Matching Items (6)
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- All Subjects: Polymer
- Creators: Vernon, Brent
- Status: Published
Description
Minimally invasive endovascular embolization procedures decrease surgery time, speed up recovery, and provide the possibility for more comprehensive treatment of aneurysms, arteriovenous malformations (AVMs), and hypervascular tumors. Liquid embolic agents (LEAs) are preferred over mechanical embolic agents, such as coils, because they achieve homogeneous filling of aneurysms and more complex angioarchitectures. The gold standard of commercially available LEAs is dissolved in dimethyl sulfoxide (DMSO), which has been associated with vasospasm and angiotoxicity. The aim of this study was to investigate amino acid substitution in an enzyme-degradable side group of an N-isopropylacrylamide (NIPAAm) copolymer for the development of a LEA that would be delivered in water and degrade at the rate that tissue is regenerated. NIPAAm copolymers have a lower critical solution temperature (LCST) due to their amphiphilic nature. This property enables them to be delivered as liquids through a microcatheter below their LCST and to solidify in situ above the LCST, which would result in the successful selective occlusion of blood vessels. Therefore, in this work, a series of poly(NIPAAm-co-peptide) copolymers with hydrophobic side groups containing the Ala-Pro-Gly-Leu collagenase substrate peptide sequence were synthesized as in situ forming, injectable copolymers.. The Gly-Leu peptide bond in these polypeptides is cleaved by collagenase, converting the side group into the more hydrophilic Gly-Ala-Pro-Gly-COOH (GAPG-COOH), thus increasing the LCST of the hydrogel after enzyme degradation. Enzyme degradation property and moderate mechanical stability convinces the use of these copolymers as liquid embolic agents.
ContributorsRosas Gomez, Karime Jocelyn (Author) / Vernon, Brent (Thesis advisor) / Weaver, Jessica (Committee member) / Pal, Amrita (Committee member) / Arizona State University (Publisher)
Created2019
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
This report provides information concerning qualities of methylcellulose and how those properties affect further experimentation within the biomedical world. Utilizing the compound’s biocompatibility many issues, ranging from surgical to cosmetic, can be solved. As of recent, studies indicate, methylcellulose has been used as a physically cross-linked gel, which cannot sustain a solid form within the body. Therefore, this report will ultimately explore the means of creating a non-degradable, injectable, chemically cross-linking methylcellulose- based hydrogel. Methylcellulose will be evaluated and altered in experiments conducted within this report and a chemical cross-linker, developed from Jeffamine ED 2003 (O,O′-Bis(2-aminopropyl) polypropylene glycol-block-polyethylene glycol-block-polypropylene glycol), will be created. Experimentation with these elements is outlined here, and will ultimately prompt future revisions and analysis.
ContributorsBundalo, Zoran Luka (Author) / Vernon, Brent (Thesis director) / LaBelle, Jeffrey (Committee member) / Overstreet, Derek (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
This analysis explores what the time needed to harden, and time needed to degrade is of a PLGA bead, as well as whether the size of the needle injecting the bead and the addition of a drug (Vismodegib) may affect these variables. Polymer degradation and hardening are critical to understand for the polymer’s use in clinical settings, as these factors help determine the patients’ and healthcare providers’ use of the drug and estimated treatment time. Based on the literature, it is expected that the natural logarithmic polymer mass degradation forms a linear relationship to time. Polymer hardening was tested by taking video recordings of gelatin plates as they are injected with microneedles and performing RGB analysis on the polymer “beads” created. Our results for the polymer degradation experiments showed that the polymer hardened for all solutions and trials within approximately 1 minute, presenting a small amount of time in which the patient would have to remain motionless in the affected area. Both polymer bead size and drug concentration may have had a modest impact on the hardening time experiments, while bead size may affect the time required for the polymer to degrade. Based on the results, the polymer degradation is expected to last multiple weeks, which may allow for the polymer to be used as a long-term drug delivery system in treatment of basal cell carcinoma.
ContributorsEltze, Maren Caterina (Author) / Vernon, Brent (Thesis director) / Buneo, Christopher (Committee member) / Harrington Bioengineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Intraoperative diagnosis in neurosurgery has traditionally relied on frozen and formalin-fixed, paraffin-embedded section analysis of biopsied tissue samples. Although this technique is considered to be the “gold standard” for establishing a histopathologic diagnosis, it entails a number of significant limitations such as invasiveness and the time required for processing and interpreting the tissue. Rapid intraoperative diagnosis has become possible with a handheld confocal laser endomicroscopy (CLE) system. Combined with appropriate fluorescent stains or labels, CLE provides an imaging technique for real-time intraoperative visualization of histopathologic features of the suspected tumor and healthy tissues.
This thesis scrutinizes CLE technology for its ability to provide real-time intraoperative in vivo and ex vivo visualization of histopathological features of the normal and tumor brain tissues. First, the optimal settings for CLE imaging are studied in an animal model along with a generational comparison of CLE performance. Second, the ability of CLE to discriminate uninjured normal brain, injured normal brain and tumor tissues is demonstrated. Third, CLE was used to investigate cerebral microvasculature and blood flow in normal and pathological conditions. Fourth, the feasibility of CLE for providing optical biopsies of brain tumors was established during the fluorescence-guided neurosurgical procedures. This study established the optimal workflow and confirmed the high specificity of the CLE optical biopsies. Fifth, the feasibility of CLE was established for endoscopic endonasal approaches and interrogation of pituitary tumor tissue. Finally, improved and prolonged near wide-field fluorescent visualization of brain tumor margins was demonstrated with a scanning fiber endoscopy and 5-aminolevulinic acid.
These studies suggested a novel paradigm for neurosurgery-pathology workflow when the noninvasive intraoperative optical biopsies are used to interrogate the tissue and augment intraoperative decision making. Such optical biopsies could shorten the time for obtaining preliminary information on the histological composition of the tissue of interest and may lead to improved diagnostics and tumor resection. This work establishes a basis for future in vivo optical biopsy use in neurosurgery and planning of patient-related outcome studies. Future studies would lead to refinement and development of new confocal scanning technologies making noninvasive optical biopsy faster, convenient and more accurate.
This thesis scrutinizes CLE technology for its ability to provide real-time intraoperative in vivo and ex vivo visualization of histopathological features of the normal and tumor brain tissues. First, the optimal settings for CLE imaging are studied in an animal model along with a generational comparison of CLE performance. Second, the ability of CLE to discriminate uninjured normal brain, injured normal brain and tumor tissues is demonstrated. Third, CLE was used to investigate cerebral microvasculature and blood flow in normal and pathological conditions. Fourth, the feasibility of CLE for providing optical biopsies of brain tumors was established during the fluorescence-guided neurosurgical procedures. This study established the optimal workflow and confirmed the high specificity of the CLE optical biopsies. Fifth, the feasibility of CLE was established for endoscopic endonasal approaches and interrogation of pituitary tumor tissue. Finally, improved and prolonged near wide-field fluorescent visualization of brain tumor margins was demonstrated with a scanning fiber endoscopy and 5-aminolevulinic acid.
These studies suggested a novel paradigm for neurosurgery-pathology workflow when the noninvasive intraoperative optical biopsies are used to interrogate the tissue and augment intraoperative decision making. Such optical biopsies could shorten the time for obtaining preliminary information on the histological composition of the tissue of interest and may lead to improved diagnostics and tumor resection. This work establishes a basis for future in vivo optical biopsy use in neurosurgery and planning of patient-related outcome studies. Future studies would lead to refinement and development of new confocal scanning technologies making noninvasive optical biopsy faster, convenient and more accurate.
ContributorsBelykh, Evgenii (Author) / Preul, Mark C (Thesis advisor) / Vernon, Brent (Thesis advisor) / Nakaji, Peter (Committee member) / Stabenfeldt, Sarah E (Committee member) / Arizona State University (Publisher)
Created2020
Description
In an embolization therapy, a material is injected into a vessel to block blood flow. While this therapy is useful in starving cancerous cells it can be dangerous, with some blockades in the brain dislodging and causing strokes or blindness. Currently, embolic materials on the market such as metal coils, balloons, and liquid embolic agents do not have a quick removal procedure. An ultrasound cleavable material could be removed in an emergency situation without invasive surgery. The primary goal of this research is to design and synthesize a polymer that can be broken down by high intensity focused ultrasound (HIFU). Initially, we have tested the ultrasound sensitive qualities on PPODA-QT hydrogel, a common embolic agent, but the gel showed no physical change after HIFU exposure. It is theorized that PNIPAAm combined with HIFU sensitive monomers can develop a temperature and ultrasound sensitive embolic agent. In our studies, poly(NIPAAm-co-tBa) had a slight lower critical solution temperature (LCST) change of about 2˚C from before to after HIFU while the study with poly(NIPAAm-co-ACL-BME) and PPODA-QT showed no change in LCST.
ContributorsLein, Karolena (Author) / Vernon, Brent (Thesis director) / Pal, Amrita (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05