Preoperative prediction of angular insertion depth of lateral wall cochlear implant electrode arrays

Hearing outcomes following cochlear implantation with anatomic or default frequency mapping in postlingual deafness adults

PURPOSE

The aim of this study was to compare the outcomes of different mapping procedures based on anatomic or default frequency distribution in postlingual deafness adults who underwent cochlear implantation (CI).

METHODS

Forty-eight adults with postlingual deafness who underwent CI (MED-EL) from January 2021 to May 2022 in our hospital were prospectively recruited. The participants were randomly assigned to two groups (the anatomic group and the default group). Postoperative computerized tomography (CT) scans were evaluated with Otoplan® to determine the angular insertion depth (AID) and the specific locations of the intracochlear electrodes. Anatomic maps were imported into MAESTRO 9.0 software (MED-EL) for anatomy-based fitting for anatomic group, while default mapping program was set up for the default group. Hearing thresholds, Speech Recognition Scores (SRS), and subjects' auditory and musical abilities were evaluated 1 year after using the CI. Differences were determined in two groups using Stata statistical software, with significance defined as p < 0.05.

RESULTS

SRS under noisy conditions was significantly greater for anatomic group than the default group (p = 0.02). Under quiet conditions, however, mean hearing thresholds (0.5, 1, 2, and 4 kHz) and SRS did not differ significantly between the two groups (p = 0.07). Modified questionnaires showed that auditory (p = 0.02) and musical (p = 0.01) quality were significantly better following the anatomic mapping than the default procedure.

CONCLUSION

CI program based on the anatomic distribution may bring better SRS under noise conditions as well as better auditory and musical qualities than based on the default frequency distribution.

Hybrid active shape and deep learning method for the accurate and robust segmentation of the intracochlear anatomy in clinical head CT and CBCT images

Purpose: Robust and accurate segmentation methods for the intracochlear anatomy (ICA) are a critical step in the image-guided cochlear implant programming process. We have proposed an active shape model (ASM)-based method and a deep learning (DL)-based method for this task, and we have observed that the DL method tends to be more accurate than the ASM method while the ASM method tends to be more robust. Approach: We propose a DL-based U-Net-like architecture that incorporates ASM segmentation into the network. A quantitative analysis is performed on a dataset that consists of 11 cochlea specimens for which a segmentation ground truth is available. To qualitatively evaluate the robustness of the method, an experienced expert is asked to visually inspect and grade the segmentation results on a clinical dataset made of 138 image volumes acquired with conventional CT scanners and of 39 image volumes acquired with cone beam CT (CBCT) scanners. Finally, we compare training the network (1) first with the ASM results, and then fine-tuning it with the ground truth segmentation and (2) directly with the specimens with ground truth segmentation. Results: Quantitative and qualitative results show that the proposed method increases substantially the robustness of the DL method while having only a minor detrimental effect (though not significant) on its accuracy. Expert evaluation of the clinical dataset shows that by incorporating the ASM segmentation into the DL network, the proportion of good segmentation cases increases from 60/177 to 119/177 when training only with the specimens and increases from 129/177 to 151/177 when pretraining with the ASM results. Conclusions: A hybrid ASM and DL-based segmentation method is proposed to segment the ICA in CT and CBCT images. Our results show that combining DL and ASM methods leads to a solution that is both robust and accurate.

Comprehensive Analysis of Factors Affecting Cochlear Size: A Systematic Review and Meta-analysis

OBJECTIVES

To determine the cochlea's average size in humans and evaluate the relationships between certain covariates and cochlear size.

METHODS

A systematic search on articles on cochlear size and published in English was conducted using Cochrane, PubMed, Web of Science, and Scopus databases up to September 15, 2020. Data were pooled using random-effects with three models. The effect of demographic, clinical, and measurement-related parameters was specifically analyzed. Meta-regression and subgroup analyses were conducted. The overall effect estimation was made for outcomes.

RESULTS

The meta-analysis included 4,708 cochleae from 56 studies. The overall length of the organ of Corti was 32.94 mm (95% confidence interval [CI]: 32.51-33.38). The first and second models revealed that age, gender, country, continent, measurement method (direct, indirect), measured structure ("A" value, cochlear lateral wall), origin (in vivo, in vitro), and type (histology specimens, plastic casts, imaging) of the cochlear material did not affect the cochlear size. However, study populations (general population, patients with a cochlear implant, and patients with congenital sensorineural hearing loss [CSNHL]) were found to affect the outcomes. Compared to the other populations, patients with CSNHL had shorter cochleae. Therefore, we developed a third model and found that the general population and patients with cochlear implants did not differ in cochlear size.

CONCLUSION

This meta-analysis investigated the factors that could affect the cochlear size and found that patients with CSNHL had significantly shorter cochleae, whereas other covariates had no significant effect. Laryngoscope, 2021.

Application of Multispectral Imaging in the Human Tympanic Membrane

Multispectral imaging has recently shown good performance in determining information about physiology, morphology, and composition of tissue. In the endoscopy field, many researches have shown the ability to apply multispectral or narrow-band images in surveying vascular structure based on the interaction of light wavelength with tissue composition. However, there has been no mention to assess the contrast between other components in the middle ear such as the tympanic membrane, malleus, and the surrounding area. Using CT, OCT, or ODT can clearly describe the tympanic membrane structure; nevertheless, these approaches are expensive, more complex, and time-consuming and are not suitable for most common middle ear diagnoses. Here, we show the potential of using the multispectral imaging technique to enhance the contrast of the tympanic membrane compared to the surrounding tissue. The optical absorption and scattering of biological tissues constituents are not the same at different wavelengths. In this pilot study, multiwavelength images of the tympanic membrane were captured by using the otoscope with LED light source at three distinct spectral regions: 450 nm, 530 nm, and 630 nm. Subsequently, analyses of the intensity images as well as the histogram of these images point out that the 630 nm illumination image features an evident contrast in the intensity of the tympanic membrane and malleus compared to the surrounding area. Analysis of such images could facilitate the boundary determination and segmentation of the tympanic membrane (TM) with high precision.