Fully Automated Measurement of Cochlear Duct Length From Clinical Temporal Bone Computed Tomography

Abstract

Objectives/Hypothesis: To present and validate a novel fully automated method to measure cochlear dimensions, including cochlear duct length (CDL).Study Design: Cross-sectional study.Methods: The computational method combined 1) a deep learning (DL) algorithm to segment the cochlea and otic capsule and 2) geometric analysis to measure anti-modiolar distances from the round window to the apex. The algorithm was trained using 165 manually segmented clinical computed tomography (CT). A Testing group of 159 CTs were then measured for cochlear diameter and width (A-and B-values) and CDL using the automated system and compared against manual measurements. The results were also compared with existing approaches and historical data. In addition, pre-and postimplantation scans from 27 cochlear implant recipients were studied to compare predicted versus actual array insertion depth.Results: Measurements were successfully obtained in 98.1% of scans. The mean CDL to 900 was 35.52 mm (SD, 2.06; range, [30.91-40.50]), the mean A-value was 8.88 mm (0.47; [7.67-10.49]), and mean B-value was 6.38 mm (0.42; [5.16-7.38]). The R 2 fit of the automated to manual measurements was 0.87 for A-value, 0.70 for B-value, and 0.71 for CDL. For anti-modiolar arrays, the distance between the imaged and predicted array tip location was 0.57 mm (1.25; [0.13-5.28]). Conclusion:Our method provides a fully automated means of cochlear analysis from clinical CTs. The distribution of CDL, dimensions, and cochlear quadrant lengths is similar to those from historical data. This approach requires no radiographic experience and is free from user-related variation.

Automated Radiomic Analysis of Vestibular Schwannomas and Inner Ears Using Contrast-Enhanced T1-Weighted and T2-Weighted Magnetic Resonance Imaging Sequences and Artificial Intelligence

“…), generalizing previous results to T2+ images obtained with different protocols and devices (13). Our model was able to achieve good test accuracy despite a modest training set, likely due in part to our use of transfer learning from our models in previous studies (13–15). Additional contributing factors include the homogeneity of the anatomical shape of the inner ear compared with tumors, the hyperintense signal of the perilymph in T2+ imaging, and the smaller input size of the cropped region of interest around the tumor, which reduces false positives.…”

“…In contrast to VS tumors that are heterogeneous in size, shape, and signal on MRI, the inner ear is consistent in appearance and typically more straightforward for automated segmentation. Our group has described the good accuracy of DL segmentation models for the inner ear using computed tomographic images (13) and the potential applications of these systems to planning for cochlear implant surgery (15) The automated segmentation of the inner ear provides additional information of the position of VS. VS IEC min = minimum distance from the VS to the IEC. VS IEC max = maximum distance from the VS to the IEC.…”

“…In contrast to VS tumors that are heterogeneous in size, shape, and signal on MRI, the inner ear is consistent in appearance and typically more straightforward for automated segmentation. Our group has described the good accuracy of DL segmentation models for the inner ear using computed tomographic images (13) and the potential applications of these systems to planning for cochlear implant surgery (15). Vaidyanathan et al (22) demonstrated the feasibility of a 3D U-Net model for segmenting the inner ear using high-resolution T2 MRI sequences (3D cochlea, DRIVE, SPC_TRA_ISO).…”

“…For both VS and IE models, preprocessing techniques that emphasized structure enhancement compared with their surroundings, as well as data augmentation techniques tested in previous studies (13)(14)(15), were used to improve model training.…”

Estimation of Cochlear Implant Insertion Depth Using 2D-3D Registration of Postoperative X-Ray and Preoperative CT Images

“…The final position of a cochlear implant (CI) electrode array is an important determinant of hearing outcomes (1,2). A skull radiograph (i.e., skull x-ray) is often obtained after cochlear implantation to confirm electrode placement within the cochlea and assess for kinks and tip fold over which may reduce performance or necessitate revision surgery.…”