Current methods of anterior talofibular ligament (ATFL) reconstruction fail to restore the stability of the native ATFL. Therefore, augmented anatomic ATFL reconstruction gained popularity in patients with attenuated tissue and additional stress on the lateral ankle ligament complex. The aim of the present study was to evaluate the biomechanical stability of the InternalBrace^® (Arthrex Inc., Naples, FL, USA), a tape augmentation designed to augment the traditional Broström procedure.

Pathologic fractures in patients with bone metastases are a common problem in clinical orthopaedic routine. On one hand recognition of metastatic lesions, which are at a high risk of fracture, is essential for timely prophylactic fixation, while on the other hand patients with a low risk of pathologic fractures should be spared from overtreatment. The purpose of this review is to identify all methods for fracture risk evaluation in patients with femoral metastases in the literature and to evaluate their predictive values in clinical applications. A MEDLINE database literature research was conducted in order to identify clinical scoring systems, conclusions from prospective and retrospective radiologic and/or clinical studies, as well as data from biomechanical experiments, numerical computational methods, and computer simulations. The search identified 441 articles of which 18 articles met the inclusion criteria; 4 more articles were identified from citations of the primarily found studies. In principle there are two distinct methodologies, namely fracture risk prediction factors based on clinical and radiological data such as the most deployed the Mirels' score and fracture risk prediction based on engineering methods. Fracture risk prediction using Mirels' score, based on pure clinical data, shows a negative predictive value between 86 and 100%, but moderate to poor results in predicting non-impending fractures with a positive predictive value between 23 and 70%. Engineering methods provide a high accuracy (correlation coefficient between ex vivo and results from numerical calculations: 0.68 < r2 < 0.96) in biomechanical lab experiments, but have not been applied to clinical routine yet. This review clearly points out a lack of adequate clinical methods for fracture risk prediction in patients with femoral metastases. Today's golden standard, the Mirels' score leads to an overtreatment. Whereas, engineering methods showed high potential but require a clinical validation. In future definition of patient-specific, quantitative risk factor based modelling methods could serve as useful decision support for individualized treatment strategies in patients with a metastatic lesion.

Background: This study aimed to provide an extensive and up-to-date analysis of running-related injuries (RRI) and analyze a broad range of contributing factors for a large heterogeneous and non-selected running population from Central Europe. Methods: Anthropometric, training, footwear, anatomic malalignment, and injury data from 196 injured runners were assessed case-controlled and retrospectively. Univariate and multivariate regression models were developed to identify associated factors for specific injury locations and diagnoses. Results: The majority of patients were female (56%). Three most frequently observed malalignments included varus knee alignment, pelvic obliquity, and patellar squinting. The most common injuries were the patellofemoral pain syndrome (PFPS), the iliotibial band friction syndrome (ITBFS), patellar tendinopathy, spinal overload, and ankle instability. A number of contributing factors were identified. Previous injury history was a contributing factor for knee injuries and ITBFS. Lower training load was reported with a higher incidence of PFPS, while a higher training load was positively associated with injuries of the lower leg. Runners with a higher body mass index (BMI) were at a significantly higher risk for lower back injuries. Conclusions: Running-related injuries are multifactorial associated with a combination of variables including personal data, training load, anatomic malalignments, and injury history. They can furthermore result from a lack of experience/training as well as from overuse. Suffering a specific RRI of high risk could be defined based on individual predispositions and help to induce appropriate training balance.

Predicting pathologic fractures in femora with metastatic lesions remains a clinical challenge. Currently used guidelines are inaccurate, especially to predict non-impeding fractures. This study evaluated the ability of a nonlinear quantitative computed tomography (QCT)-based homogenized voxel finite element (hvFE) model to predict patient-specific pathologic fractures. The hvFE model was generated highly automated from QCT images of human femora. The femora were previously loaded in a one-legged stance setup in order to assess stiffness, failure load, and fracture location. One femur of each pair was tested in its intact state, while the contralateral femur included a simulated lesion on either the superolateral- or the inferomedial femoral neck. The hvFE model predictions of the stiffness (0.47 < R² < 0.94), failure load (0.77 < R² < 0.98), and exact fracture location (68%) were in good agreement with the experimental data. However, the model underestimated the failure load by a factor of two. The hvFE models predicted significant differences in stiffness and failure load for femora with superolateral- and inferomedial lesions. In contrast, standard clinical guidelines predicted identical fracture risk for both lesion sites. This study showed that the subject-specific QCT-based hvFE model could predict the effect of metastatic lesions on the biomechanical behaviour of the proximal femur with moderate computational time and high level of automation and could support treatment strategy in patients with metastatic bone disease.