The meniscus is comprised largely of type I collagen, as well as fibrochondrocytes and proteoglycans. In articular cartilage and intervertebral disc, proteoglycans make a significant contribution to mechanical stiffness of the tissue via negatively charged moieties which generate Donnan osmotic pressures. To date, such a role for proteoglycans in meniscal tissue has not been established. This study aimed to investigate whether meniscal proteoglycans contribute to mechanical stiffness of the tissue via electrostatic effects.

Following local University Ethics Committee approval, discs of meniscal tissue two millimetres thick and of five millimetres diameter were obtained from 12 paired fresh frozen human menisci, from donors < 6 5 years of age, with no history of osteoarthritis or meniscal injury. Samples were taken from anterior, middle and posterior meniscal regions. Each disc was placed within a custom confined compression chamber, permeable at the top and bottom only and then bathed in one of three solutions − 0.14M PBS (mimics cellular environment), deionised water (negates effect of mobile ions) or 3M PBS (negates all ionic effects). The apparatus was mounted within a Bose Electroforce 3100 materials testing machine and a 0.3N preload was applied. The sample was allowed to reach equilibrium, before being subjected to a 10% ramp compressive strain followed by a 7200 second hold phase. Equal numbers of samples from each meniscus and meniscal region were tested in each solution. Resultant stress relaxation curves were fitted to a nonlinear poroviscoelastic model with strain dependent permeability using FEBio finite element modelling software. Goodness of fit (R2) was assessed using a coefficient of determination. All samples were assayed for proteoglycan content. Comparison of resultant mechanical parameters was undertaken using multivariate ANOVA with Bonferroni adjustment for multiple comparisons.

36 samples were tested. A significant difference (p < 0 .05) was observed in the value of the Young's modulus (E) between samples tested in deionised water compared to 0.14M/3M PBS, with the meniscus found to be stiffest in deionised water (E = 1.15 MPa) and least stiff in 3M PBS (E = 0.43 MPa), with the value of E in 0.14M PBS falling in between (0.68 MPa). No differences were observed in the zero strain permeability or the exponential strain dependent/stiffening coefficients. The viscoelastic coefficient and relaxation time values were not found to improve model fit and were thus held at zero. The mean R2 value was 0.78, indicating a good fit and did not differ significantly between solutions. Proteoglycan content was not found to differ with solution, but was found to be significantly increased in the middle region of both menisci.

Proteoglycans make a significant electrostatic contribution to mechanical stiffness of the meniscus, increasing it by 58% in the physiological condition, and are hence integral to its function. It is important to include the influence of ionic effects when modelling meniscus, particularly where fluid flow or localised strain is modelled. From a clinical perspective, it is critical that meniscal regeneration strategies such as scaffolds or allografts attempt to preserve, or compensate for, the function of proteoglycans to ensure normal meniscal function.

Knee osteoarthritis results in pain and functional limitations. In cases where the arthritis is limited to one compartment of the knee joint then a unicondylar knee arthroplasty (UKA) is successful, bone preserving option. UKA have been shown to result in superior clinical and functional outcomes compared to TKA patients. However, utilisation of this procedure has been limited due primarily to the high revision rates reported in joint registers. Robotic assisted devices have recently been introduced to the market for use in UKA. They have limited follow up periods but have reported good implant accuracy when compared to the pre-operative planned implant placement.

UKA was completed on 25 cadaver specimens (hip to toe) using an image-free approach with infrared optical navigation system with a hand held robotically assisted cutting tool. Therefore, no CT scan or MRI was required. The surface of the condylar was mapped intra operatively using a probe to record the 3 dimensional surface of the area of the knee joint to be resurfaced. Based on this data the size and orientation of the implant was planned. The user was able to rotate and translate the implant in all three planes. The system also displays the predicted gap balance graph through flexion as well as the predicted contact points on the femoral and tibial component through flexion. The required bone was removed using a bur. The depth of the cut was controlled by the robotically controlled freehand sculpting tool.

Four users (3 consultant orthopaedic surgeon and a post-doctoral research associate) who had been trained on the system prior to the cadaveric study carried out the procedures. The aim of this study was to quantify the differences between the ‘planned’ and ‘achieved’ cuts. A 3D image of the ‘actual’ implant position was overlaid on the ‘planned’ implant image. The errors between the ‘actual’ and the ‘planned’ implant placement were calculated in three planes and the three rotations. The maximum femoral RMS angular error was 2.34°. The maximum femoral RMS translational error across all directions was up to 1.61mm. The maximum tibial RMS angular error was 2.60°. The maximum tibial RMS translational error across all directions was up to 1.67mm.

In conclusion, the results of this cadaver study reported low RMS errors in implant position placement compared to the plan. The results were comparable with those published from clinical studies investigating other robotic orthopaedic devices. Therefore, the freehand sculpting tool was shown to be a reliable tool for cutting bone in UKA and the system allows the surgeon to plan the placement of the implant intra operatively and then execute the plan successfully.

Unicondylar knee arthroplasty (UKA) is a treatment for osteoarthritis when the disease only affects one compartment of the knee joint. The popularity in UKA grew in the 1980s but due to high revision rates the usage decreased. A high incidence of implant malalignment has been reported when using manual instrumentation. Recent developments include surgical robotics systems with navigation which have the potential to improve the accuracy and precision of UKA.

UKA was carried out using an imageless navigation system – the Navio Precision Freehand Sculpting system (Blue Belt Technologies, Pittsburgh, USA) with a medical Uni Knee Tornier implant (Tornier, Montbonnot Saint Martin, France) on nine fresh frozen cadaveric lower limbs (8 males, 1 females, mean age 71.7 (SD 13.3)). Two users (consultant orthopaedic surgeon and post doctoral research associate) who had been trained on the system prior to the cadaveric study carried out 4 and 5 implants respectively. The aim of this study was to quantify the differences between the planned and achieved cuts.

A 3D image of the ‘actual’ implant position was overlaid on the planned implant image. The errors between the ‘actual’ and the planned implant placement were calculated in three planes and the three rotations. The maximum femoral implant rotational error was 3.7° with a maximum RMS angular error of 2°. The maximum femoral implant translational error was 2.6mm and the RMS translational error across all directions was up to 1.1mm. The maximum tibial implant rotational error was 4.1° with a maximum RMS angular error was 2.6°. The maximum translational error was 2.7mm and the RMS translational error across all directions was up to 2.0mm.

The results were comparable to those reported by other robotic assistive devices on the market for UKA. This technology still needs clinical assessment to confirm these promising results.

Clinical laxity tests are frequently used for assessing knee ligament injuries and for soft tissue balancing in total knee arthroplasty (TKA). Current routine methods are highly subjective with respect to examination technique, magnitude of clinician-applied load and assessment of joint displacement. Alignment measurements generated by computer-assisted technology have led to the development of quantitative TKA soft tissue balancing algorithms. However to make the algorithms applicable in practice requires the standardisation of several parameters: knee flexion angle should be maintained to minimise the potential positional variation in ligament restraining properties; hand positioning of the examining clinician should correspond to a measured lever arm, defined as the perpendicular distance of the applied force from the rotational knee centre; accurate measurement of force applied is required to calculate the moment applied to the knee joint; resultant displacement of the knee should be quantified.

The primary aim of this study was to determine whether different clinicians could reliably assess coronal knee laxity with a standardised protocol that controlled these variables. Furthermore, a secondary question was to examine if the experience of the clinician makes a difference. We hypothesised that standardisation would result in a narrow range of laxity measurements obtained by different clinicians.

Six consultant orthopaedic surgeons, six orthopaedic trainees and six physiotherapists were instructed to assess the coronal laxity of the right knee of a healthy volunteer. Points were marked over the femoral epicondyles and the malleoli to indicate hand positioning and give a constant moment arm. The non-invasive adaptation of a commercially available image-free navigation system enabled real-time measurement of coronal and sagittal mechanical femorotibial (MFT) angles. This has been previously validated to an accuracy of ±1°. Collateral knee laxity was defined as the amount of angular displacement during a stress manoeuvre. Participants were instructed to maintain the knee joint in 2° of flexion whilst performing a varus-valgus stress test using what they perceived as an acceptable load. They were blinded to the coronal MFT angle measurements. A hand-held force application device (FAD) was then employed to allow the clinicians to apply a moment of 18Nm. This level was based on previous work to determine a suitable subject tolerance limit. They were instructed to repeat the test using the device in the palm of their right hand and to apply the force until the visual display and an auditory alarm indicated that the target had been reached. The FAD was then removed and participants were asked to repeat the clinical varus-valgus stress test, but to try and apply the same amount of force as they had been doing with the device.

Maximum MFT angular deviation was automatically recorded for each stress test and the maximum moment applied was recorded for each of the tests using the FAD. Means and standard deviations (SD) were used to compare different clinicians under the same conditions. Paired t-tests were used to measure the change in practice of groups of clinicians before, during and after use of the FAD for both varus and valgus stress tests.

All three groups of clinicians initially produced measurements of valgus laxity with consistent mean values (1.5° for physiotherapists, 1.8° for consultants and 1.6° for trainees) and standard deviations (<1°). For varus, mean values were consistent (5.9° for physiotherapists, 5.0° for consultants and 5.4° for trainees) but standard deviations were larger (0.9° to 1.6°). When using the FAD, the standard deviations remained low for all groups for both varus and valgus laxity. Introducing the FAD overall produced a significantly greater angulation in valgus (2.4° compared to 1.6°, p<0.001) but not varus (p = 0.67) when compared to the initial examination. In attempting to reach the target moment of 18Nm, the mean ‘overshoot’ was 0.9Nm for both varus and valgus tests. Standard deviations for varus laxity were lower for all groups following use of the FAD. The consultants' performance remained consistent and valgus assessment remained consistent for all groups. The only statistically significant change in practice for a group before and after use of the FAD was for the trainees testing valgus, who may have been trained to push harder (p = 0.01). Standardising the applied moment indicated that usually a lower force is applied during valgus stress testing than varus. This was re-enforced by clinicians, one third of whom commented that they felt they had to push harder for valgus than varus, despite the FAD target being the same.

We have successfully standardised the manual technique of coronal knee laxity assessment by controlling the subjective variables. The results support the hypothesis of producing a narrow range of laxity measurements but with valgus laxity appearing more consistent than varus. The incorporation of a FAD into assessment of coronal knee laxity did not affect the clinicians' ability to produce reliable and repeatable measurements, despite removing the manual perception of laxity. The FAD also provided additional information about the actual moment applied. This information may have a role in improving the balancing techniques of TKA and the management of collateral ligament injuries with regard initial diagnosis and grading as well as rehabilitation.

Finally, the results suggest that following use of the FAD, more experienced clinicians returned to applying their usual manual force, while trainees appeared to use this augmented feedback to adapt their technique. Therefore this technique could be a way to harness the experience of senior clinicians and use it to enhance the perceptive skills of more junior trainees who do not have the benefit of this knowledge.

Knee alignment is a fundamental measurement in the assessment, monitoring and surgical management of patients with osteoarthritis [OA]. In spite of extensive research into the consequences of malalignment, our understanding of static tibiofemoral alignment remains poor with discrepancies in the reported weight-bearing characteristics of the knee joint and there is a lack of data regarding the potential variation between supine and standing (functional) conditions. In total knee arthroplasty [TKA] the lower limb alignment is usually measured in a supine condition and decisions on prosthesis placement made on this. An improved understanding of the relationship between supine and weight-bearing conditions may lead to a reassessment of current surgical goals.

The purpose of this study was to explore the relationship between supine and standing lower limb alignment in asymptomatic, osteoarthritic and prosthetic knees. Our hypothesis was that the change in alignment of these three groups would be different.

A non-invasive infrared position capture system (accuracy ±1° in both coronal and sagittal plane) was used to assess the knee alignment for 30 asymptomatic controls and 31 patients with OA, both before and after TKA. Coronal and sagittal mechanical femorotibial (MFT) angles in extension (negative values indicating varus in the coronal plane and hyperextension in the sagittal plane) were measured with each subject supine and in bi-pedal stance. For the supine test, the lower limb was supported at the heel and the subject told to relax. For the standing position subjects were asked to assume their normal stance. The change in alignment between these two conditions was analysed using a paired t-test for both coronal and sagittal planes. To quantify the change in 3D, vector plots of ankle centre displacement relative to the knee centre from the supine to standing condition were produced.

Alignment in both planes changed significantly from supine to standing for all three groups. For the coronal plane the supine and standing measurements (in degrees, mean(SD)) were 0.1(2.5) and −1.1(3.7) in the asymptomatic group, −2.5(5.7) and −3.6(6) in the OA group and −0.7(1.4) and −2.5(2) in the TKA group. For the sagittal plane the numbers were −1.7(3.3) and −5.5(4.9); 7.7(7.1) and 1.8(7.7); 6.8(5.1) and 1.4((7.6) respectively. This change was most frequently towards relative varus and extension. Vector plots showed that the trend of relative varus and extension in stance was similar in overall magnitude and direction between the three groups.

Knee alignment can change from supine to standing for asymptomatic and osteoarthritic knees, most frequently towards relative varus and hyperextension. The similarities between each group did not support our hypothesis. The consistent kinematic pattern for different knee types suggests that soft tissue restraints rather than underlying joint deformity may be more influential in dynamic control of alignment from lying to standing. In spite of some evidence suggesting a difference between supine and standing knee alignment a mechanical femorotibial (MFT) angle of 0° is a common intra-operative target as well as the desired post-operative weight-bearing alignment. These results indicated that arthroplasties positioned in varus intra-operatively could potentially become ‘outliers’ (>3° varus) when measured weight-bearing. Mild flexion contractures may correct when standing, reducing the need for intra-operative posterior release. These potential changes should be considered when positioning TKA components on supine limbs as post-operative functional alignment may be different.