Nikola Mijailovic

Numerical and experimental analysis of factors leading to suture dehiscence after Billroth II gastric resection

The main goal of this study was to numerically quantify risk of duodenal stump blowout after Billroth II (BII) gastric resection. Our hypothesis was that the geometry of the reconstructed tract after BII resection is one of the key factors that can lead to duodenal dehiscence. We used computational fluid dynamics (CFD) with finite element (FE) simulations of various models of BII reconstructed gastrointestinal (GI) tract, as well as non-perfused, ex vivo, porcine experimental models. As main geometrical parameters for FE postoperative models we have used duodenal stump length and inclination between gastric remnant and duodenal stump. Virtual gastric resection was performed on each of 3D FE models based on multislice Computer Tomography (CT) DICOM. According to our computer simulation the difference between maximal duodenal stump pressures for models with most and least preferable geometry of reconstructed GI tract is about 30%. We compared the resulting postoperative duodenal pressure from computer simulations with duodenal stump dehiscence pressure from the experiment. Pressure at duodenal stump after BII resection obtained by computer simulation is 4-5 times lower than the dehiscence pressure according to our experiment on isolated bowel segment. Our conclusion is that if the surgery is performed technically correct, geometry variations of the reconstructed GI tract by themselves are not sufficient to cause duodenal stump blowout. Pressure that develops in the duodenal stump after BII resection using omega loop, only in the conjunction with other risk factors can cause duodenal dehiscence. Increased duodenal pressure after BII resection is risk factor. Hence we recommend the routine use of Roux en Y anastomosis as a safer solution in terms of resulting intraluminal pressure. However, if the surgeon decides to perform BII reconstruction, results obtained with this methodology can be valuable.

Modeling of abdominal aortic aneurism rupture by using experimental bubble inflation test

Aneurysm rupture is a biomechanical phenomenon that occurs when the mechanical stress acting on the inner wall exceeds the failure strength of the diseased aortic tissue. Besides numerous advantages in surgical and anaesthesiological management, emergency procedure leads to fatal outcome in 20-50% of those who reach hospital. Prediction of influence of dynamic blood flow on natural history of aneurysmatic disease and outcome of therapeutic procedures could contribute to treatment strategy and results. In this study we presented experimental design for estimation of the material property of real human aorta tissue from bubble inflation test. Then we investigated fluid-structure interaction of pulsatile blood flow in the specific patient three-dimensional model of abdominal aortic aneurysms (AAAs). Numerical predictions of blood flow patterns and nonlinear wall stresses in AAAs are performed in compliant wall anisotropic model using the finite element method. These computational procedures together with experimental determination of the nonlinear material property could provide us more accurate assessment of aneurysm rupture risk.

Manufacturing of Biodegradable Scaffolds to Engineer Artificial Blood Vessel

Abstract Blood vessels diseases such as cardiac infarction with coronary artery occlusion, peripheral arterial disorders, or stroke of carotid or cerebral arteries, are the leading causes of death in the world. One of medical procedures for clinical treatment of vascular diseases is the blood vessels grafting. As the autologous blood vessels, which are the “golden standard” for coronary grafting, are not always suitable for blood vessels grafting, there is a need to develop artificial blood vessels as a vascular prostheses, either from natural and synthetic materials, permanent synthetic or biodegradable scaffolds which would be suitable for vascular grafts. Considering this to be our study goal we made bilayered biodegradable polycaprolactone scaffolds with different properties and evaluated their morphological and biomechanical characteristics.

Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers

Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of the region of interest from a breast image, followed by the identification of suspicious mass regions, their classification, and comparison with the existing image database. It is often the case that already existing image databases have large sets of data whose processing requires a lot of time, and thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. In this paper, the implementation of the already existing algorithm for region-of-interest based image segmentation for mammogram images on High-Performance Reconfigurable Dataflow Computers (HPRDCs) is proposed. As a dataflow engine (DFE) of such HPRDC, Maxelers acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable Dataflow Computers (RDCs) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave a different acceleration value of algorithm execution. Those acceleration values are presented and experimental results showed good acceleration.

Assessment of Mechanical Stiffness of Jumping Using Force Plate

In this paper the basic information about methodology of assessment human body stiffness during vertical jump analysis is presented. Ten subjects (professional football player) perform ten periodic jumps and vertical ground reaction force is measured using a force plate with one axial load cell force sensor. The stiffness calculation is based on the analogy of the periodic jumping and oscillation movement of the system which consists of spring and body appropriate mass. The frequency of oscillation is obtained using Fourier transform.

Modeling of radiation dose of human head during CT scanning using neural networks

In this study the authors present the method for determination of exposure dose on human head during computer tomography (CT) scanning procedure. The method is based on the use of the feed-forward neural network (FFNN) model to predict the exposure dose on human head. The neural network with Levenberg-Marquardt learning is constructed. The training data are obtained using the Monte Carlo method simulation. The simulation is performed by generating random numbers for determination of photon direction and for quantification of interaction between X-ray photon and head tissue. Spectra of photon energy is used for 3DCT scanner, X-ray tube Model XRS-125-7K-P. The FFNN predicted values are in accordance with the values obtained by the simulation with correlation coefficient around 0.99.

Assessment of Knee Cartilage Stress Distribution and Deformation Using Motion Capture System and Wearable Sensors for Force Ratio Detection.

Knowledge about the knee cartilage deformation ratio as well as the knee cartilage stress distribution is of particular importance in clinical studies due to the fact that these represent some of the basic indicators of cartilage state and that they also provide information about joint cartilage wear so medical doctors can predict when it is necessary to perform surgery on a patient. In this research, we apply various kinds of sensors such as a system of infrared cameras and reflective markers, three-axis accelerometer, and force plate. The fluorescent marker and accelerometers are placed on the patients hip, knee, and ankle, respectively. During a normal walk we are recording the space position of markers, acceleration, and ground reaction force by force plate. Measured data are included in the biomechanical model of the knee joint. Geometry for this model is defined from CT images. This model includes the impact of ground reaction forces, contact force between femur and tibia, patient body weight, ligaments, and muscle forces. The boundary conditions are created for the finite element method in order to noninvasively determine the cartilage stress distribution.