A fast, robust, accurate, and automatic registration technique based on magnetic resonance (MR) active microcoils (active markers) for registration of tracked medical devices to preprocedural MR-images is presented. This allows for a straightforward integration of position measurement systems into clinical procedures. The presented method is useful for guidance purposes in clinical applications with high demands on accuracy and ease-of-use (e.g., neurosurgical or orthopedic applications). The determination of the positions of the active markers is integrated into the preparation phase of the actual MR imaging scan. The technique features a generic interface using DICOM standards for communication with navigation workstations linked to an MR system. The position of the active markers is fixed with respect to a reference system of an optical positioning measurement system (OPMS) and thus the coregistration of the MR system and the OPMS is established. In a phantom study, a mean overall targeting accuracy of 0.9 +/- 0.1 mm was achieved and compared favorably to results obtained from manual registration tests (1.8 +/- 0.3 mm) carried out in parallel. For a test person trained for both registration methods, workflow improvements of 3-6 min per registration step were found. The need for manual interaction is entirely eliminated thus avoiding user-bias, which is advantageous for the usage in clinical routine. The method improves the ease-of-use of tracking equipment during stereotactic guidance. The method is finally demonstrated in a volunteer study using a model of a Mayfield skull clamp with integrated active and optical reference markers.

Computer-assisted navigation shall reliably guide the surgeon to a planned target position. Various medical image modalities are required for a safe diagnosis and intervention planning. For treatment forms like LITT, therapy simulation should be part of a planning scenario. In soft tissues, the intervention usually will render preoperative images inappropriate if tissue shifts occur. In these cases intraoperative images are necessary to show the current state, to update the preoperative data, and to register preoperative images to the current situation. The update is an iterative process triggered by situational changes during the ongoing intervention. This paper presents our concept of iterative multimodal navigation that has been implemented in the LOCALITE Navigator for interventional MR and ultrasound.

Introduction Biopsy and resection of brain tumors in eloquent areas remain challenging tasks because of the potential risk of postoperative neurological deficits and, consequently, a severe deterioration of life quality Biopsy and resection of brain tumors in eloquent areas remain challenging tasks because of the potential risk of postoperative neurological deficits and, consequently, a severe deterioration of life quality. Currently, many intraoperative identifications of eloquent brain areas are still based on anatomical landmarks. It is well known, however, that there is no exact correspondence between functional areas and anatomical structures. In addition, these structures can be altered by the tumor and the perifocal edema. Functional magnetic resonance imaging (fMRI) is widely accepted as a reliable method for the non-invasive localization of eloquent areas. For interventional neurosurgical procedures with an open MR scanner, it is, therefore, highly desirable for the neurosurgeon to map preoperative fMRI results onto the oblique anatomical iMRI planes determined by a localization device. An excellent correlation between fMRI maps and invasive intraoperative electrophysiological stimulation has been shown in a few studies involving the sensorimotor cortex [1,2,3]. In the presented work, an existing interventional navigation system (LOCALITE) has been extended by an fMRI module to allow the integration of preoperative functional MR data into intraoperatively acquired 3D-MR data sets. The aim of our study was to evaluate the feasibility of this promising combination as a tool for improved neurosurgical navigation. Methods Out of a patient group selected for open MR-guided resection, eight patients with cerebral lesions close to the central sulcus were enrolled in this preliminary study Out of a patient group selected for open MRguided resection, eight patients with cerebral lesions close to the central sulcus were enrolled in this preliminary study. The preoperative functional data were acquired on a 1.5 T scanner (Magnetom Vision, Siemens, Erlangen, Germany) using EPI (TR 4 sec, TE 66 ms, 128 x 128, FOV 23 cm, 60 NEX). The sensorimotor cortex activation was achieved with a finger tapping paradigm. For fMRI post processing, the Siemens software mripp was used. Anatomical reference images were recorded with T1 weighting (TR 448 ms, TE 15 ms). These images are inherently registered with the EPI data set and serve as a basis for fMRI–iMRI mapping. Intraoperative imaging was performed on an open MRI scanner (Signa SP, 0.5 T, GEMS, Milwaukee, WI) equipped with a hand-held localization device (Flashpoint, IGT, Boulder, CO). Conventional neuronavigation with this system is based on T1-weighted real time images (TR 30 ms, TE 7.5 ms, one frame every 4 secs). The certified LOCALITE Navigator (GMD, Sankt Augustin, Germany) has been introduced into this environment to improve navigation procedures with respect to speed and image quality [4]. Simulated real time navigation (3 frames per sec) is achieved by rendering high quality image planes out of intraoperatively acquired 3D data sets using a 3D (FSPGR) T1-weighted sequence (TR 13.3 ms, TE 2.7 ms/fr). The extension modules fMRI Tester and fMRI Navigator (LOCALITE GmbH, Bonn, Germany) have been designed to integrate functional information into this enhanced neuronavigation. Integration of the fMRI data into the intraoperative environment is currently based on the identification of corresponding fiducial markers or anatomical landmarks in the preoperative (1.5 T) anatomical reference images and in the intraoperative images, respectively. Results A screenshot of the LOCALITE fMRI Tester is displayed in Fig A screenshot of the LOCALITE fMRI Tester is displayed in Fig. 1. The position of the displayed border line between the acquired EPI data set (top part) and the corresponding anatomical T1-weighted reference images (bottom part) can be interactively manipulated in different planes. Although inherently registered, this comparison allows the evaluation whether the patient has moved between both data acquisitions. In this case, no significant shifting could be observed and the T1-weighted images could be used as a reference set for functional navigation. In the fMRI Navigator environment, the T1 data set of the functional investigation was registered (here, using three marker pairs) and overlayed ontop of a previously acquired 3D iMRI data set (Fig. 2). The quality of the resulting overlay can be evaluated within an arbitrary slice by moving a lens across the screen. For quality control, the distances of the marker positions in the common (registered) coordinate frame and their mean value (here, 0.9 mm) will be given as guiding values. Overlays of preoperative functional (BOLD) MR data onto intraoperative 3D anatomical MR images are the basis for the determination of distances between tumor and eloquent areas (static mode, Fig. 3) and for functional neurosurgical navigation (real time mode, Fig. 4).

Medical imaging permits high precision minimally invasive interventions even in very delicate situations but leads to complex medical procedures not easily applied in a hospital setting. The LOCALITE Navigator is an interactive navigation system that comprises state-of-the art registration and visualization of multimodal medical images for minimally invasive interventions with an interventional magnetic resonance imaging (iMRI) system. The focus is on an intuitive and simple user interface that can be handled by the medical personnel themselves without relying on computer experts. The system has got a CE certificate in 2001 and is used by all GE SIGNA SP installations in Germany.

Minimally invasive techniques often require special biomedical monitoring schemes. In the case of laser coagulation of tumors (LITT) accurate temperature mapping is desirable for therapy control. While magnetic resonance (MR)-based thermometry can easily yield qualitative results it is still difficult to calibrate this technique with independent temperature probes for the entire 2D field of view. Calculated temperature maps derived from Monte-Carlo simulations (MCS), on the other hand, are suitable for therapy planning and dosimetry but typically can not account for the exact individual tissue parameters and physiological changes upon heating (tissue state, perfusion, etc.).In this work, online thermometry was combined with MCS techniques to explore the feasibility and potential of such a bimodal approach for surgical assist systems. For the first time, the results of a 3D simulation were evaluated with MR techniques. An MR thermometry system was used to monitor the temperature evolution during laser-induced thermal treatment of bovine liver using a commercially available water-cooled applicator. A systematic comparison between MR-derived 2D temperature maps in different orientations and corresponding snapshots of a 3D MCS of the laser-induced processes is presented.The MCS is capable of resolving the complex temperature patterns observed in the MR-derived images and yields a good agreement with respect to absolute temperatures (T) and damage volume dimensions (d). The observed quantitative agreement is around 10 degrees C (Delta T) and on the order of 10 % (Delta d/d), respectively. The integrated simulation-and-monitoring approach has the potential to improve surgical assistance during thermal interventions.

Der LOCALITE Brain Navigator ist ein bildgestütztes Navigationssystem, das minimalinvasive neurochirurgische Eingriffe an interventionellen Kernspintomographen unterstützt, indem es Nachteile bestehender Systeme - die fehlende Integration einer Operationsplanung sowie die langsame Bildwiederholungsrate von ca. 0, 3 Hz, und schlechte Bildqualität der MR-Realzeitbilder - kompensiert. Basis für diese Verbesserungen sind intraoperativ gewonnene MR-Volumendatensätze mit deren Hilfe zunächst eine Operationsplanung durchgeführt wird. Während des Eingriffs werden mit ca. 5–10 Hz dem Realzeitbild entsprechende Schnittbilder mit deutlich gesteigerter Qualität aus diesen Volumendatens ätzen berechnet. Das Auffinden des Operationskanals wird durch eine speziell entwickelte Navigationsszene deutlich beschleunigt.

One of the major problems in neurosurgery is to find an optimal access route towards the area of interest, e.g., a lesion to be treated chirurgically. The quality of a route depends on the type of pathology to treat, its location, the functional areas surrounding it and many other aspects. The overall goal of route optimization is of course, to treat the patient as effectively as possible while minimizing additional damage. In addition, the operation field must be sufficiently accessible to the surgeon. To identify such a route, besides other aids, radiological images of the area of interest (often CT/MR-images) are consulted, and the decision is based on the location and extent of the pathology as discernible in the images, sometimes supported by functional MRI data. Unfortunately, two-dimensional images communicate only limited information about the spatial and structural relationships, although experienced radiologists and surgeons develop the ability to build mental models of the three-dimensional structures from the images alone. But this process takes much time and a lot of experience. Furthermore, surgeons and radiologists have to cooperate and come to a common understanding to find the optimum treatment. This proves difficult as they have radically different views on the patient. While radiologists often feel comfortable with stacks of two-dimensional images, the surgeon’s primary view is on what he finds once the skull is open. Computer technology can help to bridge the gap and shorten the discussion. Using the experiences from other medical projects we developed a software system that is built on the paradigm of enabling systems. This approach focuses on the cognitive processes that take place in the mind of experts and tries to support the less experienced user with cognitive aids that help to develop expertship faster and more easily. Under this paradigm, visualizations, algorithms, and technical aids are chosen primarily with respect to their ability to enable the user to gain insight into the data and the underlying processes. In the remainder of this article we give a short introduction into the paradigm, describe the application of enabling systems to neurosurgery and discuss our current system and its properties.