Background: Atherosclerosis is associated with chronic inflammation and lipid metabolism. The neutrophil to lymphocyte ratio (NLR) as an indicator of inflammation has been confirmed to be associated with cardiovascular disease prognosis. However, few studies have explored the effects of blood lipid variability on NLR. The aim of this study was to explore the relationship between variability in blood lipid levels and NLR. Methods: The association between variability in blood lipids and NLR was assessed with both univariate and multivariate linear regression. Multivariate linear regression was also performed for a subgroup analysis. Results: The variability of high-density lipoprotein cholesterol (HDL-C) (regression coefficients [β] 4.008, standard error (SE) 0.503, P-value<0.001) and low-density lipoprotein cholesterol (LDL-C) ([β] 0.626, SE 0.164, P-value<0.001) were risk factors for the NLR value, although baseline LDL-C and HDL-C were not risk factors for NLR values. Variability of HDL-C ([β] 4.328, SE 0.578, P-value<0.001) and LDL-C ([β] 0.660, SE 0.183, P-value<0.001) were risk factors for NLR variability. Subgroup analysis demonstrated that the relationship between variability of LDL-C and NLR was consistent with the trend of the total sample for those with diabetes mellitus, controlled blood lipid, statins, atorvastatin. The relationship between the variability of HDL-C and NLR was consistent with the trend of the total sample in all subgroups. Conclusion: The variability of HDL-C and LDL-C are risk factors for the value and variability of NLR, while the relationship between variability of HDL-C and NLR is more stable than the variability of LDL-C in the subgroup analysis, which provides a new perspective for controlling inflammation in patients undergoing PCI.
In endoscopic surgery, the surgical navigation needs to calculate the internal deformation of the soft tissue by biomechanical model which needs to determine the elastic properties and boundary conditions. However, these information cannot be obtained accurately in a real operation scenario. For example, only a limited portion of a liver surface can be observed in a hepatic surgery under endoscope while its elastic properties remain unknown. In addition, simple boundary conditions such as fixed constraints and free-force constraints are not physically adequate to simulate the elastic effect of ligaments attached to the liver. Biomechanical models of the soft tissue have been thoroughly studied in recent years. In these studies, boundary conditions play an important role in identification of elastic properties for mechanical model based methods. But they rarely combine these unknown conditions together to construct the model, and instead set boundary conditions or elastic properties as known for simplification. In this paper, we present a novel method to identify the Young’s modulus and equivalent spring constraint boundary conditions of a partially observed soft object with incomplete boundary conditions. The spring constraint boundary condition is applied to alternate the conventional displacement boundary conditions (e.g. free constraint and fixed constraint) and an inverse algorithm based on the standard finite element method (FEM) and Gauss-Newton (GN) method is developed, which takes external forces and displacements of observable nodes as inputs. A series of numerical simulation experiments are implemented and the analysis of simulation results show the feasibility of the proposed method.
Young's modulus and equivalent spring constraint boundary conditions of the soft tissue with locally observed displacements for endoscopic liver surgery, Computer Methods in Biomechanics and Biomedical Engineering,
3D needle insertion is important both in theoretical research and clinic practice. In literature, most needle insertion experiments use 2D experiment platforms. A few studies use 3D experiment platforms based on ultrasound or traditional stereo camera. The ultrasound has low resolution and traditional stereo camera is difficult to reconstruct objects without textures, which is not suitable for markers reconstruction. Hence, it is needed to design a 3D needle insertion experiment platform with high resolution and 3D reconstruction ability. In this paper, we design a 3D needle insertion platform based on the orthogonal-arranged dual camera. Error analysis and accuracy verification are carried out as well. First, experiment platform framework is designed and essential modules are introduced. Second, the error analyses based on Frechet distance are carried out to quantify the error led by the bevel facing angle and insertion angle. Third, to verify the 3D reconstruction accuracy, the 2D distance sensitivity experiments and 3D reconstruction experiments are carried out for the dual camera system. The accuracy of 3D reconstruction in the region of interest has been verified. To optimize the 3D needle insertion platform, a needle holder to ensure concentricity is applied. Besides, pre-insertion process and orthogonal-arranged double chessboard calibration are introduced into setup procedures. Finally, a 3D needle insertion experiment platform is designed and validated through needle path planning algorithm verification. Results show that the proposed experiment platform can steer the needle accurately and reconstruct the needle path and markers in acceptable accuracy.
This paper presents a novel dynamic path planning methodology for needle steering into the soft tissue. A real-time finite element model is used to simulate the procedure of a flexible needle into the homogeneous soft tissue, which provides the dynamic deformation information for the path planning. The relationship between needle base and tip is formulated as the transformations of homogeneous matrix with quasi-static assumptions. Based on the reachability of the flexible needle, the real-time motions of obstacles and target are considered through the dynamic needle-tissue interactions. A testbed including a XY linear stage, one rotator, and a CCD camera is constructed, and the experiments are designed to validate the proposed method. The 23G PTC needle was inserted into the PVA phantom with markers, and the CCD camera was utilized to record the needle trajectories and motions of target and obstacles. The targeting errors between the experimental and planned paths are less than 1.20 mm, and the distance from the obstacle to needle is not smaller than 1.16 mm. The results demonstrate that the proposed algorithm is effective for online planning the paths in the needle-tissue interactive environment.
High repeatability of needle insertion experiments is essential to the needle-phantom interaction model validation. However, the influential factors governing the accuracy of the phantom and needle deformations have not been systematically studied. In this paper, the impact of influential factors, including phantom characteristic represented by the ratio of DMSO and thawing time (TT), needle properties represented by needle external diameter (NED) and operating factors such as needle insertion velocity (IV), insertion positions (IP) and repeated insertion times (RITs) are analyzed by orthogonal experiment design. The range calculation shows the most sensitive parameters to phantom deformations are RITs, IV and DMSO while the most sensitive parameters to needle deflection are DMSO, TT and NED. By variance analysis, the significant factors on maximum tissue deformation (MTD) are IV, followed by RITs, DMSO and IP. And NED and TT have nearly no significant impact on MTD. The significant sequence on maximum needle deflection (MND) is as follows: DMSO, TT and NED. Results show that, among all impacting factors, phantom deformation is susceptible to both material properties and operative factors while the needle deflection is more susceptible to material properties of the phantom, which can help researchers in related fields to conduct experiments in a more precise manner and better understand the needle-phantom interaction mechanism.
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