HRCT-Based Three-Dimensional Morphometric Analysis of the External Auditory Canal for Transcanal Surgical Planning and Navigation

To establish a preliminary pathway-planning framework for continuum robotic navigation within the external auditory canal (EAC) by reconstructing the three-dimensional (3D) centerline and quantifying key anatomical parameters, including curvature index, volume, surface area, and canal dimensions, using high-resolution computed tomography (HRCT).

A retrospective study was conducted in 75 adults (103 ears; 52 male and 51 female ears; mean age, 46.55 ± 12.37 years) who underwent temporal bone HRCT with a slice thickness of 0.67 mm. Three-dimensional reconstruction and centerline extraction of the EAC were performed using 3D Slicer software. Morphological parameters, including EAC length, mean radius, volume, surface area, and curvature index, were measured. Statistical analyses were performed using parametric or non-parametric tests according to data distribution.

The mean EAC length was 29.92 ± 2.69 mm, mean radius was 3.29 ± 0.36 mm, volume was 1020.34 ± 207.64 mm³, surface area was 688.61 ± 97.81 mm², and curvature index was 1.07 ± 0.04. Male participants exhibited significantly larger EAC dimensions than female participants, including greater volume (1082.79 vs. 956.66 mm³), surface area (725.12 vs. 651.38 mm²), and length (30.79 vs. 29.04 mm; all P < 0.05). Right-sided EACs demonstrated larger volume (1028.37 vs. 954.30 mm³) and greater radius (3.32 vs. 3.20 mm) than left-sided EACs (P < 0.05). EAC volume showed a strong positive correlation with radius (r = 0.904) and a moderate negative correlation with length (r = −0.341), suggesting two anatomical phenotypes: “slender” canals characterized by greater length and smaller radius, and “robust” canals characterized by shorter length and larger radius.

This study presents a preliminary anatomical framework for continuum robotic navigation within the EAC based on centerline coordinates derived from 3D HRCT reconstruction. Quantitative morphometric parameters, including curvature index and canal radius, may provide important reference data for the design, validation, and trajectory planning of flexible robotic systems. The proposed methodology may also support future development of individualized transcanal surgical navigation and minimally invasive otologic interventions.