Robot-assisted unicondylar knee arthroplasty: A critical ... · Critical review icensee A ublishin...

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Critical review

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For citation purposes: Kini SG, Sathappan SS. Robot-assisted unicondylar knee arthroplasty: A critical review. OA Orthopaedics 2013 Jun 01;1(1):4.

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Robot-assisted unicondylar knee arthroplasty: A critical review

SG Kini1*, SS Sathappan2

AbstractIntroductionUnicompartmental knee arthro-plasty (UKA) is an effective surgical treatment for unicompartmental arthritis. Although results can be optimized with careful patient se-lection and use of a sound implant design, the most important deter-minant of success of UKA is com-ponent alignment. Studies have shown that component malalign-ment by as little as 2° may predis-pose to implant failure after UKA. Robot-assisted UKA has been pro-jected to address this issue, which combines patient specificity and navigation. Modern-day robots overcome the problems with older- generation robots like iatrogenic fractures and also introduce in vivo dynamic assessment of the knee that incorporates soft tissue ten-sion. Issues with learning curve, longer operating times and high cost investment persist. We discuss the technique of one such modern robotic design and review the lit-erature with respect to accuracy in restoring limb alignment and their functional outcome.ConclusionShort-term results for robot-assist-ed UKA are promising, although long-term results are awaited to de-termine implant survivorship and functional outcome.

IntroductionUnicompartmental knee arthroplasty (UKA) can provide durable pain relief and functional improvement in great-er than 90% of patients with focal ar-thritis or osteonecrosis of the medial or lateral compartments of the knee1.Concerns with UKA are early failure of the femoral2 or tibial3 components. The main cause of early failure is malpositioning of components with overcorrection or undercorrection of limb alignment. Swienckowski and Page reported that coronal mala-lignment of the tibial component beyond 3° predisposed to failure4. Malalignment of the femoral compo-nent has been found to cause femoral fracture5, patellar impingement and tibial component loosening6. In addi-tion, excessive posterior slope (>7°) of the tibial component has been linked to tibial component loosen-ing, anterior cruciate ligament (ACL) rupture7 and abnormal stress forces on the periprosthetic bone8. There-fore, though UKA has many benefits, technical difficulties in achieving ac-curate alignment have impeded wide-spread adoption of this procedure by orthopaedic surgeons. As many as 40% to 60% of components may be malaligned by more than 2° from the preoperative plan with conventional methods9,10. In a bid to improve UKA outcomes, orthopaedic surgeons have begun taking advantage of sev-eral technological innovations, in-cluding the use of computer-assisted navigation and robotics.

Navigation has been shown to im-prove postoperative leg alignment over that obtained in conventional UKA10–12. Although navigation is a powerful visual aid, surgical out-comes still depend on the mechanical

tools used in procedures. However, even with computer navigation, the number of outliers (beyond 2° of the preoperatively planned implant posi-tion) may approach 15%10.

Recently developed robotic sys-tems have tremendous potential to improve the outcomes of proce-dures such as UKA. Crucially, these new robots are ‘semi-active’; that is, the surgeon retains ultimate control of the procedure while benefiting from robotic guidance within target zones and surgical field boundaries. These zones and boundaries are determined by preoperative com-puted-tomography-based (CT-based) planning with continuous intraop-erative visual feedback. The system incorporates navigation and robot technology. The combination allows for more accurate reproduction of the preoperative plan of implant placement, which may improve over-all leg alignment and reduce iatro-genic morbidity9,13–15.

The aim of this critical review was to discuss robot-assisted unicondy-lar knee arthroplasty.

DiscussionIndications for robot-assisted UKA follow essentially the same criteria as for conventional UKA set by Koz-inn and Scott16.• Low demand patients >60 years

with unicompartmental arthritis• Weight less than 82 kg• Minimum 90° flexion arc• Fixed flexion deformity less than

5°• Coronal plane correctable deform-

ity not exceeding 10° of varus or15° valgus

• Asymptomatic patellofemoral andtibiofemoral compartment.

* Corresponding author Email: [email protected] Department of Orthopaedics, Concord Re-

patriation General Hospital/Sydney Private Hospital, Sydney, Australia

2 Department of Orthopaedics, Tan Tock Seng Hospital, Singapore

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One of the newer robotic design systems/software is MAKO Tactile Guidance System and the procedure is MAKOplasty that is referred to here.

Preoperative imagingPreoperative CT scans are obtained for all patients. Scan protocol re-quires supine positioning with a mo-tion rod attached to the affected leg. One-millimetre slices are taken at the knee joint, and 5-mm slices are taken through the hip and ankle. Im-ages are saved and transferred to the software of the Tactile Guidance Sys-tem so that sagittal slices of the dis-tal femur and proximal tibia may be segmented, defined, and recombined to produce three-dimensional (3-D) models of each. Implant models are then positioned, with correspond-ing cement mantles on the recon-structed bone models, resulting in patient-specific CT-based planning (Figure 1).

visualization of implant position en-sures proper sizing. For example, we advocate a 2-mm rim of bone sur-rounding the pocket created for the inlay tibial component. This rim can be planned and measured directly on the 3-D model. On the femur, the prosthesis is sized such that coverage is maintained while symmetric flex-ion and extension gaps are created. In addition, depth of resection can be planned precisely; 3 mm of tibial bone resection is typically planned. This resection depth can be modified according to intraoperative gap kin-ematics.

Operative setup and robot registrationAfter conventional positioning and sterile draping of the affected limb, robot registration is performed (Figure 2). The surgeon moves the robotic arm through a defined 3-D path to calibrate its movements and set the centrepoint for the cutting instrument. The femoral and tibial reference arrays are then attached. Bone pins are placed in the femur and tibia, and optical arrays are se-curely attached. The camera is now positioned to track the robot and leg arrays through all ranges of motion (ROMs). Anatomical surface land-marks are registered before the skin is incised, and the leg is put through full ROM while the appropriate valgus load is applied on the joint. After skin incision, small juxta-articular check-point pins are inserted on the tibia and femur, and the two bone surfaces are registered at these points.

Exposure and bone registrationThe knee is exposed through a me-dial parapatellar skin incision for a varus knee that extends from the su-perior pole of the patella to just me-dial to the tibial tubercle. The joint is exposed by medial parapatellar ar-throtomy.

The femur registration starts with 32 spheres visible on the screen ( Figure 3). The surgeon has to place

CT-based planning is limited in that soft tissues cannot be visualized with CT. Consequently, guidance for soft-tissue balancing is lacking, only bony alignment can be used for planning, and the plan must be intraoperative-ly modified to achieve precise gap balancing and long-leg alignment. CT planning allows for the assessment of the subchondral bone bed, osteo-phyte formations, and volume defini-tion of cysts and avascular necrosis.

Preliminary sizing of componentsThe preliminary plan is based on alignment parameters and 3-D visu-alization of implant position (Fig-ure 1). During surgery, the plan is modified according to gap kinematic measurements and dynamic lower limb alignment values. In addition, more than 7° of posterior slope of the tibial component has been shown to increase the risk for ACL rupture9. We therefore recommend placing the tibial components in 2° to 4° of varus and avoiding more than 7° of posterior slope. In patients with ACL deficiency, the posterior sagittal slope of the tibia is maintained be-tween 2° and 5°. Three-dimensional

Figure 1: Implant sizes superimposed on different sections of CT scan including a 3-D image.

Relative contraindications are obesi-ty, incompetent ACL (if UKA is cons-idered, then posterior slope should be minimized) and younger patients (as an alternative to osteotomy).

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Figure 3: Onscreen display of femur registration points.

Figure 4: Onscreen display of the preoperative deformity in extension.

the tip of the blue probe (corre-sponding to the colour of the large spheres) to the point on the bone corresponding to one of the larger spheres displayed on the screen that then turns white if verified correctly with an accuracy of 1 mm. Similarly, the tibial registration is carried on that requires the user to acquire six points along the tibial tuberosity.

Dynamic assessmentAfter intraoperative registration of bony anatomy, a dynamic soft-tissue gap balancing algorithm is initiated. Varus deformity is manually cor-rected with application of a valgus force to the knee, while lower limb alignment is simultaneously moni-tored and recorded by the naviga-tion system (Figures 4 and 5). As the virtual components are optimized to fill the space necessary to correct this deformity, the final lower limb alignment is reliably predicted. We target final lower limb alignment of approximately 2° of varus. The limb is moved from extension to flexion in a smooth manner with gentle valgus correction making sure to capture at least five completed poses in the arc (Figures 6 and 7). The Joint Balanc-ing page facilitates capture of live limb alignment for use in implant planning. The flexion/extension an-gle, varus/valgus angle and internal/external rotation values of the leg/implant plan are displayed on the screen.

Graph display The graph displays a visual represen-tation of the tightness or looseness of the knee at captured pose angles (Figure 8). The graph shows that the knee is loose in all poses from extension to 90° flexion. Moving the femoral component inferiorly in the sagittal plane on the screen will tighten the extension gap (Figure 9). Similarly, moving the femoral com-ponent posteriorly will tighten the flexion gap (Figure 10). The graph appears loose only in midflexion.

Figure 2: Registration of the robot in the operating room.

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Resection of the bone surface can be accomplished with the 6 mm or 2 mm ball burrs, depending on the cho-sen implant system. All implant posts are resected using the 6 mm Ball Burr, the Onlay keel is resected us-ing the 2 mm router. CT view allows the user to use the tip of the active burr or tracked probe to investigate real-time correlation of resection po-sitions relative to the pre-operative plan, the CT data and the patient anatomy.

When active, the CT view screen will display a transverse, sagittal, coronal and 3-D view of the CT data and implant model with a live update of any active probe or burr.

Once the bone is prepared, trial components are inserted and stabil-ity is verified in all ranges of motion. Dynamic long-leg alignment is dis-played on the computer monitor so that final alignment can be tracked. Finally, once the implant is satisfacto-rily positioned, both implant compo-nents are cemented (Figure 15) and a final ROM of the knee joint is execut-ed so that original, trial and final im-plant kinematics and knee alignment can be compared. Before site closure, the mini-checkpoints and bone refer-ence arrays are removed. Postopera-tive radiographs are taken to assess component positioning (Figures 16 and 17).UKA can be performed using conventional, navigation or more recently the robotic technique.

Berger and colleagues17 found that the implant survival rate for 62 consecutive UKAs performed with cemented modular Miller–Galante implants was 98% after 10 years and 96% after 13 years, using revision and radiographic loosening as the re-spective endpoints. The survival rate was 100% at 13 years with aseptic loosening as the end point.

This can be made tighter by tilting the component using the curved ar-row cursor on the screen (Figure 11). Now the graph appears rightly bal-anced indicating correct tensioning. This now indicates the final position-ing of the components and proceeds to bone milling.

BurringThe region to resect appears on the screen as a green volume on the 3D

Figure 5: Onscreen display after passive correction of the deformity to the desired value.

Figure 6: Pose capture at 45° knee flexion maintaining passive correction.

model of the bone (Figure 12). Idea-lly, removing all of this green volum-e will create a resected pocket iden-tical to that of the operative plan (F-igures 13 and 14). In case the surge-on goes beyond the 1 mm planned depth, then the area turns red indic-ating to stop. The stereotactic boun-daries guide resection by restricting the burr position and increasing the resistance of the robotic arm to mo-vement. If the user exerts force agai-

nst the stereotactic boundaries in burring mode, the system will emit audible beeps.

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Price and colleagues19 reported 10-year all-cause implant survival with an Oxford mobile-bearing me-dial UKA of 91% in patients younger than 60% and 96% in patients 60 or older.

The main issue with the conven-tional techniques is its reproducibility.

As previously stated, 40% to 60% of cases involving conventional meth-ods may have alignment that is off by more than 2° from the preoperative plan (Figure 2). In addition, range of component alignment varies consid-erably, even among cases managed by skilled knee surgeons24.

A study by Collier et al.20 found that of 245 medial UKAs, the mean tibial component varus was 8 ± 3 (range, -5 to +21) and the mean posterior tibial component slope was 9 ± 4 (range, -2 to +21).

Recently, minimally invasive tech-niques have achieved an overall reduction in soft tissue and bone trauma; however, it has been noted that minimal invasive techniques are not as accurate as open UKA with regard to the anteroposterior-tibial placement and the postop-erative leg alignment and overall revision rate21–23. According to an analysis of the results of 221 con-secutive UKAs performed through an MIS approach, the range of tibial component alignment was large (18° varus to 6° valgus; mean 6°; SD 4°)23. In a series by Fisher et al.22,there was a statistically significant difference in the coronal alignment of the tibial component in UKA per-formed with a minimally invasive technique compared with a stand-ard open technique with a medial parapatellar arthrotomy (84.6 ± 2.8 [range, 78–97] compared with 85.9 ± 2.1 [range, 80–92], respectively; p = 0.001).

Computer navigation was intro-duced to UKA to reduce the number of outliers and improve accuracy, but the percentage of outliers (>2° from the planned implant position) may still approach 15%10.

Figure 7: Pose capture at 90° knee flexion maintaining passive correction.

Figure 8: Graph showing knee tension at various degrees of flexion.

Emerson and Higgins18 reporting their personal experience with 55 mobile-bearing Oxford UKAs, noted a 90% rate of 10-year implant survival

with progression of lateral compart-ment arthritis as the endpoint and 96% with component loosening as the endpoint.

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History of robotic knee dates to the year 2000. The initial robots had limitations due to which it went out of vogue. Drawbacks of these robotic systems include the necessity for an invasive frame connecting the robot and patient, thus limiting free motion throughout the surgical procedure. In addition, frame fixation has been shown to be problematic, associated with an expanded approach, local infections and even iatrogenic frac-tures.

The robot needed to be rigidly fixed to the patient’s bony anatomy. This led to complications such as in-fection, iatrogenic fractures or soft tissue injury, because of the robot’s weight and movement. In addition, another drawback of rigid fixation is a potential reduction in the scope of the approach to the knee and intru-sion into the surgical field.

Modern day robots are independ-ent of the patient’s positioning or movement. Therefore, there is no further rigid fixation device neces-sary. Also, there is greater preci-sion in burring of the bony surface compared with regular UKA cutting guides. The surface flatness of tibial bone cuts prepared by a robot-assist-ed procedure ranged between 0.15 and 0.29 mm versus 0.16 and 0.42 mm during conventional surgery us-ing an oscillating saw. This difference in favour of robot-assisted surgery is clinically important, because the maximal distance between the bone and the prosthetic component that allows bone ingrowth to occur is 0.3 to 0.5 mm24–26. It permits the creation of individual bony surfaces of any shape, which cannot be generated by an oscillating saw. Consequently, a press-fit cavity for the implant can be created. Thus, preservation of the remaining bone surface is possible, which can be very useful for revi-sions and conversions to total knee prosthesis.

The present generation robots also allow for assessment of dynamic correction of deformity that mimics

Figure 9: Femoral component moved inferiorly to tighten knee extension.

Figure 10: Femoral component moved posteriorly to tighten knee at 90° flexion.

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the total improved from 41 to 21; pain improved from 8 to 4; stiffness improved from 4 to 2; and physical function improved from 29 to 15.

Lonner29 compared the postop-erative radiographic alignment of the tibial component with the preopera-tively planned position in 31 knees in 31 consecutive patients undergoing UKA using robotic arm-assisted bone preparation and in 27 consecutive pa-tients who underwent unilateral UKA using conventional manual instru-mentation to determine the error of bone preparation and variance with each technique. Radiographically, the root mean square error of the posterior tibial slope was 3.1° when using manual techniques compared with 1.9° when using robotic arm assistance for bone preparation. In addition, the variance using manual instruments was 2.6 times greater than the robotically guided proce-dures. In the coronal plane, the aver-age error was 2.7 ± 2.1 more varus of the tibial component relative to the mechanical axis of the tibia using manual instruments compared with 0.2 ± 1.8 with robotic technology.

Pearle30 in his series of 10 cases of robot-assisted UKA concluded that the difference between planned and intraoperative tibiofemoral angle was within 1° and the postoperative long leg axis radiographs were with-in 1.6°.

There are limitations with this procedure. The overall costs of the system are high, excluding additional costs for CT scanning and regular maintenance of the robot. It is also necessary to use additional skilled personnel in the OR. Finally, CT-based systems fail to incorporate soft tissue tension into the planning. Gap kinematics, however, are tracked in-traoperatively by tracking a manual flexion/extension cycle of the knee before the burring process. The im-plant placement can be refined based on the predicted gaps; this soft tissue balancing process is distinct from tra-ditional practices, and its reliability

Figure 11: Femoral component tilted forward to tighten knee at 45° flexion.

Figure 12: Onscreen display depicting the area of the distal femur and tibial plateau to be resected.

accurately in vivo ligament tension and accordingly adjust the final im-plant positioning to obtain a well-balanced knee in all ranges of motion.

Cobb et al.9 were able to dem-onstrate, in a prospective clinical study, a significant improvement in implant placement, and that accu-rate leg alignment can be achieved successfully with the aid of a semi-active (Acrobot) robot system in UKA.

Coon27 showed results in com-parison of 35 robotic cases with 45

conventional ones and found the accuracy of the tibial implant slope to be 2.5 times better (p < 0.05), varus alignment to be 3.2° better (p < 0.05) and SD to be 2.8 times less (p < 0.05) in the robotic arm group.

Roche28 and colleagues11 reported on their first 43 patients. The range of motion increased from 121° to 126°; KSS improved from 95 to 150; and Medical Outcomes 12-Item Short Form Survey (SF-12) Physical Summary scores improved from 19 to 30. Regarding WOMAC scores,

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is unknown. Mid- and long-term follow-up is not available given the recent adoption of this technology. Further follow-ups will be necessary to determine whether the reduction in alignment errors that we observed with robotic arm-assisted bone prep-aration will ultimately influence im-plant function or survival.

ConclusionRobot-assisted UKA allows sur-geons to prepare a patient-specific CT-based preoperative plan that can be executed precisely. The surgical field is predefined, and inadvertent deviation outside the field is prevent-ed by active constraints of the robotic arm, thus minimizing iatrogenic mor-bidity and maximizing bone preser-vation. Burring of the exact cavity of interest for the specific implants al-lows for greater conservation of bony surfaces during arthroplasty. Al-though results are preliminary, dra-matically improved surgical accuracy and improved ligament dynamics do show a promising trend for its con-tinued use in the future. Short-term results are encouraging and clinical trials to determine long-term effi-cacy with respect to functional out-come and implant survivorship are necessary.

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Figure 13: Image after burring of the distal femur.

Figure 14: Image after burring of the tibial plateau.

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Figure 16: Anteroposterior radiograph of the knee with implants.

Figure 17: Lateral radiograph of the knee with implants.

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