal, M. P. Mohith, Natasha Varghese Isaac, D. V. S. Praneeth, Ajay KoushikAbstract
Background:
Alternative alignment philosophies, i.e., kinematic and functional alignment (FA), have emerged alongside conventional mechanical alignment in total knee arthroplasty, with growing emphasis on soft-tissue-guided rather than purely bone-referenced component positioning. Most alignment frameworks, however, remain defined on conventional two-position (0°/90°) assessment despite native knee laxity varying nonuniformly through the flexion arc.
Methodology:
A narrative review was conducted following the Scale for the Assessment of Narrative Review Article principles. Searches were structured across four evidence streams: sensor-guided balancing, robotic dynamic balancing, flexion-arc alignment behavior, and clinical outcomes/controversies, across PubMed, Embase, and the Cochrane Library to June 2026. Evidence was organized into a literature matrix and synthesized narratively given technological and methodological heterogeneity.
Results:
Sensor and robotic platforms enable continuous, motion-arc-based balancing, a addressing a demonstrated biomechanical limitation of conventional, checkpoint-based assessment. Dynamic and functional balancing technologies consistently improve quantitative balance and joint-specific measures such as the Forgotten Joint Score, but this advantage translates inconsistently to legacy composite scores (Knee Society Score, Oxford Knee Score, and Knee Injury and Osteoarthritis Score). Definitional inconsistency across “FA” techniques, cost-driven access disparity favoring high-volume centers, and absent long-term survivorship data remain significant limitations.
Conclusion:
Dynamic alignment offers a biomechanically sound refinement of intraoperative balancing but remains an evolving, unproven-at-scale concept rather than an established standard. Its future value likely lies in integration with static phenotype classification and postoperative sensor-based functional monitoring.