Patient-Specific Simulations in Interventional Cardiology Practice: Early Results From a Clinical/Engineering Centre

Patient-specific models have been recently applied to investigate a wide range of cardiovascular problems including cardiac mechanics, hemodynamic conditions and structural interaction with devices [1]. The development of dedicated computational tools which combined the advances in the field of image elaboration, finite element (FE) and computational fluid-dynamic (CFD) analyses has greatly supported not only the understanding of human physiology and pathology, but also the improvement of specific interventions taking into account realistic conditions [2, 3]. However, the translation of these technologies into clinical applications is still a major challenge for the engineering modeling community, which has to compromise between numerical accuracy and response time in order to meet the clinical needs [4]. Hence, the validation of in silico against in vivo results is crucial. Finally, if the development of novel tools has recently attracted big investments [5], it has not been similarly easy to dedicate funds and time to test the developed technologies on large numbers of patient cases.

A New Method to Concentrate Electromagnetic Field Within ROI Using a High Dielectric Material in 3T Body MRI

We present numerical simulation results showing that high dielectric materials (HDMs) when placed between the human body model and the body coil significantly alter the electromagnetic field inside the body. The numerical simulation results show that the electromagnetic field (E, B, and SAR) within a region of interest (ROI) is concentrated (increased). In addition, the average electromagnetic fields decreased significantly outside the region of interest. The calculation results using a human body model and HDM of Barium Strontium Titanate (BST) show that the mean local SAR was decreased by about 56% (i.e., 18.7 vs. 8.2 W/kg) within the body model.

Challenges in Blood Flow Simulation: Numerical Methods and Image Processing Tools

We report on recent results in modeling ocular blood flow (some parts were presented at ARVO 2013 [1]). For this simulations we used discrete exterior calculus based numerical methods. These methods aim to preserve the main features of the original analytical equations and are very suitable for curved surfaces. We will discuss the model and present the numerical methods. We will also give an overview of existing/available segmentation methods to extract the vascular tree from given retina images and our plans how to use them as a front end to our model.

The Effect of Static and Dynamic Loading on Degradation of PLLA Stent Fibers

PLLA is a commonly used biodegradable polymer in stent designs because it is non-toxic and easily eliminated from the body. However, very little is known about the effect of loading conditions on the degradation rate. Rajagopal and Wineman developed a model of polymer degradation which is driven by load applied to the fiber [1]. Soares et. al. further developed this model for use with PLLA stent fibers under tensile loading conditions [2]. In this model the degradation rate is linearly related to deformation through the radius in the (IB, IIB) plane. Both models predict that greater deformation will induce a higher degree of degradation.

Tesla-Based Blood Pump and its Applications

A continuous flow left ventricular assist device (LVAD) that the Penn State University has developed utilizes Tesla turbomachinery technology. Tesla pumping technology patented by Nikola Tesla in the early 20th century has multiple intriguing characteristics such as simpler manufacturing process, reduced turbulent-related stress, less cavitation due to viscous flow distribution over larger surface areas, and less hemolysis by smooth transition of fluid energy. We successfully tested the 1st version of the Penn State Tesla LVAD [1, 2]. We recently tested the 2nd version of the Tesla pump; to make the pump usable in a wide range of patients, the size of the pump was significantly reduced while trying to avoid any degradation of hemodynamic and hemolytic characteristics.

Workflow for Creating a Simulation Ready Virtual Population for Finite Element Modeling

A proof of concept workflow is demonstrated to easily translate 3D medical image data into finite element (FE) simulation ready phantom models. First, novel methods are used to drastically reduce manual segmentation time for a virtual population. Next, using Simpleware software, the segmented voxel datasets are extracted into faceted 3D CAD objects for tissues, while simultaneously maintaining conformal multi-tissue interfaces. Finally, the 3D CAD geometries are demonstrated to be readily compatible in a commercial 3D electromagnetic simulator, ANSYS HFSS.

Development of a New Artificial Knee Joint for an Asian and Middle Eastern Population

Design of an artificial knee was developed using computer 3-D modeling, the high flexion knee was obtained by using a multi-radii design pattern, The increase of final 20 degrees in flexion was obtained by increasing the condylar radii of curvature. The model of the high flexion knee was developed and one of the models was subjected to finite element modeling and analysis. The compositions of components in the artificial knee were, femoral component and the tibial component were metal, whereas the patellar component and the meniscal insert were made using polyethylene. The metal component used for the analysis in this study was Ti6Al4V and the polyethylene used was UHMWPE. Overall biomaterials chosen were: meniscus (UHMWPE, mass = 0.0183701 kg, volume = 1.97518e-005 m3), tibial component (Ti6Al4V, mass = 0.0584655 kg, volume = 1.32013e-005 m3), femoral component (Ti6Al4V, mass = 0.153122 kg, volume = 3.45742e-005 m3), total artificial assembly (mass = 0.229958 kg, volume = 6.75e-005m3). However, in this design the load had been taken to 10 times the body weight. The weight over single knee is only half the maximum load as the load is shared between the two knee joints. Following were the loading conditions, taking average body weight to be 70Kgs and taking extreme loading conditions of up to 10 times the body weight, i.e. 700Kgs on each of the leg performed the Finite Element Analysis (FEA) over the newly designed knee. The loading was done at an increment of 100 Kgs. The loading conditions and the meshing details for the analysis of the assembly were Jacobian check: 4 points, element size: 0.40735 cm, tolerance: 0.20367 cm, quality: high, number of elements: 80909, number of nodes: 126898. A maximum load of 600 Kgs is optimum for this model. The other components observed linear elastic behavior for the applied loads. Based on these results it was determined that the load bearing capacity of the model were well within the failure levels of the materials used for the analysis. A maximum load of 600 Kgs is optimum for this model. The other components observed linear elastic behavior for the applied loads. Based on these results it was determined that the load bearing capacity of the model were well within the failure levels of the materials used for the analysis. Conclusion drawn from this is that for the first time an innovative new design of an artificial knee joint to suite a segment of some religious population has been developed. This allows them to pray, bend in different positions and squat without too much difficulty.

Optimization of Balloon Obstruction for Simulating Equivalent Pressure Drop in In-Vivo Conditions

The study of hemodynamics in an animal model associated with coronary stenosis has been limited due to the lack of a safe, accurate, and reliable technique for creating an artificial stenosis. Creating artificial stenosis using occluders in an open-chest procedure has often caused myocardial infarction (MI) or severe injury to the vessel resulting in high failure rates. To minimize these issues, closed-chest procedures with internal balloon obstruction were often used to create artificial stenosis. However, it should be noted that the hemodynamics in a blood vessel with internal balloon obstruction as opposed to physiological stenosis hasn’t been compared. Hence, the aim of this research is to computationally evaluate the pressure drop in balloon obstruction and compare with that in physiological stenosis. It was observed that the flow characteristics in balloon obstruction are more viscous dominated, whereas it is momentum dominated in physiological stenosis. Balloon radius was iteratively varied to get a pressure drop equivalent to that of physiological stenosis at mean hyperemic flow rates. A linear relation was obtained to predict equivalent balloon obstruction for physiological stenosis.

A Multiscale Specimen-Specific Data Set to Enable Comprehensive Modeling and Simulation of the Tibiofemoral Joint

The tibiofemoral joint is a complex structure and its overall mechanical response is dictated by its numerous substructures at both macro and micro levels. An in-depth understanding of the mechanics of the joint is necessary to develop preventative measures and treatment options for pathological conditions and common injuries. Finite element (FE) analysis is a widely used tool in joint biomechanics studies focused on understanding the underlying mechanical behavior at joint, tissue and cell levels [1]. Studies, regardless of their purpose (descriptive or predictive), when employing FE analysis, require anatomical and mechanical data at single or multiple scales. It is also critical that FE representations are validated and closely represent specifics of the joint of interest, anatomically and mechanically. This is an utmost need if these models are intended to be used to support clinical decision making (in surgery or for rehabilitation) and for the development of implants.

Quantitative Assessment of the Risk of Variations During Medical Device Lifecycle

The majority of medical devices are monitoring devices. Therefore, data communication and analysis are playing a crucial rule in predicting the effectiveness and reliability of a device. Device related data, patient related data and device-patient related data stored in Data Bases (DBs) are great sources for enhancing either new designs or improving already existing ones. Analyzing such data can provide researchers and device development teams with a complete justification and patterns of interest about a device’s performance, life and reliability. Data can be formulated into stochastic models based their statistical characteristics to consider the variability in data and the uncertainty about processes and procedures during early stages of the design process. This strengthens the device’s ability to function under a broader range of operating conditions. The work herein aims at targeting unwanted variations in device performance during the device development process. It employs a novel technique for variation risk management of device performance based historical process data modeling and visualization. The introduced technique is a proactive systematic procedure comprises a tool set that is being placed in the larger framework of the risk management procedure and fully utilizing data from the DBs to predict and address the risk of variations at the early stages of the design process rather than at the end of each major stage.