Medical Journal
Computer navigation is a useful intra-operative tool for joint line
measurement in total knee arthroplasty
- Gerard Ee
- Hee Nee Pang
- Hwei Chi Chong
- Mann Hong Tan
- Ngai Nung Lo
- Seng Jin Yeo
Article history:
Received 16 July 2012
Received in revised form 19 October 2012 Accepted 28 October 2012
Key finding
This study found that joint line changes ≥4 mm during computer-assisted total knee arthroplasty (TKA) were associated with significantly poorer clinical outcomes at both 6 months and 2 years. Patients with smaller shifts (<4 mm) showed better Oxford, Function, Knee, and SF-36 scores. Computer navigation enabled precise intraoperative joint line assessment, helping improve surgical outcomes
Keywords:
Knee
Arthroplasty
Computer
Joint line
Fixed-bearing
Posterior cruciate retaining Posterior stabilised
ABSTRACT
Background: Restoration of the native joint line in total knee arthroplasty is important in restoring ligamentous balance and normal knee kinematics. Failure to achieve this could lead suboptimal outcomes. The purpose of this study was to analyze the clinical and functional outcome of patients who demonstrated joint line changes after computer-assisted (CAS) total knee arthroplasty (TKA).
Methods: One hundred sixty-eight patients (168 knees) underwent CAS TKA by two surgeons at a single insti- tution with 2 years follow-up. The final change in joint line was calculated from the verified tibial resection and distal femoral cuts. Group A patients had joint line changes of less than 4 mm and Group B patients had joint line changes of more than 4 mm. Post-operative Oxford scores, Knee scores, Function scores and SF-36 scores were obtained at 6 months and 2 years post TKA.
Results: There was significant linear correlation between joint line changes and Oxford scores (P=0.0001), Function scores (P = 0.0001) and Knee scores (P = 0.0001) at 6 months and Oxford scores (P = 0.0001) alone at 2 years with increasing joint line changes having poorer outcome scores. Group A compared to Group B patients demonstrated better Oxford scores (P=0.0001), Function scores (P=0.0001), Knee scores (P=0.0001) and total SF-36 scores (P=0.003) at 6 months as well as better Oxford scores (P=0.0001) and Knee scores (P=0.014) at 2 years.
Conclusions: CAS is a useful intra-operative tool for assessing the final joint line in TKA. Outliers in joint line changes of ≥4 mm are associated with poorer clinical outcome scores.
Level of evidence: Prognostic Study, Level II-1.
1. Introduction
The success of total knee arthroplasty (TKA) hinges upon the res- toration of the mechanical axis, joint line, balanced flexion-extension gaps, balancing of soft tissue and restoration of patellofemoral align- ment [1].
Gap balancing affects the final knee kinematics [2] and suboptimal soft tissue balancing can lead to accelerated polyethylene wear. Changes in the joint line with respect to the attachments of the collateral ligaments can decrease range of motion as well as result in poor tracking of the patella [3]. Joint line malposition has also been shown to not only lead to instability but also to an increased incidence of anterior knee pain, accounting for the decrease in joint flexion [4]. Martin and Whiteside demonstrated that proximal displacement of the joint line, as little as 5 mm could result in midflexion instability [5].
Elevated joint line could result in patella baja, resulting in im- pingement of the patella implant on the anterior aspect of the tibia polyethylene component. This often results in patients complaining of anterior knee pain and decrease flexion [6].
Distalization of joint line results in patella alta. This increases patella strains, alters patella tracking, and increases the risk of patella subluxation and often re- sults in midflexion instability [7]. Restoration of joint line is therefore essential.
Computer navigation has been proven as a useful tool in better correction of alignment [8] and more precise placement of implants in TKA and can provide quantitative data to balance the joint line both in flexion as well in extension [9]. Numerous studies have eval- uated the effect of joint line changes in posterior cruciate retaining mobile-bearing TKA [10], as well as the effect of joint line in revision TKA [11]. However, there has been no literature evaluating the effect of joint line changes measured using CAS with fixed-bearing TKA on clinical outcomes and functional scores.
This is a prospective analysis of patients undergoing a CAS TKA with a fixed-bearing tibial prosthesis over a 2 year period with a duration of 2 years follow-up. The primary objective was to evaluate the effect of joint line changes on clinical outcomes and functional scores, and we hypothesize that larger changes in joint line were associated with poorer outcome scores.
2. Materials and methods
2.1. Study design
From 2007 to 2008, 168 consecutive patients (168 knees) underwent computer navigated TKA were included in this prospec- tive study after approval was sought for our study protocol from our hospital’s ethics committee. All patients who participated in the study provided consent. The inclusion criterion was primary osteoar- thritis of the knee. Exclusion criteria included patients with rheuma- toid arthritis, previous knee surgery, infection and those who could not be treated with unconstrained TKA and a short stem tibial im- plant. Only fixed-bearing tibial components were used. There were 135 females and 33 males, with a mean age of 67.5 years (range, 50–90 years). There were 84 knees with Posterior Stabilised (PS) im- plants and 84 with Cruciate Retaining (CR) implants. At the end of 2 years, a total of 17 patients were lost to follow-up. Three patients passed away, eight were out of the country, two were warded in other hospitals for other reasons and four could not be contacted.
We then proceeded to divide the patients into two groups, Group A and B, and sequential analysis was carried out for joint line changes at 0.5 mm intervals. We started from a 2 mm joint line change in- creasing at 0.5 mm intervals until statistical significance in the differ- ence in outcome scores was reached for a certain joint line change from the box plots.
2.2. Source of funding
The authors received no external funding source.
3. Operative procedure
The operations were performed by the two senior surgeons. A PFC femoral component and an all polyethelyene fixed-bearing tibial prosthesis (PFC, Depuy Orthopaedic International, Leeds, UK) was used in each patient. All patellae were resurfaced.
Operative anaesthesia was either general or spinal. Thirty-nine patients underwent general anaesthesia and 129 patients underwent spinal anaesthesia. Each oper- ation was performed with the aid of a tourniquet after a single injection of intravenous prophylactic antibiotic (cefazolin or vancomycin if the patient was allergic to penicillins). A midline skin incision was made and the joint was exposed through a standard medial parapatellar approach with patellar eversion. All tibiae were prepared before the femurs, and the duration of the surgery was documented at the end of operation.
The software used for the CAS was Ci Mi TKR Version 2.0 by BrainLab/ Depuy Orthopaedic Inc (Johnson and Johnson, Leeds, UK). Anatomical landmarks were registered through the use of dual 3 mm unicortical pins drilled into the femur and tibia at a distance from the surgical approach, and a pointer with passive infrared reflec- tors. The tibial cut was made first.
This was followed by bone morphing of the femur and ligament balancing.
The Tensor Sensor from Depuy (Fig. 1) was used to deliver a constant pressure of 23 N/cm2 to both me- dial and lateral compartments simultaneously [12] and this was based on the data collated on natural tension in the knee.
Soft tissue releases were made to achieve a rectangular gap at 0° extension (Fig. 2) and the space between the distal femur and proximal tibia was stored. Sub- sequently, the knee was brought to 90° flexion and the space between the posterior femoral condyles and proximal tibia recorded.
The size and the position of the femoral component were adjusted on a virtual computer model to achieve equal flexion and extension gaps and the planned polyethylene thickness was recorded. The planned femoral component was then rotated to achieve a rectangular flexion space at
4. Measurement of joint line changes
After the femoral modeling, the computer automatically generated the amount of bony resection, size of femoral component and the thickness of the tibial insert to create rectangular gaps. The projected amount of joint line shift was also demonstrated on the screenshot (Fig. 3). The bony resections were performed as planned, and the amount of distal femoral and tibial resections was confirmed by the plane verifier. The final joint line change was calculated from the projected joint line change and the amount of verified bony cuts, using the following formula.
Final joint line change (mm)=Planned joint line change (mm)+ Deviated distal femoral resection (mm)+Deviated tibial resection (mm).
The planned joint line change was calculated before any cuts were made, and the deviated distal femoral resection and deviated tibial resection were the resection errors deviated from the planned cuts (Figs. 4 and 5). The value was negative if the joint line position had been lowered and positive if it had been raised. Analysis of the linear correlation between the joint line changes from the box cuts and clinical outcomes was performed.
5. Post-operative management
Each patient received graduated compression stockings and inter- mittent pneumatic calf pumps as prophylaxis against deep vein thrombosis. All patients had the same post-operative analgesics regime and underwent the same rehabilitation protocol. The active range of movement of each knee was documented daily by the phys- iotherapist using a goniometer. The patients were further evaluated with the Oxford Knee score [13], Knee Society Score [14], Function score and the SF-36 questionnaire [13] at 6 months and at 2 years. Standardized 101.6 cm tube-to-film distance radiographs were taken in the anterior–posterior orientation with the patient in a weight bearing position. They were done at 6 weeks post-operatively to mea-sure the mechanical axes of the knees[15]. The overall limb alignment was taken as connecting line through the centre of the hip, the centre of the knee and the centre of the ankle [16].
Fig. 2. Soft tissue balancing.
6. Statistical analysis
Univariate analysis was performed with unpaired T test for comparison of clinical outcome scores both pre and post TKA. The Mann–Whitney U test was used to compare the non-parametric scores between our two groups. An ANOVA analysis was done using the Kruskal–Wallis test to exclude the effect of possible confounding factors on clinical outcome. A Spearman rank correlation was used to demonstrate no significance between CAS measurements and radiographic measurement techniques. A p value of less than 0.05 was considered significant.
Fig. 3. Femoral planning.
Fig. 4. Verify distal femoral resection.
Fig. 5. Verify tibia resection.
7. Results
7.1. Demographics (Table 1)
There was no significant difference in demographic data between Group A and Group B as well as between the PS and CR implants. There were a total of 76 PS and 77 CR implants in Group A and 8 PS implants and 7 CR implants in Group B. This was not statistically significant.
7.2. Joint line changes
The average joint line shift all of the 168 patients was 1.63 mm (−6 mm to +6 mm), with 49 cases having a distal shift while 99 cases had a proximal shift. The direction of a proximal shift was assigned a negative value and the distal a positive value. The average distal shift was 1.6 mm while the average proximal shift was −1.9 mm. 20 cases had no change in joint line. The average joint line shift was calcu- lated based on absolute valves. A total of 153 (91.1%) patients were grouped in Group A and 15 (8.9%) patients in Group B at the start of our study. Average change in joint line for the PS knees and CR knees were (1.59 mm±1.32 mm vs. 1.67 mm±1.38 mm, P=0.70) respectively. Fig. 6 shows that the outcomes were generally poorer in patients with greater joint line changes.
7.3. Clinical outcomes
We compared the pre-operative and post-operative clinical outcome scores among Group A and Group B and found significant improvement in Oxford scores, Function scores, Knee scores and SF36 scores at the 2 year follow-up. For Group A patients, we found an improvement in mean Oxford scores (35±8 vs. 18±4, P=0.0001), Function scores (56±18 vs. 71±2, P=0.0046), Knee scores (41±20 vs. 87±10, P=0.0001) and SF-36 scores (461 ± 135 vs. 605 ± 138, P = 0.0001). Group B patients also showed similar significant improvement in Oxford scores (35±9 vs. 27±3, P=0.047), Function scores (52±12 vs. 71±15, P=0.0008), Knee scores (39±18 vs. 78±17, P=0.0001) and SF-36 scores (459 ± 67 vs. 576 ± 175, P = 0.027). There was also no statistically signif- icant difference in clinical and functional outcomes between the PS and CR knees in each group.
We analysed a total of 151 (89.9%) patients found significant linear correlation between changes in joint line and Oxford scores and Function scores. This correlation was established for Oxford scores (P=0.0001) with Correlation coefficient (r)= 0.523 and Function scores (P=0.0001) with Correlation coefficient (r)=−0.498 and Knee scores (P = 0.0001) with Correlation coefficient (r) = − 0.616 at 6 months and *PF, physical functioning; RFP, role functioning due to physical problems; BP, bodily pain, GE, general health role limitation due to emotional problems; EV, energy/vitality, SF, social functioning; RFE, role functioning due to emotional problems, ME, mental health.
Oxford scores (P=0.0001) with Correlation coefficient (r)=0.743 alone at 2 years as illustrated in Fig. 6 previously. Our correlation demonstrated that is an association between joint line changes and outcome scores at 6 months and at 2 years, with a larger change in joint line resulting in higher Oxford scores and lower Function and Knee scores.
There were a total of 137 (81.5%) patients in Group A and 14 (8.3%) patients in Group B at 2 years. There were significant better outcomes in Group A compared to Group B at 6 months with regards to the Oxford score (P=0.0001), Function score (P=0.0001), Knee score (P=0.0001), SF-1 (P=0.03), SF-2 (P=0.05), SF-5 (P=0.04), SF-6 (P = 0.003), SF-7 (P = 0.03), SF-8 (P = 0.004) and SF-Total scores (P = 0.003). At the 2 years follow-up, Group A patients had better Oxford scores (P=0.0001) and Knee scores (P = 0.014) compared to Group B (Table 2).
7.4. Joint alignment and range of motion
The average pre-operative mechanical axis was varus 13°. Average post-operative valgus was 0.5±2°, with no knees in varus alignment. Pre-operative mean flexion was 119±19° and mean extension was 4±9°. Post-operative mean flexion at 6 months was 112 ± 14° with a mean extension of 3 ± 5°. At 2 years, post-operative mean flexion was 120±8 and mean extension was 0.3±2°.
We also compared Group A and Group B’s pre-operative, 6 months and 2 years post-operative range of motion as well as alignment (Table 3). There was no significant difference (P>0.05) between range of motion as well as mechanical axis alignment in our 2 groups, although Group B did demonstrate a decrease in range of motion and limitation in flexion at 6 months and at 2 years.
Fig. 6. Linear correlation Oxford 2 year.
8. Complications
Two patients (1.2%) in Group A developed a superficial wound infection. Both patients responded to intravenous antibiotics.
9. Discussion
Our results have demonstrated that with CAS, we have shown that intra-operative joint line changes of more than 4 mm were associated with significantly poorer clinical outcome scores after 6 months and 24 months of follow-up.
The adverse effect of joint line changes on the clinical outcomes of total knee arthroplasty has been extensively studied and we now understand the effects these changes have on knee kinematics.
Eleva- tion in the joint line results in an inferior shift of the contact point the retropatella relative to the femur, with patellofemoral contact forces increasing by 3% per millimeter of displacement [17]. This affects patella function and subluxation and has been shown to correlate with wear patterns [18], lifespan of the patella component [19], decrease clin- ical outcomes [20], and decrease range of motion [21]. Impingement of the patella tendon against the anterior aspect of the tibia component may also result in pain, structural damage and limitation in knee flexion [22]. Abnormalities of the patellofemoral joint have been shown to account for up to 50% of all TKR related complications [23].
Computer aided surgery has been shown to be beneficial in deter- mining crucial landmarks including component orientation and mechanical axis [24]. Meta-analysis of alignment outcomes for CAS versus conventional TKA indicates significant improvement in mechanical axis and femoral or tibial alignment [25]. Moreover, studies have shown that with CAS, most knees are well within 3° of valgus or varus, providing the best outcome in terms of aseptic loosening [26].
The mean joint line change in our study was 1.63 mm and this correlated well with other studies [27]. CAS has been proven to reduced outliers in implant positioning [28] and mechanical axis [29]. Similarly, this study has demonstrated minimal number of outliers with joint line change of more than 4 mm. As mentioned above, it is well understood the effect joint line changes has on the outcome of a TKA. Before the evolution of CAS, there has not been any reliable method to evaluate changes in joint line intra-operatively. Our results have shown that using CAS, we can accurately determine the joint line intra-operatively and this co-relates well with clinical and functional outcomes at 6 months as well as at the 2 years follow-up.
Computer-assisted gap balancing technique was performed to achieve optimal soft tissue tension in our patients. Although Lee et al. [30] and Tigani et al. [31] reported significantly more joint line changes with the gap balancing technique when compared to measured resection technique, we believe that computer navigation empowers the surgeon to control the joint line shift [32].
The joint line shift in our study was minimal with a mean of 1.63 mm, which was similar to the study by Yang et al. [27]. By keeping the joint line shift within 4 mm, it would be possible to benefit from the advan- tages of the gap balancing technique [33] without excessive changes in joint line. We agree that there were some outliers in our study (8.3% of patients) which were not eliminated with the use of CAS. These outliers were associated with poorer outcomes which highlighted the importance of maintaining the joint line positioning.
Joint line measurements have traditionally been done using radiographic measurements post-operatively. There has not been an accurate and reproducible way to evaluate the changes in joint line intra-operatively.
Moreover, the control of the joint line is difficult intra-operatively as the only useful reference point is the transepicondylar axis of the femur [34]. Pre- and post-operative radiographic measurements may also be inaccurate as a flexion contracture in the knee joint will alter the apparent joint space, as the radiographic beams will not parallel to the joint in an anterior posterior view [35]. Joint misalignment with pre-existing external rotation will also cause joint line measurements to be inaccurate [34]. Lastly, magnification of pre- and post-operative radiographs varies and templates which have a standardized magnification may hence result in inaccuracy [36]. The introduction and development of computer-assisted surgery has allowed accurate and quantitative measurement of intra-operative joint line changes and we are hence able to reliably plot these measurements with the outcome scores.
We believe that as opposed to conventional surgery, CAS has allowed us to accurately determine changes in joint line and we have shown that 4 mm is the threshold before these changes in joint line start to become clinically relevant. In closer analysis of our outcome scores, patient perform far worse in kneeling down and getting up again as well as going down a flight of stairs.
Mobile-bearing TKA designs were excluded from our study, as we believe that having 2 articulating surface, the polyethylene-femoral surface and the polyethylene-tibial surface, creates 2 functional joint lines and as a result may be more forgiving to overall joint line changes. Yang et al. could not demonstrate any effect on clinical outcome of computer-assisted mobile-bearing knee arthroplasty with joint line changes in the range −1 to +5 mm [27]. Bottros et al. postulated that this may also be attributed to the surgical tech- nique, with more attention paid to balancing flexion and extension gaps as compared to a fixed-bearing TKA [37].
We acknowledge that joint line calculations are based on registra- tion by the surgeon. Hence if these points are placed inaccurately, the joint line calculation would hence be affected and we recognize this to be a potential problem in inexperienced CAS users. The two senior surgeons involved in this study have independently performed more than 800 CAS knee arthroplasties and we believe that the outliers in the data presented were not due to errors in the CAS technique.
Any errors in the CAS technique were minimized by acquiring a large number of points during the registration phase. This was done both through acquiring multiple landmarks across a bony surface as well as through acquiring single landmarks on the bone. A verification step was performed in all cases. Here the surgeon checks on the CAS screens if the area shown on the screen correctly corresponds to the actual area on the bone. Secondly, a pointer was also ran along the bone to check whether the area shown on the screen correctly corre- sponds to the actual area on the bone.
In conclusion, we believe CAS allows the surgeon to accurately determine changes in joint line intra-operatively and we have shown that changes in joint line of more than 4 mm showed signifi- cantly poorer clinical outcome scores at the 6 month and 24 month follow-up.
Conflict of Interest
Ngai Nung Lo, Seng Jin Yeo declares being a consultant to DePuy
Orthopaedics, Inc. All other authors declare no conflict of interest.
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