5-D Epanechnikov Mixture-of-Experts in Light Field Image Compression.

In this study, we propose a modeling-based compression approach for dense/lenslet light field images captured by Plenoptic 2.0 with square microlenses. This method employs the 5-D Epanechnikov Kernel (5-D EK) and its associated theories. Owing to the limitations of modeling larger image block using the Epanechnikov Mixture Regression (EMR), a 5-D Epanechnikov Mixture-of-Experts using Gaussian Initialization (5-D EMoE-GI) is proposed. This approach outperforms 5-D Gaussian Mixture Regression (5-D GMR). The modeling aspect of our coding framework utilizes the entire EI and the 5D Adaptive Model Selection (5-D AMLS) algorithm. The experimental results demonstrate that the decoded rendered images produced by our method are perceptually superior, outperforming High Efficiency Video Coding (HEVC) and JPEG 2000 at a bit depth below 0.06bpp.

Display performance optimization method for light field displays based on a neural network.

Crosstalk between adjacent views, lens aberrations, and low spatial resolution in light field displays limit the quality of 3D images. In the present study, we introduce a display performance optimization method for light field displays based on a neural network. The method pre-corrects the encoded image from a global perspective, which means that the encoded image is pre-corrected according to the light field display results. The display performance optimization network consists of two parts: the encoded image pre-correction network and the display network. The former realizes the pre-correction of the original encoded image (OEI), while the latter completes the modeling of the display unit and realizes the generation from the encoded image to the viewpoint images (VIs). The pre-corrected encoded image (PEI) obtained through the pre-correction network can reconstruct 3D images with higher quality. The VIs are accessible through the display network. Experimental results suggest that the proposed method can reduce the graininess of 3D images significantly without increasing the complexity of the system. It is promising for light field displays since it can provide improved 3D display performance.

Automatic planning of maxillary anterior dental implant based on prosthetically guided and pose evaluation indicator.

PURPOSE: Preoperative planning of maxillary anterior dental implant is a prerequisite to ensuring that the implant achieves the proper three-dimensional (3D) pose, which is essential for its long-term stability. However, the current planning process is labor-intensive and subjective, relying heavily on the surgeon's experience. Consequently, this paper proposes an automatic method for computing the optimal pose of the dental implant. METHODS: The method adopts the principle of prosthetically guided dental implant placement. Initially, the prosthesis coordinate system is established to determine the implant candidate orientations. Subsequently, virtual slices of the maxilla in the buccal-palatal direction are generated according to the prosthesis position. By extracting feature points from the virtual slices, the implant candidate starting points are acquired. Then, a candidate pose set is obtained by combining these candidate starting points and orientations. Finally, a pose evaluation indicator is introduced to determine the optimal implant pose from this set. RESULTS: Twenty-two cases were utilized to validate the method. The results show that the method could determine an ideal pose for the dental implant, with the average minimum distance between the implant and the left tooth root, the right tooth root, the palatal side, and the buccal side being 2.57 ± 0.53 mm, 2.59 ± 0.65 mm, 0.74 ± 0.19 mm, 1.83 ± 0.16 mm, respectively. The planning time was less than 9 s. CONCLUSION: Unlike manual planning, the proposed method can efficiently and accurately complete maxillary anterior dental implant planning, providing a theoretical analysis of the success rate of the implant. Thus, it has great potential for future clinical application.

In vitro study on device-induced damage to blood cellular components and degradation of von Willebrand factor in a CentriMag pump-assisted circulation.

BACKGROUND: High mechanical shear stress (HMSS) generated by blood pumps during mechanical circulatory support induces blood damage (or function alteration) not only of blood cell components but also of plasma proteins. METHODS: In the present study, fresh, healthy human blood was used to prime a blood circuit assisted by a CentriMag centrifugal pump at a flow rate of 4.5 L/min under three pump pressure heads (75, 150, and 350 mm Hg) for 4 h. Blood samples were collected for analyses of plasma-free hemoglobin (PFH), von Willebrand factor (VWF) degradation and platelet glycoprotein (GP) IIb/IIIa receptor shedding. RESULTS: The extent of all investigated aspects of blood damage increased with increasing cross-pump pressure and duration. Loss of high-molecular-weight multimers (HMWM)-VWF in Loop 2 and Loop 3 significantly increased after 2 h. PFH, loss of HMWM-VWF, and platelet GPIIb/IIIa receptor shedding showed a good linear correlation with mean shear stress corresponding to the three pump pressure heads. CONCLUSIONS: HMSS could damage red blood cells, cause pathological VWF degradation, and induce platelet activation and platelet receptor shedding. Different blood components can be damaged to different degrees by HMSS; VWF and VWF-enhanced platelet activation may be more susceptible to HMSS.

Linking Computational Fluid Dynamics Modeling to Device-Induced Platelet Defects in Mechanically Assisted Circulation.

Thrombotic and bleeding events are the most common hematologic complications in patients with mechanically assisted circulation and are closely related to device-induced platelet dysfunction. In this study, we sought to link computational fluid dynamics (CFD) modeling of blood pumps with device-induced platelet defects. Fresh human blood was circulated in circulatory loops with four pumps (CentriMag, HVAD, HeartMate II, and CH-VAD) operated under a total of six clinically representative conditions. Blood samples were collected and analyzed for glycoprotein (GP) IIb/IIIa activation and receptor shedding of GPIbα and GPVI. In parallel, CFD modeling was performed to characterize the blood flow in these pumps. Numerical indices of platelet defects were derived from CFD modeling incorporating previously derived power-law models under constant shear conditions. Numerical results were correlated with experimental results by regression analysis. The results suggested that a scalar shear stress of less than 75 Pa may have limited contribution to platelet damage. The platelet defect indices predicted by the CFD power-law models after excluding shear stress <75 Pa correlated excellently with experimentally measured indices. Although numerical prediction based on the power-law model cannot directly reproduce the experimental data. The power-law model has proven its effectiveness, especially for quantitative comparisons.

B-cell specific Moloney murine leukemia virus insertion site 1 contributes to invasion, metastasis, and poor prognosis in salivary adenoid cystic carcinoma.

Background/purpose: Upregulation of B-cell specific Moloney murine leukemia virus insertion site 1 (BMI-1) has been involved in the invasion, metastasis, and poor prognosis of many cancers. The aim of this study was to evaluate the levels and clinical significance of BMI-1 in saliva of patients with salivary adenoid cystic carcinoma (SACC), and to analyze biological function and mechanism of BMI-1 in the invasion and metastasis of SACC. Materials and methods: The levels of BMI-1 in saliva and tumor tissues of SACC patients were determined. The correlation of salivary BMI-1 levels with clinicopathological parameters and clinical outcomes in patients with SACC was analyzed. Additionally, the effects of BMI-1 on wound-healing, transwell invasion, and epithelial-mesenchymal transition (EMT)-related protein expression in vitro as well as on tumorigenicity and experimental lung metastasis in vivo were investigated through exogenous overexpression and silencing of BMI-1 in SACC cells. Results: BMI-1 levels increased in saliva and tumor tissues in SACC patients with invasion or metastasis. High salivary BMI-1 levels were correlated with poor TNM stage, poor overall survival, and disease-free survival. Exogenous expression of BMI-1 in SACC-83 promoted its migration and invasion, while silencing BMI-1 in SACC-LM inhibited its migration and invasion in vitro and suppressed tumorigenesis and lung metastasis in vivo. Furthermore, BMI-1 regulated the expression of EMT-related proteins in SACC. Conclusion: Our study shows that BMI-1 can serve as a valuable biomarker to identify tumor invasion and metastasis in SACC, predict its prognosis, and act as a promising therapeutic target for SACC.

Balanced transformer: efficient classification of glioblastoma and primary central nervous system lymphoma.

Objective.Primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) are malignant primary brain tumors with different biological characteristics. Great differences exist between the treatment strategies of PCNSL and GBM. Thus, accurately distinguishing between PCNSL and GBM before surgery is very important for guiding neurosurgery. At present, the spinal fluid of patients is commonly extracted to find tumor markers for diagnosis. However, this method not only causes secondary injury to patients, but also easily delays treatment. Although diagnosis using radiology images is non-invasive, the morphological features and texture features of the two in magnetic resonance imaging (MRI) are quite similar, making distinction with human eyes and image diagnosis very difficult. In order to solve the problem of insufficient number of samples and sample imbalance, we used data augmentation and balanced sample sampling methods. Conventional Transformer networks use patch segmentation operations to divide images into small patches, but the lack of communication between patches leads to unbalanced data layers.Approach.To address this problem, we propose a balanced patch embedding approach that extracts high-level semantic information by reducing the feature dimensionality and maintaining the geometric variation invariance of the features. This approach balances the interactions between the information and improves the representativeness of the data. To further address the imbalance problem, the balanced patch partition method is proposed to increase the receptive field by sampling the four corners of the sliding window and introducing a linear encoding component without increasing the computational effort, and designed a new balanced loss function.Main results.Benefiting from the overall balance design, we conducted an experiment using Balanced Transformer and obtained an accuracy of 99.89%, sensitivity of 99.74%, specificity of 99.73% and AUC of 99.19%, which is far higher than the previous results (accuracy of 89.6% ∼ 96.8%, sensitivity of 74.3% ∼ 91.3%, specificity of 88.9% ∼ 96.02% and AUC of 87.8% ∼ 94.9%).Significance.This study can accurately distinguish PCNSL and GBM before surgery. Because GBM is a common type of malignant tumor, the 1% improvement in accuracy has saved many patients and reduced treatment times considerably. Thus, it can provide doctors with a good basis for auxiliary diagnosis.

An H-GrabCut Image Segmentation Algorithm for Indoor Pedestrian Background Removal.

In the context of predicting pedestrian trajectories for indoor mobile robots, it is crucial to accurately measure the distance between indoor pedestrians and robots. This study aims to address this requirement by extracting pedestrians as regions of interest and mitigating issues related to inaccurate depth camera distance measurements and illumination conditions. To tackle these challenges, we focus on an improved version of the H-GrabCut image segmentation algorithm, which involves four steps for segmenting indoor pedestrians. Firstly, we leverage the YOLO-V5 object recognition algorithm to construct detection nodes. Next, we propose an enhanced BIL-MSRCR algorithm to enhance the edge details of pedestrians. Finally, we optimize the clustering features of the GrabCut algorithm by incorporating two-dimensional entropy, UV component distance, and LBP texture feature values. The experimental results demonstrate that our algorithm achieves a segmentation accuracy of 97.13% in both the INRIA dataset and real-world tests, outperforming alternative methods in terms of sensitivity, missegmentation rate, and intersection-over-union metrics. These experiments confirm the feasibility and practicality of our approach. The aforementioned findings will be utilized in the preliminary processing of indoor mobile robot pedestrian trajectory prediction and enable path planning based on the predicted results.

3D reconstruction for maxillary anterior tooth crown based on shape and pose estimation networks.

PURPOSE: The design of a maxillary anterior tooth crown is crucial to post-treatment aesthetic appearance. Currently, the design is performed manually or by semi-automatic methods, both of which are time-consuming. As such, automatic methods could improve efficiency, but existing automatic methods ignore the relationships among crowns and are primarily used for occlusal surface reconstruction. In this study, the authors propose a novel method for automatically reconstructing a three-dimensional model of the maxillary anterior tooth crown. METHOD: A pose estimation network (PEN) and a shape estimation network (SEN) are developed for jointly estimating the crown point cloud. PEN is a regression network used for estimating the crown pose, and SEN is based on an encoder-decoder architecture and used for estimating the initial crown point cloud. First, SEN adopts a transformer encoder to calculate the shape relationship among crowns to ensure that the shape of the reconstructed point cloud is precise. Second, the initial point cloud is subjected to pose transformation according to the estimated pose. Finally, the iterative method is used to form the crown mesh model based on the point cloud. RESULT: The proposed method is evaluated on a dataset with 600 cases. Both SEN and PEN are converged within 1000 epochs. The average deviation between the reconstructed point cloud and the ground truth of the point cloud is 0.22 mm. The average deviation between the reconstructed crown mesh model and the ground truth of the crown model is 0.13 mm. CONCLUSION: The results show that the proposed method can automatically and accurately reconstruct the three-dimensional model of the missing maxillary anterior tooth crown, which indicates the method has promising application prospects. Furthermore, the reconstruction time takes less than 11 s for one case, demonstrating improved work efficiency.

Person Re-Identification Based on Contour Information Embedding.

Person re-identification (Re-ID) plays an important role in the search for missing people and the tracking of suspects. Person re-identification based on deep learning has made great progress in recent years, and the application of the pedestrian contour feature has also received attention. In the study, we found that pedestrian contour feature is not enough in the representation of CNN. On this basis, in order to improve the recognition performance of Re-ID network, we propose a contour information extraction module (CIEM) and a contour information embedding method, so that the network can focus on more contour information. Our method is competitive in experimental data; the mAP of the dataset Market1501 reached 83.8% and Rank-1 reached 95.1%. The mAP of the DukeMTMC-reID dataset reached 73.5% and Rank-1 reached 86.8%. The experimental results show that adding contour information to the network can improve the recognition rate, and good contour features play an important role in Re-ID research.

Planning of Medical Flexible Needle Motion in Effective Area of Clinical Puncture.

Lung cancer is the leading cause of cancer deaths worldwide. Although several lung cancer diagnostic methods are available for lung nodule biopsy, there are limitations in terms of accuracy, safety, and invasiveness. Transbronchial needle aspiration (TBNA) is a common method for diagnosing and treating lung cancer that involves a robot-assisted medical flexible needle moving along a curved three-dimensional trajectory, avoiding anatomical barriers to achieve clinically meaningful goals in humans. Inspired by the puncture angle between the needle tip and the vessel in venipuncture, we suggest that different orientations of the medical flexible needle puncture path affect the cost of the puncture trajectory and propose an effective puncture region based on the optimal puncture direction, which is a strategy based on imposing geometric constraints on the search space of the puncture direction, and based on this, we focused on the improved implementation of RCS*. Planning within the TBNA-based lung environment was performed using the rapidly exploring random tree (RRT), resolution-complete search (RCS), and RCS* (a resolution-optimal version of RCS) within an effective puncture region. The experimental results show that the optimal puncture direction corresponding to the lowest cost puncture trajectory is consistent among the three algorithms and RCS* is more efficient for planning. The experiments verified the feasibility and practicality of our proposed minimum puncture angle and puncture effective region and facilitated the study of the puncture direction of flexible needle puncture.

The accuracy of a novel image-guided hybrid robotic system for dental implant placement: An in vitro study.

BACKGROUND: This in vitro study aims to evaluate the accuracy of dental implant placement by a novel image-guided hybrid robotic system for dental implant surgery (HRS-DIS). METHODS: The HRS-DIS with a 5 degree of freedom (DOF) serial manipulator and a 6 DOF Stewart platform was developed. To evaluate the accuracy of repeated drilling, the holes were prepared twice with a 2.2 mm drill. To evaluate the accuracy of dental implant placement, the entry, exit and angle deviations of dental implants were measured. RESULTS: Twenty-four holes were prepared twice, and mean (±SD) of diameters were measured as 2.2 ± 0.02 mm. A total of 160 dental implants were placed in 32 phantoms by HRS-DIS. The mean (±SD) of the entry, exit and angle deviation were 0.8 ± 0.54 mm, 0.87 ± 0.54 mm and 1.0 1 ± 0.44°, respectively. CONCLUSIONS: The results of the in vitro study preliminarily validated that the HRS-DIS could provide a high accuracy for dental implant surgery.

Thalamo-cortical inter-subject functional correlation during movie watching across the adult lifespan.

An increasing number of studies have shown that the functional interactions between the thalamus and cerebral cortices play an important role in cognitive function and are influenced by age. Previous studies have revealed age-related changes in the thalamo-cortical system within individuals, while neglecting differences between individuals. Here, we characterized inter-subject functional correlation (ISFC) between the thalamus and several cortical brain networks in 500 healthy participants aged 18-87 years old from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) cohort using movie-watching state fMRI data. General linear models (GLM) were performed to assess age-related changes in ISFC of thalamo-cortical networks and the relationship between ISFC and fluid intelligence. We found significant age-related decreases in ISFC between the posterior thalamus (e.g., ventral posterior nucleus and pulvinar) and the attentional network, sensorimotor network, and visual network (FDR correction with p < 0.05). Meanwhile, the ISFC between the thalamus (mainly the mediodorsal nucleus and ventral thalamic nuclei) and higher-order cortical networks, including the default mode network, salience network and control network, showed complex changes with age. Furthermore, the altered ISFC of thalamo-cortical networks was positively correlated with decreased fluid intelligence (FDR correction with p < 0.05). Overall, our results provide further evidence that alterations in the functional integrity of the thalamo-cortical system might play an important role in cognitive decline during aging.

Computational fluid dynamics analysis and experimental hemolytic performance of three clinical centrifugal blood pumps: Revolution, Rotaflow and CentriMag.

Centrifugal blood pumps have become popular for adult extracorporeal membrane oxygenation (ECMO) due to their superior blood handling and reduced thrombosis risk featured by their secondary flow paths that avoid stagnant areas. However, the high rotational speed within a centrifugal blood pump can introduce high shear stress, causing a significant shear-induced hemolysis rate. The Revolution pump, the Rotaflow pump, and the CentriMag pump are three of the leading centrifugal blood pumps on the market. Although many experimental and computational studies have focused on evaluating the hydraulic and hemolytic performances of the Rotaflow and CentriMag pumps, there are few on the Revolution pump. Furthermore, a thorough direct comparison of these three pumps' flow characteristics and hemolysis is not available. In this study, we conducted a computational and experimental analysis to compare the hemolytic performances of the Revolution, Rotaflow, and CentriMag pumps operating under a clinically relevant condition, i.e., the blood flow rate of 5 L/min and pump pressure head of 350 mmHg, for adult ECMO support. In silico simulations were used to characterize the shear stress distributions and predict the hemolysis index, while in vitro blood loop studies experimentally determined hemolysis performance. Comparative simulation results and experimental data demonstrated that the CentriMag pump caused the lowest hemolysis while the Revolution pump generated the highest hemolysis.

Texture-less surface reconstruction using shape-based image augmentation.

The development of intelligent Robot-Assisted Minimally Invasive Surgery demands geometric reconstruction from endoscopic images. However, images of human tissue surfaces are commonly texture-less. Obtaining the dense depth map of a texture-less scene is very difficult because traditional feature-based 3D reconstruction methods cannot detect enough features to build dense correspondences for depth computation. Given this problem, this study proposes a novel reconstruction method based on our shape-based image augmentation method. The main contribution of this method is the provision of a novel means to resolve the texture-less problem mainly on the input data level. In our method, we first calculate two shape gradient maps using Shape-From-Shading (SFS) method and we build Fast Point Feature Histogram (FPFH) 3D descriptor map according to the shape. Second, a series of augmented images can be computed by combining shape gradient maps, FPFH map, and the original image with different weights. Finally, we detect features on the new augmented images. Based on feature calculated sparse depth information and SFS calculated dense shape information, we further integrate a rectified dense depth map. Experiments show that our method can reconstruct texture-less surfaces with good accuracy.

Sequential Covariance Intersection Fusion Robust Time-Varying Kalman Filters with Uncertainties of Noise Variances for Advanced Manufacturing.

This paper addresses the robust Kalman filtering problem for multisensor time-varying systems with uncertainties of noise variances. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, the robust local time-varying Kalman filters are presented. Further, the batch covariance intersection (BCI) fusion and a fast sequential covariance intersection (SCI) fusion robust time-varying Kalman filters are presented. They have the robustness that the actual filtering error variances or their traces are guaranteed to have a minimal upper bound for all admissible uncertainties of noise variances. Their robustness is proved based on the proposed Lyapunov equations approach. The concepts of the robust and actual accuracies are presented, and the robust accuracy relations are proved. It is also proved that the robust accuracies of the BCI and SCI fusers are higher than that of each local Kalman filter, the robust accuracy of the BCI fuser is higher than that of the SCI fuser, and the actual accuracies of each robust Kalman filter are higher than its robust accuracy for all admissible uncertainties of noise variances. The corresponding steady-state robust local and fused Kalman filters are also presented for multisensor time-invariant systems, and the convergence in a realization between the local and fused time-varying and steady-state Kalman filters is proved by the dynamic error system analysis (DESA) method and dynamic variance error system analysis (DVESA) method. A simulation example is given to verify the robustness and the correctness of the robust accuracy relations.

CTSim: a numerical simulator of computed tomography for high-quality radiological education.

PURPOSE: Computer-based simulation offers radiological students the possibility to experiment with computed tomography in a way not possible in class or in clinical practice. The aim of this study was to design a computed tomography numerical simulator (CTSim) for high-quality radiological education. METHODS: In this study, a CTSim is designed based on the mathematical and physical principles of CT imaging. The proposed CTSim includes pen-beam module, fan-beam module, and clinical CT module. The core design of the software includes four parts: the construction of sample models, construction of imaging parameters and artifact parameters, design of data acquisition models under different scanning modes, and design of image reconstruction algorithm. After the design of the CTSim, the proposed CTSim was tested in every step of CT imaging. RESULTS: Systematic verification demonstrated that the proposed CTSim can not only perform raw CT data acquisition, image reconstruction, basic image processing, and image quality analysis like a real CT scanner, but can also simulate the formation of artifacts. The CTSim can completely get rid of the hardware and achieve the same experimental results as the hardware instrument. CONCLUSION: The proposed CTSim software shows several advantages such as low cost, less room accommodation, and no ionizing radiation damage and can be used as a virtual experimental training platform to enhance teaching and learning for general X-ray CT courses or for self-study of CT practitioners.

Acquired platelet defects are responsible for nonsurgical bleeding in left ventricular assist device recipients.

BACKGROUND: Left ventricular assist devices (LVADs) have been used as a standard treatment option for patients with advanced heart failure. However, these devices are prone to adverse events. Nonsurgical bleeding (NSB) is the most common complication in patients with continuous flow (CF) LVADs. The development of acquired von Willebrand syndrome (AVWS) in CF-LVAD recipients is thought to be a key factor. However, AVWS is seen across a majority of LVAD patients, not just those with NSB. The purpose of this study was to examine the link between acquired platelet defects and NSB in CF-LVAD patients. METHODS: Blood samples were collected from 62 CF-LVAD patients at pre- and 4 post-implantation timepoints. Reduced adhesion receptor expression (GPIbα and GPVI) and activation of platelets (GPIIb/IIIa activation) were used as markers for acquired platelet defects. RESULTS: Twenty-three patients experienced at least one NSB episode. Significantly higher levels of platelet activation and receptor reduction were seen in the postimplantation blood samples from bleeders compared with non-bleeders. All patients experienced the loss of high molecular weight monomers (HMWM) of von Willebrand Factor (vWF), but no difference was seen between the two groups. Multivariable logistic regression showed that biomarkers for reduced platelet receptor expression (GPIbα and GPVI) and activation (GPIIb/IIIa) have more predictive power for NSB, with the area under curve (AUC) values of 0.72, 0.68, and 0.62, respectively, than the loss of HMWM of vWF (AUC: 0.57). CONCLUSION: The data from this study indicated that the severity of acquired platelet defects has a direct link to NSB in CF-LVAD recipients.

An image-guided hybrid robot system for dental implant surgery.

PURPOSE: Dental implant surgery is an effective method for remediating the loss of teeth. Robot is expected to increase the accuracy of dental implant surgery. However, most of them are industrial serial robot, with low stiffness and non-unique inverse kinematic solution, which may reduce the success rate and safety of robotic surgery. Compared to serial robot, parallel robot is more stiffness and has unique inverse kinematic. However, its workspace is small, which may not meet surgical requirements. Therefore, a novel hybrid robot dedicated to dental implant is proposed. METHODS: The hybrid robot is composed of three translation joints, two revolute joints, and Stewart parallel manipulator. Stewart is used for performing surgical operation, while the joints are used for enlarging the workspace of Stewart. In order to ensure the safety of robot motion, physical human-robot interaction based on a variable admittance controller is applied in the robotic system. In addition, considering the small workspace of Stewart, an optimal model is proposed to minimize the joint movement of Stewart in adjusting the orientation of drill bit. RESULTS: Phantom experiments were carried out based on the prototype robot. In the experiments, the optimal model could be solved after 20 iterations, finding an ideal joint configuration. The proposed variable admittance controller could enhance comfort level effectively. The accuracy of robot is evaluated by angle, entry and exit deviation, which are 0.74 ± 0.25°, 0.93 ± 0.28 mm, and 0.96 ± 0.23 mm, respectively. CONCLUSION: The phantom experiments validate the functionality of the proposed hybrid robot. The satisfactory performance makes it more widely used in the practical dental implant surgery in the future.

Device-Induced Hemostatic Disorders in Mechanically Assisted Circulation.

Mechanically assisted circulation (MAC) sustains the blood circulation in the body of a patients undergoing cardiac surgery with cardiopulmonary bypass (CPB) or on ventricular assistance with a ventricular assist device (VAD) or on extracorporeal membrane oxygenation (ECMO) with a pump-oxygenator system. While MAC provides short-term (days to weeks) support and long-term (months to years) for the heart and/or lungs, the blood is inevitably exposed to non-physiological shear stress (NPSS) due to mechanical pumping action and in contact with artificial surfaces. NPSS is well known to cause blood damage and functional alterations of blood cells. In this review, we discussed shear-induced platelet adhesion, platelet aggregation, platelet receptor shedding, and platelet apoptosis, shear-induced acquired von Willebrand syndrome (AVWS), shear-induced hemolysis and microparticle formation during MAC. These alterations are associated with perioperative bleeding and thrombotic events, morbidity and mortality, and quality of life in MCS patients. Understanding the mechanism of shear-induce hemostatic disorders will help us develop low-shear-stress devices and select more effective treatments for better clinical outcomes.