Extratympanic Observation of Middle and Inner Ear Structures in Rodents Using Optical Coherence Tomography

Oh, Se-Joon; Lee, Il-Woo; Wang, Soo-Geun; Kong, Soo-Keun; Kim, Hongki; Goh, Eui-Kyung

doi:10.21053/ceo.2019.00766

Cited by 7 publications

(6 citation statements)

References 22 publications

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“…First, TEN testing in clinics is time-consuming. Introducing more advanced technologies, such as optical coherence tomography, may reduce the time needed for testing through easily used, non-invasive methods for evaluating inner ear structures; however, the depth of the image that it produces is limited to a few millimeters due to its low permeability to tissues [16]. Therefore, the TEN (HL) test is still performed as the primary tool for assessing cochlear dead regions in clinics, although it has some limitations to being more widely used.…”

Section: Discussionmentioning

confidence: 99%

Predicting the Cochlear Dead Regions Using a Machine Learning-Based Approach with Oversampling Techniques

2021

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Background and Objectives: Determining the presence or absence of cochlear dead regions (DRs) is essential in clinical practice. This study proposes a machine learning (ML)-based model that applies oversampling techniques for predicting DRs in patients. Materials and Methods: We used recursive partitioning and regression for classification tree (CT) and logistic regression (LR) as prediction models. To overcome the imbalanced nature of the dataset, oversampling techniques to duplicate examples in the minority class or to synthesize new examples from existing examples in the minority class were adopted, namely the synthetic minority oversampling technique (SMOTE). Results: The accuracy results of the 10-fold cross-validation of the LR and CT with the original data were 0.82 (±0.02) and 0.93 (±0.01), respectively. The accuracy results of the 10-fold cross-validation of the LR and CT with the oversampled data were 0.66 (±0.02) and 0.86 (±0.01), respectively. Conclusions: This study is the first to adopt the SMOTE method to assess the role of oversampling methods on audiological datasets and to develop an ML-based model. Considering that the SMOTE method did not improve the model’s performance, a more flexible model or more clinical features may be needed.

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Section: Discussionmentioning

confidence: 99%

Predicting the Cochlear Dead Regions Using a Machine Learning-Based Approach with Oversampling Techniques

2021

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“…Hereby, the photon count at the detector and the quality of the detector determines the image quality. While the penetration depth of the light in tissue is relatively short, 1 mm, a decent spatial resolution of about 1–10 µm can be achieved ( Pitris et al, 2001 ; Popescu et al, 2011 ; Subhash et al, 2012 ; Chang et al, 2013 ; Macdougall et al, 2015 ; Jeon et al, 2019a ; Burwood et al, 2019 ; Oh et al, 2020 ).…”

Section: Appendix: Methods To Measure Middle Ear Functionmentioning

confidence: 99%

Mammalian middle ear mechanics: A review

Ugarteburu

Withnell

Cardoso

et al. 2022

Front. Bioeng. Biotechnol.

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The middle ear is part of the ear in all terrestrial vertebrates. It provides an interface between two media, air and fluid. How does it work? In mammals, the middle ear is traditionally described as increasing gain due to Helmholtz’s hydraulic analogy and the lever action of the malleus-incus complex: in effect, an impedance transformer. The conical shape of the eardrum and a frequency-dependent synovial joint function for the ossicles suggest a greater complexity of function than the traditional view. Here we review acoustico-mechanical measurements of middle ear function and the development of middle ear models based on these measurements. We observe that an impedance-matching mechanism (reducing reflection) rather than an impedance transformer (providing gain) best explains experimental findings. We conclude by considering some outstanding questions about middle ear function, recognizing that we are still learning how the middle ear works.

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“…The long and widespread use of glycerol in these applications gives some confidence in glycerol's general safety and capacity to be tolerated when used in the external ear canal. To our knowledge, while optical clearing agents have previous been used for increasing the transparency of the tympanic membrane to improve infrared otoscopy (22), OCAs have not previously been used to aid middle ear OCT imaging. We envision a scenario where an optical clearing agent would be administered topically to the post-tympanoplasty tympanic membrane in clinic as an eardrop.…”

Section: Optical Coherence Tomography Of the Middle Earmentioning

confidence: 99%

Optical Clearing Agents for Optical Imaging Through Cartilage Tympanoplasties: A Preclinical Feasibility Study

Wang

Chawdhary

Yang

et al. 2022

Otology &Amp; Neurotology

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Hypothesis: Optical clearing agents (OCAs) can render cartilage tympanoplasty grafts sufficiently transparent to permit visualization of middle ear structures in an operated ear using optical coherence tomography (OCT) imaging. Methods: Pieces of human tragal cartilage were treated with glycerol, a commonly used OCA. A reference reflector was imaged with OCT through the tympanoplasty as it cleared and the optical attenuation of the graft was measured. The reversibility of clearing and the dimensional changes associated with glycerol absorption were also measured. In a separate experiment, a human cadaveric temporal bone was prepared to simulate an ossiculoplasty surgery with cartilage replacement of the tympanic membrane. A partial ossicular replacement prosthesis (PORP) inserted in the ear was imaged with OCT through a 0.4mm cartilage graft optically cleared with glycerol. Main Outcome Measure: The optical attenuation of 0.4mm cartilage grafts decreased at 2.3+/−1.1 dB/min following treatment with glycerol, reaching a total decrease in attenuation of 13.6+/−5.9 dB after 7 minutes. The optical and dimensional effects of glycerol absorption were reversable following saline washout. In the temporal bone preparation, treatment of a cartilage graft with glycerol resulted in a 13 dB increase in signal-to-noise ratio and a 13 dB increase in contrast for visualizing the PORP through the graft with OCT. Conclusions: Optical clearing agents offer a potential pathway towards optical coherence tomography imaging of the middle ear in post-surgical ears with cartilage grafts.

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Extratympanic Observation of Middle and Inner Ear Structures in Rodents Using Optical Coherence Tomography

Cited by 7 publications

References 22 publications

Predicting the Cochlear Dead Regions Using a Machine Learning-Based Approach with Oversampling Techniques

Predicting the Cochlear Dead Regions Using a Machine Learning-Based Approach with Oversampling Techniques

Mammalian middle ear mechanics: A review

Optical Clearing Agents for Optical Imaging Through Cartilage Tympanoplasties: A Preclinical Feasibility Study

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