Relevant factors affecting the outcome of ultrasound guided foam sclerotherapy of the great saphenous vein

Ultrasound guided foam sclerotherapy (UGFS) constitutes a valid ablative treatment for superficial vein diseases for the great saphenous vein (GSV), but no standardized protocol for its execution has yet been defined. Different variable factors involved in this procedure influence the final outcome and clinical results. The aim of our study was to analyze the respective influence on efficacy and side effects of three variable factors (foam volume, foam concentration, and contact time between the foam and the endothelium) for UGFS procedures for GSV insufficiency in order to select the best protocol for treatment. A retrospective analysis was made of UGFS procedures (190 patients, 201 legs) performed for GSV insufficiency in our institute from January 2007 to January 2010. All great saphenous veins included in our study exhibited a trans-ostial reflux and caliber range was 7-11 mm. In all cases, foam was prepared according to the Tessari method, using polidocanol (POL) and a gas mixture of CO2 (70%) and filtered room air (30%), in a proportion of 1:4. A single injection procedure in the GSV was performed under Doppler ultrasound guidance at mid to lower third of the thigh. Legs were randomly assigned to one of three different treatment protocols: - Group A (71 legs): POL 3%, mean foam volume 4.5 cc, intermittent groin pressure 5 min, supine bed rest 10 min; - Group B (61 legs): POL 2%, mean foam volume 9 cc, intermittent groin pressure 5 min, supine bed rest 10 min; - Group C (69 legs): POL 2%, mean foam volume 9 cc, continuous groin pressure 5 min followed by intermittent groin pressure 5 min, continuous leg compression 5 min, supine bed rest 10 min. Efficacy of treatment and occurrence of side effects were evaluated in each group at two weeks and again at two years after the procedure and the cumulative results compared. Analysis of outcomes did not show any significant difference between the complete obliteration rate (P=0.825) or occurrence of local inflammatory reactions (P=0.883) between legs in Group A and in Group B. However, a significantly better outcome was observed between the complete obliteration rates and the local inflammatory reaction for legs in Group C compared to both legs in Group A (P=0.020 and P=0.015, respectively) and legs in Group B (P=0.013 and P=0.018, respectively). The type of procedure did not seem to have any effect on the extent of recanalization (over or less than 50% of the original lumen). No major adverse events such as deep vein thrombosis, significant allergic reactions, or serious neurological events occurred in any patient in any group. Further studies are still necessary to identify the best concentration ratios, volumes and length of contact time between foam and endothelium according to class size of specific veins to promote possible standardization of the procedure. However, measures to increase the contact time between foam and endothelium were shown to improve late results. In addition, the same efficacy and side effects are observed with lower POL concentration if foam volumes are increased

Real-time Hybrid Locomotion Mode Recognition for Lower-limb Wearable Robots

Real-time recognition of locomotion-related activities is a fundamental skill that the controller of lower-limb wearable robots should possess. Subject-specific training and reliance on electromyographic interfaces are the main limitations of existing approaches. This study presents a novel methodology for real-time locomotion mode recognition of locomotion-related activities in lower-limb wearable robotics. A hybrid classifier can distinguish among seven locomotion-related activities. First, a time-based approach classifies between static and dynamical states based on gait kinematics data. Second, an event-based fuzzy logic method triggered by foot pressure sensors operates in a subject-independent fashion on a minimal set of relevant biomechanical features to classify among dynamical modes. The locomotion mode recognition algorithm is implemented on the controller of a portable powered orthosis for hip assistance. An experimental protocol is designed to evaluate the controller performance in an out-of-lab scenario without the need for a subject-specific training. Experiments are conducted on six healthy volunteers performing locomotion-related activities at slow, normal, and fast speeds under the zero-torque and assistive mode of the orthosis. The overall accuracy rate of the controller is 99.4% over more than 10,000 steps, including seamless transitions between different modes. The experimental results show a successful subject-independent performance of the controller for wearable robots assisting locomotion-related activities