Arthroscopic anatomical reconstruction of lateral collateral ligaments with ligament advanced reinforcement system artificial ligament for chronic ankle instability

BACKGROUND Recently,the use of ligament advanced reinforcement system(LARS)artificial ligament,a new graft which has several unique advantages such as no donor-site morbidity,early recovery and no risk of disease transmission which has been a significant breakthrough for anatomical ligament reconstruction.Growing studies suggested that the special design of the LARS ligament with open fibers in its intra-articular part was believed to be more resistant to torsional fatigue and wearing.However,the safety and efficacy of LARS artificial ligament for ankle joint lateral collateral ankle ligament reconstruction has not been defined to date.AIM To evaluate the clinical results of all-arthroscopic anatomical reconstruction of ankle joint lateral collateral ligaments with the LARS artificial ligament for chronic ankle instability.METHODS Twenty-two patients with chronic lateral instability underwent anatomical reconstruction of the lateral collateral ligaments of ankle with LARS artificial ligament.The visual analogue score(VAS),American Orthopaedic Foot and Ankle Society score(AOFAS score)and Karlsson score were used to evaluate the clinical results before and after surgery.RESULTS A total of 22 patients(22 ankles)were followed up for a mean of 12 mo.All patients reported significant improvement compared to their preoperative status.The mean AOFAS score improved from 42.3±4.9 preoperatively to 90.4±6.7 postoperatively.The mean Karlsson score improved from 38.5±3.2 preoperatively to 90.1±7.8 postoperatively.The mean VAS score improved from 1.9±2.5 preoperatively to 0.8±1.7 postoperatively.CONCLUSION All-arthroscopic anatomical reconstruction of the lateral collateral ligaments with LARS artificial ligament achieved a satisfactory surgical outcome for chronic ankle instability.

Characteristics of bone tunnel changes after anterior cruciate ligament reconstruction using Ligament Advanced Reinforcement System artificial ligament

Background There are different materials used for anterior cruciate ligament （ACL） reconstruction. It has been reported that both autologous grafts and allografts used in ACL reconstruction can cause bone tunnel enlargement. This study aimed to observe the characteristics of bone tunnel changes and possible causative factors following ACL reconstruction using Ligament Advanced Reinforcement System （LARS） artificial ligament. Methods Forty-three patients underwent ACL reconstruction using LARS artificial ligament and were followed up for 3 years. X-ray and CT examinations were performed at 1,3, 6, 12, 24, and 36 months after surgery, to measure the width of tibial and femoral tunnels. Knee function was evaluated according to the Lysholm scoring system. The anterior and posterior stability of the knee was measured using the KT-1000 arthrometer. Results According to the Peyrache grading method, grade 1 femoral bone tunnel enlargement was observed in three cases six months after surgery. No grade 2 or grade 3 bone tunnel enlargement was found. The bone tunnel enlargement in the three cases was close to the articular surface with an average tunnel enlargement of （2.5＋0.3） mm. Forty cases were evaluated as grade 0. The average tibial and femoral tunnel enlargements at the last follow-up were （0.8＋0.3） and （1.1＋0.3） mm, respectively. There was no statistically significant difference in bone tunnel width changes at different time points （P 〉0.05）. X-ray and CT measurements were consistent. Conclusions There was no marked bone tunnel enlargement immediately following ACL reconstruction using LARS artificial ligament. Such enlargement may, however, result from varying grafting factors involving the LARS artificial ligament or from different fixation methods.

Traffic signal control in mixed traffic environment based on advance decision and reinforcement learning

Reinforcement learning-based traffic signal control systems (RLTSC) can enhance dynamic adaptability, save vehicle travelling timeand promote intersection capacity. However, the existing RLTSC methods do not consider the driver’s response time requirement, sothe systems often face efficiency limitations and implementation difficulties.We propose the advance decision-making reinforcementlearning traffic signal control (AD-RLTSC) algorithm to improve traffic efficiency while ensuring safety in mixed traffic environment.First, the relationship between the intersection perception range and the signal control period is established and the trust region state(TRS) is proposed. Then, the scalable state matrix is dynamically adjusted to decide the future signal light status. The decision will bedisplayed to the human-driven vehicles (HDVs) through the bi-countdown timer mechanism and sent to the nearby connected automatedvehicles (CAVs) using the wireless network rather than be executed immediately. HDVs and CAVs optimize the driving speedbased on the remaining green (or red) time. Besides, the Double Dueling Deep Q-learning Network algorithm is used for reinforcementlearning training;a standardized reward is proposed to enhance the performance of intersection control and prioritized experiencereplay is adopted to improve sample utilization. The experimental results on vehicle micro-behaviour and traffic macro-efficiencyshowed that the proposed AD-RLTSC algorithm can simultaneously improve both traffic efficiency and traffic flow stability.