Engineering Commons^™

Magnetic Resonance Imaging Compatible Remote Catheter Navigation System, Mohammad Ali Tavallaei

Electronic Thesis and Dissertation Repository

Many vascular and cardiac diseases are diagnosed and treated using a medical technique known as percutaneous transluminal catheter intervention (PTC). In PTC, the interventionalist inserts a catheter into the vasculature, and using the vessel as the guiding passageway, the catheter is navigated to desired anatomical targets where it would be used for various purposes such as catheter ablation for the treatment/management of cardiac arrhythmias. The catheterization procedure is conventionally guided with x-ray fluoroscopic imaging and more recently, but rarely, with Magnetic Resonance Imaging (MRI). X-ray imaging irradiates the patient directly during the procedure, and the staff and interventionalists indirectly through …

Cardiovascular Magnetic Resonance Imaging-Based Computational Fluid Dynamics/Fluid-Structure Interaction Pilot Study To Detect Early Vascular Changes In Pediatric Patients With Type 1 Diabetes, Margaret M. Samyn, Ronak Jashwant Dholakia, Hongfeng Wang, Jennifer Co-Vu, Ke Yan, Michael E. Widlansky, John F. Ladisa Jr., Pippa Simpson, Ramin Alemzadeh

Biomedical Engineering Faculty Research and Publications

We hypothesized that pediatric patients with type 1 diabetes have cardiac magnetic resonance (CMR) detectable differences in thoracic aortic wall properties and hemodynamics leading to significant local differences in indices of wall shear stress, when compared with age-matched control subjects without diabetes. Pediatric patients with type 1 diabetes were recruited from Children’s Hospital of Wisconsin and compared with controls. All underwent morning CMR scanning, 4-limb blood pressure, brachial artery reactivity testing, and venipuncture. Patient-specific computational fluid dynamics modeling with fluid–structure interaction, based on CMR data, determined regional time-averaged wall shear stress (TAWSS) and oscillatory shear index (OSI). Twenty type 1 …

Diffusion Imaging In The Rat Cervical Spinal Cord, Elizabeth Zakszewski, Brian D. Schmit, Shekar N. Kurpad, Matthew D. Budde

Biomedical Engineering Faculty Research and Publications

Magnetic resonance imaging (MRI) is the state of the art approach for assessing the status of the spinal cord noninvasively, and can be used as a diagnostic and prognostic tool in cases of disease or injury. Diffusion weighted imaging (DWI), is sensitive to the thermal motion of water molecules and allows for inferences of tissue microstructure. This report describes a protocol to acquire and analyze DWI of the rat cervical spinal cord on a small-bore animal system. It demonstrates an imaging setup for the live anesthetized animal and recommends a DWI acquisition protocol for high-quality imaging, which includes stabilization of …

A Pneumatically Actuated Manipulandum For Neuromotor Control Research, Aaron J Suminski, Kristina Ropella, Robert Scheidt

Robert Scheidt

Functional magnetic resonance imaging (fMRI) techniques have great potential for identifying which neural structures are involved in the control of goal-directed reaching movements. However, fMRI techniques alone are not capable of probing the neural mechanisms involved in acquisition of novel motor behaviors because such studies require that the moving limb be perturbed in a controlled fashion. We outline a plan to design and develop a non-metallic, pneumatically actuated tool that, along with systems identification techniques and functional magnetic resonance imaging (fMRI), will characterize and quantify how the human central nervous system uses sensory information during practice-based motor learning.

A Comparative Study Of Two Prediction Models For Brain Tumor Progression, Deqi Zhou, Loc Tran, Jihong Wang, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images.

We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. …