Evgenios I. Kornaropoulos

Magnetic Resonance Imaging Analysis of Rotational Alignment in Patients With Patellar Dislocations

Background: The role of anatomic risk factors in patellofemoral instability is not yet fully understood, as they have been observed in patients either alone or in combination and in different degrees of severity. Purpose: To prospectively analyze rotational limb alignment in patients with patellofemoral instability and in controls using magnetic resonance imaging (MRI). Study Design: Cross-sectional study; Level of evidence, 3. Methods: Thirty patients (mean age, 22.9 y; range, 12-41 y) with a history of patellar dislocation and 30 age- and sex-matched controls (mean age, 25.2 y; range, 16-37 y) were investigated. The patients underwent MRI of the leg at 1.5 T using a peripheral angiography coil and a T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) sequence for measuring femoral antetorsion, tibial torsion, knee rotation, and mechanical axis deviation (MAD). The mean values of these parameters were compared between patients and controls. In addition, the patients underwent an assessment to determine the influence of rotational limb alignment on lateral trochlear inclination, trochlear facet asymmetry, trochlear depth, Insall-Salvati index, and tibial tuberosity–trochlear groove distance. Results: Patients had 1.56-fold higher mean femoral antetorsion (20.3° ± 10.4° vs 13.0° ± 8.4°; P < .01) and 1.6-fold higher knee rotation (9.4° ± 5.0° vs 5.7° ± 4.3°; P < .01) compared with controls. Moreover, patients had 2.9 times higher MAD (0.81 ± 0.75 mm vs −0.28 ± 0.87 mm; P < .01). Differences in tibial torsion were not significant. Also, there were no significant correlations between parameters of rotational alignment and standard anatomic risk factors. Conclusion: Our results suggest that some patients with nontraumatic patellar instability have greater internal femoral rotation, greater knee rotation, and a tendency for genu valgum compared with healthy controls. Rotational malalignment may be a primary risk factor in patellar dislocation that has so far been underestimated.

Patellofemoral joint contact forces during activities with high knee flexion.

The patellofemoral (PF) joint plays an essential role in knee function, but little is known about the in vivo loading conditions at the joint. We hypothesized that the forces at the PF joint exceed the tibiofemoral (TF) forces during activities with high knee flexion. Motion analysis was performed in two patients with telemetric knee implants during walking, stair climbing, sit‐to‐stand, and squat. TF and PF forces were calculated using a musculoskeletal model, which was validated against the simultaneously measured in vivo TF forces, with mean errors of 10% and 21% for the two subjects. The in vivo peak TF forces of 2.9–3.4 bodyweight (BW) varied little across activities, while the peak PF forces showed significant variability, ranging from less than 1 BW during walking to more than 3 BW during high flexion activities, exceeding the TF forces. Together with previous in vivo measurements at the hip and knee, the PF forces determined here provide evidence that peak forces across these joints reach values of around 3 BW during high flexion activities, also suggesting that the in vivo loading conditions at the knee can only be fully understood if the forces at the TF and the PF joints are considered together.

Effective marker placement for functional identification of the centre of rotation at the hip

The accuracy and precision of quantifying musculoskeletal kinematics, and particularly determining the centre of rotation (CoR) at the hip joint, using skin marker based motion analysis is limited by soft tissue artefact (STA). We posed the question of whether the contribution of individual markers towards improving the precision of the functional joint centre using marker based methods could be assessed, and then utilised to allow effective marker placement for determination of the CoR at the hip. Sixty-three retro-reflective skin markers were placed to encompass the thighs of seven healthy subjects, together with a set of sixteen markers on the pelvis. The weighted optimal common shape technique (wOCST) was then applied to determine the weighting, or importance, of each marker for identifying the centre of rotation at the hip. The markers with the highest weightings over all subjects and measurements were determined that identified the HJC with the highest precision. The use of six markers in selected regions (two anterior, two lateral and two posterior) allowed the HJC to be determined with a similar precision to the complete set of 63 markers, with the determined regions predominantly distant from the hip joint, excluding areas associated with the bellies of large muscles and therefore large motion artefact from muscle activity. The novel approach presented here allows an understanding of each markers contribution towards a precise joint determination, and therefore enables the targeted placement of markers for reliable assessment of musculoskeletal kinematics.

Frontal plane alignment: An imageless method to predict the mechanical femoral–tibial angle (mFTA) based on functional determination of joint centres and axes

Lower limb alignment is important for the internal loading conditions in the knee. In this study, we aimed to evaluate a new imageless, non-invasive method for quantifying frontal plane alignment by direct comparison against CT. To determine the mechanical femoral-tibial angle (mFTA), functional posture analysis was performed in 15 limbs (13 individuals) using previously published methods for the minimisation of skin marker artefact together with the functional identification of joints, and compared against a published regression method. Whilst the average Functional-mFTA (1.3 + or - 2.3) was not significantly different (p > 0.25) from the CT-mFTA (1.5 + or - 2.1), the Regression-mFTA (4.7 + or - 5.6) showed a significant error (p < 0.01). The Functional-mFTA correlated significantly (R = 0.91; p < 0.0001), with a small bias (0.3 degrees) and agreed better with the CT-mFTA than the Regression-mFTA (R = 0.76; p < 0.001), which had a bias of 3.4 degrees. The results demonstrate that the mFTA can be quantified accurately using an imageless, non-invasive functional approach, which also offers greater accuracy over regression methods.These new techniques could provide an accurate, non-invasive approach for quantifying frontal plane alignment, particularly in cases where X-rays may not be available.