Alfred M. Franz

Electromagnetic Tracking in Medicine—A Review of Technology, Validation, and Applications

Object tracking is a key enabling technology in the context of computer-assisted medical interventions. Allowing the continuous localization of medical instruments and patient anatomy, it is a prerequisite for providing instrument guidance to subsurface anatomical structures. The only widely used technique that enables real-time tracking of small objects without line-of-sight restrictions is electromagnetic (EM) tracking. While EM tracking has been the subject of many research efforts, clinical applications have been slow to emerge. The aim of this review paper is therefore to provide insight into the future potential and limitations of EM tracking for medical use. We describe the basic working principles of EM tracking systems, list the main sources of error, and summarize the published studies on tracking accuracy, precision and robustness along with the corresponding validation protocols proposed. State-of-the-art approaches to error compensation are also reviewed in depth. Finally, an overview of the clinical applications addressed with EM tracking is given. Throughout the paper, we report not only on scientific progress, but also provide a review on commercial systems. Given the continuous debate on the applicability of EM tracking in medicine, this paper provides a timely overview of the state-of-the-art in the field.

In vivo accuracy assessment of a needle-based navigation system for CT-guided radiofrequency ablation of the liver.

Computed tomography (CT)-guided percutaneous radiofrequency ablation (RFA) has become a commonly used procedure in the treatment of liver tumors. One of the main challenges related to the method is the exact placement of the instrument within the lesion. To address this issue, a system was developed for computer-assisted needle placement which uses a set of fiducial needles to compensate for organ motion in real time. The purpose of this study was to assess the accuracy of the system in vivo. Two medical experts with experience in CT-guided interventions and two nonexperts used the navigation system to perform 32 needle insertions into contrasted agar nodules injected into the livers of two ventilated swine. Skin-to-target path planning and real-time needle guidance were based on preinterventional 1 mm CT data slices. The lesions were hit in 97% of all trials with a mean user error of 2.4 +/- 2.1 mm, a mean target registration error (TRE) of 2.1 +/- 1.1 mm, and a mean overall targeting error of 3.7 +/- 2.3 mm. The nonexperts achieved significantly better results than the experts with an overall error of 2.8 +/- 1.4 mm (n=16) compared to 4.5 +/- 2.7 mm (n=16). The mean time for performing four needle insertions based on one preinterventional planning CT was 57 +/- 19 min with a mean setup time of 27 min, which includes the steps fiducial insertion (24 +/- 15 min), planning CT acquisition (1 +/- 0 min), and registration (2 +/- 1 min). The mean time for path planning and targeting was 5 +/- 4 and 2 +/- 1 min, respectively. Apart from the fiducial insertion step, experts and nonexperts performed comparably fast. It is concluded that the system allows for accurate needle placement into hepatic tumors based on one planning CT and could thus enable considerable improvement to the clinical treatment standard for RFA procedures and other CT-guided interventions in the liver. To support clinical application of the method, optimization of individual system modules to reduce intervention time is proposed.

Convergent Iterative Closest-Point Algorithm to Accomodate Anisotropic and Inhomogenous Localization Error

Since its introduction in the early 1990s, the Iterative Closest Point (ICP) algorithm has become one of the most well-known methods for geometric alignment of 3D models. Given two roughly aligned shapes represented by two point sets, the algorithm iteratively establishes point correspondences given the current alignment of the data and computes a rigid transformation accordingly. From a statistical point of view, however, it implicitly assumes that the points are observed with isotropic Gaussian noise. In this paper, we show that this assumption may lead to errors and generalize the ICP such that it can account for anisotropic and inhomogenous localization errors. We 1) provide a formal description of the algorithm, 2) extend it to registration of partially overlapping surfaces, 3) prove its convergence, 4) derive the required covariance matrices for a set of selected applications, and 5) present means for optimizing the runtime. An evaluation on publicly available surface meshes as well as on a set of meshes extracted from medical imaging data shows a dramatic increase in accuracy compared to the original ICP, especially in the case of partial surface registration. As point-based surface registration is a central component in various applications, the potential impact of the proposed method is high.

Standardized assessment of new electromagnetic field generators in an interventional radiology setting.

PURPOSE Two of the main challenges associated with electromagnetic (EM) tracking in computer-assisted interventions (CAIs) are (1) the compensation of systematic distance errors arising from the influence of metal near the field generator (FG) or the tracked sensor and (2) the optimized setup of the FG to maximize tracking accuracy in the area of interest. Recently, two new FGs addressing these issues were proposed for the well-established Aurora(®) tracking system [Northern Digital, Inc. (NDI), Waterloo, Canada]: the Tabletop 50-70 FG, a planar transmitter with a built-in shield that compensates for metal distortions emanating from treatment tables, and the prototypical Compact FG 7-10, a mobile generator designed to be attached to mobile imaging devices. The purpose of this paper was to assess the accuracy and precision of these new FGs in an interventional radiology setting. METHODS A standardized assessment protocol, which uses a precisely machined base plate to measure relative error in position and orientation, was applied to the two new FGs as well as to the well-established standard Aurora(®) Planar FG. The experiments were performed in two different settings: a reference laboratory environment and a computed tomography (CT) scanning room. In each setting, the protocol was applied to three different poses of the measurement plate within the tracking volume of the three FGs. RESULTS The two new FGs provided higher precision and accuracy within their respective measurement volumes as well as higher robustness with respect to the CT scanner compared to the established FG. Considering all possible 5 cm distances on the grid, the error of the Planar FG was increased by a factor of 5.94 in the clinical environment (4.4 mm) in comparison to the error in the laboratory environment (0.8 mm). In contrast, the mean values for the two new FGs were all below 1 mm with an increase in the error by factors of only 2.94 (Reference: 0.3 mm; CT: 0.9 mm) and 1.04 (both: 0.5 mm) in the case of the Tabletop FG and the Compact FG, respectively. CONCLUSIONS Due to their high accuracy and robustness, the Tabletop FG and the Compact FG could eliminate the need for compensation of EM field distortions in certain CT-guided interventions.

Accounting for anisotropic noise in fine registration of time-of-flight range data with high-resolution surface data

Time-of-Flight (ToF) sensors have become a considerable alternative to conventional surface acquisition techniques such as laser range scanning and stereo vision. Application of ToF cameras for the purpose of intra-operative registration requires matching of the noisy surfaces generated from ToF range data onto pre-interventionally acquired high-resolution surfaces. The contribution of this paper is twofold: Firstly, we present a novel method for fine rigid registration of noisy ToF data with high-resolution surface meshes taking into account both, the noise characteristics of ToF cameras and the resolution of the target mesh. Secondly, we introduce an evaluation framework for assessing the performance of ToF registration methods based on physically realistic ToF range data generated from a virtual scence. According to experiments within the presented evaluation framework, the proposed method outperforms the standard ICP algorithm with respect to correspondence search and transformation computation, leading to a decrease in the target registration error (TRE) of more than 70%.

Soft tissue navigation using needle-shaped markers: Evaluation of navigation aid tracking accuracy and CT registration

We evaluate two core modules of a novel soft tissue navigation system. The system estimates the position of a hidden target (e.g. a tumor) during a minimally invasive intervention from the location of a set of optically tracked needle-shaped navigation aids which are placed in the vicinity of the target. The initial position of the target relative to the navigation aids is obtained from a CT scan. The accuracy of the entire system depends on (a) the accuracy for locating a set of navigation aids in a CT image, (b) the accuracy for determining the positions of the navigation aids during the intervention by means of optical tracking, (c) the accuracy for tracking the applicator (e.g. the biopsy needle), and (d) the accuracy of the real-time deformation model which continuously computes the location of the initially determined target point from the current positions of the navigation aids. In this paper, we focus on the first two aspects. We introduce the navigation aids we constructed for our system and show that the needle tips can be tracked with submillimeter accuracy. Furthermore, we present and evaluate three methods for registering a set of navigation aid models with a given CT image. The fully-automatic algorithm outperforms both the manual method and the semi-automatic algorithm, yielding an average distance of 0.27 ± 0.08 mm between the estimated needle tip position and the reference position.

On combining internal and external fiducials for liver motion compensation

This paper presents an in-vivo accuracy study on combining skin markers (external fiducials) and fiducial needles (internal fiducials) for motion compensation during liver interventions. We compared the target registration error (TRE) for different numbers of skin markers ns and fiducial needles nf, as well as for different transformation types, in two swine using the tip of an additional tracked needle as the target. During continuous breathing, nf had the greatest effect on the accuracy, yielding mean root mean square (RMS) errors of 4.8 ± 1.1 mm (nf = 0), 2.0 ± 0.9 mm (nf = 1) and 1.7 ± 0.8 mm (nf = 2) when averaged over multiple tool arrangements (n = 18, 36, 18) with ns = 4. These values correspond to error reductions of 11%, 64% and 70%, respectively, compared to the case when no motion compensation is performed, i.e., when the target position is assumed to be constant. At expiration, the mean RMS error ranged from 1.1 mm (nf = 0) to 0.8 mm (nf = 2), which is of the order of magnitude of the target displacement. Our study further indicates that the fiducial registration error (FRE) of a rigid transformation reflecting tissue motion generally correlates strongly with the TRE. Our findings could be used in practice to (1) decide on a suitable combination of fiducials for a given intervention, considering the trade-off between high accuracy and low invasiveness, and (2) provide an intra-interventional measure of confidence for the accuracy of the system based on the FRE.

Towards mobile augmented reality for on-patient visualization of medical images

Despite considerable technical and algorithmic developments related to the fields of medical image acquisition and processing in the past decade, the devices used for visualization of medical images have undergone rather minor changes. As anatomical information is typically shown on monitors provided by a radiological work station, the physician has to mentally transfer internal structures shown on the screen to the patient. In this work, we present a new approach to on-patient visualization of 3D medical images, which combines the concept of augmented reality (AR) with an intuitive interaction scheme. The method requires mounting a Time-of-Flight (ToF) camera to a portable display (e.g., a tablet PC). During the visualization process, the pose of the camera and thus the viewing direction of the user is continuously determined with a surface matching algorithm. By moving the device along the body of the patient, the physician gets the impression of being able to look directly into the human body. The concept can be used for intervention planning, anatomy teaching and various other applications that require intuitive visualization of 3D data.

Simplified development of image-guided therapy software with MITK-IGT

Due to rapid developments in the research areas of medical imaging, medical image processing and robotics, computer assistance is no longer restricted to diagnostics and surgical planning but has been expanded to surgical and radiological interventions. From a software engineering point of view, the systems for image-guided therapy (IGT) are highly complex. To address this issue, we presented an open source extension to the well-known Medical Imaging Interaction Toolkit (MITK) for developing IGT systems, called MITK-IGT. The contribution of this paper is two-fold: Firstly, we extended MITK-IGT such that it (1) facilitates the handling of navigation tools, (2) provides reusable graphical user interface (UI) components, and (3) features standardized exception handling. Secondly, we developed a software prototype for computer-assisted needle insertions, using the new features, and tested it with a new Tabletop field generator (FG) for the electromagnetic tracking system NDI Aurora ®. To our knowledge, we are the first to have integrated this new FG into a complete navigation system and have conducted tests under clinical conditions. In conclusion, we enabled simplified development of imageguided therapy software and demonstrated the utilizability of applications developed with MITK-IGT in the clinical workflow.

Navigated liver biopsy using a novel soft tissue navigation system versus CT-guided liver biopsy in a porcine model. A prospective randomized trial

RATIONALE AND OBJECTIVES The aim of this prospective, randomized animal study was to compare a new computer guided needle-based navigation system for liver biopsy with conventional computed tomography (CT)-guided liver biopsy. Computer-navigated interventions provide continuous needle tracking during motion and deformation from patient respiration and movement. MATERIALS AND METHODS Twenty artificial tumors of about 5 mm in diameter were injected into the livers of five pigs, each at a different site. Each tumor was targeted by conventional CT-guided and computer navigated intervention. Intervention was considered complete after successful tumor biopsy. Data on procedure time, number of CT scans performed, accuracy, and success rate were recorded. RESULTS All tumors (100%) were biopsied successfully. Mean procedural time was comparable between the two techniques (20 ± 9 minutes conventional versus 20 ± 8 minutes navigation). Mean number of CT scans were 1.2 ± 0.4 with navigation and 6.1 ± 3.8 with the conventional technique (P < .01). The dose-length product in the conventional group was significantly higher (212 ± 116 mGy × cm) than in the navigated group (78 ± 22 mGy × cm; P < .001). Mean number of capsule penetrations was 4 ± 1 with navigation versus 2 ± 1 with the conventional technique (P < .001). CONCLUSION Computer-navigated liver biopsy may provide a promising and innovative device for easy, rapid, and successful liver biopsies with low morbidity. Further technical improvements and clinical studies in humans are required.