Matching Items (15)
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- All Subjects: Medical Imaging
- All Subjects: Nanoparticles
- Creators: Kodibagkar, Vikram
- Creators: Vernon, Brent
Description
Coronary computed tomography angiography (CTA) has a high negative predictive value for ruling out coronary artery disease with non-invasive evaluation of the coronary arteries. My work has attempted to provide metrics that could increase the positive predictive value of coronary CTA through the use of dual energy CTA imaging. After developing an algorithm for obtaining calcium scores from a CTA exam, a dual energy CTA exam was performed on patients at dose levels equivalent to levels for single energy CTA with a calcium scoring exam. Calcium Agatston scores obtained from the dual energy CTA exam were within ±11% of scores obtained with conventional calcium scoring exams. In the presence of highly attenuating coronary calcium plaques, the virtual non-calcium images obtained with dual energy CTA were able to successfully measure percent coronary stenosis within 5% of known stenosis values, which is not possible with single energy CTA images due to the presence of the calcium blooming artifact. After fabricating an anthropomorphic beating heart phantom with coronary plaques, characterization of soft plaque vulnerability to rupture or erosion was demonstrated with measurements of the distance from soft plaque to aortic ostium, percent stenosis, and percent lipid volume in soft plaque. A classification model was developed, with training data from the beating heart phantom and plaques, which utilized support vector machines to classify coronary soft plaque pixels as lipid or fibrous. Lipid versus fibrous classification with single energy CTA images exhibited a 17% error while dual energy CTA images in the classification model developed here only exhibited a 4% error. Combining the calcium blooming correction and the percent lipid volume methods developed in this work will provide physicians with metrics for increasing the positive predictive value of coronary CTA as well as expanding the use of coronary CTA to patients with highly attenuating calcium plaques.
ContributorsBoltz, Thomas (Author) / Frakes, David (Thesis advisor) / Towe, Bruce (Committee member) / Kodibagkar, Vikram (Committee member) / Pavlicek, William (Committee member) / Bouman, Charles (Committee member) / Arizona State University (Publisher)
Created2013
Description
Gold nanoparticles have emerged as promising nanomaterials for biosensing, imaging, photothermal treatment and therapeutic delivery for several diseases, including cancer. We have generated poly(amino ether)-functionalized gold nanorods (PAE-GNRs) using a layer-by-layer deposition approach. Sub-toxic concentrations of PAE-GNRs were employed to deliver plasmid DNA to prostate cancer cells in vitro. PAE-GNRs generated using 1,4C-1,4Bis, a cationic polymer from our laboratory demonstrated significantly higher transgene expression and exhibited lower cytotoxicities when compared to similar assemblies generated using 25 kDa poly(ethylene imine) (PEI25k-GNRs), a current standard for polymer-mediated gene delivery. Additionally, sub-toxic concentrations of 1,4C-1,4Bis-GNR nanoassemblies were employed to deliver expression vectors that express shRNA ('shRNA plasmid') against firefly luciferase gene in order to knock down expression of the protein constitutively expressed in prostate cancer cells. The roles of poly(amino ether) chemistry and zeta-potential in determining transgene expression efficacies of PAE-GNR assemblies were investigated. The theranostic potential of 1,4C-1,4Bis-GNR nanoassemblies was demonstrated using live cell two-photon induced luminescence bioimaging. The PAE class of polymers was also investigated for the one pot synthesis of both gold and silver nanoparticles using a small library poly(amino ethers) derived from linear-like polyamines. Efficient nanoparticle synthesis dependent on concentration of polymers as well as polymer chemical composition is demonstrated. Additionally, the application of poly(amino ether)-gold nanoparticles for transgene delivery is demonstrated in 22Rv1 and MB49 cancer cell lines. Base polymer, 1,4C-1,4Bis and 1,4C-1,4Bis templated and modified gold nanoparticles were compared for transgene delivery efficacies. Differences in morphology and physiochemical properties were investigated as they relate to differences in transgene delivery efficacy. There were found to be minimal differences suggestion that 1,4C-1,4Bis efficacy is not lost following use for nanoparticle modification. These results indicate that poly(amino ether)-gold nanoassemblies are a promising theranostic platform for delivery of therapeutic payloads capable of simultaneous gene silencing and bioimaging.
ContributorsRamos, James (Author) / Rege, Kaushal (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Caplan, Michael (Committee member) / Vernon, Brent (Committee member) / Garcia, Antonio (Committee member) / Arizona State University (Publisher)
Created2014
Description
This research reports on the investigation into the synthesis and stabilization of
iron oxide nanoparticles for theranostic applications using amine-epoxide polymers. Although theranostic agents such as magnetic nanoparticles have been designed and developed for a few decades, there is still more work that needs to be done with the type of materials that can be used to stabilize or functionalize these particles if they are to be used for applications such as drug delivery, imaging and hyperthermia. For in-vivo applications, it is crucial that organic coatings enclose the nanoparticles in order to prevent aggregation and facilitate efficient removal from the body as well as protect the body from toxic material.
The objective of this thesis is to design polymer coated magnetite nanoparticles with polymers that are biocompatible and can stabilize the iron oxide nanoparticle to help create mono-dispersed particles in solution. It is desirable to also have these nanoparticles possess high magnetic susceptibility in response to an applied magnetic field. The co- precipitation method was selected because it is probably the simplest and most efficient chemical pathway to obtain magnetic nanoparticles.
In literature, cationic polymers such as Polyethylenimine (PEI), which is the industry standard, have been used to stabilize IONPs because they can be used in magnetofections to deliver DNA or RNA. PEI however is known to interact very strongly with proteins and is cytotoxic, so as mentioned previously the Iron Oxide nanoparticles
i
(IONPs) synthesized in this study were stabilized with amine-epoxide polymers because of the limitations of PEI.
Four different amine-epoxide polymers which have good water solubility, biodegradability and less toxic than PEI were synthesized and used in the synthesis and stabilization of the magnetic nanoparticles and compared to PEI templated IONPs. These polymer-templated magnetic nanoparticles were also characterized by size, surface charge, Iron oxide content (ICP analysis) and superconducting quantum interference devices (SQUID) analysis to determine the magnetization values. TEM images were also used to determine the shape and size of the nanoparticles. All this was done in an effort to choose two or three leads that could be used in future work for magnetofections or drug delivery research.
iron oxide nanoparticles for theranostic applications using amine-epoxide polymers. Although theranostic agents such as magnetic nanoparticles have been designed and developed for a few decades, there is still more work that needs to be done with the type of materials that can be used to stabilize or functionalize these particles if they are to be used for applications such as drug delivery, imaging and hyperthermia. For in-vivo applications, it is crucial that organic coatings enclose the nanoparticles in order to prevent aggregation and facilitate efficient removal from the body as well as protect the body from toxic material.
The objective of this thesis is to design polymer coated magnetite nanoparticles with polymers that are biocompatible and can stabilize the iron oxide nanoparticle to help create mono-dispersed particles in solution. It is desirable to also have these nanoparticles possess high magnetic susceptibility in response to an applied magnetic field. The co- precipitation method was selected because it is probably the simplest and most efficient chemical pathway to obtain magnetic nanoparticles.
In literature, cationic polymers such as Polyethylenimine (PEI), which is the industry standard, have been used to stabilize IONPs because they can be used in magnetofections to deliver DNA or RNA. PEI however is known to interact very strongly with proteins and is cytotoxic, so as mentioned previously the Iron Oxide nanoparticles
i
(IONPs) synthesized in this study were stabilized with amine-epoxide polymers because of the limitations of PEI.
Four different amine-epoxide polymers which have good water solubility, biodegradability and less toxic than PEI were synthesized and used in the synthesis and stabilization of the magnetic nanoparticles and compared to PEI templated IONPs. These polymer-templated magnetic nanoparticles were also characterized by size, surface charge, Iron oxide content (ICP analysis) and superconducting quantum interference devices (SQUID) analysis to determine the magnetization values. TEM images were also used to determine the shape and size of the nanoparticles. All this was done in an effort to choose two or three leads that could be used in future work for magnetofections or drug delivery research.
ContributorsTamakloe, Beatrice (Author) / Rege, Kaushal (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Chang, John (Committee member) / Arizona State University (Publisher)
Created2014
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 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.
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.
ContributorsFu, Fanrui (Author) / Sadleir, Rosalind (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Kleim, Jeffrey (Committee member) / Muthuswamy, Jitendran (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
Description
Achieving effective drug concentrations within the central nervous system (CNS) remains one of the greatest challenges for the treatment of brain tumors. The presence of the blood-brain barrier and blood-spinal cord barrier severely restricts the blood-to-CNS entry of nearly all systemically administered therapeutics, often leading to the development of peripheral toxicities before a treatment benefit is observed. To circumvent systemic barriers, intrathecal (IT) injection of therapeutics directly into the cerebrospinal fluid (CSF) surrounding the brain and spinal cord has been used as an alternative administration route; however, its widespread translation to the clinic has been hindered by poor drug pharmacokinetics (PK), including rapid clearance, inadequate distribution, as well as toxicity. One strategy to overcome the limitations of free drug PK and improve drug efficacy is to encapsulate drug within nanoparticles (NP), which solubilize hydrophobic molecules for sustained release in physiological environments. In this thesis, we will develop NP delivery strategies for brain tumor therapy in two model systems: glioblastoma (GBM), the most common and deadly malignant primary brain tumor, and medulloblastoma, the most common pediatric brain tumor. In the first research chapter, we developed 120 nm poly(lactic acid-co-glycolic acid) NPs encapsulating the chemotherapy, camptothecin, for intravenous delivery to GBM. NP encapsulation of camptothecin was shown to reduce the drug’s toxicity and enable effective delivery to orthotopic GBM. To build off the success of intravenous NP, the second research chapter explored the utility of 100 nm PEGylated NPs for use with IT administration. Using in vivo imaging and ex vivo tissue slices, we found the NPs were rapidly transported by the convective forces of the CSF along the entire neuraxis and were retained for over 3 weeks. Based on their wide spread delivery and prolonged circulation, we examine the ability of the NPs to localize with tumor lesions in a leptomeningeal metastasis (LM) model of medulloblastoma. NPs administered to LM bearing mice were shown to penetrate into LM mets seeded within the meninges around the brain. These data show the potential to translate our success with intravenous NPs for GBM to improve IT chemotherapy delivery to LM.
ContributorsHouseholder, Kyle Thomas (Author) / Sirianni, Rachael W. (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Vernon, Brent (Committee member) / Caplan, Michael (Committee member) / Wechsler-Reya, Robert (Committee member) / Arizona State University (Publisher)
Created2018
Description
Rapid intraoperative diagnosis of brain tumors is of great importance for planning treatment and guiding the surgeon about the extent of resection. Currently, the standard for the preliminary intraoperative tissue analysis is frozen section biopsy that has major limitations such as tissue freezing and cutting artifacts, sampling errors, lack of immediate interaction between the pathologist and the surgeon, and time consuming.
Handheld, portable confocal laser endomicroscopy (CLE) is being explored in neurosurgery for its ability to image histopathological features of tissue at cellular resolution in real time during brain tumor surgery. Over the course of examination of the surgical tumor resection, hundreds to thousands of images may be collected. The high number of images requires significant time and storage load for subsequent reviewing, which motivated several research groups to employ deep convolutional neural networks (DCNNs) to improve its utility during surgery. DCNNs have proven to be useful in natural and medical image analysis tasks such as classification, object detection, and image segmentation.
This thesis proposes using DCNNs for analyzing CLE images of brain tumors. Particularly, it explores the practicality of DCNNs in three main tasks. First, off-the shelf DCNNs were used to classify images into diagnostic and non-diagnostic. Further experiments showed that both ensemble modeling and transfer learning improved the classifier’s accuracy in evaluating the diagnostic quality of new images at test stage. Second, a weakly-supervised learning pipeline was developed for localizing key features of diagnostic CLE images from gliomas. Third, image style transfer was used to improve the diagnostic quality of CLE images from glioma tumors by transforming the histology patterns in CLE images of fluorescein sodium-stained tissue into the ones in conventional hematoxylin and eosin-stained tissue slides.
These studies suggest that DCNNs are opted for analysis of CLE images. They may assist surgeons in sorting out the non-diagnostic images, highlighting the key regions and enhancing their appearance through pattern transformation in real time. With recent advances in deep learning such as generative adversarial networks and semi-supervised learning, new research directions need to be followed to discover more promises of DCNNs in CLE image analysis.
Handheld, portable confocal laser endomicroscopy (CLE) is being explored in neurosurgery for its ability to image histopathological features of tissue at cellular resolution in real time during brain tumor surgery. Over the course of examination of the surgical tumor resection, hundreds to thousands of images may be collected. The high number of images requires significant time and storage load for subsequent reviewing, which motivated several research groups to employ deep convolutional neural networks (DCNNs) to improve its utility during surgery. DCNNs have proven to be useful in natural and medical image analysis tasks such as classification, object detection, and image segmentation.
This thesis proposes using DCNNs for analyzing CLE images of brain tumors. Particularly, it explores the practicality of DCNNs in three main tasks. First, off-the shelf DCNNs were used to classify images into diagnostic and non-diagnostic. Further experiments showed that both ensemble modeling and transfer learning improved the classifier’s accuracy in evaluating the diagnostic quality of new images at test stage. Second, a weakly-supervised learning pipeline was developed for localizing key features of diagnostic CLE images from gliomas. Third, image style transfer was used to improve the diagnostic quality of CLE images from glioma tumors by transforming the histology patterns in CLE images of fluorescein sodium-stained tissue into the ones in conventional hematoxylin and eosin-stained tissue slides.
These studies suggest that DCNNs are opted for analysis of CLE images. They may assist surgeons in sorting out the non-diagnostic images, highlighting the key regions and enhancing their appearance through pattern transformation in real time. With recent advances in deep learning such as generative adversarial networks and semi-supervised learning, new research directions need to be followed to discover more promises of DCNNs in CLE image analysis.
ContributorsIzady Yazdanabadi, Mohammadhassan (Author) / Preul, Mark (Thesis advisor) / Yang, Yezhou (Thesis advisor) / Nakaji, Peter (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2019
Description
In medical imaging, a wide variety of methods are used to interrogate structural and physiological differences between soft tissues. One of the most ubiquitous methods in clinical practice is Magnetic Resonance Imaging (MRI), which has the advantage of limited invasiveness, soft tissue discrimination, and adequate volumetric resolution. A myriad of advanced MRI methods exists to investigate the microstructural, physiologic and metabolic characteristics of tissue. For example, Dynamic Contrast Enhanced (DCE) and Dynamic Susceptibility Contrast (DSC) MRI non-invasively interrogates the dynamic passage of an exogenously administered MRI contrast agent through tissue to quantify local tracer kinetic properties like blood flow, vascular permeability and tissue compartmental volume fractions. Recently, an improved understanding of the biophysical basis of DSC-MRI signals in brain tumors revealed a new approach to derive multiple quantitative biomarkers that identify intrinsic sub-voxel cellular and vascular microstructure that can be used differentiate tumor sub-types. One of these characteristic biomarkers called Transverse Relaxivity at Tracer Equilibrium (TRATE), utilizes a combination of DCE and DSC techniques to compute a steady-state metric which is particularly sensitive to cell size, density, and packing properties. This work seeks to investigate the sensitivity and potential utility of TRATE in a range of disease states including Glioblastomas, Amyotrophic Lateral Sclerosis (ALS), and Duchenne’s Muscular Dystrophy (DMD). The MRC measures of TRATE showed the most promise in mouse models of ALS where TRATE values decreased with disease progression, a finding that correlated with reductions in myofiber size and area, as quantified by immunohistochemistry. In the animal models of cancer and DMD, TRATE results were more inconclusive, due to marked heterogeneity across animals and treatment state. Overall, TRATE seems to be a promising new biomarker but still needs further methodological refinement due to its sensitivity to contrast to noise and further characterization owing to its non-specificity with respect to multiple cellular features (e.g. size, density, heterogeneity) that complicate interpretation.
ContributorsFuentes, Alberto (Author) / Quarles, Chad C (Thesis advisor) / Kodibagkar, Vikram (Thesis advisor) / Greger, Bradley (Committee member) / Arizona State University (Publisher)
Created2018
Description
The main objective of this research is to develop and characterize a targeted contrast agent that will recognize acute neural injury pathology (i.e. fibrin) after traumatic brain injury (TBI). Single chain fragment variable antibodies (scFv) that bind specifically to fibrin have been produced and purified. DSPE-PEG micelles have been produced and the scFv has been conjugated to the surface of the micelles; this nanoparticle system will be used to overcome limitations in diagnosing TBI. The binding and imaging properties will be analyzed in the future to determine functionality of the nanoparticle system in vivo.
ContributorsRumbo, Kailey Michelle (Author) / Stabenfeldt, Sarah (Thesis director) / Kodibagkar, Vikram (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Smart contrast agents allow for noninvasive study of specific events or tissue conditions inside of a patient's body using Magnetic Resonance Imaging (MRI). This research aims to develop and characterize novel smart contrast agents for MRI that respond to temperature changes in tissue microenvironments. Transmission Electron Microscopy, Nuclear Magnetic Resonance, and cell culture growth assays were used to characterize the physical, magnetic, and cytotoxic properties of candidate nanoprobes. The nanoprobes displayed thermosensitve MR properties with decreasing relaxivity with temperature. Future work will be focused on generating and characterizing photo-active analogues of the nanoprobes that could be used for both treatment of tissues and assessment of therapy.
ContributorsHussain, Khateeb Hyder (Author) / Kodibagkar, Vikram (Thesis director) / Stabenfeldt, Sarah (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
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” 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.
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.
ContributorsTurley, Dallas C (Author) / Pipe, James G (Thesis advisor) / Kodibagkar, Vikram (Thesis advisor) / Frakes, David (Committee member) / Sadleir, Rosalind (Committee member) / Schmainda, Kathleen (Committee member) / Arizona State University (Publisher)
Created2017