Patient Variation Limits Use of Fixed References for Femoral Rotation Component Alignment in Total Knee Arthroplasty

Twiggs, Joshua; Dickison, David; Kolos, Elizabeth; Wilcox, Caitlin E.; Roe, Justin; Fritsch, Brett; McMahon, Stephen; Miles, Brad; Ruys, Andrew J.

doi:10.1016/j.arth.2017.08.023

Cited by 18 publications

(23 citation statements)

References 43 publications

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“…A series of patients received long leg pre-operative CT scans for the routine pre-operative planning of TKA surgery [ 24 ] and to design patient-specific instrumentation. Ethics approval for all data collection and accessing information from a joint registry for this study was approved by Bellberry Ethics (Sydney, Australia) (approval 2012-03-710).…”

Section: Methodsmentioning

confidence: 99%

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

Wakelin¹,

Tran²,

Twiggs

et al. 2018

J Orthop Surg Res

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BackgroundSuccessful component alignment is a major metric of success in total knee arthroplasty. Component translational placement, however, is less well reported despite being shown to affect patient outcomes. CT scans and planar X-rays are routinely used to report alignment but do not report measurements as precisely or accurately as modern navigation systems can deliver, or with reference to the pre-operative anatomy.MethodsA method is presented here that utilises a CT scan obtained for pre-operative planning and a post-operative CT scan for analysis to recreate a computation model of the knee with patient-specific axes. This model is then used to determine the post-operative component position in 3D space.ResultsTwo subjects were investigated for reproducibility producing 12 sets of results. The maximum error using this technique was 0.9° ± 0.6° in rotation and 0.5 mm ± 0.3 mm in translation. Eleven subjects were investigated for reliability producing 22 sets of results. The intra-class correlation coefficient for each of the three axes of rotation and three primary resection planes was > 0.93 indicating excellent reliability.ConclusionsRoutine use of this analysis will allow surgeons and engineers to better understand the effect of component alignment as well as the placement on outcome.

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Section: Methodsmentioning

confidence: 99%

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

Wakelin¹,

Tran²,

Twiggs

et al. 2018

J Orthop Surg Res

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“…However, Okamoto et al found that 2D preoperative planning resulted in the internal rotation of the femoral component, and the clinical and surgical angle values measured based on X-ray and CT slices would be smaller than the 3D measurements, causing internal component rotation (12). Numerous studies have been conducted to measure relative TKA parameters from 3D models based on CT and MRI, all of which confirmed the high inter-subject variation of PCA (7,8,13). Gokhan et al indicated that the average PCA was 3.3 ± 1.5 • via 3D constructed models based on CT scans, with 2.8 % of scans identified as outliers.…”

Section: Discussionmentioning

confidence: 97%

“…However, since the sTEA had low intra- and interobserver reproductivity and the anatomic landmarks were difficult to identify during the operation, the PCL + 3° external rotation method was used more often in practice ( 5 ). Jang et al indicated that the PCL + 3° external rotation method was the most accurate compared to the sTEA but highly varied among subjects ( 6 ) since the PCA varies remarkably among patients ( 7 ).…”

Section: Introductionmentioning

confidence: 99%

The Presence of Cartilage Affects Femoral Rotational Alignment in Total Knee Arthroplasty

et al. 2022

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ObjectiveTo assess the difference between the posterior condylar angle (PCA) and the mechanical lateral distal femoral angle (mLDFA) in the osseous and cartilaginous contours in a non-arthritic Chinese population.MethodsComputed tomography (CT) and magnetic resonance imaging (MRI) were obtained from 83 patients with knee injuries before arthroscopy, and femur and distal femoral cartilage three-dimensional (3D) models were constructed. The 3D cartilage model was arranged to share physical space with the 3D femoral model, and then PCA and mLDFA were measured on the osseous and cartilaginous contours, respectively. The differences between the measurements with and without cartilage were evaluated.ResultsThe average PCA with cartilage was 2.88 ± 1.35° and without was 2.73 ± 1.34°. The difference was significant in all patients and females but not in males. The average mLDFA with cartilage was 84.73 ± 2.15° and without cartilage was 84.83 ± 2.26°, but the difference was statistically insignificant in all groups.ConclusionPCA on the osseous and cartilaginous contours significantly differed with and without cartilage in the female group, suggesting that cartilage thickness should be considered during preoperative femoral rotational resection planning.

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“…Individual variations following TKR are then influenced by the combination of implant constraint and design, surgical alignment and positioning, and specific features of a given patient's anatomy (including extraarticular, such as those that might drive variation in hip, spine and ankle biomechanics) [7,8]. These patient-specific anatomical factors include ligament offsets [9] and attachment sites [10], which contribute to ligament laxity and are linked to changes in bone and gap characteristics [11,12] following implant positioning. The interaction between these factors is complex, with individual component position parameters combining with the patient-specific musculoskeletal environment to define the dynamic behaviour of the joint.…”

Section: Introductionmentioning

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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Patient Variation Limits Use of Fixed References for Femoral Rotation Component Alignment in Total Knee Arthroplasty

Cited by 18 publications

References 43 publications

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

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

The Presence of Cartilage Affects Femoral Rotational Alignment in Total Knee Arthroplasty

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

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