Search

TiO2 scaffolds have previously shown to have promising osteoconductive properties in previous in vivo experiments. Appropriate mechanical stimuli can further promote this osteoconductive behaviour. However, the complex mechanical environment and the mechanical stimuli enhancing bone regeneration for porous bioceramics have not yet been fully elucidated. This paper aims to compare and evaluate mechanical environment of TiO2 scaffold with three commercial CaP biomaterials, i.e. Bio-Oss, Cerabone and Maxresorb under simulated perfusion culture conditions. The solid phase and fluid phase were modelled as linear elastic material and Newtonian fluid, respectively. The mechanical stimulus was analysed within these porous scaffolds quantitatively. The results showed that the TiO2 had nearly heterogeneous stress distributions, however lower effective Young's modulus than Cerabone and Maxresorb. The permeability and wall shear stress (WSS) for the TiO2 scaffold was significantly higher than other commercial bone substitute materials. Maxresorb and Bio-Oss showed lowest permeability and local areas of very high WSS. The detailed description of the mechanical performance of these scaffolds could help researchers to predict cell behaviour and to select the most appropriate scaffold for different in vitro and in vivo performances. Graphical abstract Schematic representation of the establishment procedure. Take the establishment process of Cerabone as an example. Left shows a slice of micro-CT image from Cerabone, and 1.5 mm × 1.5 mm region of interest was shown in the red box. A 1.5-mm3 cube was cut out by Boolean operation in Mimics (Materialise, Belgium), and the cubic model was remeshed in 3-Matic 6.0 (Materialise, Belgium). The cubic model is shown in blue, and the empty space in red. [ABSTRACT FROM AUTHOR]

Electrode designs and strategies for electroneurogram recordings are often tested first by computer simulations and then by animal models, but they are rarely implanted for long-term evaluation in humans. The models show that the amplitude of the potential at the surface of an axon is higher in front of the nodes of Ranvier than at the internodes; however, this has not been investigated through in vivo measurements. An original experimental method is presented to emulate a single fiber action potential in an infinite conductive volume, allowing the potential of an axon to be recorded at both the nodes of Ranvier and the internodes, for a wide range of electrode-to-fiber radial distances. The paper particularly investigates the differences in the action potential amplitude along the longitudinal axis of an axon. At a short radial distance, the action potential amplitude measured in front of a node of Ranvier is two times larger than in the middle of two nodes. Moreover, farther from the phantom axon, the measured action potential amplitude is almost constant along the longitudinal axis. The results of this new method confirm the computer simulations, with a correlation of 97.6 %. [ABSTRACT FROM AUTHOR]

This paper presents a novel hybrid medical stent device. This hybrid stent device formed by fractal mesh structures provides a flow-diverting effect and stent-assisted coil embolization. Flow-diverter stents decrease blood flow into an aneurysm to prevent its rupture. In general, the mesh size of a flow-diverter stent needs to be small enough to prevent blood flow into the aneurysm. Conventional flow-diverter stents are not available for stent-assisted coil embolization, which is an effective method for aneurysm occlusion, because the mesh size is too small to insert a micro-catheter for coil embolization. The proposed hybrid stent device is capable of stent-assisted coil embolization while simultaneously providing a flow-diverting effect. The fractal stent device is composed of mesh structures with fine and rough mesh areas. The rough mesh area can be used to insert a micro-catheter for stent-assisted coil embolization. Flow-diverting effects of two fractal stent designs were composed to three commercially available stent designs. Flow-diverting effects were analyzed using computational fluid dynamics (CFD) analysis and particle image velocimetry (PIV) experiment. Based on the CFD and PIV results, the fractal stent devices reduce the flow velocity inside an aneurism just as much as the commercially available flow-diverting stents while allowing stent-assisted coil embolization. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of developing arterial blockage at the abdominal aorta on the blood pressure waves at an externally accessible location suitable for invasive measurements such as the brachial and the femoral arteries. Arterial blockages are created surgically within the abdominal aorta of healthy Wistar rats to create narrowing resemblance conditions. Blood pressure is measured using a catheter inserted into the right femoral artery. Measurements are taken at the baseline healthy condition as well as at four different severities (20, 50, 80 and 100 %) of arterial blockage. In vivo and in vitro measurements of the lumen diameter and wall thickness are taken using magnetic resonance imaging and microscopic techniques, respectively. These data are used to validate a 3D computational fluid dynamics model which is developed to generalize the outcomes of this work and to determine the arterial stress and strain under the blockage conditions. This work indicates that an arterial blockage in excess of 20 % of the lumen diameter significantly influences the pressure wave and reduces the systolic blood pressure at the right femoral artery. High wall shear stresses and low circumferential strains are also generated at the blockage site. [ABSTRACT FROM AUTHOR]

Fitting the measured bioimpedance spectroscopy (BIS) data to the Cole model and then extracting the Cole parameters is a common practice in BIS applications. The extracted Cole parameters then can be analysed as descriptors of tissue electrical properties. To have a better evaluation of physiological or pathological properties of biological tissue, accurate extraction of Cole parameters is of great importance. This paper proposes an improved Cole parameter extraction based on bacterial foraging optimization (BFO) algorithm. We employed simulated datasets to test the performance of the BFO fitting method regarding parameter extraction accuracy and noise sensitivity, and we compared the results with those of a least squares (LS) fitting method. The BFO method showed better robustness to the noise and higher accuracy in terms of extracted parameters. In addition, we applied our method to experimental data where bioimpedance measurements were obtained from forearm in three different positions of the arm. The goal of the experiment was to explore how robust Cole parameters are in classifying position of the arm for different people, and measured at different times. The extracted Cole parameters obtained by LS and BFO methods were applied to different classifiers. Two other evolutionary algorithms, GA and PSO were also used for comparison purpose. We showed that when the classifiers are fed with the extracted feature sets by BFO fitting method, higher accuracy is obtained both when applying on training data and test data. [ABSTRACT FROM AUTHOR]

Previous studies showed that all the vascular parameters from both the morphological and topological parameters were affected with the altering of imaging resolutions. However, neither the sensitivity analysis of the vascular parameters at multiple resolutions nor the distinguishability estimation of vascular parameters from different data groups has been discussed. In this paper, we proposed a quantitative analysis method of vascular parameters for vascular networks of multi-resolution, by analyzing the sensitivity of vascular parameters at multiple resolutions and estimating the distinguishability of vascular parameters from different data groups. Combining the sensitivity and distinguishability, we designed a hybrid formulation to estimate the integrated performance of vascular parameters in a multi-resolution framework. Among the vascular parameters, degree of anisotropy and junction degree were two insensitive parameters that were nearly irrelevant with resolution degradation; vascular area, connectivity density, vascular length, vascular junction and segment number were five parameters that could better distinguish the vascular networks from different groups and abide by the ground truth. Vascular area, connectivity density, vascular length and segment number not only were insensitive to multi-resolution but could also better distinguish vascular networks from different groups, which provided guidance for the quantification of the vascular networks in multi-resolution frameworks. [ABSTRACT FROM AUTHOR]

The fetal electrocardiogram (fECG) contains important information regarding the health of the fetus. However, the fECG obtained noninvasively from the abdominal surface electrical recordings of a pregnant woman are dominated by strong interference from the maternal electrocardiogram (mECG). In this paper, based on the H(infinity) principle, two adaptive algorithms are proposed for the extraction of fECG from the trans-abdominal recordings of pregnant women. The motivation behind the application of H(infinity) techniques is the fact that they are robust with respect to model uncertainties and lack of statistical information regarding noise. The proposed algorithms are applied to simulated as well as real multichannel ECG recordings and their performances are compared to that of the well-known least-mean-square (LMS) adaptive algorithm. It is found that the proposed H(infinity) based algorithms perform superior to the LMS algorithm in extracting the fECG signal. [ABSTRACT FROM AUTHOR]

With the advent of powerful computers and parallel processing including Grid technology, the use of Monte Carlo (MC) techniques for radiation transport simulation has become the most popular method for modeling radiological imaging systems and particularly X-ray computed tomography (CT). The stochastic nature of involved processes such as X-ray photons generation, interaction with matter and detection makes MC the ideal tool for accurate modeling. MC calculations can be used to assess the impact of different physical design parameters on overall scanner performance, clinical image quality and absorbed dose assessment in CT examinations, which can be difficult or even impossible to estimate by experimental measurements and theoretical analysis. Simulations can also be used to develop and assess correction methods and reconstruction algorithms aiming at improving image quality and quantitative procedures. This paper focuses mainly on recent developments and future trends in X-ray CT MC modeling tools and their areas of application. An overview of existing programs and their useful features will be given together with recent developments in the design of computational anthropomorphic models of the human anatomy. It should be noted that due to limited space, the references contained herein are for illustrative purposes and are not inclusive; no implication that those chosen are better than others not mentioned is intended. [ABSTRACT FROM AUTHOR]

This paper presents a three-dimensional (3D) reconstruction system of the human spine for the routine evaluation of musculoskeletal pathologies like idiopathic scoliosis. The main objective of this 3D reconstruction system is to offer a versatile and robust tool for the 3D analysis of spines in any healthcare centre with standard clinical setup using standard uncalibrated radiographic images. The novel system uses a self-calibration algorithm and a weak-perspective method to reconstruct the 3D coordinates of anatomical landmarks from bi-planar radiographic images of a patient's trunk. Additionally, a small planar object of known dimensions is proposed to warrant an accurately scaled model of the spine. In order to assess the validity of the 3D reconstructions yielded by the proposed system, a clinical study using 60 pairs of digitized X-rays of adolescents was conducted. The subject cohort in the study group was composed of 51 scoliotic and 9 non-scoliotic patients, with an average Cobb angle on the frontal plane of 25 degrees. For each case, a 3D reconstruction of the spine and pelvis was obtained with the previous system used at our hospital (which requires a positioning apparatus and a calibration jacket), and with the proposed method. Results show that 3D reconstructions obtained with the new system using uncalibrated X-ray images yield geometrically accurate models with insignificant differences for 2D and 3D clinical indexes commonly used in the evaluation of spinal deformities. This demonstrates the system to be a viable and accurate tool for clinical studies and biomechanical analysis purposes, with the added advantage of versatility to any clinical setup for routine follow-ups and surgical planning. [ABSTRACT FROM AUTHOR]

Analysis of three-dimensional (3D) images of human torsos for torso deformities such as scoliosis requires classifying torso distortion. Assessing torso distortion from 3D images is not trivial as actual torsos are non-symmetric and show an outstanding range of variations leading to high classification errors. As the degree of spinal deformity (and classification of torso shape) influences scoliosis treatment options, the development of more accurate classification procedures is desirable. This paper presents a technique for assessing torso shape and classifying scoliosis into mild, moderate and severe categories using two indices, 'twist' and 'bend', obtained from orthogonally transformed images of the complete torso surface called orthogonal maps. Four transforms (axial line, unfolded cylinder, enclosing cylinder and subtracting cylinder) were used. Blind tests on 361 computer models with known deformation parameter values show 100% classification accuracy. Tests on eight volunteers without scoliosis validated the system and tests on 22 torso images of volunteers with scoliosis showed up to 95.5% classification accuracy. In addition to classifying scoliosis, orthogonal maps present the entire torso in one view and are viable for use in scoliosis clinics for monitoring the progression of scoliosis. [ABSTRACT FROM AUTHOR]

In this paper, we describe a computational model dedicated to building an apnoea monitoring system for newborn babies. The proposed model is based on whole body plethysmography, which involves non-invasive measurement of lung ventilation indirectly from the pressure deflections generated when a subject breathes inside a chamber of fixed volume (Bert in C R Soc Biol Paris 20:22-23, 1868). The computational model simulates thermal and environmental flow conditions occurring in the neonate chamber, especially steady state flow with heat transfer and carbon dioxide (CO2) transport during the exhalation phase. This permits the variance of all critical parameters and the analysis of their effects on the distributions of interest. The main objective is to study thermal and air quality comfort conditions under which infants can be monitored for long-term periods. The method deploys computational fluid dynamics techniques and parametric modelling which, by allowing input parameters to be modulated, represent a more efficient and flexible analytical tool than previous experimental techniques. Simulation data reveal that the largest flow rates occur in areas near the openings with slight formation of air recirculation zones; temperature distribution shows signs of stratification, with higher temperatures than the supplied air, CO2 distribution presents acceptable air quality level and predicted mean vote index affords a relatively acceptable thermal comfort level. This analytical approach can be considered as innovative, and can find a new application in clinical infant apnoea monitoring in a way that allows determination of the optimal location for placing a sensor to detect respiration activity without any contact with the infant's body, and without any risk, in contrast to available whole body plethysmography techniques previously tested in infants (Fleming et al. in J Appl Physiol 55:1924-1931, 1983). [ABSTRACT FROM AUTHOR]

Surface-recorded somatosensory-evoked potentials (SEPs) are neural signals elicited by an external stimulus. In the case of electrically induced SEPs, the artifact generated by the stimulation process can severely distort the signal. In some cases, the artifact tail often lasts well into the initiation of the SEP making the determination of absolute latency very difficult. In this work, a new approach was taken to identify factors that affect the tail of the artifact. The methodology adopted was the development of a lumped electrical circuit model of the artifact generation process. While the modeling of the instrumentation hardware is relatively simple, this is not the case with tissue and electrode/skin interface effects. Consequently, this paper describes a novel tissue modeling approach that uses an autoregressive moving average (ARMA) parametric technique and an artificial neural network (ANN) to estimate tissue parameters from experimental data. This coupled with an estimation of the stimulation electrode-skin impedance completes the lumped circuit model. Simulink (The Mathworks Inc.) was used to evaluate the model under several different conditions. These results show that both the stimulation electrode-skin interface impedance and nature of the body tissue directly under the recording electrodes have a profound effect on the appearance of the stimulus artifact tail. This was verified by experimentally recorded data obtained from the median nerve using surface electrodes. Conclusions drawn from this work include that stimulation electrodes with low series capacitance should be used whenever possible to minimize the duration of the artifact tail. [ABSTRACT FROM AUTHOR]

The electrogastrogram (EGG), a cutaneous measurement of gastric electrical activity, is a mixture of gastric slow waves and noise. To detect the propagation of gastric slow waves, it is desired to obtain gastric slow waves in each of multichannel EGGs. Recently, independent component analysis (ICA) has shown its efficiency in separating the gastric slow wave from noisy multichannel EGGs. However, this method is not able to recover gastric slow waves in each of the multichannel EGGs. In this paper, a two-stage combined method was proposed for extracting gastric slow waves. First, ICA was performed to separate the gastric slow wave component from noisy multichannel EGGs. Second, adaptive signal enhancement with a reference input derived by the ICA in the first stage was employed to extract gastric slow waves in each channel. Quantitative analysis showed that, with the proposed method, the maximum root-mean-square error between the estimated time lag and its theoretical value in the simulations was only 0.65. The results from real EGG data demonstrated that the combined method was able to extract gastric slow waves from individual channels of EGGs which are important to identify the slow wave propagation. Therefore, the proposed method can be used to detect propagation of gastric slow waves from multichannel EGGs. [ABSTRACT FROM AUTHOR]

The paper describes a spherical harmonic-based finite element scheme for solving Poisson-type equations throughout volumes characterised by irregularly shaped inner and outer surfaces. The inner and outer surfaces are defined by spherical harmonics, and the volume in between these surfaces is divided into nested shells that are weighted averages of the inner and outer surfaces. The resulting mesh comprises hexahedral elements, wherein each hexahedral element is defined by inner and outer shells in the radial direction and divisions in the polar and azimuthal directions. The spacing between shells can be set to any desired value. Similarly, the size of the polar and azimuthal divisions can be specified. A test of the scheme on an anisotropic sphere, meshed with 720 nodes, yielded a relative error of 0.78% on the sphere's surface. As a comparison, a previously published combined finite element/boundary element scheme with a 946-node mesh produced a corresponding error of 3.57%. [ABSTRACT FROM AUTHOR]

This study focused on the application of real-time Kalman filters to biomechanical data and, in particular, the simulation environment used to compare the performance of modified and standard two-state Kalman filters when estimating displacement and velocity from noisy displacement data. The modification proposed in this paper was the numerical tachometer, augmented by a median smoother. The numerical tachometer integrated the derivative estimates from finite differences of noisy sampled data into the Kalman filter structure; the median smoother acted before differentiation, to protect from grossly erroneous measurements. The numerical tachometer allowed better fits to the simulated data than can be achieved without it: the root mean square errors decreased by 10% in the displacement domain and by 54% in the velocity domain, for sampling frequencies and signal contamination levels that were typical in human movement sciences. The sensitivity to errors in the modelling of the signal and noise characteristics was less than in the standard filter implementation. The use of the median smoother improved the robustness of the filtering algorithm against additive white Gaussian measurement noise and allowed the cancellation of isolated noise spikes. [ABSTRACT FROM AUTHOR]