For many years, achieving a neutral coronal Hip-Knee-Ankle angle (HKA) measured on radiographs has been considered a factor of success for total knee arthroplasty (TKA). Lower limb HKA is influenced by the acquisition conditions, and static HKA (sHKA) may not be representative of the dynamic loading that occurs during gait. The primary aim of the study was to see if the sHKA is predictive of the dynamic HKA (dHKA). A secondary aim was to document to what degree the dHKA changes throughout gait.

We analysed the 3-D knee kinematics during gait of a cohort of 90 healthy individuals (165 knees) with the KneeKG™ system. dHKA was calculated and compared with sHKA values. Knees were considered “Stable” if the dHKA remained positive or negative – i.e. in valgus or varus – for greater than 95% of the corresponding phase and “Changer” otherwise. Patient characteristics of the Stable and Changer knees were compared to find contributing factors.

The dHKA absolute variation during gait was 10.9±5.3° [2 .4° – 28.3°] for the whole cohort. The variation was greater for the varus knees (10.3±4.8° [2.4° – 26.3°]), than for the valgus knees (12.8±6.1° [2.9° – 28.3°], p=0.008). We found a low to moderate correlation (r = 0.266 to 0.553, p < 0 .001) between sHKA and the dHKA values for varus knees and no correlation valgus knees. Twenty two percent (36/165) of the knees demonstrated a switch in the dHKA (Changer). Proportion of Changer knees was 15% for varus sHKA versus 39% for valgus sHKA (p < 0.001).

Lower limb radiographic measures of coronal alignment have limited value for predicting dynamic measures of alignment during gait.

Background

Achieving a neutral static Hip-Knee-Ankle angle (sHKA) measured on radiographs has been considered a factor of success for total knee arthroplasty (TKA). However, recent studies have shown that sHKA seems to have no effect on TKA survivorship. sHKA is not representative of the dynamic loading occurring during gait, unlike the dynamic HKA (dHKA).

Total knee arthroplasty (TKA) is recognised as an effective treatment for end-staged knee osteoarthritis. Up to 20% of these patients is unfortunately unsatisfied due to anterior knee pain from unknown origin (Bourne and al. 2010). The aim of this study is to compare knee 3D kinematics during gait of patients with anterior knee pain after TKA to an asymptomatic TKA group. Our hypothesis is that the painful TKA group would exhibit known kinematics characteristics during gait that increase patellofemoral (PF) stresses (i.e. dynamic flexion contracture, valgus alignment, valgus collapse or a quick internal tibial rotation movement) compared to the TKA asymptomatic group.

Thirty-eight patients (45 knees) were recruited 12–24 months post-surgery done by one of three experienced orthopaedic surgeons (31 unilateral TKA and seven bilateral TKA, all using the same knee implant). Patients were divided according to their KOOS pain score (with a cut-off at 6/20 to be included in the painful group). The KOOS questionnaire was also used to assess activities of daily living, symptoms, sports and quality of life. A complete clinical and radiological work up was done on the painful group to exclude those with known explanation for pain (i.e. loosening, malrotation, infection and clinical instability). 3D knee kinematics during treadmill walking was captured and computed using the KneeKGTM system.

For the painful and asymptomatic groups, demographic results show respectively: age of 64.4 ± 7.6 and 69.8 ± 8.3 years, BMI of 31.9 ± 5.0 and 28.1 ± 3.6 kg.m−2, speed of 1.8 ± 0.6 and 1.67 ± 0.5 miles/h., and 50% of women in each group. Only age and BMI showed to be statistically different between groups. The painful TKA group exhibited a valgus alignment when walking (at initial contact and during stance, p<0.001). No significant difference has been put forward for the flexion/extension and internal/external tibial rotation.

Since a higher valgus alignment increases the Q angle, which lateralise the patella and increases PF stresses, results provide new insight on origin of symptoms. Conservative treatments for PF pain syndrome have shown to address the valgus alignment and improve symptoms, therefore the next step will be to assess the impact on pain level and alignment during gait of a personalised conservative management for the painful TKA group. Additionally, a study assessing the change in the radiological and dynamic alignment from pre to post surgery could bring valuable insight on the impact of surgical procedure on anterior knee pain.

Accurate and reproducible measurement of three-dimensional shoulder kinematics would contribute to better understanding shoulder mechanics, and therefore to better diagnosing and treating shoulder pathologies. Current techniques of 3D kinematics analysis use external markers (acromial cluster or scapula locator) or medical imaging (MRI or CT-Scan). However those methods present some drawbacks such as skin movements for external markers or cost and irradiation for imaging techniques. The EOS low dose biplanar X-Rays system can be used to track the scapula, humerus and thorax for different arm elevation positions. The aim of this study is to propose a novel method to study scapulo-thoracic kinematics from biplanar X-rays and to assess its reliability during abduction in the scapular plane.

This study is based on the EOS™ system (EOS Imaging, Paris, France), which allows acquisition of 2 calibrated, low dose, orthogonal radiographs with the subject standing at 30 to 40° angle of coronal rotation to the plane of one of the X-ray beams, in order to limit superimposition with the ribcage and spine. Seven abduction positions in the scapular plane were maintained by the subjects for 10 seconds, during X-ray acquisition. Between two positions, the subjects returned at rest position. Arm elevations were approximately 0, 10, 20, 30, 60, 90 and 150° (position 1 to 7). Six subjects were enrolled to perform a reproducibility study based on the 3D reconstructions of 2 experienced observers three times each. For each subject, a personalised 3D reconstruction of the scapula was created. The observer digitises clearly visible anatomical landmarks on both stereoradiographs for each arm position. These landmarks are used to make a first adjustment of a parameterised 3D model of the scapula. This provides a pre-personalised model of the subject's scapula which is then rigidly registered on each pair of X-rays until its retroprojection fits best on the contours that are visible on the X-rays. The thorax coordinate system (CS) was built following the ISB (International Society of Biomechanics) recommendations. The CS associated to the scapula was a glenoid centred CS based on the ellipse which fit on the glenoid rim on the 3D model of scapula. Scapular CS orientation and translation in the thorax CS was calculated following a Y,X,Z angle sequence for each position.

Each 3D reconstruction of the scapula was performed in approximately 30 minutes. The most reproducible rotation was upward/downward rotation (along X axis) with a 95% confidence interval (95% CI) from 2.71° to 3.61°. Internal/external rotation and anterior/posterior tilting were comprised respectively between 5.18° to 8.01° and 5.50° to 7.23° (CI 95%). The most reproducible translation was superior-inferior translation (along Y axis) with a 95% CI from 1.22mm to 2.46mm. Translation along X axis (antero-posterior) and Z axis (medio-lateral) were comprised respectively between 2.49mm to 4.26mm and 2.47mm to 3.30mm (CI 95%).

We presented a new technique for 3D functional quantitative analysis of the scapulo-thoracic joint. This technique can be used with confidence; uncertainty of the measures seems acceptable compared to the literature. Main advantages of this technique are the very low dose irradiation compared to the CT-Scan and the possibility to study arm elevation above 120°.

In this study, we describe a morphological classification for greater tuberosity fractures of the proximal humerus. We divided these fractures into three types: avulsion, split and depression. We retrospectively reviewed all shoulder radiographs showing isolated greater tuberosity fractures in a Level I trauma centre between July 2007 and July 2012. We identified 199 cases where records and radiographs were reviewed and included 79 men and 120 women with a mean age of 58 years (23 to 96). The morphological classification was applied to the first 139 cases by three reviewers on two occasions using the Kappa statistic and compared with the AO and Neer classifications. The inter- and intra-observer reliability of the morphological classification was 0.73 to 0.77 and 0.69 to 0.86, respectively. This was superior to the Neer (0.31 to 0.35/0.54 to 0.63) and AO (0.30 to 0.32/0.59 to 0.65) classifications. The distribution of avulsion, split and depression type fractures was 39%, 41%, and 20%, respectively. This classification of greater tuberosity fractures is more reliable than the Neer or AO classifications. These distinct fracture morphologies are likely to have implications in terms of pathophysiology and surgical technique.

Cite this article: Bone Joint J 2014;96-B:646–51.

Purpose: Gait analysis has become an innovative approach to assess the biomechanical adaptations due to an ACL injury. However, interpreting the large amount of data collected often requires an expert. Therefore, there is a need to develop an automatic method capable to distinguish kinetic pattern of an ACL deficient patients from an asymptomatic population.

Method: 26 ACL deficient patients and 30 asymptomatic participants took part in a treadmill gait analysis. 3D ground reaction forces (vertical, medio-lateral and anterior-posterior) were collected using the ADAL 3D treadmill. Features were extracted from the 3D ground reaction forces as a function of time and then classified by the nearest neighbour rule using a wavelet decomposition method. The classification method was tested on our data base of 56 participants.

Results: The proposed classification method obtained an accuracy of 90%. The classification accuracy per class was higher for the ACL deficient group allowing classifying correctly 25 out of 26 ACL deficient patient. 25 out of the 30 asymptomatic participants were properly classified.

Conclusion: This study shows that an automatic objective computer method could be used in a clinical setting to help diagnose an anterior cruciate ligament injury during a gait analysis evaluation. Future studies should apply this method on a larger database including data from patients with other musculoskeletal pathologies to help diagnose other injuries.

Purpose: To determine if some subsets of healthy subjects displayed other than a typical gait pattern and to identify which subsets have similar kinematic pattern to patients with knee osteoarthritis.

Methods: The healthy subject dataset consisted of 106 asymptomatic volunteers. These subjects were over 17 years of age, pain-free, had no record of surgery to the lower limb and no evidence or history of arthritic disease at the time of testing. The patient population consisted of 12 patients diagnosed with knee OA, evaluated within 6 months prior to the tests. The 3D movements of right knee joint were recorded using a functional knee analyzer with magnetic sensors while subjects walked on a treadmill at their own preferred speed. The magnetic sensors are non-invasive electromagnetic devices, which track the 3D positions and orientations of sensors relative to a source. The system has been shown to be accurate, especially in the frontal and transversal planes. K-means clustering analysis was chosen to identify the gait patterns among healthy subjects based on three components of the knee joint angles, and analyses of variance were performed to determine which parameters were different between subsets.

Results: Three gait groups or patterns were identified in the healthy subjects. The first group (G1) was characterized by a kinematic profile similar to the OA group. The second group (G2) had the highest external rotation angle, which was significantly different from OA group. The abduction angles were always greater in the G2 and G3 than in the OA group. This might be attributed to a valgus static alignment in G2 and G3 comparing to a varus alignment in the patient with OA.

Conclusions: The newly developed functional knee analyzer provided a non-invasive way to accurately measure 3D kinematic data which enabled cluster analysis to distinguish three gait patterns from 106 healthy subjects. The results suggested a strong correlation between static alignment and dynamic ad-abduction angles during the gait, which need to be investigated. Funding: Other Education Grant Funding Parties: NSERC, CIHR and FCAR