The cochlea, or inner ear, is a space fully enclosed within the temporal bone of the skull, except for two membrane-covered portals connecting it to the middle ear space. One of these portals is the round window, which is covered by the Round Window Membrane (RWM). A longstanding clinical goal is to gain reliable and precise access to the cochlea with the purpose of delivering therapeutics to treat a plethora of auditory and vestibular disorders, or to aspirate fluids for diagnostic purposes. Standard of care for several difficult-to-treat diseases calls for injection of a therapeutic substance through the tympanic membrane into the middle ear space, after which a portion of the substance diffuses across the RWM into the cochlea. The efficacy of this technique is limited by an inconsistent rate of molecular transport across the RWM. Other solutions for delivery require either traumatic drilling through the bone of the cochlea, or perforating the delicate RWM, which is prone to rupturing with the use of regular surgical tools. For conducting precision diagnostics, even fewer options exist.
In our research group, utilizing a newly available technology called Two-Photon Lithography, (2PP) we have developed a suite of ultra-sharp microneedles that are able to create repeatable and reliable perforations in the RWM without tearing. These holes were seen to spontaneously heal within 48 hours, and did not cause any audiological or functional consequences. Furthermore, we have designed needles that can, while inserted into the cochlea, inject or aspirate fluid of microliter quantities, to and from the inner ear, safely.
In this thesis, I will discuss the development of these microneedles: their methods, design, use, and modeling. The results show that the microneedles hold great promise to diagnose and treat hearing and balance disorders.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/s01k-8p76 |
| Date | January 2022 |
| Creators | Aksit, Aykut |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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