Matching Items (13)

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Improving the Realism and Magnetic Resonance Imaging of Multicellular Tumor Spheroids

Description

Magnetic resonance imaging (MRI) of changes in metabolic activity in tumors and metabolic abnormalities can provide a window to understanding the complex behavior of malignant tumors. Both diagnostics and treatment

Magnetic resonance imaging (MRI) of changes in metabolic activity in tumors and metabolic abnormalities can provide a window to understanding the complex behavior of malignant tumors. Both diagnostics and treatment options can be improved through the further comprehension of the processes that contribute to tumor malignancy and growth. By detecting and disturbing this activity through personalized treatments, it is the hope to provide better diagnostics and care to patients. Experimenting with multicellular tumor spheroids (MCTS) allows for a rapid, inexpensive and convenient solution to studying multiple in vitro tumors. High quality magnetic resonance images of small samples, such as spheroid, however, are difficult to achieve with current radio frequency coils. In addition, in order for the information provided by these scans to accurately represent the interactions and metabolic activity in vivo, there is a need for a perfused vascular network. A perfused vascular network has the potential to improve metabolic realism and particle transport within a tumor spheroid. By creating a more life-like cancer model and allowing the progressive imaging of metabolic functions of such small samples, a better, more efficient mode of studying metabolic activity in cancer can be created and research efforts can expand. The progress described in this paper attempts to address both of these current shortcomings of metabolic cancer research and offers potential solutions, while acknowledging the potential of future work to improve cancer research with MCTS.

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Date Created
  • 2016-12

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Observing effects of drug modulation on electrophysiological response of Aplysia neurons

Description

The effect of three different drug modulators on the electrophysiological response of Aplysia neurons was observed through the use of extracellular and intracellular recordings. Extracellular recordings captured the effects of

The effect of three different drug modulators on the electrophysiological response of Aplysia neurons was observed through the use of extracellular and intracellular recordings. Extracellular recordings captured the effects of magnesium chloride and glutamate at a variety of concentrations for each. Intracellular recordings displayed the effects of magnesium chloride, glutamate, and GABA for two concentrations each. For extracellular recordings, the average firing rate, average peak-to-peak voltage, average SNR, and sorted units were considered. For intracellular recordings, average firing rate, average peak voltage, and average resting potential were considered. Significance of data could not be determined using statistical analysis due to having a sample size of 1 for every experiment.

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Date Created
  • 2014-05

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Modeling the Effect of Mechanical Deformation on Electrical Stimulation of Peripheral Nerve Fibers

Description

There are many challenges in designing neuroprostheses and one of them is to maintain proper axon selectivity in all situations. This project is based on an electrode that is implanted

There are many challenges in designing neuroprostheses and one of them is to maintain proper axon selectivity in all situations. This project is based on an electrode that is implanted into a fascicle in a peripheral nerve and used to provide tactile sensory feedback of a prosthetic arm. This fascicle can undergo mechanical deformation during every day motion. This work aims to characterize the effect of fascicle deformation on axon selectivity and recruitment when electrically stimulated using hybrid modeling. The main framework consists of combining finite element modeling (FEM) and simulation environment NEURON. A suite of programs was developed to first populate a fascicle with axons followed by deforming the fascicle and rearranging axons accordingly. A model of the fascicle with an implanted electrode is simulated to find the electrical potential profile through FEM. The potential profile is then used to compare which axons are activated in the two conformations of the fascicle using NERUON.

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Date Created
  • 2021-05

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Ultrahigh Field Functional Magnetic Resonance Electrical Impedance Tomography (fMREIT) in Neural Activity Imaging

Description

A direct Magnetic Resonance (MR)-based neural activity mapping technique with high spatial and temporal resolution may accelerate studies of brain functional organization.

The most widely used technique for brain functional

A direct Magnetic Resonance (MR)-based neural activity mapping technique with high spatial and temporal resolution may accelerate studies of brain functional organization.

The most widely used technique for brain functional imaging is functional Magnetic Resonance Image (fMRI). The spatial resolution of fMRI is high. However, fMRI signals are highly influenced by the vasculature in each voxel and can be affected by capillary orientation and vessel size. Functional MRI analysis may, therefore, produce misleading results when voxels are nearby large vessels. Another problem in fMRI is that hemodynamic responses are slower than the neuronal activity. Therefore, temporal resolution is limited in fMRI. Furthermore, the correlation between neural activity and the hemodynamic response is not fully understood. fMRI can only be considered an indirect method of functional brain imaging.

Another MR-based method of functional brain mapping is neuronal current magnetic resonance imaging (ncMRI), which has been studied over several years. However, the amplitude of these neuronal current signals is an order of magnitude smaller than the physiological noise. Works on ncMRI include simulation, phantom experiments, and studies in tissue including isolated ganglia, optic nerves, and human brains. However, ncMRI development has been hampered due to the extremely small signal amplitude, as well as the presence of confounding signals from hemodynamic changes and other physiological noise.

Magnetic Resonance Electrical Impedance Tomography (MREIT) methods could have the potential for the detection of neuronal activity. In this technique, small external currents are applied to a body during MR scans. This current flow produces a magnetic field as well as an electric field. The altered magnetic flux density along the main magnetic field direction caused by this current flow can be obtained from phase images. When there is neural activity, the conductivity of the neural cell membrane changes and the current paths around the neurons change consequently. Neural spiking activity during external current injection, therefore, causes differential phase accumulation in MR data. Statistical analysis methods can be used to identify neuronal-current-induced magnetic field changes.

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Date Created
  • 2019

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Improved spatial coverage of high-temporal resolution dynamic susceptibility contrast-MRI through 3D spiral-based acquisition and parallel imaging

Description

Dynamic susceptibility contrast MRI (DSC-MRI) is a powerful tool used to quantitatively measure parameters related to blood flow and volume in the brain. The technique is known as a “bolus-tracking”

Dynamic susceptibility contrast MRI (DSC-MRI) is a powerful tool used to quantitatively measure parameters related to blood flow and volume in the brain. The technique is known as a “bolus-tracking” method and relies upon very fast scanning to accurately measure the flow of contrast agent into and out of a region of interest. The need for high temporal resolution to measure contrast agent dynamics limits the spatial coverage of perfusion parameter maps which limits the utility of DSC-perfusion studies in pathologies involving the entire brain. Typical clinical DSC-perfusion studies are capable of acquiring 10-15 slices, generally centered on a known lesion or pathology.

The methods developed in this work improve the spatial coverage of whole-brain DSC-MRI by combining a highly efficient 3D spiral k-space trajectory with Generalized Autocalibrating Partial Parallel Acquisition (GRAPPA) parallel imaging without increasing temporal resolution. The proposed method is capable of acquiring 30 slices with a temporal resolution of under 1 second, covering the entire cerebrum with isotropic spatial resolution of 3 mm. Additionally, the acquisition method allows for correction of T1-enhancing leakage effects by virtue of collecting two echoes, which confound DSC perfusion measurements. The proposed DSC-perfusion method results in high quality perfusion parameter maps across a larger volume than is currently available with current clinical standards, improving diagnostic utility of perfusion MRI methods, which ultimately improves patient care.

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Date Created
  • 2017

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Advancements to Magnetic Resonance Flow Imaging in the Brain

Description

Magnetic resonance flow imaging techniques provide quantitative and qualitative information that can be attributed to flow related clinical pathologies. Clinical use of MR flow quantification requires fast acquisition and

Magnetic resonance flow imaging techniques provide quantitative and qualitative information that can be attributed to flow related clinical pathologies. Clinical use of MR flow quantification requires fast acquisition and reconstruction schemes, and minimization of post processing errors. The purpose of this work is to provide improvements to the post processing of volumetric phase contrast MRI (PCMRI) data, identify a source of flow bias for cine PCMRI that has not been previously reported in the literature, and investigate a dynamic approach to image bulk cerebrospinal fluid (CSF) drainage in ventricular shunts. The proposed improvements are implemented as three research projects.

In the first project, the improvements to post processing are made by proposing a new approach to estimating noise statistics for a single spiral acquisition, and using the estimated noise statistics to generate a mask distinguishing flow regions from background noise and static tissue in an image volume. The mask is applied towards reducing the computation time of phase unwrapping. The proposed noise estimation is shown to have comparable noise statistics as that of a vendor specific noise dynamic scan, with the added advantage of reduced scan time. The sparse flow region subset of the image volume is shown to speed up phase unwrapping for multidirectional velocity encoded 3D PCMRI scans. The second research project explores the extent of bias in cine PCMRI based flow estimates is investigated for CSF flow in the cerebral aqueduct. The dependance of the bias on spatial and temporal velocity gradient components is described. A critical velocity threshold is presented to prospectively determine the extent of bias as a function of scan acquisition parameters.

Phase contrast MR imaging is not sensitive to measure bulk CSF drainage. A dynamic approach using a CSF label is investigated in the third project to detect bulk flow in a ventricular shunt. The proposed approach uses a preparatory pulse to label CSF signal and a variable delay between the preparatory pulse and data acquisition enables tracking of the CSF bulk flow.

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Date Created
  • 2017

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Development of A Novel Virtual Tool for Donor Heart Fitting

Description

Heart transplantation is the final treatment option for end-stage heart failure. In the United States, 70 pediatric patients die annually on the waitlist while 800 well-functioning organs get discarded. Concern

Heart transplantation is the final treatment option for end-stage heart failure. In the United States, 70 pediatric patients die annually on the waitlist while 800 well-functioning organs get discarded. Concern for potential size-mismatch is one source of allograft waste and high waitlist mortality. Clinicians use the donor-recipient body weight (DRBW) ratio, a standalone metric, to evaluate allograft size-match. However, this body weight metric is far removed from cardiac anatomy and neglects an individual’s anatomical variations. This thesis body of work developed a novel virtual heart transplant fit assessment tool and investigated the tool’s clinical utility to help clinicians safely expand patient donor pools.

The tool allowed surgeons to take an allograft reconstruction and fuse it to a patient’s CT or MR medical image for virtual fit assessment. The allograft is either a reconstruction of the donor’s actual heart (from CT or MR images) or an analogue from a health heart library. The analogue allograft geometry is identified from gross donor parameters using a regression model build herein. The need for the regression model is donor images may not exist or they may not become available within the time-window clinicians have to make a provisional acceptance of an offer.

The tool’s assessment suggested > 20% of upper DRBW listings could have been increased at Phoenix Children’s Hospital (PCH). Upper DRBW listings in the UNOS national database was statistically smaller than at PCH (p-values: < 0.001). Delayed sternal closure and surgeon perceived complication variables had an association (p-value: 0.000016) with 9 of the 11 cases that surgeons had perceived fit-related complications had delayed closures (p-value: 0.034809).

A tool to assess allograft size-match has been developed. Findings warrant future preclinical and clinical prospective studies to further assess the tool’s clinical utility.

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Created

Date Created
  • 2018

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Automatic segmentation of single neurons recorded by wide-field imaging using frequency domain features and clustering tree

Description

Recent new experiments showed that wide-field imaging at millimeter scale is capable of recording hundreds of neurons in behaving mice brain. Monitoring hundreds of individual neurons at a high frame

Recent new experiments showed that wide-field imaging at millimeter scale is capable of recording hundreds of neurons in behaving mice brain. Monitoring hundreds of individual neurons at a high frame rate provides a promising tool for discovering spatiotemporal features of large neural networks. However, processing the massive data sets is impossible without automated procedures. Thus, this thesis aims at developing a new tool to automatically segment and track individual neuron cells. The new method used in this study employs two major ideas including feature extraction based on power spectral density of single neuron temporal activity and clustering tree to separate overlapping cells. To address issues associated with high-resolution imaging of a large recording area, focused areas and out-of-focus areas were analyzed separately. A static segmentation with a fixed PSD thresholding method is applied to within focus visual field. A dynamic segmentation by comparing maximum PSD with surrounding pixels is applied to out-of-focus area. Both approaches helped remove irrelevant pixels in the background. After detection of potential single cells, some of which appeared in groups due to overlapping cells in the image, a hierarchical clustering algorithm is applied to separate them. The hierarchical clustering uses correlation coefficient as a distance measurement to group similar pixels into single cells. As such, overlapping cells can be separated. We tested the entire algorithm using two real recordings with the respective truth carefully determined by manual inspections. The results show high accuracy on tested datasets while false positive error is controlled within an acceptable range. Furthermore, results indicate robustness of the algorithm when applied to different image sequences.

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Created

Date Created
  • 2016

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Compressed sensing accelerated magnetic resonance spectroscopic imaging

Description

Magnetic resonance spectroscopic imaging (MRSI) is a valuable technique for assessing the in vivo spatial profiles of metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can

Magnetic resonance spectroscopic imaging (MRSI) is a valuable technique for assessing the in vivo spatial profiles of metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can help identify tissue heterogeneity, providing prognostic and diagnostic information to the clinician. The increased uptake of glucose by solid tumors as compared to normal tissues and its conversion to lactate can be exploited for tumor diagnostics, anti-cancer therapy, and in the detection of metastasis. Lactate levels in cancer cells are suggestive of altered metabolism, tumor recurrence, and poor outcome. A dedicated technique like MRSI could contribute to an improved assessment of metabolic abnormalities in the clinical setting, and introduce the possibility of employing non-invasive lactate imaging as a powerful prognostic marker.

However, the long acquisition time in MRSI is a deterrent to its inclusion in clinical protocols due to associated costs, patient discomfort (especially in pediatric patients under anesthesia), and higher susceptibility to motion artifacts. Acceleration strategies like compressed sensing (CS) permit faithful reconstructions even when the k-space is undersampled well below the Nyquist limit. CS is apt for MRSI as spectroscopic data are inherently sparse in multiple dimensions of space and frequency in an appropriate transform domain, for e.g. the wavelet domain. The objective of this research was three-fold: firstly on the preclinical front, to prospectively speed-up spectrally-edited MRSI using CS for rapid mapping of lactate and capture associated changes in response to therapy. Secondly, to retrospectively evaluate CS-MRSI in pediatric patients scanned for various brain-related concerns. Thirdly, to implement prospective CS-MRSI acquisitions on a clinical magnetic resonance imaging (MRI) scanner for fast spectroscopic imaging studies. Both phantom and in vivo results demonstrated a reduction in the scan time by up to 80%, with the accelerated CS-MRSI reconstructions maintaining high spectral fidelity and statistically insignificant errors as compared to the fully sampled reference dataset. Optimization of CS parameters involved identifying an optimal sampling mask for CS-MRSI at each acceleration factor. It is envisioned that time-efficient MRSI realized with optimized CS acceleration would facilitate the clinical acceptance of routine MRSI exams for a quantitative mapping of important biomarkers.

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Date Created
  • 2016

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Novel nuclear magnetic resonance coil for magnetic resonance mesoscopy

Description

Magnetic Resonance Imaging (MRI) is an efficient non-invasive imaging tool widely used in medical field to produce high quality images. The MRI signal is detected with specifically developed radio frequency

Magnetic Resonance Imaging (MRI) is an efficient non-invasive imaging tool widely used in medical field to produce high quality images. The MRI signal is detected with specifically developed radio frequency (RF) systems or "coils". There are several key parameters to evaluate the performance of RF coils: signal-to-noise ratio (SNR), homogeneity, quality factor (Q factor), sensitivity, etc. The choice of coil size and configuration depends on the object to be imaged. While surface coils have better sensitivity, volume coils are often employed to image a larger region of interest (ROI) as they display better spatial homogeneity. For the cell labeling and imaging studies using the newly developed siloxane based nanoemulsions as 1H MR reporter probes, the first step is to determine the sensitivity of signal detection under controlled conditions in vitro. In this thesis, a novel designed 7 Tesla RF volume coil was designed and tested for detection of small quantities of siloxane probe as well as for imaging of labeled tumor spheroid. The procedure contains PCB circuit design, RF probe design, test and subsequent modification. In this report, both theory and design methodology will be discussed.

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Agent

Created

Date Created
  • 2014