Cadaveric Testing of Robot-Assisted Access to the Internal Auditory Canal for Vestibular Schwannoma Removal

A first exploration of the economic consequences of an autonomous surgical robot for lateral skull base surgery: an early health technology assessment

OBJECTIVES

Lateral skull base procedures, such as translabyrinthine approach (TLA), are challenging. An autonomous surgical robot might be a solution to these challenges. Our aim is to explore in an early phase the economic consequences of an autonomous surgical robot compared with conventional TLA.

METHODS

An early decision analytic model was constructed in order to perform a step-wise threshold analyses and a sensitivity analysis to analyze the impact of the several factors on the incremental costs.

RESULTS

Using surgical robot results in incremental costs - EUR 5,562 per procedure - compared to conventional TLA. These costs are most reduced by higher number of procedures, followed by lower price of the robot, saved operation time, and reduced risk of complication, respectively.

CONCLUSIONS

The incremental costs of using an autonomous surgical robot can be decreased by choosing applications with a high turnover rate, a long operation time, and a high complication rate.

Deep learning-based approach for the automatic segmentation of adult and pediatric temporal bone computed tomography images

Background

Automatic segmentation of temporal bone computed tomography (CT) images is fundamental to image-guided otologic surgery and the intelligent analysis of CT images in the field of otology. This study was conducted to test a convolutional neural network (CNN) model that can automatically segment almost all temporal bone anatomy structures in adult and pediatric CT images.

Methods

A dataset comprising 80 annotated CT volumes was collected, of which 40 samples were obtained from adults and 40 from children. A further 60 annotated CT volumes (30 from adults and 30 from children) were used to train the model. The remaining 20 annotated CT volumes were employed to determine the model's generalizability for automatic segmentation. Finally, the Dice coefficient (DC) and average symmetric surface distance (ASSD) were utilized as metrics to evaluate the performance of the CNN model. Two independent-sample t-tests were used to compare the test set results of adults and children.

Results

In the adult test set, the mean DC values of all the structures ranged from 0.714 to 0.912, and the ASSD values were less than 0.24 mm for 11 structures. In the pediatric test set, the mean DC values of all the structures ranged from 0.658 to 0.915, and the ASSD values were less than 0.18 mm for 11 structures. There was no statistically significant difference between the adult and child test sets in most temporal bone structures.

Conclusions

Our CNN model shows excellent automatic segmentation performance and good generalizability for both adult and pediatric temporal bone CT images, which can help to advance otologist education, intelligent imaging diagnosis, surgery simulation, application of augmented reality, and preoperative planning for image-guided otology surgery.

Pilot Study of Optical Topographic Imaging Based Neuronavigation for Mastoidectomy

BACKGROUND

Mastoidectomy involves drilling the temporal bone while avoiding the facial nerve, semicircular canals, sigmoid sinus, and tegmen. Optical topographic imaging (OTI) is a novel registration technique that allows rapid registration with minimal navigational error. To date, no studies have examined the use of OTI in skull-base procedures.

METHODS

In this cadaveric study, 8 mastoidectomies were performed in 2 groups-4 free-hand (FH) and 4 OTI-assisted mastoidectomies. Registration accuracy for OTI navigation was quantified with root mean square (RMS) and target registration error (TRE). Procedural time, percent of mastoid resected, and the proximity of the mastoidectomy cavity to critical structures were determined.

RESULTS

The average RMS and TRE associated with OTI-based registration were 1.44 mm (±0.83 mm) and 2.17 mm (±0.89 mm), respectively. The volume removed, expressed as a percentage of the total mastoid volume, was 37.5% (±10.2%) versus 31.2% (±2.3%), P = 0.31, for FH and OTI-assisted mastoidectomy. There were no statistically significant differences between FH and OTI-assisted mastoidectomies with respect to proximity to critical structures or procedural time.

CONCLUSIONS

This work is the first examining the application of OTI neuronavigation in lateral skull-base procedures. This pilot study revealed the RMS and TRE for OTI-based navigation in the lateral skull base are 1.44 mm (±0.83 mm) and 2.17 mm (±0.89 mm), respectively. This pilot study demonstrates that an OTI-based system is sufficiently accurate and may address barriers to widespread adoption of navigation for lateral skull-base procedures.

Statistical Shape Model of the Temporal Bone Using Segmentation Propagation

HYPOTHESIS

Automated image registration techniques can successfully determine anatomical variation in human temporal bones with statistical shape modeling.

BACKGROUND

There is a lack of knowledge about inter-patient anatomical variation in the temporal bone. Statistical shape models (SSMs) provide a powerful method for quantifying variation of anatomical structures in medical images but are time-intensive to manually develop. This study presents SSMs of temporal bone anatomy using automated image-registration techniques.

METHODS

Fifty-three cone-beam temporal bone CTs were included for SSM generation. The malleus, incus, stapes, bony labyrinth, and facial nerve were automatically segmented using 3D Slicer and a template-based segmentation propagation technique. Segmentations were then used to construct SSMs using MATLAB. The first three principal components of each SSM were analyzed to describe shape variation.

RESULTS

Principal component analysis of middle and inner ear structures revealed novel modes of anatomical variation. The first three principal components for the malleus represented variability in manubrium length (mean: 4.47 mm; ±2-SDs: 4.03-5.03 mm) and rotation about its long axis (±2-SDs: -1.6° to 1.8° posteriorly). The facial nerve exhibits variability in first and second genu angles. The bony labyrinth varies in the angle between the posterior and superior canals (mean: 88.9°; ±2-SDs: 83.7°-95.7°) and cochlear orientation (±2-SDs: -4.0° to 3.0° anterolaterally).

CONCLUSIONS

SSMs of temporal bone anatomy can inform surgeons on clinically relevant inter-patient variability. Anatomical variation elucidated by these models can provide novel insight into function and pathophysiology. These models also allow further investigation of anatomical variation based on age, BMI, sex, and geographical location.

Patient Benefit and Quality of Life after Robot-Assisted Head and Neck Surgery

Robotic systems for head and neck surgery are at different stages of technical development and clinical application. Currently, robotic systems are predominantly used for transoral surgery of the pharynx and larynx. Robotic surgery of the neck, the thyroid, and the middle and inner ear is much less common; however, some oncological and functional outcomes have been reported. This article provides an overview of the current state of robot-assisted head and neck surgery with a special emphasis on patient benefit and postoperative quality of life (QoL). The focus is placed on the role of transoral robotic surgery (TORS) for the resection of oropharyngeal carcinomas. For this application, reported long-term outcomes show functional post-operative advantages for selected oropharyngeal cancer patients after TORS compared to open surgery and primary radiotherapy. Since TORS also plays a significant role in the context of potential therapy de-escalation for HPV-positive oropharyngeal cancer patients, ongoing trials are presented. Regarding the evaluation of the therapeutic benefit and the QoL of cancer patients, special attention has to be paid to the large degree of variability of individual patients' preferences. Influencing factors and tools for a detailed assessment of QoL parameters are therefore detailed at the beginning of this article. Notably, while some robotic systems for ear and skull base surgery are being developed in Europe, TORS systems are mainly used in North America and Asia. In Europe and Germany in particular, transoral laser microsurgery (TLM) is a well-established technology for transoral tumor resection. Future trials comparing TORS and TLM with detailed investigation of QoL parameters are therefore warranted and might contribute to identifying suitable fields for the application of the different techniques.

A systematic review of robotic surgery: From supervised paradigms to fully autonomous robotic approaches

BACKGROUND

From traditional open surgery to laparoscopic surgery and robot-assisted surgery, advances in robotics, machine learning, and imaging are pushing the surgical approach to-wards better clinical outcomes. Pre-clinical and clinical evidence suggests that automation may standardise techniques, increase efficiency, and reduce clinical complications.

METHODS

A PRISMA-guided search was conducted across PubMed and OVID.

RESULTS

Of the 89 screened articles, 51 met the inclusion criteria, with 10 included in the final review. Automatic data segmentation, trajectory planning, intra-operative registration, trajectory drilling, and soft tissue robotic surgery were discussed.

CONCLUSION

Although automated surgical systems remain conceptual, several research groups have developed supervised autonomous robotic surgical systems with increasing consideration for ethico-legal issues for automation. Automation paves the way for precision surgery and improved safety and opens new possibilities for deploying more robust artificial intelligence models, better imaging modalities and robotics to improve clinical outcomes.

Robotic Milling of Electrode Lead Channels During Cochlear Implantation in an ex-vivo Model

Objective: Robotic cochlear implantation is an emerging surgical technique for patients with sensorineural hearing loss. Access to the middle and inner ear is provided through a small-diameter hole created by a robotic drilling process without a mastoidectomy. Using the same image-guided robotic system, we propose an electrode lead management technique using robotic milling that replaces the standard process of stowing excess electrode lead in the mastoidectomy cavity. Before accessing the middle ear, an electrode channel is milled robotically based on intraoperative planning. The goal is to further standardize cochlear implantation, minimize the risk of iatrogenic intracochlear damage, and to create optimal conditions for a long implant life through protection from external trauma and immobilization in a slight press fit to prevent mechanical fatigue and electrode migrations.

Methods: The proposed workflow was executed on 12 ex-vivo temporal bones and evaluated for safety and efficacy. For safety, the difference between planned and resulting channels were measured postoperatively in micro-computed tomography, and the length outside the planned safety margin of 1.0 mm was determined. For efficacy, the channel width and depth were measured to assess the press fit immobilization and the protection from external trauma, respectively.

Results: All 12 cases were completed with successful electrode fixations after cochlear insertions. The milled channels stayed within the planned safety margins and the probability of their violation was lower than one in 10,000 patients. Maximal deviations in lateral and depth directions of 0.35 and 0.29 mm were measured, respectively. The channels could be milled with a width that immobilized the electrode leads. The average channel depth was 2.20 mm, while the planned channel depth was 2.30 mm. The shallowest channel depth was 1.82 mm, still deep enough to contain the full 1.30 mm diameter of the electrode used for the experiments.

Conclusion: This study proposes a robotic electrode lead management and fixation technique and verified its safety and efficacy in an ex-vivo study. The method of image-guided robotic bone removal presented here with average errors of 0.2 mm and maximal errors below 0.5 mm could be used for a variety of other otologic surgical procedures.

Volumetric Accuracy Analysis of Virtual Safety Barriers for Cooperative-Control Robotic Mastoidectomy

HYPOTHESIS

Virtual fixtures can be enforced in cooperative-control robotic mastoidectomies with submillimeter accuracy.

BACKGROUND

Otologic procedures are well-suited for robotic assistance due to consistent osseous landmarks. We have previously demonstrated the feasibility of cooperative-control robots (CCRs) for mastoidectomy. CCRs manipulate instruments simultaneously with the surgeon, allowing the surgeon to control instruments with robotic augmentation of motion. CCRs can also enforce virtual fixtures, which are safety barriers that prevent motion into undesired locations. Previous studies have validated the ability of CCRs to allow a novice surgeon to safely complete a cortical mastoidectomy. This study provides objective accuracy data for CCR-imposed safety barriers in cortical mastoidectomies.

METHODS

Temporal bone phantoms were registered to a CCR using preoperative computed tomography (CT) imaging. Virtual fixtures were created using 3D Slicer, with 2D planes placed along the external auditory canal, tegmen, and sigmoid, converging on the antrum. Five mastoidectomies were performed by a novice surgeon, moving the drill to the limit of the barriers. Postoperative CT scans were obtained, and Dice coefficients and Hausdorff distances were calculated.

RESULTS

The average modified Hausdorff distance between drilled bone and the preplanned volume was 0.351 ± 0.093 mm. Compared with the preplanned volume of 0.947 cm3, the mean volume of bone removed was 1.045 cm3 (difference of 0.0982 cm3 or 10.36%), with an average Dice coefficient of 0.741 (range, 0.665-0.802).

CONCLUSIONS

CCR virtual fixtures can be enforced with a high degree of accuracy. Future studies will focus on improving accuracy and developing 3D fixtures around relevant surgical anatomy.

Fully automated segmentation in temporal bone CT with neural network: a preliminary assessment study

BACKGROUND

Segmentation of important structures in temporal bone CT is the basis of image-guided otologic surgery. Manual segmentation of temporal bone CT is time- consuming and laborious. We assessed the feasibility and generalization ability of a proposed deep learning model for automated segmentation of critical structures in temporal bone CT scans.

METHODS

Thirty-nine temporal bone CT volumes including 58 ears were divided into normal (n = 20) and abnormal groups (n = 38). Ossicular chain disruption (n = 10), facial nerve covering vestibular window (n = 10), and Mondini dysplasia (n = 18) were included in abnormal group. All facial nerves, auditory ossicles, and labyrinths of the normal group were manually segmented. For the abnormal group, aberrant structures were manually segmented. Temporal bone CT data were imported into the network in unmarked form. The Dice coefficient (DC) and average symmetric surface distance (ASSD) were used to evaluate the accuracy of automatic segmentation.

RESULTS

In the normal group, the mean values of DC and ASSD were respectively 0.703, and 0.250 mm for the facial nerve; 0.910, and 0.081 mm for the labyrinth; and 0.855, and 0.107 mm for the ossicles. In the abnormal group, the mean values of DC and ASSD were respectively 0.506, and 1.049 mm for the malformed facial nerve; 0.775, and 0.298 mm for the deformed labyrinth; and 0.698, and 1.385 mm for the aberrant ossicles.

CONCLUSIONS

The proposed model has good generalization ability, which highlights the promise of this approach for otologist education, disease diagnosis, and preoperative planning for image-guided otology surgery.

Robotics for Cochlear Implantation Surgery: Challenges and Opportunities

OBJECTIVES

Recent advancements in robotics have set forth a growing body of evidence for the clinical application of the robotic cochlear implantation (RCI), with many potential benefits. This review aims to summarize these efforts, provide the latest developments in this exciting field, and explore the challenges associated with the clinical implementation of RCI.

DATA SOURCES

MEDLINE, PubMed, and EMBASE databases.

STUDY SELECTION

A search was conducted using the keywords "robotics otolaryngology," "robotic cochlear implant," "minimally-invasive cochlear implantation," "minimally-invasive mastoidectomy," and "percutaneous cochlear implant" with all of their synonyms. Literature selection criteria included articles published in English, and articles from 1970 to present.

RESULTS

The use of robotics in neurotology is a relatively new endeavor that continues to evolve. Robotics is being explored by various groups to facilitate in the various steps of cochlear implant surgery, including drilling a keyhole approach to the middle ear for implants, inner ear access, and electrode insertion into the cochlea. Initial clinical trials have successfully implanted selected subjects using robotics.

CONCLUSIONS

The use of robotics in cochlear implants remains in its very early stages. It is hoped that robotics will improve clinical outcomes. Although successful implants with robots are reported in the literature, there are some challenges that need to be addressed before this approach can become an acceptable option for the conventional cochlear implant surgery, such as safety, time, efficiency, and cost. However, it is hoped that further advancements in robotic technology will help in overcoming these barriers leading to successful implementation for clinical utility.

Concept description and accuracy evaluation of a moldable surgical targeting system

Purpose: We explain our concept for customization of a guidance instrument, present a prototype, and describe a set of experiments to evaluate its positioning and drilling accuracy.

Methods: Our concept is characterized by the use of bone cement, which enables fixation of a specific configuration for each individual surgical template. This well-established medical product was selected to ensure future intraoperative fabrication of the template under sterile conditions. For customization, a manually operated alignment device is proposed that temporary defines the planned trajectory until the bone cement is hardened. Experiments (n=10) with half-skull phantoms were performed. Analysis of accuracy comprises targeting validations and experiments including drilling in bone substitutes.

Results: The resulting mean positioning error was found to be 0.41±0.30  mm at the level of the target point whereas drilling was possible with a mean accuracy of 0.35±0.30  mm.

Conclusion: We proposed a cost-effective, easy-to-use approach for accurate instrument guidance that enables template fabrication under sterile conditions. The utilization of bone cement was proven to fulfill the demands of an easy, quick, and prospectively intraoperatively doable customization. We could demonstrate sufficient accuracy for many surgical applications, e.g., in neurosurgery. The system in this early development stage already outperforms conventional stereotactic frames and image-guided surgery systems in terms of targeting accuracy.

Computational Optimization of Notch Spacing for a Transnasal Ear Endoscopy Continuum Robot

This paper presents a computational framework to optimize the visual coverage attainable by a notched-tube continuum robotic endoscope inside the middle ear cavity. Our framework combines anatomically-accurate geometric (mesh) models of the middle ear with a sampling-based motion planning algorithm (RRT) and a ray-casting procedure to quantify what regions of the middle ear can be accessed and visualized by the endoscope. To demonstrate the use of this framework, we run computer simulations to investigate the effect of varying the distance between each pair of consecutive flexure elements (i.e., notches) in our robotic endoscope.

Image-Guided Mastoidectomy with a Cooperatively Controlled ENT Microsurgery Robot

Mastoidectomy is a common surgical procedure within otology. Despite being inherently well suited for implementation of robotic assistance, there are no commercially available robotic systems that have demonstrated utility in aiding with this procedure. This article describes a robotic technique for image-guided mastoidectomy with an experimental cooperatively controlled robotic system developed for use within otolaryngology-head and neck surgery. It has the ability to facilitate enhanced operative precision with dampening of tremor in simulated surgical tasks. Its kinematic design is such that the location of the attached surgical instrument is known with a high degree of fidelity at all times. This facilitates image registration and subsequent definition of virtual fixtures, which demarcate surgical workspace boundaries and prevent motion into undesired areas. In this preliminary feasibility study, we demonstrate the clinical utility of this system to facilitate performance of a cortical mastoidectomy by a novice surgeon in 5 identical temporal bone models with a mean time of 221 ± 35 seconds.

Robotics in otorhinolaryngology - head and neck surgery

A look at the past, present and future.

State of Robotic Mastoidectomy: Literature Review

Over the past 30 years, the application of robotics in the field of neurotology has grown. Robots are able to perform increasingly complex tasks with ever improving accuracy, allowing them to be used in a broad array of applications. A mastoidectomy, in which a drill is used to remove a portion of the mastoid part of the temporal bone at the base of the skull, is one such application. To determine the current state of neurotologic robotics in the specific context of mastoidectomy, a review of the literature was carried out. This qualitative review explores what has been done in this field to date, as well as what has yet to be done. Although the research suggests that robotics can be and has been successfully used to assist with mastoidectomy, it also suggests the incompleteness of robotic development in the field. At present, only 2 robotic systems have been approved by the U.S. Food and Drug Administration for neurosurgical use and the literature lacks evidence of meaningful clinical testing of new systems to change that. The cost of robotics also remains prohibitive. However, strides have been made, with at least 1 robot for mastoidectomy having reached the point of cadaveric trials. In addition, the research suggests some of the characteristics that should be considered when designing robots for mastoidectomy, such as burr size and the type of forces that should be applied. Overall, the outlook for robots in neurotology, particularly mastoidectomy, is bright but some hurdles still remain to be overcome.