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ContributorsDaval, Charles (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-26
Description
During the past five decades neurosurgery has made great progress, with marked improvements in patient outcomes. These noticeable improvements of morbidity and mortality can be attributed to the advances in innovative technologies used in neurosurgery. Cutting-edge technologies are essential in most neurosurgical procedures, and there is no doubt that neurosurgery has become heavily technology dependent. With the introduction of any new modalities, surgeons must adapt, train, and become thoroughly familiar with the capabilities and the extent of application of these new innovations. Within the past decade, endoscopy has become more widely used in neurosurgery, and this newly adopted technology is being recognized as the new minimally invasive future of neurosurgery. The use of endoscopy has allowed neurosurgeons to overcome common challenges, such as limited illumination and visualization in a very narrow surgical corridor; however, it introduces other challenges, such as instrument "sword fighting" and limited maneuverability (surgical freedom). The newly introduced concept of surgical freedom is very essential in surgical planning and approach selection and can play a role in determining outcome of the procedure, since limited surgical freedom can cause fatigue or limit the extent of lesion resection. In my thesis, we develop a consistent objective methodology to quantify and evaluate surgical freedom, which has been previously evaluated subjectively, and apply this model to the analysis of various endoscopic techniques. This model is crucial for evaluating different endoscopic surgical approaches before they are applied in a clinical setting, for identifying surgical maneuvers that can improve surgical freedom, and for developing endoscopic training simulators that accurately model the surgical freedom of various approaches. Quantifying the extent of endoscopic surgical freedom will also provide developers with valuable data that will help them design improved endoscopes and endoscopic instrumentation.
ContributorsElhadi, Ali M. (Author) / Preul, Mark C (Thesis advisor) / Towe, Bruce (Thesis advisor) / Little, Andrew S. (Committee member) / Nakaji, Peter (Committee member) / Vu, Eric T (Committee member) / Arizona State University (Publisher)
Created2014
DescriptionThe purpose of this project is to explore the influence of folk music in guitar compositions by Manuel Ponce from 1923 to 1932. It focuses on his Tres canciones populares mexicanas and Tropico and Rumba.
ContributorsGarcia Santos, Arnoldo (Author) / Koonce, Frank (Thesis advisor) / Rogers, Rodney (Committee member) / Rotaru, Catalin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Controlled release formulations for local, in vivo drug delivery are of growing interest to device manufacturers, research scientists, and clinicians; however, most research characterizing controlled release formulations occurs in vitro because the spatial and temporal distribution of drug delivery is difficult to measure in vivo. In this work, in vivo magnetic resonance imaging (MRI) of local drug delivery is performed to visualize and quantify the time resolved distribution of MRI contrast agents. I find it is possible to visualize contrast agent distributions in near real time from local delivery vehicles using MRI. Three dimensional T1 maps are processed to produce in vivo concentration maps of contrast agent for individual animal models. The method for obtaining concentration maps is analyzed to estimate errors introduced at various steps in the process. The method is used to evaluate different controlled release vehicles, vehicle placement, and type of surgical wound in rabbits as a model for antimicrobial delivery to orthopaedic infection sites. I are able to see differences between all these factors; however, all images show that contrast agent remains fairly local to the wound site and do not distribute to tissues far from the implant in therapeutic concentrations. I also produce a mathematical model that investigates important mechanisms in the transport of antimicrobials in a wound environment. It is determined from both the images and the mathematical model that antimicrobial distribution in an orthopaedic wounds is dependent on both diffusive and convective mechanisms. Furthermore, I began development of MRI visible therapeutic agents to examine active drug distributions. I hypothesize that this work can be developed into a non-invasive, patient specific, clinical tool to evaluate the success of interventional procedures using local drug delivery vehicles.
ContributorsGiers, Morgan (Author) / Caplan, Michael R (Thesis advisor) / Massia, Stephen P (Committee member) / Frakes, David (Committee member) / McLaren, Alex C. (Committee member) / Vernon, Brent L (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsKotronakis, Dimitris (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-01
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 this study, we propose and then assess the efficacy of a new approach to static suspension to correct for facial paralysis. Our method involves placing barbed sutures through the superficial muscular aponeurotic system (SMAS) and anchoring them in the temporal fascia parallel to the underlying facial muscles. We first analyzed the ability of this procedure to improve facial symmetry by comparing the degree of asymmetry between the paralyzed and unaffected sides of a patient's face (N=10) prior to and following surgery. Then, to determine if symmetry is improved as a result of placing the sutures parallel to the direction of facial muscle forces, we measured the vectors of levator labii superioris and zygomaticus major in cadaver hemifaces (N=3) and compared them to the angles of the vectors of correction from the patient sample to angles of muscle vectors in three facial hemispheres from cadaver controls. Results indicate that: (1) facial symmetry was significantly improved in these patients and (2) this improvement. We conclude that, compared to existing protocols, our novel surgical method is a better means of static suspension for reconstruction following onset of facial paralysis as it is simple to perform, easy to replicate, able to be post-operatively adjusted in-office, has a good long-term prognosis, and, as we have demonstrated, effectively corrects the appearance of asymmetry by working with the underlying facial anatomy.
ContributorsLeach, Garrison Alecsander (Co-author) / Joganic, Jessica (Co-author) / Hooft, Nicole (Co-author) / Joganic, Edward (Co-author, Committee member) / Foy, Joseph (Thesis director) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
ContributorsDavin, Colin (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-05
Description
This thesis seeks to evaluate whether the benefits of spinal fusion surgeries are worth their increasing costs. The paper examines the trends that contribute to these surgeries' increasing prices and then evaluates the customer impact of these surgeries in order to make a conclusion on whether the surgeries are worth it. This paper discusses the main factors that contribute to the increase in prices of these surgeries and these include the aging population, the increase in diabetes rates, and the practice of purchasing physicians owned distributorships (PODs) devices in some hospitals. The paper concluded that there is a definite correlation between the increased rate of spinal surgeries performed as a result of an increase in diabetes rates in the US population. It was argued that diabetes can lead to multiple spinal diseases which increase the demand of spinal surgeries which in turn causes the prices of these surgeries to rise. The paper also argued that current technological advances have allowed us to live longer which in turn leads to an increase in spine surgeries simply due to old age and a deteriorating spine. Lastly, it was argued that the recent surge in the POD devices being used in spinal surgeries in some hospitals can be seen as a possible influence to the increase in the cost of these surgeries. This is because the hospitals that chose to purchase surgery devices from PODs are more likely to increase the cost to perform the surgery because they are paying a lot more for those devices. Looking at the customer impact, it was apparent that spinal fusion surgeries carry certain risks because they require decortication of bone and, often, placement of implants; along with extensive dissection and longer operative time. However, based on the research conducted, there was no conclusion to be made on whether spinal fusions carried more risks than all other spinal surgeries because the data used only compared the surgery to some that are arguably less complicated like discectomies.
ContributorsDisengi Nkunzi, Jossel (Author) / Allenby, Braden (Thesis director) / Bohl, Michael (Committee member) / Barrett, The Honors College (Contributor)
Created2017-12
ContributorsSanchez, Armand (Performer) / Nordstrom, Nathan (Performer) / Roubison, Ryan (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-13