Focal Spot, Spring 2002

https://digitalcommons.wustl.edu/focal_spot_archives/1090/thumbnail.jp

Quality-assured training in the evaluation of cochlear implant electrode position: a prospective experimental study

Background The objective of this study was to demonstrate the utility of an approach in training predoctoral medical students, to enable them to measure electrode-to-modiolus distances (EMDs) and insertion-depth angles (aDOIs) in cochlear implant (CI) imaging at the performance level of a single senior rater. Methods This prospective experimental study was conducted on a clinical training dataset comprising patients undergoing cochlear implantation with a Nucleus® CI532 Slim Modiolar electrode (N = 20) or a CI512 Contour Advance electrode (N = 10). To assess the learning curves of a single medical student in measuring EMD and aDOI, interrater differences (senior-student) were compared with the intrarater differences of a single senior rater (test-retest). The interrater and intrarater range were both calculated as the distance between the 0.1th and 99.9th percentiles. A "deliberate practice" training approach was used to teach knowledge and skills, while correctives were applied to minimize faulty data-gathering and data synthesis. Results Intrarater differences of the senior rater ranged from - 0.5 to 0.5 mm for EMD and - 14° to 16° for aDOI (respective medians: 0 mm and 0°). Use of the training approach led to interrater differences that matched this after the 4th (EMD) and 3rd (aDOI) feedback/measurement series had been provided to the student. Conclusions The training approach enabled the student to evaluate the CI electrode position at the performance level of a senior rater. This finding may offer a basis for ongoing clinical quality assurance for the assessment of CI electrode position

3D curved multiplanar cone beam CT reconstruction for intracochlear position assessment of straight electrodes array. A temporal bones and patients study

A retrospective review of post-op cone beam CT (CBCT) of 8 adult patients and 14 fresh temporal bones that underwent cochlear implantation with straight flexible electrodes array was performed to determine if the position of a long and flexible electrodes array within the cochlear scalae could be reliably assessed with CBCT. An oto-radiologist and two otologists examined the images and assessed the electrodes position. The temporal bone specimens underwent histological analysis for confirm the exact position. The position of the electrodes was rated as scala tympani, scala vestibule, or intermediate position for the electrodes at 180°, 360° and for the apical electrode. In the patient group, for the electrodes at 180° all observers agreed for scala tympani position except for 1 evaluation, while a discrepancy in 3 patients both for the 360° and for the apical electrode assessment were found. In five temporal bones the evaluations were in discrepancy for the 180° electrode, while at 360° a disagreement between raters on the scalar positioning was seen in six temporal bones. A higher discrepancy between was found in assessment of the scalar position of the apical electrode (average pairwise agreement 45.4%, Fleiss k = 0.13). A good concordance was found between the histological results and the consensus between raters for the electrodes in the basal turn, while low agreement (Cohen’s k 0.31, pairwise agreement 50%) was found in the identification of the apical electrode position confirming the difficulty to correct identify the electrode position in the second cochlear turn in temporal bones. In conclusion, CBCT is a reliable radiologic exam to correctly evaluate the position of a lateral wall flexible array in implanted patients using the proposed imaging reconstruction method, while some artefacts impede exact evaluation of the position of the apical electrode in temporal bone and other radiological techniques should be preferred in ex vivo studies

Min-Max Similarity: A Contrastive Learning Based Semi-Supervised Learning Network for Surgical Tools Segmentation

Segmentation of images is a popular topic in medical AI. This is mainly due to the difficulty to obtain a significant number of pixel-level annotated data to train a neural network. To address this issue, we proposed a semi-supervised segmentation network based on contrastive learning. In contrast to the previous state-of-the-art, we introduce a contrastive learning form of dual-view training by employing classifiers and projectors to build all-negative, and positive and negative feature pairs respectively to formulate the learning problem as solving min-max similarity problem. The all-negative pairs are used to supervise the networks learning from different views and make sure to capture general features, and the consistency of unlabeled predictions is measured by pixel-wise contrastive loss between positive and negative pairs. To quantitative and qualitative evaluate our proposed method, we test it on two public endoscopy surgical tool segmentation datasets and one cochlear implant surgery dataset which we manually annotate the cochlear implant in surgical videos. The segmentation performance (dice coefficients) indicates that our proposed method outperforms state-of-the-art semi-supervised and fully supervised segmentation algorithms consistently. The code is publicly available at: https://github.com/AngeLouCN/Min_Max_Similarit