Electrical and Computer Engineering Publications
Document Type
Article
Publication Date
2021
Volume
239
Issue
4
Journal
Journal of Anatomy
First Page
771
URL with Digital Object Identifier
10.1111/joa.13457
Last Page
781
Abstract
The ossicular chain is a middle ear structure consisting of the small incus, malleus and stapes bones, which transmit tympanic membrane vibrations caused by sound to the inner ear. Despite being shown to be highly variable in shape, there are very few morphological studies of the ossicles. The objective of this study was to use a large sample of cadaveric ossicles to create a set of three-dimensional models and study their statistical variance. Thirty-three cadaveric temporal bone samples were scanned using micro-computed tomography (μCT) and segmented. Statistical shape models (SSMs) were then made for each ossicle to demonstrate the divergence of morphological features. Results revealed that ossicles were most likely to vary in overall size, but that more specific feature variability was found at the manubrium of the malleus, the long process and lenticular process of the incus, and the crura and footplate of the stapes. By analyzing samples as whole ossicular chains, it was revealed that when fixed at the malleus, changes along the chain resulted in a wide variety of final stapes positions. This is the first known study to create high-quality, three-dimensional SSMs of the human ossicles. This information can be used to guide otological surgical training and planning, inform ossicular prosthesis development, and assist with other ossicular studies and applications by improving automated segmentation algorithms. All models have been made publicly available.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Citation of this paper:
Bartling ML, Rohani SA, Ladak HM, Agrawal SK. Micro-CT of the human ossicular chain: Statistical shape modeling and implications for otologic surgery. J Anat. 2021 Oct;239(4):771-781. doi: 10.1111/joa.13457. Epub 2021 May 31. PMID: 34057736; PMCID: PMC8450485.
