ingest cdrApp 2018-08-23T19:29:06.902Z d39a25df-af15-48e9-aec2-c9af81a997a2 modifyDatastreamByValue RELS-EXT fedoraAdmin 2018-08-23T19:29:58.081Z Setting exclusive relation addDatastream MD_TECHNICAL fedoraAdmin 2018-08-23T19:30:09.182Z Adding technical metadata derived by FITS addDatastream MD_FULL_TEXT fedoraAdmin 2018-08-23T19:30:32.277Z Adding full text metadata extracted by Apache Tika modifyDatastreamByValue RELS-EXT fedoraAdmin 2018-08-23T19:30:54.517Z Setting exclusive relation modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-09-26T21:31:59.079Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2019-03-20T15:32:35.666Z Christopher Giardina Author UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Identifying Surgical Trauma and Predicting Hearing Outcomes using Electrocochleography during Cochlear Implantation A patient receiving a cochlear implant (CI) has little predictive knowledge of how well he or she will ultimately perform in speech perception or hearing ability. Both pre- and intra-operative factors likely contribute to the wide variance in outcomes, but a key gap is identifying the specific causes. We have previously shown that assessing cochlear function with electrocochleography (ECochG) just prior to implantation can account for roughly half the variance in speech perception outcomes. However, surgical factors such as cochlear trauma during insertion and final implant positioning are also known to affect outcomes as well. This dissertation focuses on the use of extracochlear and intracochlear ECochG to identify trauma throughout CI insertion. An algorithm to determine the integrity of hair cell and neuronal generators from an ECochG recording was fundamental in this analysis. We also introduce two novel approaches to assess final CI positioning, using impedance and an intraoperative X-ray. Chapter 1 serves as a background to CI outcomes and intraoperative ECochG. Chapter 2 describes initial experimentation, recording at a fixed, extracochlear location and examining reversible and permanent response drops (publication). To improve the analysis of ECochG, Chapter 3 describes how an animal model with neurotoxins and ototoxins was used to develop a computational algorithm capable of estimating the contribution of hair cell and neuronal generators (publication co-written with Tatyana Khan). With this new tool, we were able to improve our speech prediction models, particularly in children with auditory neuropathy spectrum disorder. Chapter 4 integrates the model into an analysis of intracochlear ECochG throughout CI insertion, particularly in deciding which response drops were likely to predict permanent hearing loss. Chapter 4 also serves as the primarydiscussion of the thesis, comparing intra- and extracochlear ECochG and concluding with an evaluation of ECochG in accounting for outcomes and minimizing trauma. Chapter 5 focuses on post-insertion positioning as a source of variance in outcomes, describing an impedance model to estimate array positioning (publication). Chapter 6 highlights ongoing work, including extracochlear ECochG and hearing preservation, simultaneous intra and extra-cochlear ECochG, and a tool to estimate CI positioning from an X-ray. Summer 2018 2018 Biomedical engineering Cochlear Implants, Electrocochleography, Hearing Preservation eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Douglas Fitzpatrick Thesis advisor Lianne Cartee Thesis advisor Douglas Fitzpatrick Thesis advisor John Grose Thesis advisor Paul Manis Thesis advisor H Nagle Thesis advisor text Christopher Giardina Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Identifying Surgical Trauma and Predicting Hearing Outcomes using Electrocochleography during Cochlear Implantation A patient receiving a cochlear implant (CI) has little predictive knowledge of how well he or she will ultimately perform in speech perception or hearing ability. Both pre- and intra-operative factors likely contribute to the wide variance in outcomes, but a key gap is identifying the specific causes. We have previously shown that assessing cochlear function with electrocochleography (ECochG) just prior to implantation can account for roughly half the variance in speech perception outcomes. However, surgical factors such as cochlear trauma during insertion and final implant positioning are also known to affect outcomes as well. This dissertation focuses on the use of extracochlear and intracochlear ECochG to identify trauma throughout CI insertion. An algorithm to determine the integrity of hair cell and neuronal generators from an ECochG recording was fundamental in this analysis. We also introduce two novel approaches to assess final CI positioning, using impedance and an intraoperative X-ray. Chapter 1 serves as a background to CI outcomes and intraoperative ECochG. Chapter 2 describes initial experimentation, recording at a fixed, extracochlear location and examining reversible and permanent response drops (publication). To improve the analysis of ECochG, Chapter 3 describes how an animal model with neurotoxins and ototoxins was used to develop a computational algorithm capable of estimating the contribution of hair cell and neuronal generators (publication co-written with Tatyana Khan). With this new tool, we were able to improve our speech prediction models, particularly in children with auditory neuropathy spectrum disorder. Chapter 4 integrates the model into an analysis of intracochlear ECochG throughout CI insertion, particularly in deciding which response drops were likely to predict permanent hearing loss. Chapter 4 also serves as the primarydiscussion of the thesis, comparing intra- and extracochlear ECochG and concluding with an evaluation of ECochG in accounting for outcomes and minimizing trauma. Chapter 5 focuses on post-insertion positioning as a source of variance in outcomes, describing an impedance model to estimate array positioning (publication). Chapter 6 highlights ongoing work, including extracochlear ECochG and hearing preservation, simultaneous intra and extra-cochlear ECochG, and a tool to estimate CI positioning from an X-ray. Biomedical engineering Cochlear Implants; Electrocochleography; Hearing Preservation Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Douglas Fitzpatrick Thesis advisor Lianne Cartee Thesis advisor Douglas Fitzpatrick Thesis advisor John Grose Thesis advisor Paul Manis Thesis advisor H Nagle Thesis advisor 2018 2018-08 eng text Christopher Giardina Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine A patient receiving a cochlear implant (CI) has little predictive knowledge of how well he or she will ultimately perform in speech perception or hearing ability. Both pre- and intra-operative factors likely contribute to the wide variance in outcomes, but a key gap is identifying the specific causes. We have previously shown that assessing cochlear function with electrocochleography (ECochG) just prior to implantation can account for roughly half the variance in speech perception outcomes. However, surgical factors such as cochlear trauma during insertion and final implant positioning are also known to affect outcomes as well. This dissertation focuses on the use of extracochlear and intracochlear ECochG to identify trauma throughout CI insertion. An algorithm to determine the integrity of hair cell and neuronal generators from an ECochG recording was fundamental in this analysis. We also introduce two novel approaches to assess final CI positioning, using impedance and an intraoperative X-ray. Chapter 1 serves as a background to CI outcomes and intraoperative ECochG. Chapter 2 describes initial experimentation, recording at a fixed, extracochlear location and examining reversible and permanent response drops (publication). To improve the analysis of ECochG, Chapter 3 describes how an animal model with neurotoxins and ototoxins was used to develop a computational algorithm capable of estimating the contribution of hair cell and neuronal generators (publication co-written with Tatyana Khan). With this new tool, we were able to improve our speech prediction models, particularly in children with auditory neuropathy spectrum disorder. Chapter 4 integrates the model into an analysis of intracochlear ECochG throughout CI insertion, particularly in deciding which response drops were likely to predict permanent hearing loss. Chapter 4 also serves as the primarydiscussion of the thesis, comparing intra- and extracochlear ECochG and concluding with an evaluation of ECochG in accounting for outcomes and minimizing trauma. Chapter 5 focuses on post-insertion positioning as a source of variance in outcomes, describing an impedance model to estimate array positioning (publication). Chapter 6 highlights ongoing work, including extracochlear ECochG and hearing preservation, simultaneous intra and extra-cochlear ECochG, and a tool to estimate CI positioning from an X-ray. Biomedical engineering Cochlear Implants; Electrocochleography; Hearing Preservation Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Douglas Fitzpatrick Thesis advisor Lianne Cartee Thesis advisor Douglas Fitzpatrick Thesis advisor John Grose Thesis advisor Paul Manis Thesis advisor H Nagle Thesis advisor 2018 2018-08 eng text Giardina_unc_0153D_17995.pdf uuid:127bdae1-c6c4-4d72-bc80-ea505e4f8b08 2020-08-23T00:00:00 2018-07-20T22:03:24Z proquest application/pdf 15643952