A Protocol for Comprehensive Analysis of Gait in Individuals with Incomplete Spinal Cord Injury.

This is a protocol for comprehensive analysis of gait and affecting factors in individuals with incomplete paraplegia due to spinal cord injury (SCI). A SCI is a devastating event affecting both sensory and motor functions. Due to better care, the SCI population is changing, with a greater proportion retaining impaired ambulatory function. Optimizing ambulatory function after SCI remains challenging. To investigate factors influencing optimal ambulation, a multi-professional research project was grounded with expertise from clinical rehabilitation, neurophysiology, and biomechanical engineering from Karolinska Institutet, the Spinalis Unit at Aleris Rehab Station (Sweden's largest center for specialized neurorehabilitation), and the Promobilia MoveAbility Lab at KTH Royal Institute of Technology. Ambulatory adults with paraplegia will be consecutively invited to participate. Muscle strength, sensitivity, and spasticity will be assessed, and energy expenditure, 3D movements, and muscle function (EMG) during gait and submaximal contractions will be analyzed. Innovative computational modeling and data-driven analyses will be performed, including the identification of clusters of similar movement patterns among the heterogeneous population and analyses that study the link between complex sensorimotor function and movement performance. These results may help optimize ambulatory function for persons with SCI and decrease the risk of secondary conditions during gait with a life-long perspective.

Clinical phenotype and genetic function analysis of a family with hypomyelinating leukodystrophy-7 caused by POLR3A mutation.

Hypomyelinating leukodystrophy (HLD) is a rare genetic heterogeneous disease that can affect myelin development in the central nervous system. This study aims to analyze the clinical phenotype and genetic function of a family with HLD-7 caused by POLR3A mutation. The proband (IV6) in this family mainly showed progressive cognitive decline, dentin dysplasia, and hypogonadotropic hypogonadism. Her three old brothers (IV1, IV2, and IV4) also had different degrees of ataxia, dystonia, or dysarthria besides the aforementioned manifestations. Their brain magnetic resonance imaging showed bilateral periventricular white matter atrophy, brain atrophy, and corpus callosum atrophy and thinning. The proband and her two living brothers (IV2 and IV4) were detected to carry a homozygous mutation of the POLR3A (NM_007055.4) gene c. 2300G > T (p.Cys767Phe), and her consanguineous married parents (III1 and III2) were p.Cys767Phe heterozygous carriers. In the constructed POLR3A wild-type and p.Cys767Phe mutant cells, it was seen that overexpression of wild-type POLR3A protein significantly enhanced Pol III transcription of 5S rRNA and tRNA Leu-CAA. However, although the mutant POLR3A protein overexpression was increased compared to the wild-type protein overexpression, it did not show the expected further enhancement of Pol III function. On the contrary, Pol III transcription function was frustrated (POLR3A, BC200, and tRNA Leu-CAA expression decreased), and MBP and 18S rRNA expressions were decreased. This study indicates that the POLR3A p.Cys767Phe variant caused increased expression of mutated POLR3A protein and abnormal expression of Pol III transcripts, and the mutant POLR3A protein function was abnormal.

EMG-Constrained and Ultrasound-Informed Muscle-Tendon Parameter Estimation in Post-Stroke Hemiparesis.

Secondary morphological and mechanical property changes in the muscle-tendon unit at the ankle joint are often observed in post-stroke individuals. These changes may alter the force generation capacity and affect daily activities such as locomotion. This work aimed to estimate subject-specific muscle-tendon parameters in individuals after stroke by solving the muscle redundancy problem using direct collocation optimal control methods based on experimental electromyography (EMG) signals and measured muscle fiber length. Subject-specific muscle-tendon parameters of the gastrocnemius, soleus, and tibialis anterior were estimated in seven post-stroke individuals and seven healthy controls. We found that the maximum isometric force, tendon stiffness and optimal fiber length in the post-stroke group were considerably lower than in the control group. We also computed the root mean square error between estimated and experimental values of muscle excitation and fiber length. The musculoskeletal model with estimated subject-specific muscle tendon parameters (from the muscle redundancy solver), yielded better muscle excitation and fiber length estimations than did scaled generic parameters. Our findings also showed that the muscle redundancy solver can estimate muscle-tendon parameters that produce force behavior in better accordance with the experimentally-measured value. These muscle-tendon parameters in the post-stroke individuals were physiologically meaningful and may shed light on treatment and/or rehabilitation planning.

ISB clinical biomechanics award winner 2023: Medial gastrocnemius muscle and Achilles tendon interplay during gait in cerebral palsy.

BACKGROUND: The interplay between the medial gastrocnemius muscle and the Achilles tendon is crucial for efficient walking. In cerebral palsy, muscle and tendon remodelling alters the role of contractile and elastic components. The aim was to investigate the length changes of medial gastrocnemius belly and fascicles, and Achilles tendon to understand their interplay to gait propulsion in individuals with cerebral palsy. METHODS: Twelve young individuals with cerebral palsy and 12 typically developed peers were assessed during multiple gait cycles using 3D gait analysis combined with a portable ultrasound device. By mapping ultrasound image locations into the shank reference frame, the medial gastrocnemius belly, fascicle, and Achilles tendon lengths were estimated throughout the gait cycle. Participants with cerebral palsy were classified into equinus and non-equinus groups based on their sagittal ankle kinematics. FINDINGS: In typically developed participants, the Achilles tendon undertook most of the muscle-tendon unit lengthening during stance, whereas in individuals with cerebral palsy, this lengthening was shared between the medial gastrocnemius belly and Achilles tendon, which was more evident in the equinus group. The lengthening behaviour of the medial gastrocnemius fascicles resembled that of the Achilles tendon in cerebral palsy. INTERPRETATION: The findings revealed similar length changes of the medial gastrocnemius fascicles and Achilles tendon, highlighting the enhanced role of the muscle in absorbing energy during stance in cerebral palsy. These results, together with the current knowledge of increased intramuscular stiffness, suggest the exploitation of intramuscular passive forces for such energy absorption.

A correlation study between prostate necrosis rate calculated by 3D Slicer software and clinical efficacy of prostatic artery embolization, along with an analysis of predictors of clinical success after prostatic artery embolization.

PURPOSE: To analyze the correlation between the prostate necrosis rate at 1-month after prostatic artery embolization (PAE) and the clinical efficacy at 1-year after PAE, and to explore potential predictors of clinical success after PAE for the treatment of lower urinary tract symptoms secondary to benign prostatic hyperplasia (BPH). METHODS: The prostate magnetic resonance imaging data at 1-month after PAE were imported into 3D Slicer software for calculating the prostate necrosis rate and thus analyzing the relationship between the prostate necrosis rate at 1-month after PAE and the efficacy score ratio at 1-year after PAE. The 151 patients with PAE technical success were divided into a clinical success group (n = 126) and a clinical failure group (n = 25). Independent predictors of clinical success after PAE were analyzed by multifactorial logistic regression, and the predictive performance of each factor was evaluated by applying the receiver operating characteristic curve and the area under the curve (AUC). RESULTS: There was a linear negative correlation between the prostate necrosis rate at 1-month after PAE and the efficacy score ratio at 1-year after surgery (P < 0.001). In the clinical success group, both the initial prostate volume (PV) and the prostate necrosis rate at 1-month after PAE were significantly higher than in the clinical failure group (P < 0.001), and acute urinary retention (AUR) and adenomatous-dominant BPH were also associated with clinical success (P < 0.05). Multifactorial logistic regression analysis revealed that larger initial PV, a higher prostate necrosis rate at 1-month after surgery, and AUR were independent predictors of clinical success after PAE. The AUC values for these three indicators and their combination were 0.720, 0.928, 0.599, and 0.951, respectively, in which the prostate necrosis rate at 1-month after PAE demonstrating a high predictive value. CONCLUSION: The higher the prostate necrosis rate at 1-month after PAE, the better the clinical efficacy at 1-year after PAE is likely to be, and the prostate necrosis rate at 1-month after PAE is expected to become a predictor of clinical success after PAE.

A Method of Detecting Human Movement Intentions in Real Environments.

Accurate and timely movement intention detection can facilitate exoskeleton control during transitions between different locomotion modes. Detecting movement intentions in real environments remains a challenge due to unavoidable environmental uncertainties. False movement intention detection may also induce risks of falling and general danger for exoskeleton users. To this end, in this study, we developed a method for detecting human movement intentions in real environments. The proposed method is capable of online self-correcting by implementing a decision fusion layer. Gaze data from an eye tracker and inertial measurement unit (IMU) signals were fused at the feature extraction level and used to predict movement intentions using 2 different methods. Images from the scene camera embedded on the eye tracker were used to identify terrains using a convolutional neural network. The decision fusion was made based on the predicted movement intentions and identified terrains. Four able-bodied participants wearing the eye tracker and 7 IMU sensors took part in the experiments to complete the tasks of level ground walking, ramp ascending, ramp descending, stairs ascending, and stair descending. The recorded experimental data were used to test the feasibility of the proposed method. An overall accuracy of 93.4% was achieved when both feature fusion and decision fusion were used. Fusing gaze data with IMU signals improved the prediction accuracy.

An Integrated Eye-Tracking and Motion Capture System in Synchronized Gaze and Movement Analysis.

Integrating mobile eye-tracking and motion capture emerges as a promising approach in studying visual-motor coordination, due to its capability of expressing gaze data within the same laboratory-centered coordinate system as body movement data. In this paper, we proposed an integrated eye-tracking and motion capture system, which can record and analyze temporally and spatially synchronized gaze and motion data during dynamic movement. The accuracy of gaze measurement were evaluated on five participants while they were instructed to view fixed vision targets at different distances while standing still or walking towards the targets. Similar accuracy could be achieved in both static and dynamic conditions. To demonstrate the usability of the integrated system, several walking tasks were performed in three different pathways. Results revealed that participants tended to focus their gaze on the upcoming path, especially on the downward path, possibly for better navigation and planning. In a more complex pathway, coupled with more gaze time on the pathway, participants were also found having the longest step time and shortest step length, which led to the lowest walking speed. It was believed that the integration of eye-tracking and motion capture is a feasible and promising methodology quantifying visual-motor coordination in locomotion.

Influence of Input Features and EMG Type on Ankle Joint Torque Prediction With Support Vector Regression.

Reliable and accurate EMG-driven prediction of joint torques are instrumental in the control of wearable robotic systems. This study investigates how different EMG input features affect the machine learning algorithm-based prediction of ankle joint torque in isometric and dynamic conditions. High-density electromyography (HD-EMG) of five lower leg muscles were recorded during isometric contractions and dynamic tasks. Four datasets (HD-EMG, HD-EMG with reduced dimensionality, features extracted from HD-EMG with Convolutional Neural Network, and bipolar EMG) were created and used alone or in combination with joint kinematic information for the prediction of ankle joint torque using Support Vector Regression. The performance was evaluated under intra-session, inter-subject, and inter-session cases. All HD-EMG-derived datasets led to significantly more accurate isometric ankle torque prediction than the bipolar EMG datasets. The highest torque prediction accuracy for the dynamic tasks was achieved using bipolar EMG or HD-EMG with reduced dimensionality in combination with kinematic features. The findings of this study contribute to the knowledge allowing an informed selection of appropriate features for EMG-driven torque prediction.

Estimation of Joint Torque by EMG-Driven Neuromusculoskeletal Models and LSTM Networks.

Accurately predicting joint torque using wearable sensors is crucial for designing assist-as-needed exoskeleton controllers to assist muscle-generated torque and ensure successful task performance. In this paper, we estimated ankle dorsiflexion/plantarflexion, knee flexion/extension, hip flexion/extension, and hip abduction/adduction torques from electromyography (EMG) and kinematics during daily activities using neuromusculoskeletal (NMS) models and long short-term memory (LSTM) networks. The joint torque ground truth for model calibrating and training was obtained through inverse dynamics of captured motion data. A cluster approach that grouped movements based on characteristic similarity was implemented, and its ability to improve the estimation accuracy of both NMS and LSTM models was evaluated. We compared torque estimation accuracy of NMS and LSTM models in three cases: Pooled, Individual, and Clustered models. Pooled models used data from all 10 movements to calibrate or train one model, Individual models used data from each individual movement, and Clustered models used data from each cluster. Individual, Clustered and Pooled LSTM models all had relatively high joint torque estimation accuracy. Individual and Clustered NMS models had similarly good estimation performance whereas the Pooled model may be too generic to satisfy all movement patterns. While the cluster approach improved the estimation accuracy in NMS models in some movements, it made relatively little difference in the LSTM neural networks, which already had high estimation accuracy. Our study provides practical implications for designing assist-as-needed exoskeleton controllers by offering guidelines for selecting the appropriate model for different scenarios, and has potential to enhance the functionality of wearable exoskeletons and improve rehabilitation and assistance for individuals with motor disorders.

Neuromusculoskeletal model-informed machine learning-based control of a knee exoskeleton with uncertainties quantification.

Introduction: Research interest in exoskeleton assistance strategies that incorporate the user's torque capacity is growing rapidly. However, the predicted torque capacity from users often includes uncertainty from various sources, which can have a significant impact on the safety of the exoskeleton-user interface. Methods: To address this challenge, this paper proposes an adaptive control framework for a knee exoskeleton that uses muscle electromyography (EMG) signals and joint kinematics. The framework predicted the user's knee flexion/extension torque with confidence bounds to quantify the uncertainty based on a neuromusculoskeletal (NMS) solver-informed Bayesian Neural Network (NMS-BNN). The predicted torque, with a specified confidence level, controlled the assistive torque provided by the exoskeleton through a TCP/IP stream. The performance of the NMS-BNN model was also compared to that of the Gaussian process (NMS-GP) model. Results: Our findings showed that both the NMS-BNN and NMS-GP models accurately predicted knee joint torque with low error, surpassing traditional NMS models. High uncertainties were observed at the beginning of each movement, and at terminal stance and terminal swing in self-selected speed walking in both NMS-BNN and NMS-GP models. The knee exoskeleton provided the desired assistive torque with a low error, although lower torque was observed during terminal stance of fast walking compared to self-selected walking speed. Discussion: The framework developed in this study was able to predict knee flexion/extension torque with quantifiable uncertainty and to provide adaptive assistive torque to the user. This holds significant potential for the development of exoskeletons that provide assistance as needed, with a focus on the safety of the exoskeleton-user interface.

Electrical impedance myography combined with quantitative assessment techniques in paretic muscle of stroke survivors: Insights and challenges.

Aging is a non-modifiable risk factor for stroke and the global burden of stroke is continuing to increase due to the aging society. Muscle dysfunction, common sequela of stroke, has long been of research interests. Therefore, how to accurately assess muscle function is particularly important. Electrical impedance myography (EIM) has proven to be feasible to assess muscle impairment in patients with stroke in terms of micro structures, such as muscle membrane integrity, extracellular and intracellular fluids. However, EIM alone is not sufficient to assess muscle function comprehensively given the complex contributors to paretic muscle after an insult. This article discusses the potential to combine EIM and other common quantitative methods as ways to improve the assessment of muscle function in stroke survivors. Clinically, these combined assessments provide not only a distinct advantage for greater accuracy of muscle assessment through cross-validation, but also the physiological explanation on muscle dysfunction at the micro level. Different combinations of assessments are discussed with insights for different purposes. The assessments of morphological, mechanical and contractile properties combined with EIM are focused since changes in muscle structures, tone and strength directly reflect the muscle function of stroke survivors. With advances in computational technology, finite element model and machine learning model that incorporate multi-modal evaluation parameters to enable the establishment of predictive or diagnostic model will be the next step forward to assess muscle function for individual with stroke.

In vivo 3D muscle architecture quantification based on 3D freehand ultrasound and magnetic resonance imaging.

Muscle architecture parameters, such as the fascicle length, pennation angle, and volume, are important muscle morphology characteristics. Accurate in vivo quantification of these parameters allows to detect changes due to pathologies, interventions, and rehabilitation trainings, which ultimately impact on muscles' force-producing capacity. In this study, we compared three-dimensional (3D) muscle architecture parameters of the tibialis anterior and gastrocnemius medialis, which were quantified by 3D freehand ultrasound (3DfUS) and a magnetic resonance imaging (MRI) technique, diffusion tensor imaging (DTI), respectively. Sixteen able-bodied subjects were recruited where seven of them received both 3DfUS and MRI measurement, while the rest underwent 3DfUS measurements twice. Good to excellent intra-rater reliability and inter-session repeatability were found in 3DfUS measurements (intra-class correlation coefficient > 0.81). Overall, the two imaging modalities yielded consistent measurements of the fascicle length, pennation angle, and volume with mean differences smaller than 2.9 mm, 1.8°, and 5.7 cm3, respectively. The only significant difference was found in the pennation angle of the tibialis anterior, although the discrepancy was small. Our study demonstrated, for the first time, that 3DfUS measurement had high reliability and repeatability for measurement of muscle architecture in vivo and could be regarded as an alternative to MRI for 3D evaluation of muscle morphology.

Automatic Myotendinous Junction Identification In Ultrasound Images Based on Junction-based Template Measurements.

Tracking the myotendinous junction (MTJ) motion in consecutive ultrasound images is essential to assess muscle and tendon interaction and understand the mechanics' muscle-tendon unit and its pathological conditions during motion. However, the inherent speckle noises and ambiguous boundaries deter the reliable identification of MTJ, thus restricting their usage in human motion analysis. This study advances a fully automatic displacement measurement method for MTJ using prior shape knowledge on the Y-shape MTJ, precluding the influence of irregular and complicated hyperechoic structures in muscular ultrasound images. Our proposed method first adopts the junction candidate points using a combined measure of Hessian matrix and phase congruency, followed by a hierarchical clustering technique to refine the candidates approximating the position of the MTJ. Then, based on the prior knowledge of Y-shape MTJ, we finally identify the best matching junction points according to intensity distributions and directions of their branches using multiscale Gaussian templates and a Kalman filter. We evaluated our proposed method using the ultrasound scans of the gastrocnemius from 8 young, healthy volunteers. Our results present more consistent with the manual method in the MTJ tracking method than existing optical flow tracking methods, suggesting its potential in facilitating muscle and tendon function examinations with in vivo ultrasound imaging.

Clinical and imaging features of six Han patients with SAPHO syndrome.

BACKGROUND: Synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome is a rare autoimmune disease characterized by skin or osteoarticular damage. SAPHO syndrome is often misdiagnosed or missed diagnosis due to lack of overall understanding of the disease by clinicians. PURPOSE: To analyze the clinical symptoms and imaging features of six Han patients with SAPHO syndrome in order to provide reference for doctors to diagnose SAPHO syndrome. MATERIAL AND METHODS: This study retrospectively analyzed the clinical data of six Han patients with SAPHO syndrome. RESULTS: All six Han patients with SAPHO syndrome had severe acne or pustulosis of the hands and feet, and all of them had osteoarticular damage, including five cases involving the sternoclavicular joint. Some patients showed a specific and typical "bull's head" sign on 99mTc-labeled methylene diphosphonate bone imaging. Among the six patients recruited, there was one thoracic vertebra, one cervical vertebra, one sacroiliac joint, and one peripheral joint involvement. Two patients had limited activity due to severe osteoarticular damage. CONCLUSION: Due to the atypical clinical symptoms of SAPHO syndrome, most patients will experience a tortuous and long diagnostic process, while a correct understanding and timely intervention of SAPHO syndrome are essential to improve the prognosis of patients.

Ankle Joint Torque Prediction Using an NMS Solver Informed-ANN Model and Transfer Learning.

In this work, we predicted ankle joint torque by combining a neuromusculoskeletal (NMS) solver-informed artificial neural network (hybrid-ANN) model with transfer learning based on joint angle and muscle electromyography signals. The hybrid-ANN is an ANN augmented with two kinds of features: 1) experimental measurements - muscle signals and joint angles, and 2) informative physical features extracted from the underlying NMS solver, such as individual muscle force and joint torque. The hybrid-ANN model accuracy in torque prediction was studied in both intra- and inter-subject tests, and compared to the baseline models (NMS and standard-ANN). For each prediction model, seven different cases were studied using data from gait at different speeds and from isokinetic ankle dorsi/plantarflexion motion. Additionally, we integrated a transfer learning method in inter-subject models to improve joint torque prediction accuracy by transferring the learned knowledge from previous participants to a new participant, which could be useful when training data is limited. Our results indicated that better accuracy could be obtained by integrating informative NMS features into a standard ANN model, especially in inter-subject cases; overall, the hybrid-ANN model predicted joint torque with higher accuracy than the baseline models, most notably in inter-subject prediction after adopting the transfer learning technique. We demonstrated the potential of combining physics-based NMS and standard-ANN models with a transfer learning technique in different prediction scenarios. This procedure holds great promise in applications such as assistance-as-needed exoskeleton control strategy design by incorporating the physiological joint torque of the users.

Genetic Analysis and Functional Study of a Pedigree With Bruck Syndrome Caused by PLOD2 Variant.

Background: Bruck syndrome (BS) is a rare autosomal recessive inherited osteogenesis imperfecta disease characterized by increased bone fragility and joint contracture. The pathogenic gene of type I BS is FKBPl0, whereas that of type II BS is PLOD2. No significant difference has been found in the clinical phenotype between the two types of BS. In this study, we performed genetic analysis of a BS pedigree caused by PLOD2 variant and studied the corresponding cellular function. Methods: Serum biochemistry, parathyroid hormone (PTH), 25-hydroxyvitamin D [25-(OH) D], osteocalcin, and 24-h urinary calcium levels of a family member with BS was assessed. The genes of the proband were analyzed by second-generation sequencing and exon capture techniques. Sanger sequencing was also performed for the suspected responsible variant of the family member. Wild- and variant-type lentivirus plasmids were constructed by gene cloning and transfected into HEK293T cells. Cell function was verified by real-time quantitative polymerase chain reaction, western blotting, and immunofluorescence detection. Results: In this pedigree, the proband was found to have a homozygous variant c.1856G > A (p.Arg619His) in exon 17 of PLOD2 (NM_182943.3). His consanguineous parents and sisters were p.Arg619His heterozygous carriers. The mRNA expression of PLOD2 in the constructed p.Arg619His variant cells was significantly upregulated, while the expression of PLOD2 and collagen I protein in the cell lysate was significantly downregulated. Immunofluorescence revealed that the wild-type PLOD2 was mainly located in the cytoplasm, and the expression of the PLOD2 protein after c.1856G > A variant was significantly downregulated, with almost no expression, aligning with the western blot results. The serum sodium, potassium, calcium, phosphorus, magnesium, alkaline phosphatase, PTH, 25-(OH) D, osteocalcin, and 24 h urinary calcium levels of the proband, his parents, and sisters were normal. Conclusion: Through gene and cell function analyses, PLOD2 Arg619His missense variant was preliminarily confirmed to cause BS by reducing protein expression.

Lower-Limb Joint Torque Prediction Using LSTM Neural Networks and Transfer Learning.

Estimation of joint torque during movement provides important information in several settings, such as effect of athletes' training or of a medical intervention, or analysis of the remaining muscle strength in a wearer of an assistive device. The ability to estimate joint torque during daily activities using wearable sensors is increasingly relevant in such settings. In this study, lower limb joint torques during ten daily activities were predicted by long short-term memory (LSTM) neural networks and transfer learning. LSTM models were trained with muscle electromyography signals and lower limb joint angles. Hip flexion/extension, hip abduction/adduction, knee flexion/extension and ankle dorsiflexion/plantarflexion torques were predicted. The LSTM models' performance in predicting torque was investigated in both intra-subject and inter-subject scenarios. Each scenario was further divided into intra-task and inter-task tests. We observed that LSTM models could predict lower limb joint torques during various activities accurately with relatively low error (root mean square error ≤ 0.14 Nm/kg, normalized root mean square error ≤ 8.7%) either through a uniform model or through ten separate models in intra-subject tests. Furthermore, a transfer learning technique was adopted in the inter-task and inter-subject tests to further improve the generalizability of LSTM models by pre-training a model on multiple subjects and/or tasks and transferring the learned knowledge to a target task/subject. Particularly in the inter-subject tests, we could predict joint torques accurately in several movements after training from only a few movements from new subjects.

Rare Cases of Bronchial Aneurysm and Comparison of Interventional Embolization in the Treatment of True Bronchial Aneurysm and Pseudobronchial Aneurysm.

Background: Bronchial artery aneurysm (BAA) is a rare disease. Rupture of BAA can lead to life-threatening hemoptysis, and once diagnosed, treatment is needed regardless of symptoms. Transcatheter artery embolization is the first choice of treatment because it is minimally invasive and effective. This study aimed to retrospectively compare the embolization treatment of a case of true BAA and that of a pseudobranchial aneurysm and explore the choice of embolization method for BAA with short neck or no neck. Materials and Methods: Embolization treatment and imaging characteristics of one case of true BAA and one case of pseudobronchial aneurysm admitted to our hospital were analyzed retrospectively. Embolization methods and therapeutic effects of two cases of BAAs were compared. Results: Case 1 was that of an intact true BAA inside the mediastinum located at the opening of the bronchial artery. The distal end of the aneurysm was embolized, and tumor cavity was occluded. No recurrence of BAA was found after the operation. Case 2 was that of a ruptured and hemorrhagic pseudobronchial aneurysm of the mediastinum. Coil embolization combined with covered stent graft exclusion of the thoracic aorta were performed, and the left bronchial artery and BAA were almost occluded. Nine months postoperatively, the mediastinal hematoma was almost completely absorbed. Conclusion: Endovascular embolization has become the most commonly used for the treatment of BAA. Different methods should be selected according to the location and nature of the aneurysm.

Clinical outcomes of uterine artery embolization and experience of postoperative transvaginal fibroid expulsion: a retrospective analysis.

PURPOSE: To explore the efficacy of uterine artery embolization (UAE) in the treatment of uterine fibroid and share the experience of transvaginal fibroid expulsion (FE) after UAE. METHODS: We retrospectively analyzed the changes in uterine and fibroid volume in 152 patients with symptomatic uterine fibroid after UAE at Fujian Provincial Hospital and Fujian Longyan People Hospital from March 2014 to March 2020. After a 12-month follow-up, the improvement in postoperative clinical symptoms and the incidence of complications were evaluated. We also shared the clinical features and imaging findings of four patients with FE after UAE. RESULTS: All 152 patients successfully underwent UAE. After a 12-month follow-up, the postoperative volumes of the uterus and fibroid at 3, 6, and 12 months were significantly reduced or disappeared compared to those before surgery (P < 0.05). Clinical symptoms, such as menorrhagia, dysmenorrhea, prolonged menstrual period, anemia, increased leucorrhea, pelvic discomfort, and urinary tract compression, were significantly improved after UAE. Among the 152 patients, the incidences of postoperative fever, nausea, vomiting, lower abdominal pain, and increased vaginal secretion were 7.89%, 7.24%, 3.95%, 19.08%, and 4.61%, respectively. Additionally, there were six cases of FE, with an incidence of 3.95%. Three cases of fibroid specimens and pathological images of fibroid biopsy, which were expelled through the vagina, were also provided. CONCLUSION: UAE is a satisfactory alternative surgical method for symptomatic uterine fibroid with definitive efficacy and high safety. However, it is necessary to guard against the occurrence of postoperative complications such as FE.

The Effect of Step Width on Muscle Contributions to Body Mass Center Acceleration During the First Stance of Sprinting.

BACKGROUND: At the beginning of a sprint, the acceleration of the body center of mass (COM) is driven mostly forward and vertically in order to move from an initial crouched position to a more forward-leaning position. Individual muscle contributions to COM accelerations have not been previously studied in a sprint with induced acceleration analysis, nor have muscle contributions to the mediolateral COM accelerations received much attention. This study aimed to analyze major lower-limb muscle contributions to the body COM in the three global planes during the first step of a sprint start. We also investigated the influence of step width on muscle contributions in both naturally wide sprint starts (natural trials) and in sprint starts in which the step width was restricted (narrow trials). METHOD: Motion data from four competitive sprinters (2 male and 2 female) were collected in their natural sprint style and in trials with a restricted step width. An induced acceleration analysis was performed to study the contribution from eight major lower limb muscles (soleus, gastrocnemius, rectus femoris, vasti, gluteus maximus, gluteus medius, biceps femoris, and adductors) to acceleration of the body COM. RESULTS: In natural trials, soleus was the main contributor to forward (propulsion) and vertical (support) COM acceleration and the three vasti (vastus intermedius, lateralis and medialis) were the main contributors to medial COM acceleration. In the narrow trials, soleus was still the major contributor to COM propulsion, though its contribution was considerably decreased. Likewise, the three vasti were still the main contributors to support and to medial COM acceleration, though their contribution was lower than in the natural trials. Overall, most muscle contributions to COM acceleration in the sagittal plane were reduced. At the joint level, muscles contributed overall more to COM support than to propulsion in the first step of sprinting. In the narrow trials, reduced COM propulsion and particularly support were observed compared to the natural trials. CONCLUSION: The natural wide steps provide a preferable body configuration to propel and support the COM in the sprint starts. No advantage in muscular contributions to support or propel the COM was found in narrower step widths.