Clinical Implementation of Second-generation Minimally Invasive Image-guided Cochlear Implantation Surgery.

OBJECTIVE: Minimally invasive, image-guided cochlear implantation (CI) surgery consists of drilling a precise tunnel from the surface of the mastoid cortex through the facial recess to target the scala tympani. In the first set of clinical trials of this technique, heat-induced facial nerve paresis (House-Brackmann II/VI) occurred on a patient on the last day of the initial trial which was scheduled to be halted secondary to a change in the regulatory requirements dictated by the 2012 the Food and Drug Administration Safety and Innovation Act requiring Investigational Device Exemption approval for previously exempted customized medical device testing. To address this adverse event, extensive changes were made to the drilling protocol; additionally, a custom insertion tool was developed. To address the Food and Drug Administration Safety and Innovation Act, an Investigational Device Exemption was submitted and, subsequently approved. Herein is described our first clinical implementation of the modified technique. PATIENT: Seventy-year-old with profound, postlingual sensorineural hearing loss who had previously undergone right CI via traditional approach in 2015. INTERVENTION: Minimally invasive image-guided left CI. MAIN OUTCOME MEASURE: Time of intervention, final location of CI electrode array within cochlea. RESULTS: Surgery took 155 minutes of which the largest components (in descending order) were soft tissue work, closure, and drilling. Full scala tympani insertion with angular insertion depth of 557 degrees of the electrode array was achieved. There were no complications, and the patient had an uneventful recovery and activation. CONCLUSIONS: Minimally invasive, image-guided CI surgery is achievable and reduces the mastoid depression associated with traditional CI surgery. CLINICALTRIALSGOV INFORMATION: Study NCT03101917, Microtable Microstereotactic Frame and Drill Press and Associated Method for Cochlear Implantation. LEVEL OF EVIDENCE: Case Report.

Clinical accuracy of a customized stereotactic platform for deep brain stimulation after accounting for brain shift.

Previous studies have evaluated the accuracy of several approaches for the placement of electrodes for deep brain stimulation. In this paper, we present a strategy to minimize the effect of brain shift on the estimation of the electrode placement error (EPE) for a stereotactic platform in the absence of intraoperative imaging data, and we apply it to the StarFix microTargeting Platform (FHC Inc., Bowdoin, Me., USA). This method involves comparing the intraoperative stereotactic coordinates of the implant with its position in the postoperative CT images in a population for which the effect of brain shift is minimal. The study we have conducted on 75 patients demonstrates that the EPE is overestimated at least by about 60% if brain shift is not taken into account, and shows a clinical accuracy of 1.24 +/- 0.37 mm for the StarFix frame, which is similar to the reported G frame accuracy and better than the reported Nexframe accuracy (2.5 +/- 1.4 mm) [Stereotact Funct Neurosurg 2007;85:235-242].

Geometric distortion correction for echo planar images using nonrigid registration with spatially varying scale.

One method used to correct geometric and intensity distortions in echo planar images is to register them to undistorted images via nonrigid deformations. However, some areas in the echo planar images are more distorted than others, thus suggesting the use of deformations whose characteristics are adapted spatially. In this article, we incorporate into our previously developed registration algorithm a spatially varying scale mechanism, which adapts the local scale properties of the transformation by means of a scale map. To compute the scale map, a technique is proposed that relies on an estimate of the expected deformation field. This estimate is generated using knowledge of the physical processes that induce distortions in echo planar images. We evaluate the method of spatially varying scale on both simulated and real data. We find that, in comparison with our earlier method using fixed scale, our new method finds deformation fields that are smoother and finds them faster without sacrificing accuracy.

Accounting for signal loss due to dephasing in the correction of distortions in gradient-echo EPI via nonrigid registration.

Gradient-echo (GE) echo planar imaging (EPI) is susceptible to both geometric distortions and signal loss. This paper presents a retrospective correction approach based on nonrigid image registration. A new physics-based intensity correction factor derived to compensate for intravoxel dephasing in GE EPI images is incorporated into a previously reported nonrigid registration algorithm. Intravoxel dephasing causes signal loss and thus intensity attenuation in the images. The new rephasing factor we introduce, which changes the intensity of a voxel in images during the registration, is used to improve the accuracy of the intensity-based nonrigid registration method and mitigate the intensity attenuation effect. Simulation-based experiments are first used to evaluate the method. A magnetic resonance (MR) simulator and a real field map are used to generate a realistic GE EPI image. The geometric distortion computed from the field map is used as the ground truth to which the estimated nonrigid deformation is compared. We then apply the algorithm to a set of real human brain images. The results show that, after registration, alignment between EPI and multi-shot, spin-echo images, which have relatively long acquisition times but negligible distortion, is improved and that signal loss caused by dephasing can be recovered.

Comparative evaluation of similarity measures for the rigid registration of multi-modal head images.

Image registrations that are based on similarity measures simply adjust the parameters of an appropriate spatial transformation model until the similarity measure reaches an optimum. The numerous similarity measures that have been proposed in the past are differently sensitive to imaging modality, image content and differences in the image content, selection of the floating and target image, partial image overlap, etc. In this paper, we evaluate and compare 12 similarity measures for the rigid registration. To study the impact of different imaging modalities on the behavior of similarity measures, we have used 16 CT/MR and 6 PET/MR image pairs with known 'gold standard' registrations. The results for the PET/MR registration and for the registration of CT to both rectified and unrectified MR images indicate that mutual information, normalized mutual information and the entropy correlation coefficient are the most accurate similarity measures and have the smallest risk of being trapped in a local optimum. The results of an experiment on the impact of exchanging the floating and target image indicate that, especially in MR/PET registrations, the behavior of some similarity measures, such as mutual information, significantly depends on which image is the floating and which is the target.

Computer-generated fMRI phantoms with motion-distortion interaction.

As an extension of previous work on computer-generated phantoms, more accurate, realistic phantoms are generated by integrating image distortion and signal loss caused by susceptibility variations. With the addition of real motions and activations determined from actual functional MRI studies, these phantoms can be used by the fMRI community to assess with higher fidelity pre-processing algorithms such as motion correction, distortion correction and signal-loss compensation. These phantoms were validated by comparison to real echo-planar images. Specifically, studies have shown the effects of motion-distortion interactions on fMRI. We performed motion correction and activation analysis on these phantoms based on a block paradigm design using SPM2, and the results demonstrate that interactions between motion and distortion affect both motion correction and activation detection and thus represent a critical component of phantom generation.

Percutaneous cochlear access using bone-mounted, customized drill guides: demonstration of concept in vitro.

HYPOTHESIS: Percutaneous cochlear access can be performed using bone-mounted drill guides that are custom made on the basis of preintervention computed tomographic scans. BACKGROUND: We have previously demonstrated the ability to use image guidance based on fiducial markers to obtain percutaneous cochlear access in vitro. A simpler approach that has far less room for application error is to constrict the path of the drill to pass in a predetermined trajectory using a drill guide. METHODS: Cadaveric temporal bone specimens (n = 8) were affixed with three bone-implanted fiducial markers. The temporal bone computed tomographic scans were obtained and used in planning a straight trajectory from the mastoid surface to the cochlea without violating the boundaries of the facial recess, namely, the chorda tympani, the incus buttress, and the facial nerve. These surgical plans were used to manufacture a customized drill guide by means of rapid prototyping (MicroTargeting Platform; FHC Inc.; Bowdoinham, ME, U.S.A.) that mounts onto anchor pins previously used to mount fiducial markers. The specimens then underwent traditional mastoidectomy with facial recess. The drill guide was mounted, and a 1-mm drill bit was passed through the guide across the mastoid and the facial recess. The course of the drill bit and its relationship to the boundaries of the facial recess were photographed and measured. RESULTS: Eight cadaveric specimens were subjected to the study protocol. In seven of eight specimens, the drill bit trajectory was accurate; it passed from the lateral cortex to the lateral wall of the cochlea without compromise of any critical structures. In one specimen, the access to the middle ear was achieved, but the incus was hit by the drill. The average shortest distance +/- standard deviation from the edge of the drill bit to the boundaries of the facial recess was 0.78 +/- 0.56 mm (chorda tympani), 2.00 +/- 1.06 mm (incus buttress), and 1.27 +/- 0.54 mm (facial nerve). CONCLUSION: Our study demonstrates the ability to obtain percutaneous cochlear access in vitro using customized drill guides manufactured on the basis of preintervention radiographic studies.

Image-guided technique in neurotology.

To date, clinical application of image-guided surgery (IGS) to otology/neurotology has been limited, but a large potential market and numerous applications support use. Such applications include control of surgical instruments (eg, turning off a drill when close to an anatomic boundary), robotic surgery (eg, robotic mastoidectomy), and minimally invasive surgery (eg, percutaneous cochlear implantation).

Safety margins in robotic bone milling: from registration uncertainty to statistically safe surgeries.

BACKGROUND: When robots mill bone near critical structures, safety margins are used to reduce the risk of accidental damage due to inaccurate registration. These margins are typically set heuristically with uniform thickness, which does not reflect the anisotropy and spatial variance of registration error. METHODS: A method is described to generate spatially varying safety margins around vital anatomy using statistical models of registration uncertainty. Numerical simulations are used to determine the margin geometry that matches a safety threshold specified by the surgeon. RESULTS: The algorithm was applied to CT scans of five temporal bones in the context of mastoidectomy, a common bone milling procedure in ear surgery that must approach vital nerves. Safety margins were generated that satisfied the specified safety levels in every case. CONCLUSIONS: Patient safety in image-guided surgery can be increased by incorporating statistical models of registration uncertainty in the generation of safety margins around vital anatomy.

Workflow and simulation of image-to-physical registration of holes inside spongy bone.

PURPOSE: Mastoid cells as well as trabecula provide unique bone structures, which can serve as natural landmarks for registration. Preoperative imaging enables sufficient acquisition of these structures, but registration requires an intraoperative counterpart. Since versatile surgical interventions involve drilling into mastoid cells and trabecula, we propose a registration method based on endoscopy inside of these drill holes. METHODS: Recording of the surface of the inner drill hole yields bone-air patterns that provide intraoperative registration features. In this contribution, we discuss an approach that unrolls the drill hole surface into a two-dimensional image. Intraoperative endoscopic recordings are compared to simulated endoscopic views, which originate from preoperative data like computed tomography. Each simulated view corresponds to a different drill pose. The whole registration procedure and workflow is demonstrated, using high-resolution image data to simulate both preoperative and endoscopic image data. RESULTS: As the driving application is minimally invasive cochlear implantation, in which targets are close to the axis of the drill hole, Target Registration Error (TRE) was measured at points near the axis. TRE at increasing depths along the drill trajectory reveals increasing registration accuracy as more bone-air patterns become available as landmarks with the highest accuracy obtained at the center point. At the facial recess and the cochlea, TREs are ([Formula: see text]) mm and ([Formula: see text]) mm, respectively. CONCLUSION: This contribution demonstrates a new method for registration via endoscopic acquisition of small features like trabecula or mastoid cells for image-guided procedures. It has the potential to revolutionize bone registration because it requires only a preoperative dataset and intraoperative endoscopic exploration. Endoscopic recordings of at least 20 mm length and isotropic voxel sizes of 0.2 mm or smaller of the preoperative image data are recommended.

Increasing Safety of a Robotic System for Inner Ear Surgery Using Probabilistic Error Modeling Near Vital Anatomy.

Safe and effective planning for robotic surgery that involves cutting or ablation of tissue must consider all potential sources of error when determining how close the tool may come to vital anatomy. A pre-operative plan that does not adequately consider potential deviations from ideal system behavior may lead to patient injury. Conversely, a plan that is overly conservative may result in ineffective or incomplete performance of the task. Thus, enforcing simple, uniform-thickness safety margins around vital anatomy is insufficient in the presence of spatially varying, anisotropic error. Prior work has used registration error to determine a variable-thickness safety margin around vital structures that must be approached during mastoidectomy but ultimately preserved. In this paper, these methods are extended to incorporate image distortion and physical robot errors, including kinematic errors and deflections of the robot. These additional sources of error are discussed and stochastic models for a bone-attached robot for otologic surgery are developed. An algorithm for generating appropriate safety margins based on a desired probability of preserving the underlying anatomical structure is presented. Simulations are performed on a CT scan of a cadaver head and safety margins are calculated around several critical structures for planning of a robotic mastoidectomy.

Image-guided surgery: what is the accuracy?

PURPOSE OF REVIEW: Use of image-guided surgery (IGS) systems in otolaryngology, particularly rhinology, has grown exponentially in recent years. Central to their use is the understanding of the accuracy of each system. The purpose of this review is to discuss the error inherent in all IGS systems. A standardized technique (currently used in the engineering literature) for understanding and reporting error in IGS systems is reviewed. Using this technique, the error of commercially available IGS systems is reviewed. RECENT FINDINGS: The most commonly used IGS systems depend on the conformation of the skin, as opposed to relying on bone-implanted devices. For these systems, mean accuracies 2 mm or less are routinely reported. This finding is independent of fiducial markers (eg, proprietary headsets, skin-affixed markers, or laser scanning of skin surfaces). Techniques of fiducial localization and registration of CT scans to intraoperative anatomy are proprietary to each company. As such, there is great variability in reporting system specifications-particularly error of IGS systems. This lack of standardization makes comparison of one system to another difficult if not impossible. SUMMARY: Image-guided surgery systems commonly used in rhinology report mean accuracies of 2 mm or less. Surgeons must be aware that this value represents a mean of a distribution of errors. As such, 95% of the time error can be expected to be less than approximately 1.7 times its mean value. However, outliers (errors much larger and much smaller than the mean) may exist for each IGS intervention. As noted, IGS systems function to complement-not replace-knowledge of surgical anatomy.

In vitro assessment of image-guided otologic surgery: submillimeter accuracy within the region of the temporal bone.

OBJECTIVES: Application of image-guided surgery to otology has been limited by the need for submillimeter accuracy via a fiducial system that is easily usable (noninvasive and nonobstructive). METHODS: A dental bite-block was fitted with a rigid frame with 7 fiducial markers surrounding each external ear. The temporal bones of 3 cadaveric skulls were removed and replaced with surgical targets arranged in a bull's-eye pattern about the centroid of each temporal bone. The surgical targets were identified both within CT scans and in physical space using an infrared optical tracking system. The difference between positions in CT space versus physical space was calculated as target registration error. RESULTS: A total of 234 independent target registration errors were calculated. Mean +/- standard deviation = 0.73 mm +/- 0.25 mm. CONCLUSIONS: These findings show that image-guided otologic surgery with submillimeter accuracy is achievable with a minimally invasive fiducial frame. Significance In vivo validation of the system is ongoing. With such validation, this system may facilitate clinically applicable image-guided otologic surgery. EBM RATING: A.

Minimally invasive, image-guided, facial-recess approach to the middle ear: demonstration of the concept of percutaneous cochlear access in vitro.

HYPOTHESIS: Image-guided surgery will permit accurate access to the middle ear via the facial recess using a single drill hole from the lateral aspect of the mastoid cortex. BACKGROUND: The widespread use of image-guided methods in otologic surgery has been limited by the need for a system that achieves the necessary level of accuracy with an easy-to-use, noninvasive fiducial marker system. We have developed and recently reported such a system (accuracy within the temporal bone = 0.76 +/- 0.23 mm; n = 234 measurements). With this system, image-guided otologic surgery is feasible. METHODS: Skulls (n = 2) were fitted with a dental bite-block affixed fiducial frame and scanned by computed tomography using standard temporal-bone algorithms. The frame was removed and replaced with an infrared emitter used to track the skull during dissection. Tracking was accomplished using an infrared tracker and commercially available software. Using this system in conjunction with a tracked otologic drill, the middle ear was approached via the facial recess using a single drill hole from the lateral aspect of the mastoid cortex. The path of the drill was verified by subsequently performing a traditional temporal bone dissection, preserving the tunnel of bone through which the drill pass had been made. RESULTS: An accurate approach to the middle ear via the facial recess was achieved without violating the canal of the facial nerve, the horizontal semicircular canal, or the external auditory canal. CONCLUSIONS: Image-guided otologic surgery provides access to the cochlea via the facial recess in a minimally invasive, percutaneous fashion. While the present study was confined to in vitro demonstration, these exciting results warrant in vivo testing, which may lead to clinically applicable access.

Incorporating Target Registration Error Into Robotic Bone Milling.

Robots have been shown to be useful in assisting surgeons in a variety of bone drilling and milling procedures. Examples include commercial systems for joint repair or replacement surgeries, with in vitro feasibility recently shown for mastoidectomy. Typically, the robot is guided along a path planned on a CT image that has been registered to the physical anatomy in the operating room, which is in turn registered to the robot. The registrations often take advantage of the high accuracy of fiducial registration, but, because no real-world registration is perfect, the drill guided by the robot will inevitably deviate from its planned path. The extent of the deviation can vary from point to point along the path because of the spatial variation of target registration error. The allowable deviation can also vary spatially based on the necessary safety margin between the drill tip and various nearby anatomical structures along the path. Knowledge of the expected spatial distribution of registration error can be obtained from theoretical models or experimental measurements and used to modify the planned path. The objective of such modifications is to achieve desired probabilities for sparing specified structures. This approach has previously been studied for drilling straight holes but has not yet been generalized to milling procedures, such as mastoidectomy, in which cavities of more general shapes must be created. In this work, we present a general method for altering any path to achieve specified probabilities for any spatial arrangement of structures to be protected. We validate the method via numerical simulations in the context of mastoidectomy.

A Compact, Bone-Attached Robot for Mastoidectomy.

Otologic surgery often involves a mastoidectomy, which is the removal of a portion of the mastoid region of the temporal bone, to safely access the middle and inner ear. The surgery is challenging because many critical structures are embedded within the bone, making them difficult to see and requiring a high level of accuracy with the surgical dissection instrument, a high-speed drill. We propose to automate the mastoidectomy portion of the surgery using a compact, bone-attached robot. The system described in this paper is a milling robot with four degrees-of-freedom (DOF) that is fixed to the patient during surgery using a rigid positioning frame screwed into the surface of the bone. The target volume to be removed is manually identified by the surgeon pre-operatively in a computed tomography (CT) scan and converted to a milling path for the robot. The surgeon attaches the robot to the patient in the operating room and monitors the procedure. Several design considerations are discussed in the paper as well as the proposed surgical workflow. The mean targeting error of the system in free space was measured to be 0.5 mm or less at vital structures. Four mastoidectomies were then performed in cadaveric temporal bones, and the error at the edges of the target volume was measured by registering a postoperative computed tomography (CT) to the pre-operative CT. The mean error along the border of the milled cavity was 0.38 mm, and all critical anatomical structures were preserved.

Phantom validation of coregistration of PET and CT for image-guided radiotherapy.

Radiotherapy treatment planning integrating positron emission tomography (PET) and computerized tomography (CT) is rapidly gaining acceptance in the clinical setting. Although hybrid systems are available, often the planning CT is acquired on a dedicated system separate from the PET scanner. A limiting factor to using PET data becomes the accuracy of the CT/PET registration. In this work, we use phantom and patient validation to demonstrate a general method for assessing the accuracy of CT/PET image registration and apply it to two multi-modality image registration programs. An IAEA (International Atomic Energy Association) brain phantom and an anthropomorphic head phantom were used. Internal volumes and externally mounted fiducial markers were filled with CT contrast and 18F-fluorodeoxyglucose (FDG). CT, PET emission, and PET transmission images were acquired and registered using two different image registration algorithms. CT/PET Fusion (GE Medical Systems, Milwaukee, WI) is commercially available and uses a semi-automated initial step followed by manual adjustment. Automatic Mutual Information-based Registration (AMIR), developed at our institution, is fully automated and exhibits no variation between repeated registrations. Registration was performed using distinct phantom structures; assessment of accuracy was determined from registration of the calculated centroids of a set of fiducial markers. By comparing structure-based registration with fiducial-based registration, target registration error (TRE) was computed at each point in a three-dimensional (3D) grid that spans the image volume. Identical methods were also applied to patient data to assess CT/PET registration accuracy. Accuracy was calculated as the mean with standard deviation of the TRE for every point in the 3D grid. Overall TRE values for the IAEA brain phantom are: CT/PET Fusion = 1.71 +/- 0.62 mm, AMIR = 1.13 +/- 0.53 mm; overall TRE values for the anthropomorphic head phantom are: CT/PET Fusion = 1.66 +/- 0.53 mm, AMIR = 1.15 +/- 0.48 mm. Precision (repeatability by a single user) measured for CT/PET Fusion: IAEA phantom = 1.59 +/- 0.67 mm and anthropomorphic head phantom = 1.63 +/- 0.52 mm. (AMIR has exact precision and so no measurements are necessary.) One sample patient demonstrated the following accuracy results: CT/PET Fusion = 3.89 +/- 1.61 mm, AMIR = 2.86 +/- 0.60 mm. Semi-automatic and automatic image registration methods may be used to facilitate incorporation of PET data into radiotherapy treatment planning in relatively rigid anatomic sites, such as head and neck. The overall accuracies in phantom and patient images are < 2 mm and < 4 mm, respectively, using either registration algorithm. Registration accuracy may decrease, however, as distance from the initial registration points (CT/PET fusion) or center of the image (AMIR) increases. Additional information provided by PET may improve dose coverage to active tumor subregions and hence tumor control. This study shows that the accuracy obtained by image registration with these two methods is well suited for image-guided radiotherapy.

MRI simulator with object-specific field map calculations.

A new MRI simulator has been developed that generates images of realistic objects for arbitrary pulse sequences executed in the presence of static field inhomogeneities, including those due to magnetic susceptibility, variations in the applied field, and chemical shift. In contrast to previous simulators, this system generates object-specific inhomogeneity patterns from first principles and propagates the consequent frequency offsets and intravoxel dephasing through the acquisition protocols to produce images with realistic artifacts. The simulator consists of two parts. The input to part 1 is a set of "susceptibility voxels" that describe the magnetic properties of the object being imaged. It calculates a frequency offset for each voxel by computing the size of the static field offset at each voxel in the image based on the magnetic susceptibility of each tissue type within all voxels. The method of calculation is a three-dimensional convolution of the susceptibility-voxels with a kernel derived from a previously published method and takes advantage of the superposition principle to include voxels with mixtures of substances of differing susceptibilities. Part 2 produces both a signal and a reconstructed image. Its inputs include a voxel-based description of the object, frequency offsets computed by part 1, applied static field errors, chemical shift values, and a description of the imaging protocol. Intravoxel variations in both static field and time-dependent phase are calculated for each voxel. Validations of part 1 are presented for a known analytic solution and for experimental data from two phantoms. Part 2 was validated with comparisons to an independent simulation provided by the Montreal Neurological Institute and experimental data from a phantom.

Characterizing changes in MR images with color-coded Jacobians.

Image registration is the process of establishing spatial correspondence between two images or between two image volumes. Registration can be achieved by rigid, elastic, or a combination of rigid and elastic transforms that attempt to bring the two images into coincidence. A rigid transform accounts for differences in positioning and an elastic transform describes deformations due to differences in tissue properties, temporal changes due to growth or atrophy, or differences between individuals. Deformation-based morphometry uses the resulting deformation fields from these transforms to evaluate differences between the images being registered. Three methods of registration were evaluated: rigid (affine) transformation, elastic optical flow transformation, and elastic spline transformation. All three methods produce vector deformation fields that map each point in one image to a point in the other image. A 12-color map of the transformation Jacobian was used to represent local volume changes. Using the three registration methods, color-mapped Jacobians were determined using a simulated three-dimensional block with known translation, rotation, expansion, contraction, and intensity modulations. Color-coded Jacobians were also generated for experimentally measured magnetic resonance image volumes of water-filled balloons and 7-year-old twin boys. Color-coded Jacobians overlaid on anatomical images provide a convenient method to identify regional tissue expansion and contraction.

Registration of medical images using an interpolated closest point transform: method and validation.

Image registration is an important procedure for medical diagnosis. Since the large inter-site retrospective validation study led by Fitzpatrick at Vanderbilt University, voxel-based methods and more specifically mutual information-based registration methods (see for instance [IEEE Trans. Med. Imag. 22 (8) (2003) 986] for a review on these methods) have been regarded as the method of choice for rigid-body intra-subject registration problems. In this study we propose a method that is based on the Iterative Closest Point algorithm and a pre-computed closest point map obtained with a slight modification of the fast marching method proposed by Sethian. Pre-computing the closest point map speeds up the process because at each iteration point correspondence can be established by table lookup. We also show that because the closest point map is defined on a regular grid it introduces a registration error and we propose an interpolation scheme that addresses this issue. The method has been tested both on synthetic and real images, and registration results have been assessed quantitatively using the data set provided by the Retrospective Registration Evaluation Project. For these volumes, MR and CT head surfaces were extracted automatically using a level-set technique. Results show that on these data sets this registration method leads to accuracy numbers that are comparable to those obtained with voxel-based methods.