Fitsum A. Reda

Minimally invasive image-guided cochlear implantation surgery: First report of clinical implementation

Minimally invasive image‐guided approach to cochlear implantation (CI) involves drilling a narrow, linear tunnel to the cochlea. Reported herein is the first clinical implementation of this approach.

Comparison of Cochlear Implant Relevant Anatomy in Children Versus Adults

Hypothesis To test whether there are significant differences in pediatric and adult temporal bone anatomy as related to cochlear implant (CI) surgery. Background Surgeons rely upon anatomic landmarks including the round window (RW) and facial recess (FR) to place CI electrodes within the scala tympani. Anecdotally, clinicians report differences in orientation of such structures in children versus adults. Methods Institutional review board approval was obtained. High-resolution computed tomographic scans of 24 pediatric patients (46 ears) and 20 adult patients (40 ears) were evaluated using software consisting of a model-based segmentation algorithm that automatically localizes and segments temporal bone anatomy (e.g., facial nerve, chorda tympani, external auditory canal [EAC], and cochlea). On these scans, angles pertinent anatomy were manually delineated and measured blinded as to the age of the patient. Results The EAC and FR were more parallel to the basal turn (BT) of the cochlea in children versus adults (∠ EAC:BT 20.55 degrees versus 24.28 degrees, p = 0.003; ∠FR:BT 5.15degrees versus 6.88 degrees, p = 0.009). The RW was more closely aligned with the FR in children versus adults (∠FR:RW 30.43 degrees versus 36.67 degrees, p = 0.009). Comparing the lateral portion of the EAC (using LatEAC as a marker) to the most medial portion (using ⊥TM as a marker), the measured angle was 136.57 degrees in children and 172.20 degrees in adults (p < 0.001). Conclusion There are significant differences in the temporal bone anatomy of children versus adults pertinent to CI electrode insertion.

Automatic Pre- to Intra-Operative CT Registration for Image-Guided Cochlear Implant Surgery

Percutaneous cochlear implantation (PCI) is a minimally-invasive image-guided cochlear implant approach, where access to the cochlea is achieved by drilling a linear channel from the skull surface to the cochlea. The PCI approach requires pre- and intra-operative planning. Computation of a safe linear drilling trajectory is performed in a preoperative CT. This trajectory is mapped to intraoperative space using the transformation matrix that registers the pre- and intra-operative CTs. However, the difference in orientation between the pre- and intra-operative CTs is too extreme to be recovered by standard, gradient descent-based registration methods. Thus far, the registration has been initialized manually by an expert. In this paper, we present a method that aligns the scans completely automatically. We compared the performance of the automatic approach to the registration approach when an expert does the manual initialization on 11 pairs of scans. There is a maximum difference of 0.18 mm between the entry and target points of the trajectory mapped with expert initialization and the automatic registration method. This suggests that the automatic registration method is accurate enough to be used in a PCI surgery.

Automatic segmentation of intra-cochlear anatomy in post-implantation ct of unilateral cochlear implant recipients

A cochlear implant (CI) is a neural prosthetic device that restores hearing by directly stimulating the auditory nerve using an electrode array that is implanted in the cochlea. In CI surgery, the surgeon accesses the cochlea and makes an opening where he/she inserts the electrode array blind to internal structures of the cochlea. Because of this, the final position of the electrode array relative to intra-cochlear anatomy is generally unknown. We have recently developed an approach for determining electrode array position relative to intra-cochlear anatomy using a pre- and a post-implantation CT. The approach is to segment the intra-cochlear anatomy in the pre-implantation CT, localize the electrodes in the post-implantation CT, and register the two CTs to determine relative electrode array position information. Currently, we are using this approach to develop a CI programming technique that uses patient-specific spatial information to create patient-customized sound processing strategies. However, this technique cannot be used for many CI users because it requires a pre-implantation CT that is not always acquired prior to implantation. In this study, we propose a method for automatic segmentation of intra-cochlear anatomy in post-implantation CT of unilateral recipients, thus eliminating the need for pre-implantation CTs in this population. The method is to segment the intra-cochlear anatomy in the implanted ear using information extracted from the normal contralateral ear and to exploit the intra-subject symmetry in cochlear anatomy across ears. To validate our method, we performed experiments on 30 ears for which both a pre- and a post-implantation CT are available. The mean and the maximum segmentation errors are 0.224 and 0.734mm, respectively. These results indicate that our automatic segmentation method is accurate enough for developing patient-customized CI sound processing strategies for unilateral CI recipients using a post-implantation CT alone.

Automatic segmentation of the facial nerve and chorda tympani in pediatric CT scans

PURPOSE Cochlear implant surgery is used to implant an electrode array in the cochlea to treat hearing loss. The authors recently introduced a minimally invasive image-guided technique termed percutaneous cochlear implantation. This approach achieves access to the cochlea by drilling a single linear channel from the outer skull into the cochlea via the facial recess, a region bounded by the facial nerve and chorda tympani. To exploit existing methods for computing automatically safe drilling trajectories, the facial nerve and chorda tympani need to be segmented. The goal of this work is to automatically segment the facial nerve and chorda tympani in pediatric CT scans. METHODS The authors have proposed an automatic technique to achieve the segmentation task in adult patients that relies on statistical models of the structures. These models contain intensity and shape information along the central axes of both structures. In this work, the authors attempted to use the same method to segment the structures in pediatric scans. However, the authors learned that substantial differences exist between the anatomy of children and that of adults, which led to poor segmentation results when an adult model is used to segment a pediatric volume. Therefore, the authors built a new model for pediatric cases and used it to segment pediatric scans. Once this new model was built, the authors employed the same segmentation method used for adults with algorithm parameters that were optimized for pediatric anatomy. RESULTS A validation experiment was conducted on 10 CT scans in which manually segmented structures were compared to automatically segmented structures. The mean, standard deviation, median, and maximum segmentation errors were 0.23, 0.17, 0.18, and 1.27 mm, respectively. CONCLUSIONS The results indicate that accurate segmentation of the facial nerve and chorda tympani in pediatric scans is achievable, thus suggesting that safe drilling trajectories can also be computed automatically.

An artifact-robust, shape library-based algorithm for automatic segmentation of inner ear anatomy in post-cochlear-implantation CT.

A cochlear implant (CI) is a device that restores hearing using an electrode array that is surgically placed in the cochlea. After implantation, the CI is programmed to attempt to optimize hearing outcome. Currently, we are testing an imageguided CI programming (IGCIP) technique we recently developed that relies on knowledge of relative position of intracochlear anatomy to implanted electrodes. IGCIP is enabled by a number of algorithms we developed that permit determining the positions of electrodes relative to intra-cochlear anatomy using a pre- and a post-implantation CT. One issue with this technique is that it cannot be used for many subjects for whom a pre-implantation CT was not acquired. Pre-implantation CT has been necessary because it is difficult to localize the intra-cochlear structures in post-implantation CTs alone due to the image artifacts that obscure the cochlea. In this work, we present an algorithm for automatically segmenting intra-cochlear anatomy in post-implantation CTs. Our approach is to first identify the labyrinth and then use its position as a landmark to localize the intra-cochlea anatomy. Specifically, we identify the labyrinth by first approximately estimating its position by mapping a labyrinth surface of another subject that is selected from a library of such surfaces and then refining this estimate by a standard shape model-based segmentation method. We tested our approach on 10 ears and achieved overall mean and maximum errors of 0.209 and 0.98 mm, respectively. This result suggests that our approach is accurate enough for developing IGCIP strategies based solely on post-implantation CTs.

Minimally Invasive Image-Guided Cochlear Implantation for Pediatric Patients: Clinical Feasibility Study

Objective Minimally invasive image-guided cochlear implantation (CI) involves accessing the cochlea via a linear path from the lateral skull to the cochlea avoiding vital structures including the facial nerve. Herein, we describe and demonstrate the feasibility of the technique for pediatric patients. Study Design Prospective. Setting Children’s Hospital. Subjects and Methods Thirteen pediatric patients (1.5 to 8 years) undergoing traditional CI participated in this Institutional Review Board–approved study. Three fiducial markers were bone-implanted surrounding the ear, and a CT scan was acquired. The CT scan was processed to identify the marker locations and critical structures of the temporal bone. A safe linear path was determined to target the cochlea avoiding damage to vital structures. A custom microstereotactic frame was fabricated that would mount on the fiducial markers and constrain a tool to the desired trajectory. After traditional mastoidectomy and prior to cochleostomy, the custom microstereotactic frame was mounted on the bone-implanted markers to confirm that the achieved trajectory was safe and accurately accessed the cochlea. Results For all the 13 patients, it was possible to determine a safe trajectory to the cochlea. Custom microstereotactic frames were validated successfully on 9 patients. Two of these patients had inner ear malformations, and this technique helped the surgeon confirm ideal location for cochleostomy. For patients with normal anatomy, the mean and standard deviation of the closest distance of the trajectory to facial nerve and chorda tympani were 1.1 ± 0.3 mm and 1.2 ± 0.5 mm, respectively. Conclusion Minimally invasive image-guided CI is feasible for pediatric patients.

Automatic segmentation of intra-cochlear anatomy in post-implantation CT

A cochlear implant (CI) is a neural prosthetic device that restores hearing by directly stimulating the auditory nerve with an electrode array. In CI surgery, the surgeon threads the electrode array into the cochlea, blind to internal structures. We have recently developed algorithms for determining the position of CI electrodes relative to intra-cochlear anatomy using pre- and post-implantation CT. We are currently using this approach to develop a CI programming assistance system that uses knowledge of electrode position to determine a patient-customized CI sound processing strategy. However, this approach cannot be used for the majority of CI users because the cochlea is obscured by image artifacts produced by CI electrodes and acquisition of pre-implantation CT is not universal. In this study we propose an approach that extends our techniques so that intra-cochlear anatomy can be segmented for CI users for which pre-implantation CT was not acquired. The approach achieves automatic segmentation of intra-cochlear anatomy in post-implantation CT by exploiting intra-subject symmetry in cochlear anatomy across ears. We validated our approach on a dataset of 10 ears in which both pre- and post-implantation CTs were available. Our approach results in mean and maximum segmentation errors of 0.27 and 0.62 mm, respectively. This result suggests that our automatic segmentation approach is accurate enough for developing customized CI sound processing strategies for unilateral CI patients based solely on postimplantation CT scans.

Fully automatic surface-based pre- to intra-operative CT registration for cochlear implant

Percutaneous cochlear implantation (PCI) is an image-guided surgical approach, where access to the cochlea is achieved by drilling a channel from the outer skull to the cochlea. The PCI requires pre- and intra-operative planning. Computation of a safe drilling trajectory is performed in a pre-operative CT. This trajectory is mapped to intra-operative space using the transformation matrix that registers the pre- and intra-operative CTs. However, the misalignment between the two CTs is too extreme to be recovered by standard registration methods. Thus the registration is initialized manually. In this work we present a method that aligns the scans completely automatically. We compared the performance of this method to the manually initialized registration. There is a maximum difference of 0.19 mm between the entry and target points resulting from the automatic and manually initialized registrations. This suggests that the automatic method is accurate enough to be used in a PCI surgery.

Automatic pre- to intra-operative CT registration for image-guided cochlear implant surgery

Percutaneous cochlear implantation (PCI) is a minimally invasive image-guided cochlear implant approach, where access to the cochlea is achieved by drilling a linear channel from the outer skull to the cochlea. The PCI approach requires pre- and intra-operative planning. Segmentation of critical ear anatomy and computation of a safe drilling trajectory are performed in a pre-operative CT. The computed safe drilling trajectory must then be mapped to the intraoperative space. The mapping can be done using the transformation matrix that registers the pre- and intra-operative CTs. However, the difference in orientation between the pre- and intra-operative CTs is too extreme to be recovered by standard, gradient descent-based registration methods. Thus, we have so far relied on an expert to manually initialize the registration. In this work we present a method that aligns the scans automatically. We compared the performance of the automatic approach to the registration approach when an expert does the manual initialization on ten pairs of scans. There is a maximum difference of 0.19 mm between the entry and target points resulting from the automatic and manually initialized registration processes. This suggests that the automatic registration method is accurate enough to be used in a PCI surgery.