A Safe Framework for Quantitative In Vivo Human Evaluation of Image Guidance.

Goal: We present a new framework for in vivo image guidance evaluation and provide a case study on robotic partial nephrectomy. Methods: This framework (called the "bystander protocol") involves two surgeons, one who solely performs the therapeutic process without image guidance, and another who solely periodically collects data to evaluate image guidance. This isolates the evaluation from the therapy, so that in-development image guidance systems can be tested without risk of negatively impacting the standard of care. We provide a case study applying this protocol in clinical cases during robotic partial nephrectomy surgery. Results: The bystander protocol was performed successfully in 6 patient cases. We find average lesion centroid localization error with our IGS system to be 6.5 mm in vivo compared to our prior result of 3.0 mm in phantoms. Conclusions: The bystander protocol is a safe, effective method for testing in-development image guidance systems in human subjects.

Assessment of Orbital Computed Tomography (CT) Imaging Biomarkers in Patients with Thyroid Eye Disease.

To understand potential orbital biomarkers generated from computed tomography (CT) imaging in patients with thyroid eye disease. This is a retrospective cohort study. From a database of an ongoing thyroid eye disease research study at our institution, we identified 85 subjects who had both clinical examination and laboratory records supporting the diagnosis of thyroid eye disease and concurrent imaging prior to any medical or surgical intervention. Patients were excluded if imaging quality or type was not amenable to segmentation. The images of 170 orbits were analyzed with the developed automated segmentation tool. The main outcome measure was to cross 25 CT structural metrics for each eye with nine clinical markers using a Kendall rank correlation test to identify significant relationships. The Kendall rank correlation test between automatically calculated CT metrics and clinical data demonstrated numerous correlations. Extraocular rectus muscle metrics, such as the average diameter of the superior, medial, and lateral rectus muscles, showed a strong correlation (p < 0.05) with loss of visual acuity and presence of ocular motility defects. Hertel measurements demonstrated a strong correlation (p < 0.05) with volumetric measurements of the optic nerve and other orbital metrics such as the crowding index and proptosis. Optic neuropathy was strongly correlated (p < 0.05) with an increase in the maximum diameter of the superior muscle. This novel method of automated imaging metrics may provide objective, rapid clinical information. This data may be useful for appreciation of severity of thyroid eye disease and recognition of risk factors of visual impairment from dysthyroid optic neuropathy from CT imaging.

A novel method for texture-mapping conoscopic surfaces for minimally invasive image-guided kidney surgery.

PURPOSE: Organ-level registration is critical to image-guided therapy in soft tissue. This is especially important in organs such as the kidney which can freely move. We have developed a method for registration that combines three-dimensional locations from a holographic conoscope with an endoscopically obtained textured surface. By combining these data sources clear decisions as to the tissue from which the points arise can be made. METHODS: By localizing the conoscope's laser dot in the endoscopic space, we register the textured surface to the cloud of conoscopic points. This allows the cloud of points to be filtered for only those arising from the kidney surface. Once a valid cloud is obtained we can use standard surface registration techniques to perform the image-space to physical-space registration. Since our methods use two distinct data sources we test for spatial accuracy and characterize temporal effects in phantoms, ex vivo porcine and human kidneys. In addition we use an industrial robot to provide controlled motion and positioning for characterizing temporal effects. RESULTS: Our initial surface acquisitions are hand-held. This means that we take approximately 55 s to acquire a surface. At that rate we see no temporal effects due to acquisition synchronization or probe speed. Our surface registrations were able to find applied targets with submillimeter target registration errors. CONCLUSION: The results showed that the textured surfaces could be reconstructed with submillimetric mean registration errors. While this paper focuses on kidney applications, this method could be applied to any anatomical structures where a line of sight can be created via open or minimally invasive surgical techniques.

Disambiguating the optic nerve from the surrounding cerebrospinal fluid: Application to MS-related atrophy.

PURPOSE: Our goal is to develop an accurate, automated tool to characterize the optic nerve (ON) and cerebrospinal fluid (CSF) to better understand ON changes in disease. METHODS: Multi-atlas segmentation is used to localize the ON and sheath on T2-weighted MRI (0.6 mm(3) resolution). A sum of Gaussian distributions is fit to coronal slice-wise intensities to extract six descriptive parameters, and a regression forest is used to map the model space to radii. The model is validated for consistency using tenfold cross-validation and for accuracy using a high resolution (0.4 mm(2) reconstructed to 0.15 mm(2)) in vivo sequence. We evaluated this model on 6 controls and 6 patients with multiple sclerosis (MS) and a history of optic neuritis. RESULTS: In simulation, the model was found to have an explanatory R-squared for both ON and sheath radii greater than 0.95. The accuracy of the method was within the measurement error on the highest possible in vivo resolution. Comparing healthy controls and patients with MS, significant structural differences were found near the ON head and the chiasm, and structural trends agreed with the literature. CONCLUSION: This is a first demonstration that the ON can be exclusively, quantitatively measured and separated from the surrounding CSF using MRI.

Constructing a statistical atlas of the radii of the optic nerve and cerebrospinal fluid sheath in young healthy adults.

Optic neuritis is a sudden inflammation of the optic nerve (ON) and is marked by pain on eye movement, and visual symptoms such as a decrease in visual acuity, color vision, contrast and visual field defects. The ON is closely linked with multiple sclerosis (MS) and patients have a 50% chance of developing MS within 15 years. Recent advances in multi-atlas segmentation methods have omitted volumetric assessment. In the past, measuring the size of the ON has been done by hand. We utilize a new method of automatically segmenting the ON to measure the radii of both the ON and surrounding cerebrospinal fluid (CSF) sheath to develop a normative distribution of healthy young adults. We examine this distribution for any trends and find that ON and CSF sheath radii do not vary between 20-35 years of age and between sexes. We evaluate how six patients suffering from optic neuropathy compare to this distribution of controls. We find that of these six patients, five of them qualitatively differ from the normative distribution which suggests this technique could be used in the future to distinguish between optic neuritis patients and healthy controls.

Transorbital target localization with augmented ophthalmologic surgical endoscopy.

PURPOSE: Access to the space behind the eyeball is limited by the position of the globe anteriorly, the neurovascular structures embedded in fat posteriorly, and the tight bony confine of the orbit. These anatomical relationships have impeded application of minimally invasive procedures to the region, such as foreign body removal, tumor biopsy, or the administration of medical therapy directly to the optic nerve. An image-guided system was developed using a magnetically tracked flexible endoscope to navigate behind the eye, with the aim of enabling accurate transorbital surgery to user-specified target locations. METHODS: Targets were defined by microspherical bulbs containing water or gadolinium contrast, with differing visible coloring agent. Six living pigs were anesthetized and two microspheres of differing color and contrast content were implanted in the fat tissue of each orbit. Preoperative T1-weighted MRI volumes were obtained and registered intraoperatively. The system capabilities were tested with a series of targeted surgical interventions. The surgeon was required to navigate the endoscope to each lucent microsphere and identify it by color. For three pigs, 3D/2D registration was performed such that the target's image volume coordinates were used to display its location on real-time endoscope video. RESULTS: The ophthalmologic surgeon was able to correctly identify every target by color, with average intervention time of 24.2 min without enhancement and 3.2 min with enhancement. This difference is highly statistically significant [Formula: see text] for reduction in localization time. CONCLUSIONS: Accurate transorbital target localization is possible in-vivo using image-guided transorbital endoscopy, while endoscopic enhancement through the use of video augmentation significantly reduces procedure time.

Image-guided transorbital procedures with endoscopic video augmentation.

PURPOSE: Surgical interventions to the orbital space behind the eyeball are limited to highly invasive procedures due to the confined nature of the region along with the presence of several intricate soft tissue structures. A minimally invasive approach to orbital surgery would enable several therapeutic options, particularly new treatment protocols for optic neuropathies such as glaucoma. The authors have developed an image-guided system for the purpose of navigating a thin flexible endoscope to a specified target region behind the eyeball. Navigation within the orbit is particularly challenging despite its small volume, as the presence of fat tissue occludes the endoscopic visual field while the surgeon must constantly be aware of optic nerve position. This research investigates the impact of endoscopic video augmentation to targeted image-guided navigation in a series of anthropomorphic phantom experiments. METHODS: A group of 16 surgeons performed a target identification task within the orbits of four skull phantoms. The task consisted of identifying the correct target, indicated by the augmented video and the preoperative imaging frames, out of four possibilities. For each skull, one orbital intervention was performed with video augmentation, while the other was done with the standard image guidance technique, in random order. RESULTS: The authors measured a target identification accuracy of 95.3% and 85.9% for the augmented and standard cases, respectively, with statistically significant improvement in procedure time (Z=-2.044, p=0.041) and intraoperator mean procedure time (Z=2.456, p=0.014) when augmentation was used. CONCLUSIONS: Improvements in both target identification accuracy and interventional procedure time suggest that endoscopic video augmentation provides valuable additional orientation and trajectory information in an image-guided procedure. Utilization of video augmentation in transorbital interventions could further minimize complication risk and enhance surgeon comfort and confidence in the procedure.

Robust Optic Nerve Segmentation on Clinically Acquired CT.

The optic nerve is a sensitive central nervous system structure, which plays a critical role in many devastating pathological conditions. Several methods have been proposed in recent years to segment the optic nerve automatically, but progress toward full automation has been limited. Multi-atlas methods have been successful for brain segmentation, but their application to smaller anatomies remains relatively unexplored. Herein we evaluate a framework for robust and fully automated segmentation of the optic nerves, eye globes and muscles. We employ a robust registration procedure for accurate registrations, variable voxel resolution and image field-of-view. We demonstrate the efficacy of an optimal combination of SyN registration and a recently proposed label fusion algorithm (Non-local Spatial STAPLE) that accounts for small-scale errors in registration correspondence. On a dataset containing 30 highly varying computed tomography (CT) images of the human brain, the optimal registration and label fusion pipeline resulted in a median Dice similarity coefficient of 0.77, symmetric mean surface distance error of 0.55 mm, symmetric Hausdorff distance error of 3.33 mm for the optic nerves. Simultaneously, we demonstrate the robustness of the optimal algorithm by segmenting the optic nerve structure in 316 CT scans obtained from 182 subjects from a thyroid eye disease (TED) patient population.

Trans-meningeal drug delivery to optic nerve ganglion cell axons using a nanoparticle drug delivery system.

The purpose of this study was to investigate if neuroprotective drugs can cross the optic nerve sheath in vitro. Four optic nerves were used for this study. Two porcine nerves were harvested at the time of euthanasia and two human nerves were obtained at the time of therapeutic globe enucleation. The optic nerve sheaths were dissected and placed as a membrane in a two chamber diffusion cell to test meningeal penetration by both brimonidine alone and brimonidine encapsulated in nanoparticle (NP-brimonidine). Brimonidine concentration was assayed by UV-vis spectrometer measurement of absorbance at 389 nm. Increasing concentration of brimonidine on the receiver side of the chamber was measured in both the brimonidine alone and the brimonidine encapsulated experiments. The human data were fitted with a two parameter exponential regression analysis (brimonidine alone donor r(2) = 0.87 and receiver r(2) = 0.80, NP-brimonidine donor r(2) = 0.79 and receiver r(2) = 0.84). Time constant (τ) was 10.2 h (donor) and 13.1 h (receiver) in the brimonidine study, and 24.0 h (donor) and 15.9 h (receiver) in the NP-brimonidine study. Encapsulated brimonidine had a longer time to reach equilibrium. Passage of brimonidine through the optic nerve sheath was demonstrated in the experiments. Increase in time constants when comparing the NP-brimonidine with the brimonidine curves in the human studiesindicates that diffusion is delayed by the initial parameter of drug being loaded in NP. Direct treatment of injured optic nerve axons may be possible by trans-meningeal drug diffusion.

Robust optic nerve segmentation on clinically acquired computed tomography.

The optic nerve (ON) plays a critical role in many devastating pathological conditions. Segmentation of the ON has the ability to provide understanding of anatomical development and progression of diseases of the ON. Recently, methods have been proposed to segment the ON but progress toward full automation has been limited. We optimize registration and fusion methods for a new multi-atlas framework for automated segmentation of the ONs, eye globes, and muscles on clinically acquired computed tomography (CT) data. Briefly, the multi-atlas approach consists of determining a region of interest within each scan using affine registration, followed by nonrigid registration on reduced field of view atlases, and performing statistical fusion on the results. We evaluate the robustness of the approach by segmenting the ON structure in 501 clinically acquired CT scan volumes obtained from 183 subjects from a thyroid eye disease patient population. A subset of 30 scan volumes was manually labeled to assess accuracy and guide method choice. Of the 18 compared methods, the ANTS Symmetric Normalization registration and nonlocal spatial simultaneous truth and performance level estimation statistical fusion resulted in the best overall performance, resulting in a median Dice similarity coefficient of 0.77, which is comparable with inter-rater (human) reproducibility at 0.73.

A new paradigm for treatment of glaucoma.

Glaucoma is the leading irreversible cause of blindness in the world. We are developing a new image-guidance system to deliver a neuroprotective drug in a controlled release nanosponge. The system consists of a magnetically tracked image-guidance system, the nanosponge material and the drug. We have characterized the performance of each aspect in phantoms, animals and ex-vivo human tissue.

Robust Non-Local Multi-Atlas Segmentation of the Optic Nerve.

Labeling or segmentation of structures of interest on medical images plays an essential role in both clinical and scientific understanding of the biological etiology, progression, and recurrence of pathological disorders. Here, we focus on the optic nerve, a structure that plays a critical role in many devastating pathological conditions - including glaucoma, ischemic neuropathy, optic neuritis and multiple-sclerosis. Ideally, existing fully automated procedures would result in accurate and robust segmentation of the optic nerve anatomy. However, current segmentation procedures often require manual intervention due to anatomical and imaging variability. Herein, we propose a framework for robust and fully-automated segmentation of the optic nerve anatomy. First, we provide a robust registration procedure that results in consistent registrations, despite highly varying data in terms of voxel resolution and image field-of-view. Additionally, we demonstrate the efficacy of a recently proposed non-local label fusion algorithm that accounts for small scale errors in registration correspondence. On a dataset consisting of 31 highly varying computed tomography (CT) images of the human brain, we demonstrate that the proposed framework consistently results in accurate segmentations. In particular, we show (1) that the proposed registration procedure results in robust registrations of the optic nerve anatomy, and (2) that the non-local statistical fusion algorithm significantly outperforms several of the state-of-the-art label fusion algorithms.

Image-guided robotic surgery: update on research and potential applications in urologic surgery.

PURPOSE OF REVIEW: New methods of imaging and image-guidance technology have the potential to provide surgeons with spatially accurate three-dimensional information about the location and anatomical relationships of critical subsurface structures and instrument position updated and displayed during the performance of surgery. Robotic platforms and technology in various forms continues to revolutionize surgery and will soon incorporate image guidance. RECENT RESEARCH: Image-guided surgery (IGS) for abdominal and urologic interventions presents complex engineering and surgical challenges along with potential benefits to surgeons and patients. Key concepts such as registration, localization, accuracy, and targeting error are necessary for surgeons to understand and utilize the potential of IGS. Standard robotic surgeries, such as partial nephrectomy and radical prostatectomy may soon incorporate IGS. SUMMARY: Research continues to explore the potential for combining image guidance and robotics to augment and improve a variety of surgical interventions.

Image-Guided Abdominal Surgery and Therapy Delivery.

Image-Guided Surgery has become the standard of care in intracranial neurosurgery providing more exact resections while minimizing damage to healthy tissue. Moving that process to abdominal organs presents additional challenges in the form of image segmentation, image to physical space registration, organ motion and deformation. In this paper, we present methodologies and results for addressing these challenges in two specific organs: the liver and the kidney.

Comparison and assessment of semi-automatic image segmentation in computed tomography scans for image-guided kidney surgery.

PURPOSE: Image segmentation is integral to implementing intraoperative guidance for kidney tumor resection. Results seen in computed tomography (CT) data are affected by target organ physiology as well as by the segmentation algorithm used. This work studies variables involved in using level set methods found in the Insight Toolkit to segment kidneys from CT scans and applies the results to an image guidance setting. METHODS: A composite algorithm drawing on the strengths of multiple level set approaches was built using the Insight Toolkit. This algorithm requires image contrast state and seed points to be identified as input, and functions independently thereafter, selecting and altering method and variable choice as needed. RESULTS: Semi-automatic results were compared to expert hand segmentation results directly and by the use of the resultant surfaces for registration of intraoperative data. Direct comparison using the Dice metric showed average agreement of 0.93 between semi-automatic and hand segmentation results. Use of the segmented surfaces in closest point registration of intraoperative laser range scan data yielded average closest point distances of approximately 1 mm. Application of both inverse registration transforms from the previous step to all hand segmented image space points revealed that the distance variability introduced by registering to the semi-automatically segmented surface versus the hand segmented surface was typically less than 3 mm both near the tumor target and at distal points, including subsurface points. CONCLUSIONS: Use of the algorithm shortened user interaction time and provided results which were comparable to the gold standard of hand segmentation. Further, the use of the algorithm's resultant surfaces in image registration provided comparable transformations to surfaces produced by hand segmentation. These data support the applicability and utility of such an algorithm as part of an image guidance workflow.

Organ surface deformation measurement and analysis in open hepatic surgery: method and preliminary results from 12 clinical cases.

The incidence of soft tissue deformation has been well documented in neurosurgical procedures and is known to compromise the spatial accuracy of image-guided surgery systems.Within the context of image-guided liver surgery (IGLS), no detailed method to study and analyze the observed organ shape change between preoperative imaging and the intra-operative presentation has been developed. Contrary to the studies of deformation in neurosurgical procedures, the majority of deformation in IGLS is imposed prior to resection and due to laparotomy and mobilization. As such, methods of analyzing the organ shape change must be developed to use the intra-operative data (e.g. laser range scan (LRS) surfaces) acquired with the organ in its fully deformed shape. To achieve this end we use a signed closest point distance deformation metric computed after rigid alignment of the intra-operative LRS data with organ surfaces generated from the preoperative tomograms. The rigid alignment between the intra-operative LRS surfaces and pre-operative image data was computed with a feature weighted surface registration algorithm. In order to compare the deformation metrics across patients, an inter-patient non-rigid registration of the pre-operative CT images was performed. Given the inter-patient liver registrations, an analysis was performed to determine the potential similarities in the distribution of measured deformation between patients for which similar procedures had been performed. The results of the deformation measurement and analysis indicates the potential for soft tissue deformation to compromise surgical guidance information and suggests a similarity in imposed deformation among similar procedure types.

Kidney deformation and intraprocedural registration: a study of elements of image-guided kidney surgery.

INTRODUCTION: Central to any image-guided surgical procedure is the alignment of image and physical coordinate spaces, or registration. We explored the task of registration in the kidney through in vivo and ex vivo porcine animal models and a human study of minimally invasive kidney surgery. METHODS: A set of (n = 6) ex vivo porcine kidney models was utilized to study the effect of perfusion and loss of turgor caused by incision. Computed tomography (CT) and laser range scanner localizations of the porcine kidneys were performed before and after renal vessel clamping and after capsular incision. The da Vinci robotic surgery system was used for kidney surface acquisition and registration during robot-assisted laparoscopic partial nephrectomy. The surgeon acquired the physical surface data points with a tracked robotic instrument. These data points were aligned to preoperative CT for surface-based registrations. In addition, two biomechanical elastic computer models (isotropic and anisotropic) were constructed to simulate deformations in one of the kidneys to assess predictive capabilities. RESULTS: The mean displacement at the surface fiducials (glass beads) in six porcine kidneys was 4.4 ± 2.1 mm (range 3.4-6.7 mm), with a maximum displacement range of 6.1 to 11.2 mm. Surface-based registrations using the da Vinci robotic instrument in robot-assisted laparoscopic partial nephrectomy yielded mean and standard deviation closest point distances of 1.4 and 1.1 mm. With respect to computer model predictive capability, the target registration error was on average 6.7 mm without using the model and 3.2 mm with using the model. The maximum target error reduced from 11.4 to 6.2 mm. The anisotropic biomechanical model yielded better performance but was not statistically better. CONCLUSIONS: An initial point-based alignment followed by an iterative closest point registration is a feasible method of registering preoperative image (CT) space to intraoperative physical (robot) space. Although rigid registration provides utility for image-guidance, local deformations in regions of resection may be more significant. Computer models may be useful for prediction of such deformations, but more investigation is needed to establish the necessity of such compensation.

Towards image guided robotic surgery: multi-arm tracking through hybrid localization.

OBJECTIVE: Use of the robotic assisted surgery has been increasing in recent years, due both the continuous increase in the number of applications and the clinical benefits that surgical robots can provide. Currently robotic assisted surgery relies on endoscopic video for navigation, providing only surface visualization, thus limiting subsurface vision. To be able to visualize and identify subsurface information, techniques in image-guidance can be used. As part of designing an image guidance system, all arms of the robot need to be co-localized in a common coordinate system. METHODS: In order to track multiple arms in a common coordinate space, intrinsic and extrinsic tracking methods can be used. First, the intrinsic tracking of the daVinci, specifically of the setup joints is analyzed. Because of the inadequacy of the setup joints for co-localization a hybrid tracking method is designed and implemented to mitigate the inaccuracy of the setup joints. Different both optical and magnetic tracking methods are examined for setup joint localization. RESULTS: The hybrid localization method improved the localization accuracy of the setup joints. The inter-arm accuracy in hybrid localization was improved to 3.02 mm. This inter-arm error value was shown to be further reduced when the arms are co-registered, thus reducing common error.

Optimizing electrode placement using finite-element models in radiofrequency ablation treatment planning.

Conventional radiofrequency ablation (RFA) planning methods for identifying suitable electrode placements typically use geometric shapes to model ablation outcomes. A method is presented for searching electrode placements that couples finite-element models (FEMs) of RFA together with a novel optimization strategy. The method was designed to reduce the need for model solutions per local search step. The optimization strategy was tested against scenarios requiring single and multiple ablations. In particular, for a scenario requiring multiple ablations, a domain decomposition strategy was described to minimize the complexity of simultaneously searching multiple electrode placements. The effects of nearby vasculature on optimal electrode placement were also studied. Compared with geometric planning approaches, FEMs could potentially deliver electrode placement plans that provide more physically meaningful predictions of therapeutic outcomes.

Determining the presence of bias error using statistical methods.

Current techniques in image-guided surgery rely on the use of localizers for the measurement of position in physical space. These measurements are prone to error due to intrinsic properties of the localizer used. The error and thus accuracy of a localizer can be determined using various techniques, many of which assume that the error is isotropic and free of bias. A bias error adds an orientation dependence to the error of measured points. Determination of the presence of a bias error is an important component in the characterization of a localizer's performance. Statistical analysis of localized points on a rigid phantom can be used to detect the presence of a bias error. In this paper, we will examine the use of statistical techniques in the characterization of a series of localizers and how that information is useful in determining localizer efficacy.