Open Access
Review
Issue
SICOT-J
Volume 12, 2026
Article Number 4
Number of page(s) 8
Section Knee
DOI https://doi.org/10.1051/sicotj/2025068
Published online 28 January 2026

© The Authors, published by EDP Sciences, 2026

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Introduction

Functional alignment (FA), also described as functional knee positioning, has emerged as a patient-specific alignment philosophy for total knee arthroplasty (TKA) that seeks to reproduce native joint lines and soft-tissue tension in three dimensions rather than forcing a uniform mechanical neutral axis [1, 2]. FA tailors component orientation to each patient’s native limb morphology and ligamentous behavior, aiming to recreate physiological joint-line orientation and balanced gaps across coronal, sagittal, and axial planes [3]. The concept emphasizes joint-line preservation and kinematic harmony with the least possible soft-tissue release [4].

This level of individualization is greatly facilitated by robotic assistance [5]. Image-based planning and intraoperative analytics allow surgeons to iteratively adjust bone resections and component positions while observing gap symmetry in extension and flexion in real time [3, 6]. In practice, FA is implemented within predefined “guardrails” (workflow boundaries) that cap coronal alignment, tibial slope, and axial rotation (referenced to established axes), thereby enabling personalization without drifting into extreme positions [2, 3].

Despite encouraging clinical outcomes, the radiographic profile delivered by FA remains incompletely defined. Interpretation is limited by heterogeneous measurement conventions (rotational and slope references, neutral definitions, imaging modality, and intra-op vs post-op reporting) and by subgroup-only reporting instead of whole-cohort aggregates [79]. These inconsistencies make meta-analytic pooling difficult and highlight the need for a structured synthesis describing typical postoperative limb alignment (hip–knee–ankle angle [HKA], lateral distal femoral angle [LDFA], medial proximal tibial angle [MPTA]) and component positioning (femoral valgus/rotation/flexion; tibial varus/rotation/slope).

Accordingly, the objective of this systematic review was to consolidate radiological outcomes and intraoperative workflow parameters in robotic FA-TKA. The authors aimed to summarize (1) pre- and postoperative limb alignment (HKA, LDFA, MPTA), (2) femoral and tibial component positioning, including the rotational references used, and (3) the alignment boundaries that characterize FA workflow.

Materials and methods

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [10]. The protocol was prospectively registered with PROSPERO (CRD420251134340). A comprehensive search of PubMed/MEDLINE and Scopus was performed from database inception to September 2025 using the following string: (“total knee arthroplasty” OR “TKA” OR “total knee replacement” OR “TKR”) AND (“functional alignment” OR “functional knee position” OR FA OR FKP) AND (robotic OR “robotic-assisted” OR “robot-assisted”). The search was restricted to English-language publications. Reference lists of all eligible full-text articles were manually screened to identify additional studies.

Studies were eligible if they enrolled adult patients undergoing primary robotic-assisted TKA performed under FA principles and reported outcomes at a minimum follow-up of two years. Acceptable designs were randomized controlled trials, prospective or retrospective comparative cohort studies, and large case series with at least 50 patients. To ensure clinical relevance, studies were required to report at least one validated clinical outcome and, for the purpose of the present analysis, to include radiological alignment and/or component-positioning data or explicit descriptions of the FA workflow. Exclusion criteria were revision or partial knee arthroplasty, small case series with fewer than 50 patients, cadaveric/biomechanical investigations, expert opinions, narrative reviews, and non-English publications.

Study selection was performed independently by two reviewers (V.G., A.V.V.) who screened titles and abstracts and then assessed full texts; disagreements were resolved by discussion with a third reviewer (C.K.). Data extraction was completed independently by the same reviewers using a standardized form. Only the information on the FA groups (from comparative studies with other alignment philosophies) was recorded.

The radiological variables of interest were pre- and postoperative coronal alignment, including the hip–knee–ankle angle (HKA), the lateral distal femoral angle (LDFA), and the medial proximal tibial angle (MPTA) and component positioning outputs and limits: femoral valgus, femoral external-rotation reference, femoral flexion, tibial varus/valgus, tibial external-rotation reference, and tibial posterior slope. Workflow fields comprised the boundaries used in the robot for each plane (for example, 0–6° tibial varus, Akagi’s [11] line for tibial rotation, 0–3° tibial slope, and degrees for femoral external rotation), together with any stated alignment philosophy or guardrails. Outcomes were synthesized descriptively due to heterogeneous frames of reference (e.g., transepicondylar axis (TEA) vs posterior condylar axis (PCA); Akagi’s line vs soft-tissue referencing).

Continuous variables were extracted as means with standard deviations when available; medians with interquartile ranges or ranges were recorded verbatim. Because radiographic angles and rotational references were reported heterogeneously across studies (using different axes and tolerances), outcomes were synthesized primarily through descriptive statistics (typical values, ranges, and frequencies of targets/guardrails) rather than being pooled quantitatively. When units or reference frames differed, values were summarized within their native reference system without transformation to avoid misclassification. Categorical data were presented as counts and percentages.

Risk of bias was assessed at the study level using the RoB 2 tool for randomized controlled trials and the ROBINS-I tool for non-randomized studies. Overall certainty of the evidence was judged as very low, low, moderate, or high considering risk of bias, inconsistency, indirectness, imprecision, and potential publication bias.

Results

All 21 FA–robotic TKA cohorts (5360 knees) [7, 8, 1230] in the radiology dataset reported at least one alignment or component-positioning endpoint (Figure 1). Mean age across the cohorts clustered around 66–72 years, Body Mass Index (BMI) typically ~26–32 kg/m², and women comprised roughly ~50–66% of participants; all series used an image-based MAKO platform.

thumbnail Figure 1

Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flowchart.

Preoperatively, coronal deformity was predominantly varus: studies that provided HKA typically showed means around 170–176° with LDFA ~88–91° and MPTA ~85–87° where available. Postoperatively, limb alignment converged slightly varus, close to neutral, across cohorts. Where HKA was reported, most means/medians lay around 178–179.5°. LDFA generally centered at ~89–91° and MPTA at ~87–89° (Table 1).

Table 1

Pre- and post-operative radiological alignment data among the included studies.

Component positioning outputs were narrowly distributed and aligned with FA goals [3] which targets HKA 174°–180°, femoral positioning from 3° varus to 6° valgus, tibial positioning at 0°–6° varus, femoral rotation 0° internal rotation–6° external rotation. Femoral valgus clustered around ~0.5–1.5°, femoral external rotation values were small (often ~0–0.5° when a single mean was given), and femoral flexion was typically ~6–9° (e.g., Andriollo et al. 6.6–6.9° [1214]; multiple Koutserimpas et al. strata 6.2–9° [12, 2025]). Tibial coronal placement concentrated around ~3° varus and was stable across subgroups such as age, BMI, or patellar strategy [20, 22], while the posterior tibial slope was usually ~0.7–1.0°. Tibial external rotation was referenced almost uniformly to Akagi’s line, sometimes expressed simply as “Akagi’s line” and other times with an explicit narrow tolerance band (Figure 2, Table 2).

thumbnail Figure 2

The mean values of the 3-D implant positioning from the reviewed studies.

Table 2

Femoral and tibial component positioning data among the included studies.

Workflow guardrails showed striking convergence across studies that stated them explicitly. Typical femoral ranges were valgus 6° to varus 3° [7, 8, 1922, 24, 25, 2730], external/internal rotation (ER/IR) ± 6/3° [1214, 1622, 24, 25, 27, 28] from transepicondylar axis (TEA), and flexion 0–10° across all works except one study that ranged 0–7° [7].Tibial rotation was overwhelmingly referenced to Akagi’s line [7, 8, 1214, 1724, 25, 29], with a few series [15, 28, 30] describing soft-tissue balancing as the operative reference; tibial ranges commonly included 0–6° varus except from Daffara [16] ranged between 4° varus and 2° valgus; Choi [15] positioned from 3° varus to 3° valgus; Yang [28] kept between 5° varus and 5° valgus and Koutserimpas [26] applied two tibial-varus strategies: 0–3° (Group A) and 0–6° (Group B). Posterior slope ranged in all studies between 0 and 3° (Table 3).

Table 3

The boundaries for tibia and femoral implant during total knee arthroplasty among included studies.

Study quality (ROBINS-I)

Risk-of-bias assessments for the included observational cohorts were primarily moderate (19 cohorts), with a small number of studies rated as low-moderate (2 cohorts). The sole randomized controlled trial (RCT) was assessed as having a low risk of bias based on the ROB2 tool used for randomized studies

Discussion

The principal finding of this review is that robotic FA in TKA in predominantly varus knees achieves slightly varus- near to neutral reproducible radiographic targets. Across more than 5,000 FA knees with a minimum of 2 years’ follow-up, limb alignment clustered near neutral (HKA ≈178–179.5°) with component placement concentrated in narrow bands (femoral valgus ≈0.5–1.5°, tibial varus ≈3°, femoral flexion ≈6–9°, tibial slope ≈0–3°). These achieved positions show that although FA is a personalized alignment strategy using the soft tissue envelope of the knee as guidance, it leads to safe radiographic targets [31].

Mechanical alignment (MA) targets a straight mechanical axis, classically HKA 180° ± 3°, with femoral and tibial components implanted perpendicular to their respective mechanical axes and has the virtues of standardization and durability data [32, 33]. However, imposing neutral on every knee can disregard native joint-line obliquity and soft-tissue laxities, sometimes necessitating collateral releases and risking non-physiologic kinematics in anatomies that deviate from neutral [34]. In contrast, FA individualizes the femoral and tibial cuts, according to the mediolateral laxities in extension and flexion, within explicit limits (e.g., tibial varus 0–6°, femoral valgus −3° to +6°, tibial slope 0–3°, femoral ER ~3–6° to TEA), aiming to preserve the patient’s phenotype while keeping components inside safety bounds [3]. The radiological outcomes synthesized in this systematic review show that FA usually lands slightly “constitutional”, with subtle femoral valgus and modest tibial varus; yet the overall limb remains near-neutral, aligning with contemporary survivorship goals.

Kinematic Alignment (KA) seeks to “resurface the knee” and fully restore the native joint lines with minimal or no releases by preserving native femoral anatomy [35]. Adjustments, if needed, are preferentially made on the tibial side [36]. While KA may yield favorable kinematics and patellofemoral tracking, valgus morphotypes may be driven toward excess femoral valgus and internal rotation, risking trochlear under-coverage or malorientation unless implants or limits are adapted [37, 38]. However, FA leverages image-based robotic analytics to restore joint-line obliquity and to restore the anterior compartment of the TKA [3942]. Notably, the FA cohorts in this review achieved almost neutral-leaning HKA and constrained component positions without signals of instability or anterior-compartment overstuffing [42] at early follow-up [9].

These concerns have motivated “restricted KA” (rKA), which retains the kinematic intent but introduces caps to avoid extremes. As described by Vendittoli [43], rKA applies the kinematic philosophy but imposes explicit limits to avoid extreme positions. In practice, rKA caps coronal deviation to ≤5° at both the femur and tibia and keeps the overall limb at HKA ~180° ± 3°. The goal is to preserve the native (often oblique) joint line and respect each patient’s anatomy while preferentially adapting corrections on the tibial side when fine-tuning is needed. Building on rKA, FA keeps the respect for native joint-line obliquity but operationalizes it with robot-defined guardrails and real-time gap analytics, shifting from “restore with caps” to “personalize” in three dimensions and positioning within limits [44].

Thus, FA represents a three-dimensional conceptual approach to TKA in which planning and execution are guided by bony morphology, extension–flexion gap behavior, and patellofemoral kinematics. The trochlea is deliberately oriented while the ligaments are preserved, using controlled adjustments in femoral rotation and sagittal positioning to approximate the patient’s native trochlear geometry, thereby promoting balanced gaps and physiologic soft-tissue tension [45, 46]. Given that FA is a personalized alignment strategy, it is expected to preserve the patient’s underlying knee morphotype. In the studies included, the preoperative coronal profile was predominantly varus (typical HKA 170–176°, LDFA 88–91°, MPTA 85–87°). Under FA, these parameters were adjusted toward neutral but not fully neutralized, resulting in constitutionally oriented postoperative radiographs (HKA ~178–179.5°, LDFA ~89–91°, MPTA ~87–89°). This pattern reflects the intended preservation of each knee’s native morphotype while achieving balanced alignment. Component positions mostly stayed inside narrow guardrails (femoral valgus ~1°, tibial varus ~3°, posterior slope ~0–1°, tibial rotation referenced to Akagi’s line).

This review has several important limitations. First, most included cohorts were retrospective, single-center series, and only one randomized trial was available; these features raise the possibility of selection and reporting bias. Most cohorts were single-center, retrospective, with relatively short follow-up; thus, the relationship between these radiographic targets and longer-term wear or loosening cannot be fully assessed. Cohorts mixed means with medians/IQRs without raw data, precluding robust pooling. The timing of postoperative imaging was inconsistent, and few studies reported inter-/intra-observer reliability or blinded measurements. Finally, potential overlap between institutional cohorts and the predominance of high-volume centers may temper generalizability.

In conclusion, across 21 cohorts, robotic FA consistently produced a radiographic profile that was adjusted toward neutrality while still reflecting each patient’s native morphotype. Component positions clustered tightly within the predefined guardrails, indicating high adherence and reproducibility of the FA workflow. Collectively, these findings suggest that FA, when executed with image-based robotic analytics, reliably restores joint-line orientation and balanced alignment without overcorrecting towards absolute neutrality or drifting into malalignment.

Funding

This research received no external funding.

Conflicts of interest

Authors 1, 2, 3, 4, and 5 have nothing to declare. Author 6: Consultant for Stryker. Author 7: Consultant for Smith Nephew. Funding from the “MEDIKUS” program, University of Patras, Greece. Author 8: Consultant for Stryker.

Data availability statement

Data is available upon reasonable request to the corresponding author.

Author contribution statement

Author 1: Conceptualization, Methodology, Data curation, Writing an original draft.

Author 2: Conceptualization, Methodology, Data curation, Writing an original draft.

Author 3: Data curation, Methodology, Writing, Reviewing, and Editing.

Author 4: Data curation, Methodology, Writing

Author 5: Conceptualization, Methodology, Writing, Reviewing.

Author 6: Conceptualization, Supervision, Validation, Writing, Reviewing, and Editing.

Author 7: Conceptualization, Supervision, Validation, Writing, Reviewing, and Editing.

Author 8: Conceptualization, Supervision, Validation, Writing, Reviewing, and Editing.

Ethics approval

The protocol of this review has been prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO) (registration number: CRD420251134340).

References

  1. Koutserimpas C, Andriollo L, Gregori P, et al. (2025) Revisiting terminology: The transition from “functional alignment” to “functional knee positioning.” Knee Surg Sports Traumatol Arthrosc 33, 1948–1953. [Google Scholar]
  2. Begum FA, Kayani B, Magan AA, et al. (2021) Current concepts in total knee arthroplasty : mechanical, kinematic, anatomical, and functional alignment. Bone Jt Open 2, 397–404. [Google Scholar]
  3. Shatrov J, Battelier C, Sappey-Marinier E, et al. (2022) Functional alignment philosophy in total knee arthroplasty – rationale and technique for the varus morphotype using a CT based robotic platform and individualized planning. SICOT J 8, 11. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  4. Shatrov J, Parker D (2020) Computer and robotic – assisted total knee arthroplasty: a review of outcomes. J Exp Orthop 7, 70. [Google Scholar]
  5. Dretakis K, Koutserimpas C (2024) Pitfalls with the MAKO robotic-arm-assisted total knee arthroplasty. Medicina (Kaunas) 60, 262. [CrossRef] [PubMed] [Google Scholar]
  6. Batailler C, Greiner S, Rekik H-L, et al. (2024) Intraoperative patellar tracking assessment during image-based robotic-assisted total knee arthroplasty: technical note and reliability study. SICOT J 10, 44. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  7. Clark GW, Steer RA, Khan RN, et al. (2023) Maintaining joint line obliquity optimizes outcomes of functional alignment in total knee arthroplasty in patients with constitutionally varus knees. J Arthroplasty 38, S239–S244. [Google Scholar]
  8. Nixon J, Tadros BJ, Moreno-Suarez I, et al. (2024) Functionally aligned total knee arthroplasty: A lateral flexion laxity up to 6 mm is safe! Knee Surg Sports Traumatol Arthrosc 32, 1317–1323. [Google Scholar]
  9. Leal-Blanquet J, Haddad F, Lustig S, et al. (2025) Restoring the native knee or designing the “optimal prosthetic”: Alignment, phenotypes and AI-powered personalization in total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. https://doi.org/10.1002/ksa.70147. [Google Scholar]
  10. Moher D, Liberati A, Tetzlaff J, et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol 62, 1006–1012. [CrossRef] [PubMed] [Google Scholar]
  11. Akagi M, Oh M, Nonaka T, et al. (2004) An anteroposterior axis of the tibia for total knee arthroplasty. Clin Orthop Relat Res 420, 213–219. [CrossRef] [Google Scholar]
  12. Andriollo L, Koutserimpas C, Gregori P, et al. (2025) Beyond the coronal plane in robotic total knee arthroplasty-Part 1: Variations in tibial slope and distal femoral flexion do not affect outcomes. Knee Surg Sports Traumatol Arthrosc 33, 2928–2938. [Google Scholar]
  13. Andriollo L, Gregori P, Koutserimpas C, et al. (2025) Beyond the coronal plane in robotic total knee arthroplasty-Part 2: Combined flexion does not affect outcomes. Knee Surg Sports Traumatol Arthrosc 33, 2939–2949. [Google Scholar]
  14. Andriollo L, Koutserimpas C, Gregori P, et al. (2025) A new parameter in the era of robotic total knee arthroplasty: Coronal alignment at 90° of flexion impacts clinical outcomes. Knee Surg Sports Traumatol Arthrosc 33, 2581–2591. [Google Scholar]
  15. Choi BS, Kim SE, Yang M, et al. (2023) Functional alignment with robotic-arm assisted total knee arthroplasty demonstrated better patient-reported outcomes than mechanical alignment with manual total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc 31, 1072–1080. [CrossRef] [PubMed] [Google Scholar]
  16. Daffara V, Zambianchi F, Bazzan G, et al. (2023) No difference in clinical outcomes between functionally aligned cruciate-retaining and posterior-stabilized robotic-assisted total knee arthroplasty. Int Orthop 47, 711–717. [CrossRef] [PubMed] [Google Scholar]
  17. Diquattro E, Andriollo L, Koutserimpas C, et al. (2025) Patellofemoral alignment safe zones in robotic-assisted TKA do not affect outcomes but do influence patellar resurfacing rates. Knee Surg Sports Traumatol Arthrosc 34(1), 153–163. [Google Scholar]
  18. Diquattro E, Gregori P, Koutserimpas C, et al. (2025) Does patellar resurfacing matter in robotic-assisted total knee arthroplasty with functional alignment principles? Knee Surg Sports Traumatol Arthrosc 33(12), 4234–4243. [Google Scholar]
  19. Koutserimpas C, Andriollo L, Gregori P, et al. (2025) Robotic total knee arthroplasty with functional alignment yields comparable outcomes across age and gender groups. J ISAKOS 14, 100930. [Google Scholar]
  20. Koutserimpas C, Caria C, Gregori P, et al. (2025) Functional alignment in robotic total knee arthroplasty achieves comparable outcomes in varus and valgus knees despite distinct intraoperative strategies: Analysis of 355 consecutive cases. Knee Surg Sports Traumatol Arthrosc 33(11), 3925–3934. [Google Scholar]
  21. Koutserimpas C, Garibaldi R, Olivier F, et al. (2025) Tibial implant varus >3° does not adversely affect outcomes or revision rates in functionally aligned image-based robotic total knee arthroplasty in a minimum of 2-year follow-up. Knee Surg Sports Traumatol Arthrosc 33, 2917–2927. [Google Scholar]
  22. Koutserimpas C, Gregori P, Andriollo L, et al. (2025) Impact of high body mass index on functionally aligned image-based robotic total knee arthroplasty: Comparable functional outcomes but higher mechanical failures. J ISAKOS 12, 100861. [CrossRef] [PubMed] [Google Scholar]
  23. Koutserimpas C, Gregori P, Andriollo L, et al. (2025) Comparable outcomes between cruciate-substituting and posterior-stabilized inserts in robotic total knee arthroplasty under the functional alignment principles. Knee Surg Sports Traumatol Arthrosc 33, 2605–2613. [Google Scholar]
  24. Koutserimpas C, Gregori P, Veizi E, et al. (2025) Cementless versus cemented fixation in image-based robotic total knee arthroplasty guided by functional knee positioning principles. SICOT J 11, 32. [Google Scholar]
  25. Koutserimpas C, Mazzella GG, Andriollo L, et al. (2025) Preoperative flexion contracture does not impair outcomes or early revision rates following robotic total knee arthroplasty with functional alignment. Knee Surg Sports Traumatol Arthrosc 34(1), 183–191. [Google Scholar]
  26. Koutserimpas C, Dretakis K, Veizi E, et al. (2025) Comparable outcomes and early revision rates between restricted and unrestricted functional knee positioning in robotic-assisted total knee arthroplasty for varus deformities ≥10°. Knee Surg Sports Traumatol Arthrosc. https://doi.org/10.1002/ksa.70055. [Google Scholar]
  27. Manara JR, Nixon M, Tippett B, et al. (2024) A case-matched series comparing functional outcomes for robotic-assisted unicompartmental knee arthroplasty versus functionally aligned robotic-assisted total knee arthroplasty. Bone Jt Open 5, 1123–1129. [Google Scholar]
  28. Yang H-Y, Seon J-K, Yim J-H, et al. (2025) Functional alignment achieved a more balanced knee after robotic arm-assisted total knee arthroplasty than modified kinematic alignment. J Clin Med 14, 820. [Google Scholar]
  29. Young SW, Tay ML, Kawaguchi K, et al. (2025) The John N. Insall Award: functional versus mechanical alignment in total knee arthroplasty: a randomized controlled trial. J Arthroplasty 40, S20–S30.e2. [Google Scholar]
  30. Yu M, Xu Y, Wang Y, et al. (2025) Failure to restore normal trochlear orientation does not affect postoperative patella-related outcomes in robotic-assisted functional alignment total knee arthroplasty. J Arthroplasty 40, 3131–3137. [Google Scholar]
  31. Katsaras A, Noeth U, Rackwitz L, et al. (2025) Precision analysis of robotic-assisted total knee arthroplasty. Experience from a high-volume center. Arch Orthop Trauma Surg 145, 417. [Google Scholar]
  32. Freeman M a. R, Swanson S a. V, Todd RC (1973) Total replacement of the knee using the Freeman-Swanson knee prosthesis. Clin Orthop Relat Res 416, 4–21. [Google Scholar]
  33. Bonnin MP, Basiglini L, Archbold HAP (2011) What are the factors of residual pain after uncomplicated TKA? Knee Surg Sports Traumatol Arthrosc 19, 1411–1417. [Google Scholar]
  34. Beckers G, Meneghini RM, Hirschmann MT, et al. (2024) Ten Flaws of Systematic Mechanical Alignment Total Knee Arthroplasty. J Arthroplasty 39, 591–599. [Google Scholar]
  35. Howell SM, Papadopoulos S, Kuznik KT, Hull ML (2013) Accurate alignment and high function after kinematically aligned TKA performed with generic instruments. Knee Surg Sports Traumatol Arthrosc 21, 2271–2280. [CrossRef] [PubMed] [Google Scholar]
  36. Lee YS, Howell SM, Won Y-Y, et al. (2017) Kinematic alignment is a possible alternative to mechanical alignment in total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc 25, 3467–3479. [CrossRef] [PubMed] [Google Scholar]
  37. Rivière C, Dhaif F, Shah H, et al. (2018) Kinematic alignment of current TKA implants does not restore the native trochlear anatomy. Orthop Traumatol Surg Res 104, 983–995. [CrossRef] [PubMed] [Google Scholar]
  38. Sappey-Marinier E, Pauvert A, Batailler C, et al. (2020) Kinematic versus mechanical alignment for primary total knee arthroplasty with minimum 2 years follow-up: a systematic review. SICOT J 6, 18. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  39. Sterneder CM, Faschingbauer M, Haralambiev L, et al. (2024) Why kinematic alignment makes little sense in valgus osteoarthritis of the knee: a narrative review. J Clin Med 13, 1302. [CrossRef] [PubMed] [Google Scholar]
  40. Shatrov J, Coulin B, Batailler C, et al. (2023) Alignment philosophy influences trochlea recreation in total knee arthroplasty: a comparative study using image-based robotic technology. Int Orthop 47, 329–341. [CrossRef] [PubMed] [Google Scholar]
  41. Koutserimpas C, Saffarini M, Bonnin M, et al. (2025) Optimizing the patellofemoral compartment in total knee arthroplasty: Is it time for dynamic assessment? Knee Surg Sports Traumatol Arthrosc 33, 387–392. [CrossRef] [PubMed] [Google Scholar]
  42. Koutserimpas C, Giovanoulis V, Saffarini M, et al. (2025) The effects of over- and under-stuffing the anterior knee compartment in primary TKA: A systematic review. Knee Surg Sports Traumatol Arthrosc. https://doi.org/10.1002/ksa.70033. [Google Scholar]
  43. Almaawi AM, Hutt JRB, Masse V, et al. (2017) The Impact of Mechanical and Restricted Kinematic Alignment on Knee Anatomy in total knee arthroplasty. J Arthroplasty 32, 2133–2140. [CrossRef] [PubMed] [Google Scholar]
  44. Kenanidis E, Milonakis N, Maslaris A, Tsiridis E (2025) Robotic evaluation of articular laxity (REAL) classification: a new intraoperative knee soft-tissue laxity classification using ROSA robotic software. Eur J Orthop Surg Traumatol 35, 139. [Google Scholar]
  45. Kayani B, Fontalis A, Haddad IC, et al. (2023) Robotic-arm assisted total knee arthroplasty is associated with comparable functional outcomes but improved forgotten joint scores compared with conventional manual total knee arthroplasty at five-year follow-up. Knee Surg Sports Traumatol Arthrosc 31, 5453–5462. [CrossRef] [PubMed] [Google Scholar]
  46. Lustig S, Sappey-Marinier E, Fary C, et al. (2021) Personalized alignment in total knee arthroplasty: current concepts. SICOT J 7, 19. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]

Cite this article as: Giovanoulis V, Vasiliadis AV, Tsiridis E, Andriollo L, Gregori P, Dretakis K, Koutserimpas C & Lustig S (2026) A systematic review of radiological outcomes and implant positioning in robotic-assisted functionally aligned robotic total knee arthroplasty. SICOT-J 12, 4. https://doi.org/10.1051/sicotj/2025068.

All Tables

Table 1

Pre- and post-operative radiological alignment data among the included studies.

Table 2

Femoral and tibial component positioning data among the included studies.

Table 3

The boundaries for tibia and femoral implant during total knee arthroplasty among included studies.

All Figures

thumbnail Figure 1

Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flowchart.

In the text
thumbnail Figure 2

The mean values of the 3-D implant positioning from the reviewed studies.

In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.