Practicable assessment of cochlear size and shape from clinical CT images

Abstract

There is considerable interpersonal variation in the size and shape of the human cochlea, with evident consequences for cochlear implantation. The ability to characterize a specific cochlea, from preoperative computed tomography (CT) images, would allow the clinician to personalize the choice of electrode, surgical approach and postoperative programming. In this study, we present a fast, practicable and freely available method for estimating cochlear size and shape from clinical CT. The approach taken is to fit a template surface to the CT data, using either a statistical shape model or a locally affine deformation (LAD). After fitting, we measure cochlear size, duct length and a novel measure of basal turn non-planarity, which we suggest might correlate with the risk of insertion trauma. Gold-standard measurements from a convenience sample of 18 micro-CT scans are compared with the same quantities estimated from low-resolution, noisy, pseudo-clinical data synthesized from the same micro-CT scans. The best results were obtained using the LAD method, with an expected error of 8–17% of the gold-standard sample range for non-planarity, cochlear size and duct length.

CT imaging-based approaches to cochlear duct length estimation—a human temporal bone study

“…With a CDL range between 35.5 and 43.1 mm, the overall CDL range is in accordance to the values reported in the literature [ 24 , 35 ]. However, only few studies considered the influence of imaging quality and resolution by applying the methods in different imaging modalities and lack a comparison of methods that are not authorized for clinical application to a clinically approved otosurgical planning software [ 22 , 36 ]. Summarizing these results, a gold standard for the determination of the CDL is still missing.…”

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

“…These considerations represent a substantiative advantage of the system presented over existing automated methods. Some of which still require some degree of time‐consuming and error‐prone manual establishment of anatomic landmarks to estimate CDL based upon calculations 16–18,26 . Other fully automated methods train their DL models on ultra‐high‐definition CT scans that are not widely found in the clinical environment 25 …”

“…Several methods for measuring cochlear length have been developed based on statistical shape models and also on the co‐registration of an anatomical atlas derived from microCTs 12,15,26,31 . The scarcity of microCT datasets limits the sample sizes used and may reduce the robustness of this approach.…”

“…Some of which still require some degree of timeconsuming and error-prone manual establishment of anatomic landmarks to estimate CDL based upon calculations. [16][17][18]26 Other fully automated methods train their DL models on ultra-high-definition CT scans that are not widely found in the clinical environment. 25 The variability of cochlear length 11,[35][36][37][38] between individuals and the potential for personalized preoperative assessment to improve clinical outcomes has motivated several methods to estimate the CDL.…”

“…Several methods for measuring cochlear length have been developed based on statistical shape models and also on the co-registration of an anatomical atlas derived from microCTs. 12,15,26,31 The scarcity of microCT datasets limits the sample sizes used and may reduce the robustness of this approach. Heutink et al 25 developed a cochlear identification and measurement method with a multi-step DL approach through the analysis of ultrahigh resolution clinical CT images.…”