A Web-Based Automated Image Processing Research Platform for Cochlear Implantation-Related Studies.

The robust delineation of the cochlea and its inner structures combined with the detection of the electrode of a cochlear implant within these structures is essential for envisaging a safer, more individualized, routine image-guided cochlear implant therapy. We present Nautilus-a web-based research platform for automated pre- and post-implantation cochlear analysis. Nautilus delineates cochlear structures from pre-operative clinical CT images by combining deep learning and Bayesian inference approaches. It enables the extraction of electrode locations from a post-operative CT image using convolutional neural networks and geometrical inference. By fusing pre- and post-operative images, Nautilus is able to provide a set of personalized pre- and post-operative metrics that can serve the exploration of clinically relevant questions in cochlear implantation therapy. In addition, Nautilus embeds a self-assessment module providing a confidence rating on the outputs of its pipeline. We present a detailed accuracy and robustness analyses of the tool on a carefully designed dataset. The results of these analyses provide legitimate grounds for envisaging the implementation of image-guided cochlear implant practices into routine clinical workflows.

Bayesian logistic shape model inference: Application to cochlear image segmentation.

Incorporating shape information is essential for the delineation of many organs and anatomical structures in medical images. While previous work has mainly focused on parametric spatial transformations applied to reference template shapes, in this paper, we address the Bayesian inference of parametric shape models for segmenting medical images with the objective of providing interpretable results. The proposed framework defines a likelihood appearance probability and a prior label probability based on a generic shape function through a logistic function. A reference length parameter defined in the sigmoid controls the trade-off between shape and appearance information. The inference of shape parameters is performed within an Expectation-Maximisation approach in which a Gauss-Newton optimization stage provides an approximation of the posterior probability of the shape parameters. This framework is applied to the segmentation of cochlear structures from clinical CT images constrained by a 10-parameter shape model. It is evaluated on three different datasets, one of which includes more than 200 patient images. The results show performances comparable to supervised methods and better than previously proposed unsupervised ones. It also enables an analysis of parameter distributions and the quantification of segmentation uncertainty, including the effect of the shape model.

Inner-ear augmented metal artifact reduction with simulation-based 3D generative adversarial networks.

Metal Artifacts creates often difficulties for a high quality visual assessment of post-operative imaging in computed tomography (CT). A vast body of methods have been proposed to tackle this issue, but these methods were designed for regular CT scans and their performance is usually insufficient when imaging tiny implants. In the context of post-operative high-resolution CT imaging, we propose a 3D metal artifact reduction algorithm based on a generative adversarial neural network. It is based on the simulation of physically realistic CT metal artifacts created by cochlea implant electrodes on preoperative images. The generated images serve to train a 3D generative adversarial networks for artifacts reduction. The proposed approach was assessed qualitatively and quantitatively on clinical conventional and cone beam CT of cochlear implant postoperative images. These experiments show that the proposed method outperforms other general metal artifact reduction approaches.

Pupillometry Assessment of Speech Recognition and Listening Experience in Adult Cochlear Implant Patients.

OBJECTIVE: The aim of the present study was to investigate the pupillary response to word identification in cochlear implant (CI) patients. Authors hypothesized that when task difficulty (i.e., addition of background noise) increased, pupil dilation markers such as the peak dilation or the latency of the peak dilation would increase in CI users, as already observed in normal-hearing and hearing-impaired subjects. METHODS: Pupillometric measures in 10 CI patients were combined to standard speech recognition scores used to evaluate CI outcomes, namely, speech audiometry in quiet and in noise at +10 dB signal-to-noise ratio (SNR). The main outcome measures of pupillometry were mean pupil dilation, maximal pupil dilation, dilation latency, and mean dilation during return to baseline or retention interval. Subjective hearing quality was evaluated by means of one self-reported fatigue questionnaire, and the Speech, Spatial, and Qualities (SSQ) of Hearing scale. RESULTS: All pupil dilation data were transformed to percent change in event-related pupil dilation (ERPD, %). Analyses show that the peak amplitudes for both mean pupil dilation and maximal pupil dilation were higher during the speech-in-noise test. Mean peak dilation was measured at 3.47 ± 2.29% noise vs. 2.19 ± 2.46 in quiet and maximal peak value was detected at 9.17 ± 3.25% in noise vs. 8.72 ± 2.93% in quiet. Concerning the questionnaires, the mean pupil dilation during the retention interval was significantly correlated with the spatial subscale score of the SSQ Hearing scale [r(8) = -0.84, p = 0.0023], and with the global score [r(8) = -0.78, p = 0.0018]. CONCLUSION: The analysis of pupillometric traces, obtained during speech audiometry in quiet and in noise in CI users, provided interesting information about the different processes engaged in this task. Pupillometric measures could be indicative of listening difficulty, phoneme intelligibility, and were correlated with general hearing experience as evaluated by the SSQ of Hearing scale. These preliminary results show that pupillometry constitutes a promising tool to improve objective quantification of CI performance in clinical settings.

Method to quantitatively assess electrode migration from medical images: Feasibility and application in patients with straight cochlear implant arrays.

Objective: To propose a method for quantitative assessment of the migration of lateral-wall, straight electrode arrays after surgery based on postoperative Cone Beam Computed Tomography (CBCT) images and automated medical image analysis techniques. Methods: A preliminary study is conducted on 19 implanted ears. For each implantation, two CBCT images are objectively analyzed. Electrode arrays are consistently projected into the same coordinate system in order to estimate precisely the migration of each electrode. Spatial configuration changes are characterized with the overall curvature of the electrode array. Results: From the samples analyzed no significant electrode migration, extrusion or electrode curvature changes were found. Mean infinitesimal local migration reveals a tendency where apical electrodes tend to move away from the modiolus and basal electrodes away from the round window. Conclusion: CBCT images demonstrate adequate resolution with limited artifacts to assess the electrode array position in vivo. Automated medical image analysis techniques and consistent coordinate system allow to quantitatively estimate migration and extrusion effect for lateral-wall, straight electrode array.

Motor cortex neurovascular coupling: inputs from ultra-high-frequency ultrasound imaging in humans.

OBJECTIVE: Neurovascular coupling reflects the link between neural activity and changes in cerebral blood flow. Despite many technical advances in functional exploration of the brain, including functional MRI, there are only a few reports of direct evidence of neurovascular coupling in humans. The authors aimed to explore, for the first time in humans, the local cerebral blood flow of the primary motor cortex using ultra-high-frequency ultrasound (UHF-US) Doppler imaging to detect low blood flow velocity (1 mm/sec). METHODS: Four consecutive patients underwent awake craniotomy for glioma resection using cortical direct electrostimulation for brain mapping. The primary motor cortical area eliciting flexion of the contralateral forearm was identified. UHF-US color Doppler imaging of this cortical area was acquired at rest, during repeated spontaneous forearm flexion, and immediately after the movement's termination. In each condition, the surface areas of the detectable vessels were measured after extraction of non-zero-velocity colored pixels and summed. RESULTS: During movement, local cerebral blood flow increased significantly by 14.4% (range 5%-30%) compared with baseline. Immediately after the termination of movements, the local hyperemia decreased significantly by 8.6% (range 1.9%-15.7%). CONCLUSIONS: To the authors' knowledge, this study is the first to provide a real-time demonstration of the neurovascular coupling in the human cortex by ultrasound imaging. They assume that UHF-US may be used to gather original and advanced data on brain functioning, which could be used to help in the identification of functional cortical areas during brain surgery.Clinical trial registration no.: NCT03179176 (clinicaltrials.gov).

Automated analysis of human cochlea shape variability from segmented µCT images.

The aim of this study is to define an automated and reproducible framework for cochlear anatomical analysis from high-resolution segmented images and to provide a comprehensive and objective shape variability study suitable for cochlear implant design and surgery planning. For the scala tympani (ST), the scala vestibuli (SV) and the whole cochlea, the variability of the arc lengths and the radial and longitudinal components of the lateral, central and modiolar paths are studied. The robustness of the automated cochlear coordinate system estimation is validated with synthetic and real data. Cochlear cross-sections are statistically analyzed using area, height and width measurements. The cross-section tilt angle is objectively measured and this data documents a significant feature for occurrence of surgical trauma.

Impact of the surgical experience on cochleostomy location: a comparative temporal bone study between endaural and posterior tympanotomy approaches for cochlear implantation.

The goal of this study was to evaluate, in the hands of an inexperienced surgeon, the cochleostomy location of an endaural approach (MINV) compared to the conventional posterior tympanotomy (MPT) approach. Since 2010, we use in the ENT department of Nice a new surgical endaural approach to perform cochlear implantation. In the hands of an inexperienced surgeon, the position of the cochleostomy has not yet been studied in detail for this technique. This is a prospective study of 24 human heads. Straight electrode arrays were implanted by an inexperienced surgeon: on one side using MPT and on the other side using MINV. The cochleostomies were all antero-inferior, but they were performed through an endaural approach with the MINV or a posterior tympanotomy approach with the MPT. The positioning of the cochleostomies into the scala tympani was evaluated by microdissection. Cochleostomies performed through the endaural approach were well placed into the scala tympani more frequently than those performed through the posterior tympanotomy approach (87.5 and 16.7 %, respectively, p ≤ 0.001). This study highlights the biggest challenge for an inexperienced surgeon to achieve a reliable cochleostomy through a posterior tympanotomy, which requires years of experience. In case of an uncomfortable view through a posterior tympanotomy, an inexperienced surgeon might be able to successfully perform a cochleostomy through an endaural (combined approach) or an extended round window approach in order to avoid opening the scala vestibuli.