Videofluoroscopic Evaluation of the Influence of a Gradually Reducing Femoral Radius on Joint Kinematics During Daily Activities in Total Knee Arthroplasty.

BACKGROUND: Paradoxical anterior translation in midflexion is reduced in total knee arthroplasties (TKAs) with a gradually reducing femoral radius, when compared to a 2-radii design. This reduction has been shown in finite element model simulations, in vitro tests, intraoperatively, and recently also in vivo during a lunge and unloaded flexion-extension. However, TKA kinematics are task dependent and this reduction has not been tested for gait activities. METHODS: Thirty good outcome subjects (≥1 year postoperatively) with a unilateral cruciate-retaining TKA with a gradually reducing (n = 15) or dual (n = 15) femoral radius design were assessed during 5 complete cycles of level walking, stair descent (0.18-m steps), deep knee bend, and sitting down onto and standing up from a chair, using a moving fluoroscope (25 Hz, 1 ms shutter time). Kinematic data were extracted by 2D/3D image registration. RESULTS: Tibiofemoral ranges of motion for flexion-extension, abduction-adduction, internal-external rotation, and anteroposterior (AP) translation were similar for both groups, whereas the pattern of AP translation-flexion-coupling differed. The subjects with the dual-radii design showed a sudden change in direction of AP translation around 30° of flexion, which was not present in the subjects with the gradually reducing femoral radius design. CONCLUSION: Through the unique ability of moving fluoroscopy, the present study confirmed that the gradually reducing femoral radii eliminated the paradoxical sudden anterior translation at 30° present in the dual-radii design in vivo during daily activities, including gait and stair descent.

Development of VariLeg, an exoskeleton with variable stiffness actuation: first results and user evaluation from the CYBATHLON 2016.

BACKGROUND: Powered exoskeletons are a promising approach to restore the ability to walk after spinal cord injury (SCI). However, current exoskeletons remain limited in their walking speed and ability to support tasks of daily living, such as stair climbing or overcoming ramps. Moreover, training progress for such advanced mobility tasks is rarely reported in literature. The work presented here aims to demonstrate the basic functionality of the VariLeg exoskeleton and its ability to enable people with motor complete SCI to perform mobility tasks of daily life. METHODS: VariLeg is a novel powered lower limb exoskeleton that enables adjustments to the compliance in the leg, with the objective of improving the robustness of walking on uneven terrain. This is achieved by an actuation system with variable mechanical stiffness in the knee joint, which was validated through test bench experiments. The feasibility and usability of the exoskeleton was tested with two paraplegic users with motor complete thoracic lesions at Th4 and Th12. The users trained three times a week, in 60 min sessions over four months with the aim of participating in the CYBATHLON 2016 competition, which served as a field test for the usability of the exoskeleton. The progress on basic walking skills and on advanced mobility tasks such as incline walking and stair climbing is reported. Within this first study, the exoskeleton was used with a constant knee stiffness. RESULTS: Test bench evaluation of the variable stiffness actuation system demonstrate that the stiffness could be rendered with an error lower than 30 Nm/rad. During training with the exoskeleton, both users acquired proficient skills in basic balancing, walking and slalom walking. In advanced mobility tasks, such as climbing ramps and stairs, only basic (needing support) to intermediate (able to perform task independently in 25% of the attempts) skill levels were achieved. After 4 months of training, one user competed at the CYBATHLON 2016 and was able to perform 3 (stand-sit-stand, slalom and tilted path) out of 6 obstacles of the track. No adverse events occurred during the training or the competition. CONCLUSION: Demonstration of the applicability to restore ambulation for people with motor complete SCI was achieved. The CYBATHLON highlighted the importance of training and gaining experience in piloting an exoskeleton, which were just as important as the technical realization of the robot.

Interpretation of natural tibio-femoral kinematics critically depends upon the kinematic analysis approach: A survey and comparison of methodologies.

While there is general agreement on the transverse plane knee joint motion for loaded flexion activities, its kinematics during functional movements such as level walking are discussed more controversially. One possible cause of this controversy could originate from the interpretation of kinematics based on different analysis approaches. In order to understand the impact of these approaches on the interpretation of tibio-femoral motion, a set of dynamic videofluoroscopy data presenting continuous knee bending and complete cycles of walking in ten subjects was analysed using six different kinematic analysis approaches. Use of a functional flexion axis resulted in significantly smaller ranges of condylar translation compared to anatomical axes and contact approaches. All contact points were located significantly more anteriorly than the femur fixed axes after 70° of flexion, but also during the early/mid stance and late swing phases of walking. Overall, a central to medial transverse plane centre of rotation was found for both activities using all six kinematic analysis approaches, although individual subjects exhibited lateral centres of rotation using certain approaches. The results of this study clearly show that deviations from the true functional axis of rotation result in kinematic crosstalk, suggesting that functional axes should be reported in preference to anatomical axes. Contact approaches, on the other hand, can present additional information on the local tibio-femoral contact conditions. To allow a more standardised comparison and interpretation of tibio-femoral kinematics, results should therefore be reported using at least a functionally determined axis and possibly also a contact point approach.

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results.

Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder translating DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties could enable clinical review of the most uncertain regions, thereby building trust and paving the way toward clinical translation. Several uncertainty estimation methods have recently been introduced for DL medical image segmentation tasks. Developing scores to evaluate and compare the performance of uncertainty measures will assist the end-user in making more informed decisions. In this study, we explore and evaluate a score developed during the BraTS 2019 and BraTS 2020 task on uncertainty quantification (QU-BraTS) and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation. This score (1) rewards uncertainty estimates that produce high confidence in correct assertions and those that assign low confidence levels at incorrect assertions, and (2) penalizes uncertainty measures that lead to a higher percentage of under-confident correct assertions. We further benchmark the segmentation uncertainties generated by 14 independent participating teams of QU-BraTS 2020, all of which also participated in the main BraTS segmentation task. Overall, our findings confirm the importance and complementary value that uncertainty estimates provide to segmentation algorithms, highlighting the need for uncertainty quantification in medical image analyses. Finally, in favor of transparency and reproducibility, our evaluation code is made publicly available at https://github.com/RagMeh11/QU-BraTS.