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Related Concept Videos

Anatomy of the Ear01:16

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Auditory sensation, commonly called hearing, involves the transformation of sonic waves into neural impulses facilitated by the structures of the auditory organ. The prominent, flesh-like structure on the side of the head, called the auricle, directs sound waves towards the auditory canal. The auricle is often mislabeled as the pinna, a term more aligned with mobile structures like a feline's external ear. The auditory canal penetrates the cranium via the external auditory meatus of the...
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Finite-Element Modelling Based on Optical Coherence Tomography and Corresponding X-ray MicroCT Data for Three Human

Marzieh Golabbakhsh1, Xuan Wang1, Dan MacDougall2

  • 1Department of BioMedical Engineering, McGill University, Montréal, QC, Canada.

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|May 10, 2023
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Summary

Finite-element (FE) modeling combined with optical coherence tomography (OCT) accurately simulates middle ear vibrations. This approach, using subject-specific anatomy, shows promise for identifying middle ear abnormalities in future patient diagnostics.

Keywords:
Finite-element modellingHumanMiddle earOptical coherence tomographyVibration measurementmicroCT

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Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Computational Mechanics

Background:

  • Optical coherence tomography (OCT) is a non-invasive imaging technique capable of capturing in vivo anatomy and vibrations.
  • Finite-element (FE) modeling offers a powerful tool for analyzing mechanical behaviors based on anatomical data.

Purpose of the Study:

  • To explore the application of FE modeling using OCT data for analyzing middle ear mechanics.
  • To validate FE models against OCT measurements of human cadaver middle ears.

Main Methods:

  • Human cadaver middle ears were imaged using OCT for vibration analysis and X-ray microCT for anatomical data.
  • Three subject-specific FE models were constructed using microCT geometries, with material properties and boundary conditions from existing literature.
  • FE models were used to compute tympanic membrane (TM) vibration patterns and frequency responses, which were compared to OCT measurements and literature values.

Main Results:

  • Simulated TM displacement patterns showed qualitative similarity to OCT measurements.
  • Model predictions closely matched OCT results at 500 Hz and 1 kHz, with greater discrepancies at 2 kHz.
  • Parameter sensitivity analyses were conducted and compared across models and with existing literature.

Conclusions:

  • This study demonstrates the feasibility of integrating OCT measurements with subject-specific FE modeling for middle ear analysis.
  • The combined approach provides a foundation for future development of patient-specific FE models to aid in the diagnosis of middle ear pathologies.