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Objective Optimal atrial septal defect (ASD) closure should combine off-pump techniques with the effectiveness and versatility of open-heart techniques. We report our experience with off-pump ASD closure using the Universal Cardiac Introducer (UCI) in a porcine model. The goal was to create an ASD over the fossa ovale (FO) and position a patch over the ASD under ultrasound (US) imaging and augmented virtual reality guidance. Methods An US probe (tracked with a magnetic tracking system) was positioned into the esophagus (transesophageal echocardiographic probe) for real-time image-guidance. The right atrium (RA) of six pigs was exposed via a right lateral thoracotomy or medial sternotomy. The UCI was attached to the RA wall. A punching tool was introduced via the UCI, navigated and positioned, under US guidance, to create an ASD into the FO. A patch with its holder and a stapling device were introduced into the RA via the UCI. The patch was positioned on the ASD. Occlusion of the ASD was determined using US and Doppler imaging. Results The FO membrane was excised successfully in all animals. US image-guidance provided excellent visualization. The patch was positioned in all cases with complete occlusion of the ASD. The stapling device proved too bulky, impeding circumferential positioning. Conclusions Using the UCI, ASD closure was safe and feasible. US imaging, combined with virtual and augmented reality provided accurate navigating and positioning. This study also provided valuable information on the future design of anchoring devices for intracardiac procedures.

Error models associated with point-based medical image registration problems were first introduced in the late 1990s. The concepts of fiducial localizer error, fiducial registration error, and target registration error are commonly used in the literature. The model for estimating the target registration error at a position r in a coordinate frame defined by a set of fiducial markers rigidly fixed relative to one another is ubiquitous in the medical imaging literature. The model has also been extended to simulate the target registration error at the point of interest in optically tracked tools. However, the model is limited to describing the error in situations where the fiducial localizer error is assumed to have an isotropic normal distribution in R3. In this work, the model is generalized to include a fiducial localizer error that has an anisotropic normal distribution. Similar to the previous models, the root mean square statistic rmstre is provided along with an extension that provides the covariance matrix Sigmatre. The new model is verified using a Monte Carlo simulation and a set of statistical hypothesis tests. Finally, the differences between the two assumptions, isotropic and anisotropic, are discussed within the context of their use in 1) optical tool tracking simulation and 2) image registration.

In image-guided interventions, anatomical models of organs are often generated from pre-operative images and further employed in planning and guiding therapeutic procedures. However, the accuracy of these models, along with their registration to the subject are crucial for successful therapy delivery. These factors are amplified when manipulating soft tissue undergoing large deformations, such as the heart. When used in guiding beating-heart procedures, pre-operative models may not be sufficient for guidance and they are often complemented with real-time, intra-operative cardiac imaging. Here we demonstrate via in vitro endocardial "therapy" that ultrasound-enhanced model-guided navigation provides sufficient guidance to preserve a clinically-desired targeting accuracy of under 3 mm independently of the model-to-subject misregistrations. These results emphasize the direct benefit of integrating real-time imaging within intra-operative visualization environments considering that model-to-subject misalignments are often encountered clinically.

Peripheral nerve block treatments are ubiquitous in hospitals and pain clinics worldwide. State of the art techniques use ultrasound (US) guidance and/or electrical stimulation to verify needle tip location. However, problems such as needle-US beam alignment, poor echogenicity of block needles and US beam thickness can make it difficult for the anesthetist to know the exact needle tip location. Inaccurate therapy delivery raises obvious safety and efficacy issues. We have developed and evaluated a needle guidance system that makes use of a magnetic tracking system (MTS) to provide an augmented reality (AR) guidance platform to accurately localize the needle tip as well as its projected trajectory. Five anesthetists and five novices performed simulated nerve block deliveries in a polyvinyl alcohol phantom to compare needle guidance under US alone to US placed in our AR environment. Our phantom study demonstrated a decrease in targeting attempts, decrease in contacting of critical structures, and an increase in accuracy of 0.68 mm compared to 1.34mm RMS in US guidance alone. Currently, the MTS uses 18 and 21 gauge hypodermic needles with a 5 degree of freedom sensor located at the needle tip. These needles can only be sterilized using an ethylene oxide process. In the interest of providing clinicians with a simple and efficient guidance system, we also evaluated attaching the sensor at the needle hub as a simple clip-on device. To do this, we simultaneously performed a needle bending study to assess the reliability of a hub-based sensor.

Trans-esophageal echocardiography (TEE) is a standard component of patient monitoring during most cardiac surgeries. In recent years magnetic tracking systems (MTS) have become sufficiently robust to function effectively in appropriately structured operating room environments. The ability to track a conventional multiplanar 2D TEE transducer in 3D space offers incredible potential by greatly expanding the cumulative field of view of cardiac anatomy beyond the limited field of view provided by 2D and 3D TEE technology. However, there is currently no TEE probe manufactured with MTS technology embedded in the transducer, which means sensors must be attached to the outer surface of the TEE. This leads to potential safety issues for patients, as well as potential damage to the sensor during procedures. This paper presents a standard 2D TEE probe fully integrated with MTS technology. The system is evaluated in an environment free of magnetic and electromagnetic disturbances, as well as a clinical operating room in the presence of a da Vinci robotic system. Our first integrated TEE device is currently being used in animal studies for virtual reality-enhanced ultrasound guidance of intracardiac surgeries, while the "second generation" TEE is in use in a clinical operating room as part of a project to measure perioperative heart shift and optimal port placement for robotic cardiac surgery. We demonstrate excellent system accuracy for both applications.

Image-guided surgery systems have a wide range of applications where the level of accuracy required for each application varies from millimeters to low sub-millimeter range. In systems that use optical tracking, it is typical to use point-based registration without any weighting schemes to determine the pose of the tracked tool with very good accuracy. However, recent advancements in methods to estimate the measurement uncertainty for each tracked marker and the development of an anisotropically weighted point-based registration algorithm have allowed for the optical tracking accuracy to be improved. In this article, we demonstrate a new tracking method that improves the tracking accuracy by 20 – 45% over the traditional tracking methodology.

Target registration error (TRE) has become a widely accepted error metric in point-based registration since the error metric was introduced in the 1990s. It is particularly prominent in image-guided surgery (IGS) applications where point-based registration is used in both image registration and optical tracking. In point-based registration, the TRE is a function of the fiducial marker geometry, location of the target and the fiducial localizer error (FLE). While the first two items are easily obtained, the FLE is usually estimated using an a priori technique and applied without any knowledge of real-time information. However, if the FLE can be estimated in real-time, particularly as it pertains to optical tracking, then the TRE can be estimated more robustly. In this paper, a method is presented where the FLE statistics are estimated from the latest measurement of the fiducial registration error (FRE) statistics. The solution is obtained by solving a linear system of equations of the form Ax=b for each marker at each time frame where x are the six independent FLE covariance parameters and b are the six independent estimated FRE covariance parameters. The A matrix is only a function of the tool geometry and hence the inverse of the matrix can be computed a priori and used at each instant in which the FLE estimation is required, hence minimizing the level of computation at each frame. When using a good estimate of the FRE statistics, Monte Carlo simulations demonstrate that the root mean square of the FLE can be computed within a range of 70-90 microm. Robust estimation of the TRE for an optically tracked tool, using a good estimate of the FLE, will provide two enhancements in IGS. First, better patient to image registration will be obtained by using the TRE of the optical tool as a weighting factor of point-based registration used to map the patient to image space. Second, the directionality of the TRE can be relayed back to the surgeon giving the surgeon the option of changing their strategy in order to improve the overall system accuracy and, in turn, the quality of procedure.

Ultrasound is garnering significant interest as an imaging modality for surgical guidance, due to its affordability, real-time temporal resolution and ease of integration into the operating room. Minimally-invasive intracardiac surgery performed on the beating-heart prevents direct vision of the surgical target, and procedures such as mitral valve replacement and atrial septal defect closure would benefit from intraoperative ultrasound imaging. We propose that placing 4D ultrasound within an augmented reality environment, along with a patient-specific cardiac model and virtual representations of tracked surgical tools, will create a visually intuitive platform with sufficient image information to safely and accurately repair tissue within the beating heart. However, the quality of the imaging parameters, spatial calibration, temporal calibration and ECG-gating must be well characterized before any 4D ultrasound system can be used clinically to guide the treatment of moving structures. In this paper, we describe a comprehensive accuracy assessment framework that can be used to evaluate the performance of 4D ultrasound systems while imaging moving targets. We image a dynamic phantom that is comprised of a simple robot and a tracked phantom to which point-source, distance and spherical objects of known construction can be attached. We also follow our protocol to evaluate 4D ultrasound images generated in real-time by reconstructing ECG-gated 2D ultrasound images acquired from a tracked multiplanar transesophageal probe. Likewise, our evaluation framework allows any type of 4D ultrasound to be quantitatively assessed.

Catheter-driven cardiac interventions have emerged in response to the need of reducing invasiveness associated with the traditional cut-and-sew techniques. Catheter manipulation is traditionally performed under real-time fluoroscopy imaging, resulting in an overall trade-off of procedure invasiveness for radiation exposure of both the patient and clinical staff. Our approach to reducing and potentially eliminating the use of flouroscopy in the operating room entails the use of multi-modality imaging and magnetic tracking technologies, wrapped together into an augmented reality environment for enhanced intra-procedure visualization and guidance. Here we performed an in vitro study in which a catheter was guided to specific targets located on the endocardial atrial surface of a beating heart phantom. "Therapy delivery" was modeled in the context of a blinded procedure, mimicking a beating heart, intracardiac intervention. The users navigated the tip of a magnetically tracked Freezor 5 CRYOCATH catheter to the specified targets. Procedure accuracy was determined as the distance between the tracked catheter tip and the tracked surgical target at the time of contact, and it was assessed under three different guidance modalities: endoscopic, augmented reality, and ultrasound image guidance. The overall RMS targeting accuracy achieved under augmented reality guidance averaged to 1.1 mm. This guidance modality shows significant improvements in both procedure accuracy and duration over ultrasound image guidance alone, while maintianing an overall targeting accuracy comparable to that achieved under endoscopic guidance.

In image-guide surgery, optimizing the accuracy in localizing the surgical tools within the virtual reality environment or 3D image is vitally important, significant effort has been spent reducing the measurement errors at the point of interest or target. This target registration error (TRE) is often defined by a root-mean-square statistic which reduces the vector data to a single term that can be minimized. However, lost in the data reduction is the directionality of the error which, can be modelled using a 3D covariance matrix. Recently, we developed a set of expressions that modeled the TRE statistics for point-based registrations as a function of the fiducial marker geometry, target location and the fiducial localizer error (FLE). Unfortunately, these expressions are only as good as the definition of the FLE. In order to close the gap, we have subsequently developed a closed form expression that estimates the FLE as a function of the estimated fiducial registration error (FRE, the error between the measured fiducials and the best fit locations of those fiducials). The FRE covariance matrix is estimated using a sliding window technique and used as input into the closed form expression to estimate the FLE. The estimated FLE can then used to estimate the TRE which, can be given to the surgeon to permit the procedure to be designed such that the errors associated with the point-based registrations are minimized.

In image-guided interventions, anatomical models of organs are often generated from pre-operative images and further employed in planning and guiding therapeutic procedures. However, the accuracy of these models, along with their registration to the subject are crucial for successful therapy delivery. These factors are amplified when manipulating soft tissue undergoing large deformations, such as the heart. When used in guiding beating-heart procedures, pre-operative models may not be sufficient for guidance and they are often complemented with real-time, intra-operative cardiac imaging. Here we demonstrate via in vitro endocardial "therapy" that ultrasound-enhanced model-guided navigation provides sufficient guidance to preserve a clinically-desired targeting accuracy of under 3 mm independently of the model-to-subject misregistrations. These results emphasize the direct benefit of integrating real-time imaging within intra-operative visualization environments considering that model-to-subject misalignments are often encountered clinically.

Minimally invasive beating heart intracardiac surgery is an area of research with many unique challenges. Surgical targets are in constant motion in a blood-filled environment that prevents direct line-of-sight guidance. The restrictive workspace requires compact, yet robust tools for proper therapy delivery. Our novel method for approaching multiple targets inside the beating heart allows their identification and access under augmented reality-assisted image guidance. The surgical platform integrates real-time ultrasound imaging with virtual models of the surgical instruments, along with virtual cardiac anatomy acquired from pre-operative images. Extensive in vitro studies were performed to assess the operator's ability to "deliver therapy" to dynamic intracardiac targets via both transmural and transluminal access, and demonstrated significantly more accurate targeting under augmented reality guidance compared to ultrasound image guidance alone, accompanied by a reduction of procedure time by half. Moreover, preliminary in vivo acute studies on porcine models showed successful prosthesis positioning for beating-heart septal defect repair and mitral valve implantation via direct surgical access. While still in its infancy, this work emphasizes the promise of ultrasound-enhanced model-guided environments for minimally-invasive cardiac therapy, whether delivered via a catheter introduced into the vascular system or a cannula inserted through the heart wall.

Anesthetic nerve blocks are a common therapy performed in hospitals around the world to alleviate acute and chronic pain. Tracking systems have shown considerable promise in other forms of therapy, but little has been done to apply this technology in the field of anesthesia. We are developing a guidance system for combining tracked needles with non-invasive ultrasound (US) and patient-specific geometric models. In experiments with phantoms two augmented reality (AR) guidance systems were compared to the exclusive use of US for lumbar facet injection therapy. Anesthetists and anesthesia residents were able to place needles within 0.57mm of the intended targets using our AR systems compared to 5.77 mm using US alone. A preliminary cadaver study demonstrated the system was able to accurately place radio opaque dye on targets. The combination of real time US with tracked tools and AR guidance has the potential to replace CT and fluoroscopic guidance, thus reducing radiation dose to patients and clinicians, as well as reducing health care costs.

In the context of our ongoing objective to reduce morbidity associated with cardiac interventions, minimizing invasiveness has inevitably led to more limited visual access to the target tissues. To ameliorate these challenges, we provide the surgeons with a complex visualization environment that integrates interventional ultrasound imaging augmented with pre-operative anatomical models and virtual surgical instruments within a virtual reality environment. In this paper we present an in vitro study on a cardiac phantom aimed at assessing the feasibility and targeting accuracy of our surgical system in comparison to traditional ultrasound imaging for intra-operative surgical guidance. The 'therapy delivery' was modeled in the context of a blinded procedure, mimicking a closed-chest intervention. Four users navigated a tracked pointer to a target, under guidance provide by either US imaging or virtual reality-enhanced ultrasound. A 2.8 mm RMS targeting error was achieved using our novel surgical system, which is adequate from both a clinical and engineering perspective, under the inherent procedure requirements and limitations of the system.

A 2D ultrasound enhanced virtual reality surgical guidance system has been under development for some time in our lab. The new surgical guidance platform has been shown to be effective in both the laboratory and clinical settings, however, the accuracy of the tracked 2D ultrasound has not been investigated in detail in terms of the applications for which we intend to use it (i.e., mitral valve replacement and atrial septal defect closure). This work focuses on the development of an accuracy assessment protocol specific to the assessment of the calibration methods used to determine the rigid transformation between the ultrasound image and the tracked sensor. Specifically, we test a Z-bar phantom calibration method and a phantomless calibration method and compared the accuracy of tracking ultrasound images from neuro, transesophageal, intracardiac and laparoscopic ultrasound transducers. This work provides a fundamental quantitative description of the image-guided accuracy that can be obtained with this new surgical guidance system.

As part of an ongoing theme in our laboratory on reducing morbidity during minimally-invasive intracardiacprocedures, we developed a computer-assisted interventi on system that provides safe access inside the beatingheart and sucient visualization to deliver therapy to intracardiac targets while maintaining the ecacy of theprocedure. Integrating pre-operative information, 2D trans-esophageal ultrasound for real-time intra-operativeimaging, and surgical tool tracking using the NDI Aurora TM magnetic tracking system in an augmented virtualenvironment, our system allows the surgeons to navigate instruments inside the heart in spite of the lack ofdirect target visualization. This work focuses on further enhancing intracardiac visualization and navigation bysupplying the surgeons with detailed 3D dynamic cardiac models constructed from high-resolution pre-operativeMR data and overlaid onto the intra-operative imaging environment. Here we report our experience during an invivo porcine study. A feature-based registration technique previously explored and validated in our laboratorywas employed for the pre-operative to intra-operative mapping. This registration method is suitable for invivo interventional applications as it involves the selection of easily identi“able landmarks, while ensuring a goodalignment of the pre-operative and intra-operative surgical targets. The resulting augmented reality environmentfuses the pre-operative cardiac model with the intra-operative real-time US images with approximately 5 mmaccuracy for structures located in the vicinity of the valvular region. Therefore, we strongly believe that ouraugmented virtual environment signi“cantly enhances intracardiac navigation of surgical instruments, while on-target detailed manipulations are performed under real-time US guidance.Keywords: Image-Guided Cardiac Procedures, Pre-operative Modeling, Intra-operative Imaging, AugmentedVirtual Reality, Data Integration for the Clinic/OR.

Cardiopulmonary bypass surgery, although a highly invasive interventional approach leading to numerous complications, is still the most common therapy option for treating many forms of cardiac disease. We are currently engaged in a project designed to replace many bypass surgeries with less traumatic, minimally invasive intracardiac therapies. This project combines real-time intra-operative echocardiography with a virtual reality environment providing the surgeon with a broad range of valuable information. Pre-operative images, electrophysiological data, positions of magnetically tracked surgical instruments, and dynamic surgical target representations are among the data that can be presented to the surgeon to augment intra-operative ultrasound images. This augmented reality system is applicable to procedures such as mitral valve replacement and atrial septal defect repair, as well as ablation therapies for treatment of atrial fibrillation. Our goal is to develop a robust augmented reality system that will improve the efficacy of intracardiac treatments and broaden the range of cardiac surgeries that can be performed in a minimally invasive manner. This paper provides an overview of our interventional system and specific experiments that assess its pre-clinical performance.

Target registration error (TRE) refers to the uncertainty in localizing a point of interest after a point-based registration is performed. Common in medical image registration, the metric is typically represented as a root-mean-square statistic. In the late 1990s, a statistical model was developed based on the rigid body definition of the fiducial markers and the localization error associated in measuring the fiducials. The statistical model assumed that the fiducial localizer error was isotropic, but recently the model was reworked to handle anisotropic fiducial localizer error (FLE). In image guided surgery, the statistical model is used to predict the surgical tool tip tracking accuracy associated with optical spatial measurement systems for which anisotropic FLE models are required. However, optical tracking systems often track the surgical tools relative to a patient based reference tool. Here the formulation for modeling the TRE of a surgical probe relative to a reference frame is developed mathematically and evaluated using a Monte Carlo simulation. The effectiveness of the statistical model is directly related to the FLE model, the fiducial marker design and the distance from centroid to target.

Target registration error (TRE) refers to the uncertainty in localizing a point of interest after a point-based registration is performed. Common in medical image registration, the metric is typically represented as a root-mean-square statistic. In the late 1990s, a statistical model was developed based on the rigid body definition of the fiducial markers and the localization error associated in measuring the fiducials. The statistical model assumed that the fiducial localizer error was isotropic, but recently the model was reworked to handle anisotropic fiducial localizer error (FLE). In image guided surgery, the statistical model is used to predict the surgical tool tip tracking accuracy associated with optical spatial measurement systems for which anisotropic FLE models are required. However, optical tracking systems often track the surgical tools relative to a patient based reference tool. Here the formulation for modeling the TRE of a surgical probe relative to a reference frame is developed mathematically and evaluated using a Monte Carlo simulation. The effectiveness of the statistical model is directly related to the FLE model, the fiducial marker design and the distance from centroid to target.

Minimally invasive techniques for use inside the beating heart, such as mitral valve replacement and septal defect repair, are the focus of this work. Traditional techniques for these procedures require an open chest approach and a cardiopulmonary bypass machine. New techniques using port access and a combined surgical guidance tool that includes an overlaid two-dimensional ultrasound image in a virtual reality environment are being developed. To test this technique, a cardiac phantom was developed to simulate the anatomy. The phantom consists of an acrylic box filled with a 7% glycerol solution with ultrasound properties similar to human tissue. Plate inserts mounted in the box simulate the physical anatomy. An accuracy assessment was completed to evaluate the performance of the system. Using the cardiac phantom, a 2mm diameter glass toroid was attached to a vertical plate as the target location. An elastic material was placed between the target and plate to simulate the target lying on a soft tissue structure. The target was measured using an independent measurement system and was represented as a sphere in the virtual reality system. The goal was to test the ability of a user to probe the target using three guidance methods: (i) 2D ultrasound only, (ii) virtual reality only and (iii) ultrasound enhanced virtual reality. Three users attempted the task three times each for each method. An independent measurement system was used to validate the measurement. The ultrasound imaging alone was poor in locating the target (5.42 mm RMS) while the other methods proved to be significantly better (1.02 mm RMS and 1.47 mm RMS respectively). The ultrasound enhancement is expected to be more useful in a dynamic environment where the system registration may be disturbed.

Clinical research has been rapidly evolving towards the development of less invasive surgical procedures. We recently embarked on a project to improve intracardiac beating heart interventions. Our novel approach employs new surgical technologies and support from image-guidance via pre-operative and intra-operative imaging (i.e. two-dimensional echocardiography) to substitute for direct vision. Our goal was to develop a versatile system that allowed for safe cardiac port access, and provide sufficient image-guidance with the aid of a virtual reality environment to substitute for the absence of direct vision, while delivering quality therapy to the target. Specific targets included the repair and replacement of heart valves and the repair of septal defects. The ultimate objective was to duplicate the success rate of conventional open-heart surgery, but to do so via a small incision, and to evaluate the efficacy of the procedure as it is performed. This paper describes the software and hardware components, along with the methodology for performing mitral valve replacement as one example of this approach, using ultrasound and virtual tool models to position and fasten the valve in place.

Highly accurate spatial measurement systems are among the enabling technologies that have made image-guided surgery possible in modern operating theaters. Assessing the accuracies of such systems is subject to much ambiguity, though. The underlying mathematical models that convert raw sensor data into position and orientation measurements of sufficient accuracy complicate matters by providing measurements having non-uniform error distributions throughout their measurement volumes. Users are typically unaware of these issues, as they are usually presented with only a few specifications based on some "representative" statistics that were themselves derived using various data reduction methods. As a result, much of the important underlying information is lost. Further, manufacturers of spatial measurement systems often choose protocols and statistical measures that emphasize the strengths of their systems and diminish their limitations. Such protocols often do not reflect the end users' intended applications very well. Users and integrators thus need to understand many aspects of spatial metrology in choosing spatial measurement systems that are appropriate for their intended applications. We examine the issues by discussing some of the protocols and their statistical measures typically used by manufacturers. The statistical measures for a given protocol can be affected by many factors, including the volume size, region of interest, and the amount and type of data collected. We also discuss how different system configurations can affect the accuracy. Single-marker and rigid body calibration results are presented, along with a discussion of some of the various factors that affect their accuracy. Although the findings presented here were obtained using the NDI Polaris optical tracking systems, many are applicable to spatial measurement systems in general.

Manufacturers of 3D tracking systems use a wide variety of statistical measures, assessment protocols and measurement volumes when stating their systems’ accuracies. These factors typically differ according to the underlying technologies and the manufacturers’ personal preferences and experience, but because of competitive pressures, manufacturers tend to use protocols and statistical measures that emphasize their systems’ strengths and provide the best numerical values for comparisons. In addition, since 3D tracking systems generally have errors whose spatial distributions are nonuniform and which seldom follow known analytic distributions, the common practice of using a small number of statistical measures to represent “typical” accuracies for these sys- tems is usually inadequate, and occasionally misleading. This can lead to a form of specmanship that can confuse potential users attempting to select the tracking systems best suited for their specific needs. We discuss some of the key accuracy factors often used to compare tracking systems, and we demonstrate some of the subtleties involved in accuracy specifications that potential customers should be aware of. The example systems cited are all manufactured by NDI.