Abstract

Abstract

Focal cartilage defects (FCDs) found in medial and lateral compartments of the knee are accompanied with patient-reported pain and loss of joint function. There is a deficit of evidence to explain why they occur. We hypothesise that aberrant knee joint loading may be partially responsible for FCD pathology, therefore this study aims to use 3-dimensional motion capture (MoCap) analysis methods to investigate differences in gait biomechanics of subjects with symptomatic FCDs.

11 subjects with Outerbridge grade II FCDs of the tibiofemoral joint (5 medial compartment, 6 lateral compartment) and 10 non-pathological controls underwent level-gait MoCap analysis using an infra-red camera (Qualisys) and force-plate (Bertec) passive marker system. 6-degree of freedom models were generated and used to calculate spatio-temporal measures, and frontal and sagittal plane knee, hip and ankle rotation and moment waveforms (Visual 3D). Principle component analysis (PCA) was used to score subjects based on common waveform features, and PC scores were tested for differences using Mann-Whitney tests (SPSS).

No group differences were found in BMI, age or spatio-temporal measures. Medial-knee FCD subjects experienced higher (p=0.05) overall knee adduction moments (KAMs) compared to controls. Conversely, lateral-knee FCD subjects found lower (p=0.031) overall KAMs. Knee flexion and extension moments (KFMs/KEMs) were relatively reduced (p=0.013), but only in medial FCD subjects. This was accompanied by a significantly (p=0.019) higher knee flexion angle (KFA) during late-stance.

KAMs have been shown to be predictive of frontal plane joint contact forces, and therefore our results may be reflective of FCD subjects overloading their respective diseased knee condyles. The differences in knee sagittal plane knee moments (KFMs/KEMs) and angles (KFA) seen in medial FCD subjects are suggestive of gait adaptations to pain. Overall these results suggest treatments of FCDs should consider offloading the respective affected condyle for better surgical outcomes.

The aim of this study was to examine the loading of the other joints of the lower limb in patients with unilateral osteoarthritis (OA) of the knee. We recruited 20 patients with no other symptoms or deformity in the lower limbs from a consecutive cohort of patients awaiting knee replacement. Gait analysis and electromyographic recordings were performed to determine moments at both knees and hips, and contraction patterns in the medial and lateral quadriceps and hamstrings bilaterally. The speed of gait was reduced in the group with OA compared with the controls, but there were only minor differences in stance times between the limbs. Patients with OA of the knee had significant increases in adduction moment impulse at both knees and the contralateral hip (adjusted p-values: affected knee: p < 0.01, unaffected knee p = 0.048, contralateral hip p = 0.03), and significantly increased muscular co-contraction bilaterally compared with controls (all comparisons for co-contraction, p < 0.01).

The other major weight-bearing joints are at risk from abnormal biomechanics in patients with unilateral OA of the knee.

Cite this article: Bone Joint J 2013;95-B:348–53.

INTRODUCTION

Useful feedback from a Total Knee Replacement (TKR) can be obtained from post-surgery in-vivo assessments. Dynamic Fluoroscopy and 3D model registration using the method of Banks and Hodge (1996) [1] can be used to measure TKR kinematics to within 1° of rotation and 0.5mm of translation, determine tibio-femoral contact locations and centre of rotation. This procedure also provides an accurate way of quantifying natural knee kinematics and involves registering 3D implant or bone models to a series of 2D fluoroscopic images of a dynamic movement.

Introduction: Inaccuracies in kinematic data recording due to skin movement artefact are inherent with motion analysis. Image registration techniques have been used extensively to measure joint kinematics more accurately. The aim of this study was to assess the feasibility of using MRI for creating 3D models and to quantify errors in data collection methods by comparing kinematics computed from motion analysis and image registration.

Methodology : 5 healthy and 5 TKR knees were examined for a step up/down task using dynamic fluoroscopy and motion capture. MRI scans of the knee, femur and tibia were performed on the healthy subjects and were subsequently segmented using ScanIP(Simpleware) to produce 3D bone models. Registration of the models produced from fine and coarse scan data was used to produce bony axes for the femoral and tibial models. Tibial and femoral component CAD models were obtained for the TKR patients. The 3D knee solid models and the TKR CAD models were then registered to a series of frames from the 2D fluoroscopic image data (Figure 1) obtained for the 10 subjects, using KneeTrack(S. Banks, Florida) to produce kinematic waveforms. The same subjects were also recorded whilst performing the same action, using a Qualisys (Sweden) motion capture system with a pointer and marker cluster-based technique developed to quantify the knee kinematics.

Results: The motion analysis method measured significantly larger frontal and transverse knee rotations and significantly larger translations than the image registration method.

Conclusion: The study demonstrated that MRI, rather than CT scan, can be used as a non-invasive tool for developing segmented 3D bone models, thus avoiding highly invasive CT scanning on healthy volunteers. It describes an application of combining fine and coarse scan models to establish anatomical or mechanical axes within the bones for use with kinematic modeling software. It also demonstrates a method to investigate errors associated with measuring knee kinematics.