IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING
Year:2014 | Volume:8 | Issue:3|Papers Count:8

To develop the advanced technologies in medical device industry, design and manufacturing of cervical cage was performed in Iran for the first time. This research-based industrial project should be accomplished based on precise biomechanical studies and mechanical tests. Hence, this study presents the optimization and biomechanical functional investigations of the first Iranian cervical cage (Manufactured by Attila Ortopaed Co.). For this purpose the intact cervical spine (C2-C7) was developed and was validated with in-vitro experiments. Three inputs (i.e. geometrical parameters of the cage) and two outputs (i.e. deformation of the teeth in static and dynamic tests) parameters were selected for optimization procedure. Furthermore, the surgery in C5-C6 level was simulated by implanting the cervical cage. Finally, the biomechanical responses were investigated. The result confirmed that the biomechanical response of cervical cage is within the standard range and can be used well in clinics for surgical procedures.

Statistical Shape Models are used to interpret shapes. They include mean and variance of corresponding points of training shapes. One of the most important challenges in building statistical shape models is to establish correct correspondences among landmarks in a training set. In this paper, the non-rigid CPD (Coherent Point Drift) method is used to find correct correspondences among points. This method uses both Deterministic Annealing and a non-rigid scheme to register two shapes simultaneously. Then, the statistical shape model is built using a rigid transformation. The proposed method is evaluated using Compactness, Generalization ability and Specificity measures. The built model is compared to models created using the ICP (Iterative Closest Point), TPS-RPM (Thin Plate Spline – Robust Point Matching) and MDL (Minimum Descreption Length) methods by these metrics. The results show that the proposed method performs like the MDL regarding Specificity measure (0.21±0.06). The Compactness and Generalization ability measures of the proposed method are very similar to those for the MDL method. The run-time of our proposed method is about 68 seconds which is faster than non-rigid TPS-RPM and MDL approaches (390 and 3600 seconds respectively). Our results are superior to the ICP and TPS-RPM algorithms.

A hallmark of Alzheimer disease (the most common type of dementia in the elderly) is the aggregation and deposition of toxic species ranging from small soluble oligomers to insoluble fibril plaques of Amyloid-Beta protein originates from the cleavage of APP by Beta and Gama Secretase (Amyloid Hypothesis). An attractive therapeutic approach to treat AD is to identify small ligands capable of binding to A-Beta monomers and reverse its amyloidosis process. Here, a peptide drug having the sequence of GLMVG which has been derived from the C-terminal of A-Beta was used as breaker for a monomer of Beta sheet rich structure. The combination of Docking and Molecular Dynamics methods were used for simulation of drug-receptor interaction. This simulation implied that pent apeptide altered secondary structure of A-Beta monomer and declined its stability. This study proved that pent apeptide is capable to reverse Beta-sheet formation and can be considered as an AD drug in other preclinical studies.

Coronary Artery Diseases are one of the main reasons of mortality. When these arteries occlude, usually a Coronary Artery Bypass Graft (CABG) surgery is performed. Sine human Saphenous Veins (SV) is used for CABG, they are of interest for researchers. In this study human SV samples undergo inflation test, using an inflation test device. Displacements of the samples for different pressures are analyzed, and average values are used as input of a computational method. In the numerical simulation the tissue is assumed as an elastic, isotropic, and homogenous solid material, and its output is Young’s Modulus (E) of the tissue. Results show that E of the SV increases linearly with the distension pressure. Although simplifications were applied in this study, it can be helpful for giving a basic insight about mechanical properties of human Saphenous Vein, which can be followed by more realistic studies in the future.

Soman is one of the strongest nerve agents and treatment of poisoning with Soman is difficult and time-critical. Pyridostigmine bromide is an inhibitor of cholinesterase used for protecting against toxicity by Soman. In this study, a new injectable thermo sensitive sustained release dosage form of pyridostigmine bromide was achieved by chitosan/glycerol phosphate solution. In this study, thermo sensitivity and rheological properties of chitosan solution (2% w/v) in aqueous hydrochloric acid (0.1 molar) with different percent of glycerol phosphate salt as well as the release profile of pyridostigmine bromide have been investigated. It was observed that increasing the glycerol phosphate salt concentration would increase the pH of chitosan solution, while decrease its gelation time and loss or storage modulus. It was also observed that glycerol phosphate salt concentration has direct effect on hydrogel thermo reversibility. The presented results indicated that hydrogel containing 2% w/v of chitosan and 16% w/v of glycerol phosphate salt could sustain the delivery of pyridostigmine bromide, through Fickian diffusion, up to four days.

Functional changes in the brain motor network are responsible for the major clinical features of Parkinson’s disease (PD). Recent studies on investigation of the brain function show that there are spontaneous fluctuations between regions at rest as resting state network affected in various disorders. In this paper, we examine changes of functional dependency between brain regions of interest associated with known anatomical pathology in Parkinson Disease (PD) using copula theory on resting state fMRI. Five types of copulas were tested: Gaussian and t (Euclidean), Clayton, Gumbel and Frank (Archimedean). We used an efficient maximum likelihood procedure for estimating copula parameters. Goodness of fits was tested using root mean square error (RMSE) and kulback-leibler divergence between each copula function and joint empirical cumulative distribution. Control vs PD group comparison was also done on dependency parameter using parametric and nonparametric tests. The results show that functional dependency between cerebellum and basal ganglia is much stronger in PD than in control. In this paper, we proposed for the first time that joint distribution characteristics could potentially provide information on discriminative features for functional connectivity analysis between healthy and patients.

A new implementation of a synthetic aperture focusing technique is presented in the paper. Standard medical ultrasound imaging is done using line-by-line transmission with classical Delay-and-Sum (DAS) image reconstruction. Synthetic aperture imaging, however, has a better resolution and frame rate in cost of more computational load. To overcome this problem, block processing algorithms are used in radar and sonar which are relatively unknown in medical. To extend the methods to medical field, one should concern the parameters difference such as carrier frequency, signal band width, beam width and depth of imaging. In this paper, we extended one of these methods called wavenumber to medical ultrasound imaging with a simple model of synthetic aperture focus. We have also used chirp pulse excitation followed by matched filtering, windowing and spotlighting algorithm to compensate the effect of differences in parameters between radar and medical imaging. Computational complexity of the two reconstruction methods, wavenumber and DAS, have been calculated. Field II simulated point data has been used to evaluate the results in terms of resolution and contrast. Evaluations with simulated data show that for typical phantoms, reconstruction by wavenumber algorithm is almost 20 times faster than classical DAS while retaining the resolution.

Multiple muscle groups may be activated simultaneously during the most of activities. So, the appropriate muscle coordination must be emerged during a normal activity. Consequaently, for rehabilitation of movements such as hand writing and paiting in patients for example suffering from carpal channel syndrom or incomplete spinal cord injury, the correct muscle coordination patterns between the finger muscles and wrist muscles must be reestablished. So, in this paper a prediction methodology based on artificial neural networks (ANN) is proposed to approximate the Thumb fingure extensor and flexor muscles desired activation pattern during the hand writing and Painting. In the presented strategy, A nonlinear auto-regressive neural network (NARX), Recurrent Neural Network (RNN), Radial Basis Function (RBF), Multy Layer Perceptron (MLP) and an Adaptive-network-based fuzzy inference system (ANFIS) are trained to forecast the Extensor pollicis longus and Flexor pollicis brevis muscles activity of one thumb finger of hand using Extensor carpi radialis brevis and Flexor carpi ulnaris muscles activity of forearm. Quantitative evaluations show the promising performance of developed neural networks. Eight healthy volunteers participated in the experiments.