Altered knee kinematics after posterior cruciate ligament single-bundle reconstruction-a comprehensive prospective biomechanical in vivo analysis.

Purpose: Passive tibiofemoral anterior-posterior (AP) laxity has been extensively investigated after posterior cruciate ligament (PCL) single-bundle reconstruction. However, the PCL also plays an important role in providing rotational stability in the knee. Little is known in relation to the effects of PCL single-bundle reconstruction on passive tibiofemoral rotational laxity. Gait biomechanics after PCL reconstruction are even less understood. The aim of this study was a comprehensive prospective biomechanical in vivo analysis of the effect of PCL single-bundle reconstruction on passive tibiofemoral rotational laxity, passive anterior-posterior laxity, and gait pattern. Methods: Eight patients undergoing PCL single-bundle reconstruction (seven male, one female, mean age 35.6 ± 6.6 years, BMI 28.0 ± 3.6 kg/m2) were analyzed preoperatively and 6 months postoperatively. Three of the eight patients received additional posterolateral corner (PLC) reconstruction. Conventional stress radiography was used to evaluate passive translational tibiofemoral laxity. A previously established rotometer device with a C-arm fluoroscope was used to assess passive tibiofemoral rotational laxity. Functional gait analysis was used to examine knee kinematics during level walking. Results: The mean side-to-side difference (SSD) in passive posterior translation was significantly reduced postoperatively (12.1 ± 4.4 mm vs. 4.3 ± 1.8 mm; p < 0.01). A significant reduction in passive tibiofemoral rotational laxity at 90° knee flexion was observed postoperatively (27.8° ± 7.0° vs. 19.9° ± 7.5°; p = 0.02). The range of AP tibiofemoral motion during level walking was significantly reduced in the reconstructed knees when compared to the contralateral knees at 6-month follow-up (16.6 ± 2.4 mm vs. 13.5 ± 1.6 mm; p < 0.01). Conclusion: PCL single-bundle reconstruction with optional PLC reconstruction reduces increased passive tibiofemoral translational and rotational laxity in PCL insufficient knees. However, increased passive tibiofemoral translational laxity could not be fully restored and patients showed altered knee kinematics with a significantly reduced range of tibiofemoral AP translation during level walking at 6-month follow-up. The findings of this study indicate a remaining lack of restoration of biomechanics after PCL single-bundle reconstruction in the active and passive state, which could be a possible cause for joint degeneration after PCL single-bundle reconstruction.

Patient-specific resurfacing implant knee surgery in subjects with early osteoarthritis results in medial pivot and lateral femoral rollback during flexion: a retrospective pilot study.

PURPOSE: Metallic resurfacing implants have been developed for the treatment of early, small, condylar and trochlear osteoarthritis (OA) lesions. They represent an option for patients who do not fulfill the criteria for unicompartmental knee arthroplasty (UKA) or total knee arthroplasty (TKA) or are too old for biological treatment. Although clinical evidence has been collected for different resurfacing types, the in vivo post-operative knee kinematics remain unknown. The present study aims to analyze the knee kinematics in subjects with patient-specific episealer implants. This study hypothesized that patient-specific resurfacing implants would lead to knee kinematics close to healthy knees, resulting in medial pivot and a high degree of femoral rollback during flexion. METHODS: Retrospective study design. Fluoroscopic analysis during unloaded flexion-extension and loaded lunge was conducted at > 12 months post-surgery in ten episealer knees, and compared to ten healthy knees. Pre- and post-operative clinical data of the episealer knees were collected using a visual analog scale (VAS), the EQ 5d Health, and the Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaires. RESULTS: A consistent medial pivot was observed in both episealer and healthy knees. Non-significant differences were found in the unloaded (p = 0.15) and loaded (p = 0.51) activities. Although lateral rollback was observed in both groups, it was significantly higher for the episealer knees in both the unloaded (p = 0.02) and loaded (p = 0.01) activities. Coupled axial rotation was significantly higher in the unloaded (p = 0.001) but not in the loaded (p = 0.06) activity in the episealer knees. Improved scores were observed at 1-year post-surgery in the episealer subjects for the VAS (p = 0.001), KOOS (p = 0.001) and EQ Health (p = 0.004). CONCLUSION: At 12 month follow-up, a clear physiological knee kinematics pattern of medial pivot, lateral femoral rollback and coupled axial external femoral rotation during flexion was observed in patients treated with an episealer resurfacing procedure. However, higher femoral rollback and axial external rotation in comparison to healthy knees was observed, suggesting possible post-operative muscle weakness and consequent insufficient stabilization at high flexion.

PCL insufficient patients with increased translational and rotational passive knee joint laxity have no increased range of anterior-posterior and rotational tibiofemoral motion during level walking.

Passive translational tibiofemoral laxity has been extensively examined in posterior cruciate ligament (PCL) insufficient patients and belongs to the standard clinical assessment. However, objective measurements of passive rotational knee laxity, as well as range of tibiofemoral motion during active movements, are both not well understood. None of these are currently quantified in clinical evaluations of patients with PCL insufficiency. The objective of this study was to quantify passive translational and rotational knee laxity as well as range of anterior-posterior and rotational tibiofemoral motion during level walking in a PCL insufficient patient cohort as a basis for any later clinical evaluation and therapy. The laxity of 9 patient knees with isolated PCL insufficiency or additionally posterolateral corner (PLC) insufficiency (8 males, 1 female, age 36.78 ± 7.46 years) were analysed and compared to the contralateral (CL) knees. A rotometer device with a C-arm fluoroscope was used to assess the passive tibiofemoral rotational laxity while stress radiography was used to evaluate passive translational tibiofemoral laxity. Functional gait analysis was used to examine the range of anterior-posterior and rotational tibiofemoral motion during level walking. Passive translational laxity was significantly increased in PCL insufficient knees in comparison to the CL sides (15.5 ± 5.9 mm vs. 3.7 ± 1.9 mm, p < 0.01). Also, passive rotational laxity was significantly higher compared to the CL knees (26.1 ± 8.2° vs. 20.6 ± 5.6° at 90° knee flexion, p < 0.01; 19.0 ± 6.9° vs. 15.5 ± 5.9° at 60° knee flexion, p = 0.04). No significant differences were observed for the rotational (16.3 ± 3.7° vs. 15.2 ± 3.6°, p = 0.43) and translational (17.0 ± 5.4 mm vs. 16.1 ± 2.8 mm, p = 0.55) range of anterior-posterior and rotational tibiofemoral motion during level walking conditions for PCL insufficient knees compared to CL knees respectively. The present study illustrates that patients with PCL insufficiency show a substantial increased passive tibiofemoral laxity, not only in tibiofemoral translation but also in tibiofemoral rotation. Our data indicate that this increased passive multiplanar knee joint laxity can be widely compensated during level walking. Further studies should investigate progressive changes in knee joint laxity and kinematics post PCL injury and reconstruction to judge the individual need for therapy and effects of physiotherapy such as quadriceps force training on gait patterns in PCL insufficient patients.

Statistical Shape Models: Understanding and Mastering Variation in Anatomy.

In our chapter we are describing how to reconstruct three-dimensional anatomy from medical image data and how to build Statistical 3D Shape Models out of many such reconstructions yielding a new kind of anatomy that not only allows quantitative analysis of anatomical variation but also a visual exploration and educational visualization. Future digital anatomy atlases will not only show a static (average) anatomy but also its normal or pathological variation in three or even four dimensions, hence, illustrating growth and/or disease progression.Statistical Shape Models (SSMs) are geometric models that describe a collection of semantically similar objects in a very compact way. SSMs represent an average shape of many three-dimensional objects as well as their variation in shape. The creation of SSMs requires a correspondence mapping, which can be achieved e.g. by parameterization with a respective sampling. If a corresponding parameterization over all shapes can be established, variation between individual shape characteristics can be mathematically investigated.We will explain what Statistical Shape Models are and how they are constructed. Extensions of Statistical Shape Models will be motivated for articulated coupled structures. In addition to shape also the appearance of objects will be integrated into the concept. Appearance is a visual feature independent of shape that depends on observers or imaging techniques. Typical appearances are for instance the color and intensity of a visual surface of an object under particular lighting conditions, or measurements of material properties with computed tomography (CT) or magnetic resonance imaging (MRI). A combination of (articulated) Statistical Shape Models with statistical models of appearance lead to articulated Statistical Shape and Appearance Models (a-SSAMs).After giving various examples of SSMs for human organs, skeletal structures, faces, and bodies, we will shortly describe clinical applications where such models have been successfully employed. Statistical Shape Models are the foundation for the analysis of anatomical cohort data, where characteristic shapes are correlated to demographic or epidemiologic data. SSMs consisting of several thousands of objects offer, in combination with statistical methods or machine learning techniques, the possibility to identify characteristic clusters, thus being the foundation for advanced diagnostic disease scoring.

An efficient Riemannian statistical shape model using differential coordinates: With application to the classification of data from the Osteoarthritis Initiative.

We propose a novel Riemannian framework for statistical analysis of shapes that is able to account for the nonlinearity in shape variation. By adopting a physical perspective, we introduce a differential representation that puts the local geometric variability into focus. We model these differential coordinates as elements of a Lie group thereby endowing our shape space with a non-Euclidean structure. A key advantage of our framework is that statistics in a manifold shape space becomes numerically tractable improving performance by several orders of magnitude over state-of-the-art. We show that our Riemannian model is well suited for the identification of intra-population variability as well as inter-population differences. In particular, we demonstrate the superiority of the proposed model in experiments on specificity and generalization ability. We further derive a statistical shape descriptor that outperforms the standard Euclidean approach in terms of shape-based classification of morphological disorders.