Andrew D. Wiles

A Statistical Model for Point-Based Target Registration Error With Anisotropic Fiducial Localizer Error

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.

Virtual reality-enhanced ultrasound guidance: a novel technique for intracardiac interventions.

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.

A hardware and software protocol for the evaluation of electromagnetic tracker accuracy in the clinical environment: a multi-center study

This paper proposes an assessment protocol that incorporates both hardware and analysis methods for evaluation of electromagnetic tracker accuracy in different clinical environments. The susceptibility of electromagnetic tracker measurement accuracy is both highly dependent on nearby ferromagnetic interference sources and non-isotropic. These inherent limitations combined with the various hardware components and assessment techniques used within different studies makes the direct comparison of measurement accuracy between studies difficult. This paper presents a multicenter study to evaluate electromagnetic devices in different clinical environments using a common hardware phantom and assessment techniques so that results are directly comparable. Measurement accuracy has been shown to be in the range of 0.79-6.67mm within a 180mm3 sub-volume of the Aurora measurement space in five different clinical environments.

Image Guidance for Spinal Facet Injections Using Tracked Ultrasound

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 0.57 mm 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.

An augmented reality environment for image-guidance of off-pump mitral valve implantation

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.

Real-Time Estimation of FLE Statistics for 3-D Tracking With Point-Based Registration

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 mum. 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.

Improved statistical TRE model when using a reference frame

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.

Object identification accuracy under ultrasound enhanced virtual reality for minimally invasive cardiac surgery

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.

Specifying 3D Tracking System Accuracy One Manufacturer’s Views

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.

Target Tracking Errors for 5D and 6D Spatial Measurement Systems

In recent years, magnetic tracking systems, whose fundamental unit of measurement is a 5D transformation (three translational and two rotational degrees-of-freedom), have become much more popular. Two 5D sensors can be combined to obtain a 6D transformation similar to the ones provided by the point-based registration in optical tracking. However, estimates of the tool tip uncertainty, which we have called the target tracking error (TTE) since no registration is explicitly performed, are not available in the same manner as their optical counterpart. If the systematic bias error can be corrected and estimates of the 5D or 6D fiducial localizer error (FLE) are provided in the form of zero mean normally distributed random variables in ¿5 and ¿6, respectively, then the TTE can be modeled. In this paper, the required expressions that model the TTE as a function of the systematic bias, FLE and target location are derived and then validated using Monte Carlo simulations. We also show that the first order approximation is sufficient beyond the range of errors typically observed during an image-guided surgery (IGS) procedure. Applications of the models are described for a minimally invasive intracardiac surgical guidance system and needle-based therapy systems. Together with the target registration error (TRE) statistical models for point-based registration, the models presented in this article provide the basic framework for estimating the total system measurement uncertainty for an IGS system. Future work includes developing TRE models for commonly used registration methods that do not already have them.