Further Validity Evidence for Patient-Specific Virtual Reality Temporal Bone Surgical Simulation.

OBJECTIVE: Patient-specific virtual reality (VR) simulation of cochlear implant (CI) surgery potentially enables preoperative rehearsal and planning. We aim to gather supporting validity evidence for patient-specific simulation through the analysis of virtual performance and comparison with postoperative imaging. METHODS: Prospective, multi-institutional study. Pre- and postoperative cone-beam CT scans of CI surgical patients were obtained and processed for patient-specific VR simulation. The virtual performances of five trainees and four attendings were recorded and (1) compared with volumes removed during actual surgery as determined in postoperative imaging, and (2) assessed using the Copenhagen Cochlear Implant Surgery Assessment Tool (CISAT) by two blinded raters. The volumes compared were cortical mastoidectomy, facial recess, and round window (RW) cochleostomy as well as violation of the facial nerve and chorda. RESULTS: Trainees drilled more volume in the cortical mastoidectomy and facial recess, whereas attendings drilled more volume for the RW cochleostomy and made more violations. Except for the cochleostomy, attendings removed volumes closer to that determined in postoperative imaging. Trainees achieved a higher CISAT performance score compared with attendings (22.0 vs. 18.4 points) most likely due to lack of certain visual cues. CONCLUSION: We found that there were differences in performance of trainees and attendings in patient-specific VR simulation of CI surgery as assessed by raters and in comparison with actual drilled volumes. The presented approach of volume comparison is novel and might be used for further validation of patient-specific VR simulation before clinical implementation for preoperative rehearsal in temporal bone surgery. LEVEL OF EVIDENCE: n/a Laryngoscope, 134:1403-1409, 2024.

Pipeline for Automated Processing of Clinical Cone-Beam Computed Tomography for Patient-Specific Temporal Bone Simulation: Validation and Clinical Feasibility.

OBJECTIVE: Patient-specific simulation allows the surgeon to plan and rehearse the surgical approach ahead of time. Preoperative clinical imaging for this purpose requires time-consuming manual processing and segmentation of landmarks such as the facial nerve. We aimed to evaluate an automated pipeline with minimal manual interaction for processing clinical cone-beam computed tomography (CBCT) temporal bone imaging for patient-specific virtual reality (VR) simulation. STUDY DESIGN: Prospective image processing of retrospective imaging series. SETTING: Academic hospital. METHODS: Eleven CBCTs were selected based on quality and used for validation of the processing pipeline. A larger naturalistic sample of 36 CBCTs were obtained to explore parameters for successful processing and feasibility for patient-specific VR simulation.Visual inspection and quantitative metrics were used to validate the accuracy of automated segmentation compared with manual segmentation. Range of acceptable rotational offsets and translation point selection variability were determined. Finally, feasibility in relation to image acquisition quality, processing time, and suitability for VR simulation was evaluated. RESULTS: The performance of automated segmentation was acceptable compared with manual segmentation as reflected in the quantitative metrics. Total time for processing for new data sets was on average 8.3 minutes per data set; of this, it was less than 30 seconds for manual steps. Two of the 36 data sets failed because of extreme rotational offset, but overall the registration routine was robust to rotation and manual selection of a translational reference point. Another seven data sets had successful automated segmentation but insufficient suitability for VR simulation. CONCLUSION: Automated processing of CBCT imaging has potential for preoperative VR simulation but requires further refinement.

Automated Calculation of Cochlear Implant Electrode Insertion Parameters in Clinical Cone-Beam CT.

HYPOTHESIS: Automated processing of postoperative clinical cone-beam CT (CBCT) of cochlear implant (CI) patients can be used to accurately determine electrode contacts and integrated with an atlas-based mapping of cochlear microstructures to calculate modiolar distance, angular insertion distance, and scalar location of electrode contacts. BACKGROUND: Hearing outcomes after CI surgery are dependent on electrode placement. CBCT is increasingly used for in-office temporal bone imaging and might be routinely used for pre- and post-surgical evaluation. METHODS: Thirty-six matched pairs of pre- and postimplant CBCT scans were obtained. These were registered with an atlas to model cochlear microstructures in each dataset. Electrode contact center points were automatically determined using thresholding and electrode insertion parameters were calculated. Automated localization and calculation were compared with manual segmentation of contact center points as well as manufacturer specifications. RESULTS: Automated electrode contact detection aligned with manufacturer specifications of spacing and our algorithms worked for both distantly- and closely spaced arrays. The average difference between the manual and the automated selection was 0.15 mm, corresponding to a 1.875 voxel difference in each plane at the scan resolution. For each case, we determined modiolar distance, angular insertion depth, and scalar location. These calculations also resulted in similar insertion values using manual and automated contact points as well as aligning with electrode properties. CONCLUSION: Automated processing of implanted high-resolution CBCT images can provide the clinician with key information on electrode placement. This is one step toward routine use of clinical CBCT after CI surgery to inform and guide postoperative treatment.

Atlas-based segmentation of cochlear microstructures in cone beam CT.

PURPOSE: To develop an automated segmentation approach for cochlear microstructures [scala tympani (ST), scala vestibuli (SV), modiolus (Mod), mid-modiolus (Mid-Mod), and round window membrane (RW)] in clinical cone beam computed tomography (CBCT) images of the temporal bone for use in surgical simulation software and for preoperative surgical evaluation. METHODS: This approach was developed using the publicly available OpenEar (OE) Library that includes temporal bone specimens with spatially registered CBCT and 3D micro-slicing images. Five of these datasets were spatially aligned to our internal OSU atlas. An atlas of cochlear microstructures was created from one of the OE datasets. An affine registration of this atlas to the remaining OE CBCT images was used for automatically segmenting the cochlear microstructures. Quantitative metrics and visual review were used for validating the automatic segmentations. RESULTS: The average DICE metrics were 0.77 and 0.74 for the ST and SV, respectively. The average Hausdorff distance (AVG HD) was 0.11 mm and 0.12 mm for both scalae. The mean distance between the centroids for the round window was 0.32 mm, and the mean AVG HD was 0.09 mm. The mean distance and angular rotation between the mid-modiolar axes were 0.11 mm and 9.8 degrees, respectively. Visually, the segmented structures were accurate and similar to that manually traced by an expert observer. CONCLUSIONS: An atlas-based approach using 3D micro-slicing data and affine spatial registration in the cochlear region was successful in segmenting cochlear microstructures of temporal bone anatomy for use in simulation software and potentially for pre-surgical planning and rehearsal.

Segmentation of Temporal Bone Anatomy for Patient-Specific Virtual Reality Simulation.

OBJECTIVES: Virtual reality (VR) simulation for patient-specific pre-surgical planning and rehearsal requires accurate segmentation of key surgical landmark structures such as the facial nerve, ossicles, and cochlea. The aim of this study was to explore different approaches to segmentation of temporal bone surgical anatomy for patient-specific VR simulation. METHODS: De-identified, clinical computed tomography imaging of 9 pediatric patients aged 3 months to 12 years were obtained retrospectively. The patients represented normal anatomy and key structures were manually segmented using open source software. The OTOPLAN (CAScination AG, Bern, Switzerland) otological planning software was used for guided segmentation. An atlas-based algorithm was used for computerized, automated segmentation. Experience with the different approaches as well as time and resulting models were compared. RESULTS: Manual segmentation was time consuming but also the most flexible. The OTOPLAN software is not designed specifically for our purpose and therefore the number of structures that can be segmented is limited, there was some user-to-user variation as well as volume differences compared with manual segmentation. The atlas-based automated segmentation potentially allows a full range of structures to be segmented and produces segmentations comparable to those of manual segmentation with a processing time that is acceptable because of the minimal user interaction. CONCLUSION: Segmentation is fundamental for patient-specific VR simulation for pre-surgical planning and rehearsal in temporal bone surgery. The automated segmentation algorithm currently offers the most flexible and feasible approach and should be implemented. Further research is needed in relation to cases of abnormal anatomy. LEVEL OF EVIDENCE: 4.

Standard Setting of Competency in Mastoidectomy for the Cross-Institutional Mastoidectomy Assessment Tool.

OBJECTIVE: Competency-based surgical training involves progressive autonomy given to the trainee. This requires systematic and evidence-based assessment with well-defined standards of proficiency. The objective of this study is to develop standards for the cross-institutional mastoidectomy assessment tool to inform decisions regarding whether a resident demonstrates sufficient skill to perform a mastoidectomy with or without supervision. METHODS: A panel of fellowship-trained content experts in mastoidectomy was surveyed in relation to the 16 items of the assessment tool to determine the skills needed for supervised and unsupervised surgery. We examined the consensus score to investigate the degree of agreement among respondents for each survey item as well as additional analyses to determine whether the reported skill level required for each survey item was significantly different for the supervised versus unsupervised level. RESULTS: Ten panelists representing different US training programs responded. There was considerable consensus on cut-off scores for each item and trainee level between panelists, with moderate (0.62) to very high (0.95) consensus scores depending on assessment item. Further analyses demonstrated that the difference between supervised and unsupervised skill levels was significantly meaningful for all items. Finally, minimum-passing scores for each item was established. CONCLUSION: We defined performance standards for the cross-institutional mastoidectomy assessment tool using the Angoff method. These cut-off scores that can be used to determine when trainees can progress from performance under supervision to performance without supervision. This can be used to guide training in a competency-based training curriculum.

Atlas-based segmentation of temporal bone surface structures.

PURPOSE: To develop a time-efficient automated segmentation approach that could identify surface structures on the temporal bone for use in surgical simulation software and preoperative surgical training. METHODS: An atlas-based segmentation approach was developed to segment the tegmen, sigmoid sulcus, exterior auditory canal, interior auditory canal, and posterior canal wall in normal temporal bone CT images. This approach was tested in images of 20 cadaver bones (10 left, 10 right). The results of the automated segmentation were compared to manual segmentation using quantitative metrics of similarity, Mahalanobis distance, average Hausdorff distance, and volume similarity. RESULTS: The Mahalanobis distance was less than 0.232 mm for all structures. The average Hausdorff distance was less than 0.464 mm for all structures except the posterior canal wall and external auditory canal for the right bones. Volume similarity was 0.80 or greater for all structures except the sigmoid sulcus that was 0.75 for both left and right bones. Visually, the segmented structures were accurate and similar to that manually traced by an expert observer. CONCLUSIONS: An atlas-based approach using a deformable registration of a Gaussian-smoothed temporal bone image and refinements using surface landmarks was successful in segmenting surface structures of temporal bone anatomy for use in pre-surgical planning and training.

Cross-Institutional Evaluation of a Mastoidectomy Assessment Instrument.

OBJECTIVE: The objective of this work is to obtain validity evidence for an evaluation instrument used to assess the performance level of a mastoidectomy. The instrument has been previously described and had been formulated by a multi-institutional consortium. DESIGN: Mastoidectomies were performed on a virtual temporal bone system and then rated by experts using a previously described 15 element task-based checklist. Based on the results, a second, similar checklist was created and a second round of rating was performed. SETTING: Twelve otolaryngological surgical training programs in the United States. PARTICIPANTS: In all, 65 mastoidectomy performances were evaluated coming from 37 individuals with a variety of temporal bone dissection experience, from medical students to attending physicians. Raters were attending surgeons from 12 different institutions. RESULTS: Intraclass correlation scores varied greatly between items in the checklist with some being low and some being high. Percentage agreement scores were similar to previous rating instruments. There is strong evidence that a high score on the task-based checklist is necessary for a rater to consider a mastoidectomy to be performed at the level of an expert but a high score is not a sufficient condition. CONCLUSIONS: Rewording of the instrument items to focus on safety does not result in increased reliability of the instrument. The strong result of the Necessary Condition Analysis suggests that going beyond simple correlation measures can give extra insight into grading results. Additionally, we suggest using a multiple point scale instead of a binary pass/fail question combined with descriptive mastery levels.

Atlas-Based Segmentation of Temporal Bone Anatomy.

PURPOSE: To develop a time-efficient automated segmentation approach that could identify critical structures in the temporal bone for visual enhancement and use in surgical simulation software. METHODS: An atlas-based segmentation approach was developed to segment the cochlea, ossicles, semicircular canals (SCCs), and facial nerve in normal temporal bone CT images. This approach was tested in images of 26 cadaver bones (13 left, 13 right). The results of the automated segmentation were compared to manual segmentation visually and using DICE metric, average Hausdorff distance, and volume similarity. RESULTS: The DICE metrics were greater than 0.8 for the cochlea, malleus, incus, and the SCCs combined. It was slightly lower for the facial nerve. The average Hausdorff distance was less than one voxel for all structures, and the volume similarity was 0.86 or greater for all structures except the stapes. CONCLUSIONS: The atlas-based approach with rigid body registration of the otic capsule was successful in segmenting critical structures of temporal bone anatomy for use in surgical simulation software.

Multi-Institutional Development of a Mastoidectomy Performance Evaluation Instrument.

OBJECTIVE: A method for rating surgical performance of a mastoidectomy procedure that is shown to apply universally across teaching institutions has not yet been devised. This work describes the development of a rating instrument created from a multi-institutional consortium. DESIGN: Using a participatory design and a modified Delphi approach, a multi-institutional group of expert otologists constructed a 15-element task-based checklist for evaluating mastoidectomy performance. This instrument was further refined into a 14-element checklist focusing on the concept of safety after using it to rate a large and varied population of performances. SETTING: Twelve otolaryngological surgical training programs in the United States. PARTICIPANTS: A total of 14 surgeons from 12 different institutions took part in the construction of the instrument. RESULTS: By using 14 experts from 12 different institutions and a literature review, individual metrics were identified, rated as to the level of importance and operationally defined to create a rating scale for mastoidectomy performance. Initial use of the rating scale showed modest rater agreement. The operational definitions of individual metrics were modified to emphasize "safe" as opposed to "proper" technique. A second rating instrument was developed based on this feedback. CONCLUSIONS: Using a consensus-building approach with multiple rounds of communication between experts is a feasible way to construct a rating instrument for mastoidectomy. Expert opinion alone using a Delphi method provides face and content validity evidence, however, this is not sufficient to develop a universally acceptable rating instrument. A continued process of development and experimentation to demonstrate evidence for reliability and validity making use of a large population of raters and performances is necessary to achieve universal acceptance.

Expert subjective comparison of haptic models for bone-drill interaction.

PURPOSE: A haptic algorithm to simulate the interaction between a surgical drill and bone using a constraint-based algorithm has been previously demonstrated. However, there has been no blinded study to determine whether this algorithm is preferred by professionals who commonly use this type of system METHODS: Fourteen otologic surgeons were presented with a spring-damper model and a constraint-based model of drill-bone interaction rendered on a low-cost haptic device with only linear feedback. The participants were blinded as to what algorithm they were using. They then answered survey questions about their opinions of the models. RESULTS: The surgeons overwhelmingly preferred the constraint-based model. They generally preferred the constraint-based model in the individual questions as well. CONCLUSIONS: Follow-up work can be done to fine-tune the parameters in the model, but this study shows that a sophisticated algorithm can make a significant difference even on a low-fidelity haptic device.

Integration of high-resolution data for temporal bone surgical simulations.

PURPOSE: To report on the state of the art in obtaining high-resolution 3D data of the microanatomy of the temporal bone and to process that data for integration into a surgical simulator. Specifically, we report on our experience in this area and discuss the issues involved to further the field. DATA SOURCES: Current temporal bone image acquisition and image processing established in the literature as well as in house methodological development. REVIEW METHODS: We reviewed the current English literature for the techniques used in computer-based temporal bone simulation systems to obtain and process anatomical data for use within the simulation. Search terms included "temporal bone simulation, surgical simulation, temporal bone." Articles were chosen and reviewed that directly addressed data acquisition and processing/segmentation and enhancement with emphasis given to computer-based systems. We present the results from this review in relationship to our approach. CONCLUSIONS: High-resolution CT imaging ([Formula: see text] voxel resolution), along with unique image processing and rendering algorithms, and structure-specific enhancement are needed for high-level training and assessment using temporal bone surgical simulators. Higher-resolution clinical scanning and automated processes that run in efficient time frames are needed before these systems can routinely support pre-surgical planning. Additionally, protocols such as that provided in this manuscript need to be disseminated to increase the number and variety of virtual temporal bones available for training and performance assessment.

Anatomical Volume Visualization with Weighted Distance Fields.

We describe the use of the weighted distance transform (WDT) to enhance applications designed for volume visualization of segmented anatomical datasets. The WDT is presented as a general technique to generate a derived characteristic of a scalar field that can be used in multiple ways during rendering. We obtain real-time interaction with the volume by calculating the WDT on the graphics card. Several examples of this technique as it applies to an application for teaching anatomical structures are detailed, including rendering embedded structures, fuzzy boundaries, outlining, and indirect lighting estimation.

Simulation of punch biopsies: a case study.

As the incidence of skin cancer continues to rise, there is an increasing need for skilled practitioners that are proficient in identifying suspicious lesions and competent in acquiring biopsies that provide for optimal determination of malignancy and staging. We report on the development of a prototype simulation that emulates the basic procedures necessary to acquire a punch biopsy. The objective of this effort is to produce a low-cost, effective method to teach non-specialists, i.e., nurse practitioners, internists, etc., the optimal placement of the punch to obtain a biopsy for pathological analysis. The simulation can be utilized for synchronous sessions with remote experts, as well as asynchronous sessions for deliberate practice. The simulation is designed to allow for easy import of digital images of various lesions to promote use and present the wide pathological variance experienced in the clinic.

Translating human simulation technologies to veterinary surgical training: accelerating adoption.

Through the reduction of live animal use in teaching surgical technique, the opportunities to deliberately study complex regional anatomy and practice surgical technique have decreased. With reduced exposure, there is concern some individuals are graduating without the requisite knowledge and proficiency to perform adequate surgical techniques. Ultimately, animals may unnecessarily suffer due to morbidities from limited or poor surgical competencies. We have translated developments derived from the human surgical simulation field for application to veterinary surgical training. We present our work on intuitive software for learning regional anatomy, surgical simulations, and on several limiting factors that impede the validation and adoption of simulation technologies for use by the veterinarian surgical community.

Evaluating elicited anxiety in a simulated environment.

Simulated environments are increasingly being used to evaluate human behavior in a wide variety of situations. These virtual environments are particularly useful in the study of behavior involving dangerous conditions. Quantifying the impact of these environments on the subject is essential to validate the efficacy of the simulation as a virtualization of reality. We have developed a prototypical environment that simulates a common agricultural setting that provides the potential for acute injuries. We report on an exploratory study to evaluate the efficacy of our design to illicit a sense of realism and subsequently evoke a physiological response of anxiety in the subject. We present on the components that comprise the environment, our study design, and preliminary results.