abstract: 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. / Dissertation/Thesis / Ph.D. Neuroscience 2014
| Identifer | oai:union.ndltd.org:asu.edu/item:24890 |
| Date | January 2014 |
| Contributors | Elhadi, Ali M. (Author), Preul, Mark C (Advisor), Towe, Bruce (Advisor), Little, Andrew S (Committee member), Nakaji, Peter (Committee member), Vu, Eric T (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Doctoral Dissertation |
| Format | 105 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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