Medical Engineering & Physics最新文献

Introduction

The pre-operative planning and intra-operative navigation of the endovascular aneurysm repair (EVAR) procedure are currently challenged by the aortic deformations that occur due to the insertion of a stiff guidewire. Hence, a fast and accurate predictive tool may help clinicians in the decision-making process and during surgical navigation, potentially reducing the radiations and contrast dose. To this aim, we generated a reduced order model (ROM) trained on parametric finite element simulations of the aortic wall-guidewire interaction.

Method

A Design of Experiments (DOE) consisting of 300 scenarios was created spanning over seven parameters. Radial basis functions were used to achieve a morphological parametrization of the aortic geometry. The ROM was built using 200 scenarios for training and the remaining 100 for validation.

Results

The developed ROM estimated the displacement of aortic nodes with a relative error below 5.5% for all the considered validation cases. From a preliminary analysis, the aortic elasticity, the stiffness of the guidewire and the tortuosity of the cannulated iliac artery proved to be the most influential parameters.

Conclusions

Once built, the ROM provided almost real-time and accurate estimations of the guidewire-induced aortic displacement field, thus potentially being a promising pre- and intra-operative tool for clinicians.

This study focuses on evaluating the failure resistance of a previously reduced tibia with internal fixation implants as PLate (PL) or InterMedullary Nail (IMN), subjected later to a tibial lateral trauma. To replicate this type of trauma, which can be caused by a road accident, a three-point bending test is considered using experimental tests and numerical simulations.

The withstand evaluation of the tibia-PL and tibia-IMN structures was conducted by following the load transfer through, the bone and the used implants. The analysis, up to tibia failure, required the use of an elasto-plastic behavior law coupled to damage. The model parameters were identified using experimental tests.

Il was shown that the tibia-IMN structure provided a bending resistant load up to three-times higher than the tibia-PL. In fact, the used screws for plate fixation induced a high level of stress in the vicinity of threaded region, leading to a crack initiation and a damage propagation. However, in tibia-IMN structure the highest stress was generated in the trapped zone between the loader and the nail, promoting crack formation.

From a biomechanical point of view, the structure with IMN is safer than the structure with PL, whose fixation induces earlier damage in bone.

This study aimed to measure trunk rotation angle representations from images using a single camera combined with a posture mirror and to examine its reliability and validity. We applied a trunk rotation angle model using a tripod and markers simulating trunk rotation. We compared two methods of trunk rotation angle measurement: the conventional method from the superior aspect using a manual goniometer and a novel measurement method using images from a digital camera and a posture mirror. Measurement error was calculated as the average absolute error between the angle measured by the goniometer and that calculated from the camera and mirror image. The intraclass correlation coefficient (ICC 1, 1) and ICC (2, 1) were calculated as the intra-rater reliability and agreement between the measurement angles of the two methods, respectively. Systematic errors of the angles measured by the two methods were examined by a Bland‒Altman analysis. The mean (SD) of the mean absolute error was 1.17° (0.71°). ICC (1, 1) was 0.978, and ICC (2, 1) was 0.991. The Bland‒Altman analysis showed no systematic errors. The results suggest the validity and accuracy of our novel method to measure the angle of trunk rotation, which does not require high-cost equipment or a special environment.

There is currently no definitive evidence for the implant of choice for the treatment of reverse pertrochanteric fractures. Here, we aimed to compare the stability provided by two implant options: long and short intramedullary nails.

We performed finite element simulations of different patterns of reverse pertrochanteric fractures with varying bone quality, and compared the short vs long nail stabilization under physiological loads. For each variable combination, the micromotions at the fracture site, bone strain, and implant stress were computed.

Mean micromotions at the fracture surface and absolute and relative fracture surface with micromotions >150 µm were slightly lower with the short nail (8%, 3%, and 3%, respectively). The distal fracture extension negatively affected the stability, with increasing micromotions on the medial side. Bone strain above 1 % was not affected by the nail length. Fatigue stresses were similar for both implants, and no volume was found above the yield and ultimate stress in the tested conditions.

This simulation study shows no benefit of long nails for the investigated patterns of reverse pertrochanteric fractures, with similar micromotions at the fracture site, bone strain, and implant stress.

To explore the biomechanical effects of different internal fixation methods on femoral neck fractures under various postoperative conditions, mechanical analyses were conducted, including static and dynamic assessments. Ultimately, a mechanical stability evaluation system was established to determine the weights of each mechanical index and the evaluation scores for each sample. In static analysis, it was found that the mechanical stability of each model met the fixation requirements post-fracture. During the healing process, the maximum stress on the hollow nail slightly increased, and stress distribution shifted from multi-point to a more uniform single-point distribution, which contributes to fracture healing and reduces the risk of stress concentration. In dynamic analysis, resonance points frequently occurred at low frequencies. With increasing walking speed, the maximum stress increased significantly. At slow speeds, the maximum stress approached the material's yield limit. Under cyclic dynamic loading, the number of cycles barely met the requirements of the healing period, and increasing walking speed may lead to fatigue fractures. The evaluation model established in this study comprehensively considers different mechanical performances in static and dynamic analyses. Based on various mechanical analyses and evaluation systems, the applicability of internal fixation treatment plans can be assessed from multiple dimensions, providing the optimal simulated mechanical solution for each case of femoral neck fracture treatment.

Tracking the position and orientation of a two-dimensional (2D) ultrasound scanner to reconstruct a 3D volume is common, and its accuracy is important. In this study, a specific miniaturized electromagnetic (EM) tracking system was selected and integrated with a 2D ultrasound scanner, which was aimed to capture hip displacement in children with cerebral palsy. The objective of this study was to determine the optimum configuration, including the distance between the EM source and sensor, to provide maximum accuracy. The scanning volume was aimed to be 320 mm × 320 mm × 76 mm. The accuracy of the EM tracking was evaluated by comparing its tracking with those from a motion capture camera system. A static experiment showed that a warm-up time of 20 min was needed. The EM system provided the highest precision of 0.07 mm and 0.01° when the distance between the EM source and sensor was 0.65 m. Within the testing volume, the maximum position and rotational errors were 2.31 mm and 1.48°, respectively. The maximum error of measuring hip displacement on the 3D hip phantom study was 4 %. Based on the test results, the tested EM system was suitable for 3D ultrasound imaging of pediatric hips to assess hip displacement when optimal configuration was used.

Heart failure, broadly characterized by the gradual decline of the ability of the heart to maintain adequate blood flow throughout the body's vascular network of veins and arteries, is one of the leading causes of death worldwide. Mechanical Circulatory Support is one of the few available alternative interventions for late-stage heart failure with reduced ejection fraction. A ventricular assist device is surgically implanted and connected to the left and or right heart ventricles to provide additional bloodflow, off-loading the work required by the heart to maintain circulation. Modern mechanical circulatory support devices generate non-physiological flow conditions that can lead to the damage and rupture of blood cells (hemolysis), and the formation of blood clots (thrombosis), which pose severe health risks to the patient. It is essential to improve prediction tools for blood damage to reduce the risk of hemolysis and thrombosis. A simulation-based approach examines the interaction between hemolysis and thrombosis. Incompressible finite-volume computational fluid dynamics simulations are executed on an open-hub axial flow ventricular assist device. A continuum model of thrombosis and the intrinsic coagulation process is extended to include the effect of hemolysis. The model accounts for the effect of activation of platelets by shear stress, paracrine signaling, adhesion, and hemoglobin and ADP released during hemolysis. The effect of hemolysis with thrombosis is modelled by accounting for the hyper-adhesivity of von-Willebrand Factor on extracellular hemoglobin, and the increased rate of platelet activation induced by ADP release. Thrombosis is assessed at varying inflow rates and rotor speeds, and cases are executed where thrombosis is affected by ADP release and Hb-induced hyper-adhesivity. It is found that there is a non-negligible effect from hemolysis on thrombosis across a range of rotor speeds, and that hyperadhesivity plays a dominant role in thrombus formation in the presence of hemolysis.

Background and Objective

Imaging methodologies such as, computed tomography (CT) aid in three-dimensional (3D) reconstruction of patient-specific aneurysms. The radiological data is useful in understanding their location, shape, size, and disease progression. However, there are serious impediments in discerning the blood vessel wall thickness due to limitations in the current imaging modalities. This further restricts the ability to perform high-fidelity fluid structure interaction (FSI) studies for an accurate assessment of rupture risk. FSI studies would require the arterial wall mesh to be generated to determine realistic maximum allowable wall stresses by performing coupled calculations for the hemodynamic forces with the arterial walls.

Methods

In the present study, a novel methodology is developed to geometrically model variable vessel wall thickness for the lumen isosurface extracted from CT scan slices of patient-specific aneurysms based on clinical and histopathological inputs. FSI simulations are carried out with the reconstructed models to assess the importance of near realistic wall thickness model on rupture risk predictions.

Results

During surgery, clinicians often observe translucent vessel walls, indicating the presence of thin regions. The need to generate variable vessel wall thickness model, that embodies the wall thickness gradation, is closer to such clinical observations. Hence, corresponding FSI simulations performed can improve clinical outcomes. Considerable differences in the magnitude of instantaneous wall shear stresses and von Mises stresses in the walls of the aneurysm was observed between a uniform wall thickness and a variable wall thickness model.

Conclusion

In the present study, a variable vessel wall thickness generation algorithm is implemented. It was shown that, a realistic wall thickness modeling is necessary for an accurate prediction of the shear stresses on the wall as well as von Mises stresses in the wall. FSI simulations are performed to demonstrate the utility of variable wall thickness modeling.

Purpose

Rehabilitation technology can be used to provide intensive training in the early phases after stroke. The current study aims to assess the feasibility of combining robotics and functional electrical stimulation (FES), with an assist-as-needed approach to support actively-initiated leg movements in (sub-)acute stroke patients.

Method

Nine subacute stroke patients performed repetitions of ankle dorsiflexion and/or knee extension movements, with and without assistance. The assist-as-needed algorithm determined the amount and type of support needed per repetition. The number of repetitions and range of motion with and without assistance were compared with descriptive statistics. Fatigue scores were obtained using the visual analogue scale (score 0–10).

Results

Support was required in 44 % of the repetitions for ankle dorsiflexion and in 5 % of the repetitions of knee extension, The median fatigue score was 2.0 (IQR: 0.2) and 4.0 (IQR: 1.5) for knee and ankle, respectively, indicating mild to moderate perceived fatigue.

Conclusion

This study demonstrated the feasibility of assist-as-needed assistance through combined robotic and FES support of leg movements in stroke patients. It proved particularly useful for ankle dorsiflexion. Future research should focus on implementing this approach in a clinical setting, to assess clinical applicability and potential effects on leg function.

Epilepsy is a chronic disease caused by repeated abnormal discharge of neurons in the brain. Accurately predicting the onset of epilepsy can effectively improve the quality of life for patients with the condition. While there are many methods for detecting epilepsy, EEG is currently considered one of the most effective analytical tools due to the abundant information it provides about brain activity. The aim of this study is to explore potential time-frequency and channel features from multi-channel epileptic EEG signals and to develop a patient-specific seizure prediction network. In this paper, an epilepsy EEG signal classification algorithm called Channel Recurrent Criss-cross Attention Network (CRCANet) is proposed. Firstly, the spectrograms processed by the short-time fourier transform is input into a Convolutional Neural Network (CNN). Then, the spectrogram feature map obtained in the previous step is input into the channel attention module to establish correlations between channels. Subsequently, the feature diagram containing channel attention characteristics is input into the recurrent criss-cross attention module to enhance the information content of each pixel. Finally, two fully connected layers are used for classification. We validated the method on 13 patients in the public CHB-MIT scalp EEG dataset, achieving an average accuracy of 93.8 %, sensitivity of 94.3 %, and specificity of 93.5 %. The experimental results indicate that CRCANet can effectively capture the time-frequency and channel characteristics of EEG signals while improving training efficiency.