Robotic-assisted total knee arthroplasty with the OMNIBot platform: a review of the principles of use and outcomes

Shatrov, Jobe; Murphy, Geoffrey; Duong, Julian; Fritsch, Brett

doi:10.1007/s00402-021-04173-8

Cited by 17 publications

(14 citation statements)

References 21 publications

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“…However, the cost and radiation exposure are disadvantages [24], as are the size and low transportability of the machine itself. Imageless systems such as OMNIbot reduce radiation exposure and do not incur the cost of pre-operative imaging, but subsequently rely on the operator's accuracy to correctly register landmarks [25]. Anatomical mapping in cases of large deformity, bone loss, or post-trauma may be prone to registration error [26], and there is not an option for virtual gap balancing allowing pre-cut adjustment based on gap data in a femur-first approach.…”

Section: Introductionmentioning

confidence: 99%

How does the use of quantified gap-balancing affect component positioning and limb alignment in robotic total knee arthroplasty using functional alignment philosophy? A comparison of two robotic platforms

Murphy

Shatrov

Duong

et al. 2023

International Orthopaedics (SICOT)

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Purpose This study aimed to compare the effect of an image-based (MAKO) system using a gap-balancing technique with an imageless (OMNIbot) robotic tool utilising a femur-first measured resection technique. Methods A retrospective cohort study was performed on patients undergoing primary TKA with a functional alignment philosophy performed by a single surgeon using either the MAKO or OMNIbot robotic systems. In all cases, the surgeon’s goal was to create a balanced knee and correct sagittal deformity (eliminate any fixed flexion deformity). Intra-operative data and patient-reported outcomes (PROMS) were compared. Results A total of 207 MAKO TKA and 298 OMNIbot TKAs were analysed. MAKO TKA patients were younger (67 vs 69, p=0.002) than OMNIbot patients. There were no other demographic or pre-operative alignment differences. Regarding implant positioning, in MAKO TKAs the femoral component was more externally rotated in relation to the posterior condylar axis (2.3° vs 0.1°, p<0.001), had less valgus femoral cuts (1.6° vs 2.7° valgus, p<0.001) and more varus tibial cuts (2.4° vs 1.9° varus, p<0.001), and had more bone resected compared to OMNIbot TKAs. OMNIbot cases were more likely to require tibial re-cuts than MAKO (15% vs 2%, p<0.001). There were no differences in femur recut rates, soft tissue releases, or rate of achieving target coronal and sagittal leg alignment between robotic systems. A subgroup analysis of 100 MAKO and 100 OMNIbot propensity-matched TKAs with 12-month follow-up showed no significant difference in OKS (42 vs 43, p=0.7) or OKS PASS scores (83% vs 91%, p=0.1). MAKO TKAs reported significantly better symptoms according to their KOOS symptoms score than patients that had OMNIbot TKAs (87 vs 82, p=0.02) with a higher proportion of KOOS PASS rates, at a slightly longer follow-up time (20 months vs 14 months, p<0.001). There were no other differences in PROMS. Conclusion A gap-balanced technique with an image-based robotic system (MAKO) results in different implant positioning and bone resection and reduces tibial recuts compared to a femur-first measured resection technique with an imageless robotic system (OMNIbot). Both systems achieve equal coronal and sagittal deformity correction and good patient outcomes at short-term follow-ups irrespective of these differences.

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Section: Introductionmentioning

confidence: 99%

How does the use of quantified gap-balancing affect component positioning and limb alignment in robotic total knee arthroplasty using functional alignment philosophy? A comparison of two robotic platforms

Murphy

Shatrov

Duong

et al. 2023

International Orthopaedics (SICOT)

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“…The lateral tibial condylar landmark remained in the mid-coronal plane even in cases of valgus knees with isolated posterolateral cartilage loss. Due to the imageless nature of the robotics system, a morphometric model of the distal femur is created by digitizing, or “painting”, points using the navigation probe [ 25 ]. The medial and lateral distal femoral condylar points were automatically calculated from this bone morph as the most distal points on each condyle along the direction of the femoral mechanical axis.…”

Section: Methodsmentioning

confidence: 99%

Imageless robotic total knee arthroplasty determines similar coronal plane alignment of the knee (CPAK) parameters to long leg radiographs

Edelstein,

Orsi,

Plaskos

et al. 2024

Arthroplasty

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Background The coronal plane alignment of the knee (CPAK) classification was first developed using long leg radiographs (LLR) and has since been reported using image-based and imageless robotic total knee arthroplasty (TKA) systems. However, the correspondence between imageless robotics and LLR-derived CPAK parameters has yet to be investigated. This study therefore examined the differences in CPAK parameters determined with LLR and imageless robotic navigation using either generic or optimized cartilage wear assumptions. Methods Medial proximal tibial angle (MPTA) and lateral distal femoral angle (LDFA) were determined from the intraoperative registration data of 61 imageless robotic TKAs using either a generic 2 mm literature-based wear assumption (Navlit) or an optimized wear assumption (Navopt) found using an error minimization algorithm. MPTA and LDFA were also measured from preoperative LLR by two observers and intraclass correlation coefficients (ICCs) were calculated. MPTA, LDFA, joint line obliquity (JLO), and arithmetic hip-knee-ankle angle (aHKA) were compared between the robotic and the average LLR measurements over the two observers. Results ICCs between observers for LLR were over 0.95 for MPTA, LDFA, JLO, and aHKA, indicating excellent agreement. Mean CPAK differences were not significant between LLR and Navlit (all differences within 0.6°, P > 0.1) or Navopt (all within 0.1°, P > 0.83). Mean absolute errors (MAE) between LLR and Navlit were: LDFA = 1.4°, MPTA = 2.0°, JLO = 2.1°, and aHKA = 2.7°. Compared to LLR, the generic wear classified 88% and the optimized wear classified 94% of knees within one CPAK group. Bland–Altman comparisons reported good agreement for LLR vs. Navlit and Navopt, with > 95% and > 91.8% of measurements within the limits of agreement across all CPAK parameters, respectively. Conclusions Imageless robotic navigation data can be used to calculate CPAK parameters for arthritic knees undergoing TKA with good agreement to LLR. Generic wear assumptions determined MPTA and LDFA with MAE within 2° and optimizing wear assumptions showed negligible improvement.

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“…1A). 18 With the tensioner in the joint, and the back of the thigh supported to minimize the effect of the limb weight, the knee was manually extended from 90 degrees flexion to full extension with the foot supported at the heel, the knee supported posteriorly, and the patella reduced for three separate flexion-extension cycles. For the first cycle, the robotic-assisted tensioner applied 70 N of equilateral load across the joint.…”

Section: Methodsmentioning

confidence: 99%

Ligament Tension and Balance before and after Robotic-Assisted Total Knee Arthroplasty — Dynamic Changes with Increasing Applied Force

Sharma

Plaskos²,

Shalhoub³

et al. 2023

J Knee Surg

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The optimal force applied during ligament balancing in total knee arthroplasty (TKA) is not well understood. We quantified the effect of increasing distraction force on medial and lateral gaps throughout the range of knee motion, both prior to and after femoral resections in tibial-first gap-balancing TKA. Twenty-five consecutive knees in 21 patients underwent robotic-assisted TKA. The posterior cruciate ligament was resected, and the tibia was cut neutral to the mechanical axis. A digital ligament tensioning tool recorded gaps and applied equal mediolateral loads of 70 N (baseline), 90 N, and 110 N from 90 degrees to full extension. A gap-balancing algorithm planned the femoral implant position to achieve a balanced knee throughout flexion. After femoral resections, gap measurements were repeated under the same conditions. Paired t-tests identified gap differences between load levels, medial/lateral compartments, and flexion angle. Gaps increased from 0 to 20 degrees in flexion, then remain consistent through 90 degrees of flexion. Baseline medial gap was significantly smaller than lateral gap throughout flexion (p <0.05). Increasing load had a larger effect on the lateral versus medial gaps (p <0.05) and on flexion versus extension gaps. Increasing distraction force resulted in non-linear and asymmetric gap changes mediolaterally and from flexion to extension. Digital ligament tensioning devices can give better understanding of the relationship between joint distraction, ligament tension, and knee stiffness throughout the range of flexion. This can aid in informed surgical decision making and optimal soft tissue tensioning during TKA.

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Robotic-assisted total knee arthroplasty with the OMNIBot platform: a review of the principles of use and outcomes

Cited by 17 publications

References 21 publications

How does the use of quantified gap-balancing affect component positioning and limb alignment in robotic total knee arthroplasty using functional alignment philosophy? A comparison of two robotic platforms

How does the use of quantified gap-balancing affect component positioning and limb alignment in robotic total knee arthroplasty using functional alignment philosophy? A comparison of two robotic platforms

Imageless robotic total knee arthroplasty determines similar coronal plane alignment of the knee (CPAK) parameters to long leg radiographs

Ligament Tension and Balance before and after Robotic-Assisted Total Knee Arthroplasty — Dynamic Changes with Increasing Applied Force

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