Statistical shape modeling of the human inner ear through micro-computed tomography imaging.

Abstract

The human inner ear (IE) is a complex structure whose morphological variability underpins both normal function and the manifestation of otologic pathologies. Previous studies aiming to describe the structural variability of the IE have been limited by low-resolution imaging and small sample numbers. This study utilized the largest number of cadaveric high-resolution micro-computed tomography (CT) images to date to characterize the bony morphology of the healthy human IE. Fifty-four cadaveric temporal bone specimens underwent micro-CT imaging. Images were semi-automatically segmented and converted to three-dimensional surface mesh models for morphological measurement and analysis. Statistical shape models (SSMs) were created for the IE, cochlea, and vestibular system, as well as for sex- and side-based subgroups. Normative ranges for linear and volumetric dimensions of the IE were determined, and mean values were consistent with those previously reported. Significant sex-based differences and strong univariate linear relationships were identified for many dimensions and volumes. SSMs highlighted the semicircular canals, cochlear basal turn, and hook regions as key contributors to morphological variability across the total sample set. Sex-specific SSMs revealed distinct variation patterns: females exhibited greater vestibular variability, while males showed cochlear basal turn/hook region variability. Multivariate models were developed for the prediction of IE volumes from dimensions obtainable from clinical quality scans, with high accuracy. The morphological variability of the healthy IE was described in extensive detail and depicted in three dimensions. These findings may be used to inform the assessment of IE malformations, analysis of drug delivery strategies to the IE, and otologic implant design optimization.