Accurate determination of post-operative 3D component positioning in total knee arthroplasty: the AURORA protocol

Wakelin, Edgar A.; Tran, Linda; Twiggs, Joshua; Theodore, W; Roe, Justin; Solomon, Michael; Fritsch, Brett; Miles, Brad

doi:10.1186/s13018-018-0957-0

Cited by 18 publications

(18 citation statements)

References 41 publications

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“…While there was not a minimum thickness, engineers resample incoming CT scans to 1.25 mm for and higher resolution datasets received to reduce processing time. The protocol is fully described in a prior publication [ 28 ]. All radiology centres were trained on the protocol and qualified by engineers under the direction of the lead study author to ensure consistency.…”

Section: Methodsmentioning

confidence: 99%

Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved

Twiggs¹,

Miles²,

Parker

et al. 2022

Knee Surg Sports Traumatol Arthrosc

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Purpose Joint dynamics following Total Knee Arthroplasty (TKA) may influence patient-reported outcome. Simulations allow many knee alignment approaches to a single patient to be considered prior to surgery. The simulated kinematics can be matched to patient-reported outcome to predict kinematic patterns most likely to give the best outcome. This study aims to validate one such previously developed algorithm based on a simulated deep knee bend (the Dynamic Knee Score, DKS). Methods 1074 TKA patients with pre- and post-operative Computerised Tomography (CT) scans and 12-month post-operative Knee Injury and Osteoarthritis Outcomes (KOOS) Scores were identified from the 360 Med Care Joint Registry. Landmarking and registration of implant position was performed on all CT scans, and each of the achieved TKAs was computationally simulated and received a predictive outcome score from the DKS. In addition, a set of potential alternative surgical plans which might have been followed were simulated. Comparison of patient-reported issues and DKS score was evaluated in a counter-factual study design. Results Patient-reported impairment with the knee catching and squatting was shown to be 30% lower (p = 0.005) and 22% lower (p = 0.026) in patients where the best possible DKS result was the one surgically achieved. Similar findings were found relating attainment of the best tibial slope and posterior femoral resection DKS plans to patient-reported difficulty straightening the knee (40% less likely, p < 0.001) and descending stairs (35% less likely, p = 0.006). Conclusion The DKS has been shown to correlate with presence of patient-reported impairments post-TKA and the resultant algorithm can be applied in a pre-operative planning setting. Outcome optimization in the future may come from patient-specific selection of an alignment strategy and simulations may be a technological enabler of this trend. Level of evidence. III (Retrospective Cohort Study).

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Section: Methodsmentioning

confidence: 99%

Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved

Twiggs¹,

Miles²,

Parker

et al. 2022

Knee Surg Sports Traumatol Arthrosc

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“…In this way, the manufacturer provided implant models and the detailed pre-operative bone models were aligned in the position and orientation achieved during the TKA (Figure 1). Reproducibility for this process has been previously published [25].…”

Section: Data Collectionmentioning

confidence: 99%

“…All radiology centres were specifically trained to ensure consistency of imaging protocol. The protocol has been previously described [25].…”

Section: Data Collectionmentioning

confidence: 99%

Can TKA outcomes be predicted with computational simulation? Generation of a patient specific planning tool

Twiggs¹,

Miles²,

Roe

et al. 2021

The Knee

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Background: Computer simulations of knee movement allow Total Knee Arthroplasty (TKA) dynamic outcomes to be studied. This study aims to build a model predicting patient reported outcome from a simulation of post-operative TKA joint dynamics. Methods: Landmark localisation was performed on 239 segmented pre-operative computerized tomography (CT) scans to capture patient specific soft tissue attachments. The preoperative bones and 3D implant files were registered to post-operative CT scans following TKA. Each post-operative knee was simulated undergoing a deep knee bend with assumed ligament balancing of the extension space. The kinematic results from this simulation were used in a Multivariate Adaptive Regression Spline algorithm, predicting attainment of a Patient Acceptable Symptom State (PASS) score in captured 12 month post-operative Knee Injury and Osteoarthritis Outcome Scores (KOOS). An independent series of 250 patients was evaluated by the predictive model to assess how the predictive model behaved in a pre-operative planning context. Results: The generated predictive algorithm, called the Dynamic Knee Score (DKS) contained features, in order of significance, related to tibio-femoral force, patello-femoral motion and tibio-femoral motion. Area Under the Curve for predicting attainment of the PASS KOOS Score was 0.64. The predictive model produced a bimodal spread of predictions, reflecting a tendency to either strongly prefer one alignment plan over another or be ambivalent. Conclusion:A predictive algorithm relating patient reported outcome to the outputs of a computational simulation of a deep knee bend has been derived (the DKS). Simulation outcomes related to tibio-femoral balance had the highest correlation with patient reported outcome.

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“…A subset of these patients had surgery performed with the OMNIbotics navigation system from which the width of the laxity profile in midflexion (40°) was extracted. Segmented pre-operative bones, patient specific landmarks and component geometries were registered to the post-operative CT to determine the achieved component placement as per the AURORA protocol [5]. A musculoskeletal computational model with similar boundary conditions to the Oxford Knee Rig developed and validated as described by Theodore et al [6] was used to simulate post-TKA knee dynamics using Adams MSC software (Newport, CA), see Figure 1.…”

Section: Methodsmentioning

confidence: 99%

Intra-Operative and Anatomic Verification of a TKA Computational Model for Pre-Operative Surgical Planning

Twiggs¹,

Wakelin²,

Roe³

et al.

EPiC Series in Health Sciences

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A promising measure of dynamic outcomes in Total Knee Arthroplasty (TKA) is the simulation of joint dynamics. These simulations are potentially useful for pre-operative planning, but are not yet validated for patient-specific variations in anatomy, which forms the aim of this paper. 284 patients from a database of total knee arthroplasty patients were analysed using a pre-operatively defined simulation predicting post-operative knee dynamics; each patient had previously undergone pre- and post-operative CT imaging and had been assessed using the Knee Injury and Osteoarthritis Outcome (KOOS) score at 6 months following surgery. A significant correlation was found between the simulated contact force and laxity in mid-flexion (r=-0.452, p<0.0001), and between the medio- lateral difference in contact force and difference in distal-vs-posterior femoral collateral ligament offset (r=-0.473, p<0.0001). A significant difference of 5 KOOS pain points (p=0.02) was found for patients with unusually low or high simulated contact force compared to normal. These results indicate the preoperative simulation is capable of distinguishing patient-specific kinematics prior to surgery, thereby demonstrating the utility of this simulation for making pre-surgical predictions of patient-specific kinematics and patient-reported outcomes.

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Accurate determination of post-operative 3D component positioning in total knee arthroplasty: the AURORA protocol

Cited by 18 publications

References 41 publications

Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved

Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved

Can TKA outcomes be predicted with computational simulation? Generation of a patient specific planning tool

Intra-Operative and Anatomic Verification of a TKA Computational Model for Pre-Operative Surgical Planning

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