An ultrasonic approach to localization of fiducial markers for interactive, image-guided neurosurgery--Part II: Implementation and automation

Vector field analysis for surface registration in computer-assisted ENT surgery

BACKGROUND

Manual paired-point registration for navigated ENT-surgery is prone to human errors; automatic surface registration is often caught in local minima.

METHODS

Anatomical features of the human occiput are integrated into an algorithm for surface registration. A vector force field is defined between the patient and operating room datasets; registration is facilitated through gradient-based vector field analysis optimization of an energy function. The method is validated exemplarily on patient surface data provided by a mechanically positioned A-mode ultrasound sensor.

RESULTS

Successful registrations were achieved within the entire parameter space, as well as from positions of local minima that were found by the Gaussian fields algorithm for surface registration. Sub-millimetric registration error was measured in clinically relevant anatomical areas on the anterior skull and within the generally accepted margin of 1.5 mm for the entire head.

CONCLUSION

The satisfactory behavior of this approach potentially suggests a wider clinical integration.

A Transcutaneous Bone Digitizer for Minimally Invasive Registration in Orthopedics: A Real-Time Focused Ultrasound Beam Approach

Computer-guided navigation of surgical tool position in computer-assisted orthopedic systems requires the registration of computer tomographic (CT) images with underlying bone. This process is presently performed by manually digitizing points on bone with a pointer and aligning them to a preoperative CT scan. We propose the use of ultrasound to obtain points on bone transcutaneously. A custom-made A-mode probe features a modular lens focusing system and a one-step calibration method. A stable and precise echo detection algorithm is also implemented. The accuracies of three signal detection algorithms--standard deviation, cross-correlation (XCORR) and short-time Fourier transform--were compared using a known reflected signal. XCORR showed the most accurate and stable operation. To test our method of obtaining bone surface points, a plastic model of the fourth human lumbar vertebra was CT scanned and then immersed in a water bath. Six surface registrations of the vertebra using an accurate pointing device were compared to ten registrations obtained using the US probe (using the XCORR algorithm). Student's T-test showed no significant difference in error between the two methods, proving that ultrasound registration, using our method, is equivalent to the more conventional pointer method.

Fast and accurate registration of cranial CT images with A-mode ultrasound

PURPOSE

Within the CRANIO project, a navigation module based on preoperative computed tomography (CT) data was developed for Computer and Robot Assisted Neurosurgery. The approach followed for non-invasive user-interactive registration of cranial CT images with the physical operating space consists of surface-based registration following pre-registration based on anatomical landmarks. Surface-based registration relies on bone surface points digitized transcutaneously by means of an optically tracked A-mode ultrasound (US) probe. As probe alignment and thus bone surface point digitization may be time-consuming, we investigated how to obtain high registration accuracy despite inaccurate pre-registration and a limited number of digitized bone surface points. Furthermore, we aimed at efficient man-machine-interaction during the probe alignment process. Finally, we addressed the problem of registration plausibility estimation in our approach.

METHOD

We modified the Iterative Closest Point (ICP) algorithm, presented by Besl and McKay and frequently used for surface-based registration, such that it can escape from local minima of the cost function to be iteratively minimized. The random-based ICP (R-ICP) we developed is less influenced by the quality of the pre-registration as it can escape from local minima close to the starting point for iterative optimization in the 6D domain of rigid transformations. The R-ICP is also better suited to approximate the global minimum as it can escape from local minima in the vicinity of the global minimum, too. Furthermore, we developed both CT-less and CT-based probe alignment tools along with appropriate man-machine strategies for a more time-efficient palpation process. To improve registration reliability, we developed a simple plausibility test based on data readily available after registration.

RESULTS

In a cadaver study, where we evaluated the R-ICP algorithm, the probe alignment tools, and the plausibility test, the R-ICP algorithm consistently outperformed the ICP algorithm. Almost no influence of the pre-registration on the final R-ICP registration accuracy could be observed. The probe alignment tools were judged to be useful and allowed for the digitization of 18 bone surface points within 2 min on average. The plausibility test was helpful to detect poor registration accuracy.

CONCLUSION

The R-ICP algorithm can provide high registration accuracy despite inaccurate pre-registration and a very limited number of data points. R-ICP registration was shown to be practical and robust versus the quality of the pre-registration. Time-efficiency of the cranial palpation process may be greatly increased and should encourage clinical acceptance.

Construction of a frameless camera-based stereotactic neuronavigator

We built an infrared vision system to be used as the real time 3D motion sensor in a prototype low cost, high precision, frameless neuronavigator. The objective of the prototype is to develop accessible technology for increased availability of neuronavigation systems in research labs and small clinics and hospitals. We present our choice of technology including camera and IR emitter characteristics. We describe the methodology for setting up the 3D motion sensor, from the arrangement of the cameras and the IR emitters on surgical instruments, to triangulation equations from stereo camera pairs, high bandwidth computer communication with the cameras and real time image processing algorithms. We briefly cover the issues of camera calibration and characterization. Although our performance results do not yet fully meet the high precision, real time requirements of neuronavigation systems we describe the current improvements being made to the 3D motion sensor that will make it suitable for surgical applications.

Self-calibrating 3D-ultrasound-based bone registration for minimally invasive orthopedic surgery

Intraoperative freehand three-dimensional (3-D) ultrasound (3D-US) has been proposed as a noninvasive method for registering bones to a preoperative computed tomography image or computer-generated bone model during computer-aided orthopedic surgery (CAOS). In this technique, an US probe is tracked by a 3-D position sensor and acts as a percutaneous device for localizing the bone surface. However, variations in the acoustic properties of soft tissue, such as the average speed of sound, can introduce significant errors in the bone depth estimated from US images, which limits registration accuracy. We describe a new self-calibrating approach to US-based bone registration that addresses this problem, and demonstrate its application within a standard registration scheme. Using realistic US image data acquired from 6 femurs and 3 pelves of intact human cadavers, and accurate Gold Standard registration transformations calculated using bone-implanted fiducial markers, we show that self-calibrating registration is significantly more accurate than a standard method, yielding an average root mean squared target registration error of 1.6 mm. We conclude that self-calibrating registration results in significant improvements in registration accuracy for CAOS applications over conventional approaches where calibration parameters of the 3D-US system remain fixed to values determined using a preoperative phantom-based calibration.

Coregistration accuracy and detection of brain shift using intraoperative sononavigation during resection of hemispheric tumors

OBJECTIVE

Sononavigation, which combines real-time anatomic ultrasound data with neuronavigation techniques, is a potentially valuable adjunct during the surgical excision of brain tumors.

METHODS

In this study, we report our preliminary observations using this technology on 58 adult patients harboring hemispheric tumors. Data regarding coregistration accuracy was collected from various landmarks that typically do not shift as well as from tumor boundaries and the cortical surface. In a subset of patients, we evaluated the extent and direction of postresection brain displacement and its relationship with patient age, tumor histology, tumor volume, and use of mannitol.

RESULTS

For all structures excluding the cortex, average coregistration accuracy measurements between ultrasound and preoperatively acquired magnetic resonance imaging scans were within the range of 2 mm. The most accurate alignments were obtained with the choroid plexus and the falx, and the least reliable structure in terms of coregistration accuracy was the cortical surface.

CONCLUSION

Sononavigation provides real-time information during tumor removal in alignment with the preoperative magnetic resonance imaging scans, thus enabling the surgeon to detect intraoperative hemorrhage, cyst drainage, and tumor resection, and it allows for calculation of brain shift during the use of standard navigation techniques.

Computer-aided navigation in neurosurgery

The article comprises three main parts: a historical review on navigation, the mathematical basics for calculation and the clinical applications of navigation devices. Main historical steps are described from the first idea till the realisation of the frame-based and frameless navigation devices including robots. In particular the idea of robots can be traced back to the Iliad of Homer, the first testimony of European literature over 2500 years ago. In the second part the mathematical calculation of the mapping between the navigation and the image space is demonstrated, including different registration modalities and error estimations. The error of the navigation has to be divided into the technical error of the device calculating its own position in space, the registration error due to inaccuracies in the calculation of the transformation matrix between the navigation and the image space, and the application error caused additionally by anatomical shift of the brain structures during operation. In the third part the main clinical fields of application in modern neurosurgery are demonstrated, such as localisation of small intracranial lesions, skull-base surgery, intracerebral biopsies, intracranial endoscopy, functional neurosurgery and spinal navigation. At the end of the article some possible objections to navigation-aided surgery are discussed.

An ultrasonic approach to localization of fiducial markers for interactive, image-guided neurosurgery--Part I: Principles

Fiducial markers are reference points used in the registration of image space(s) with physical (patient) space. As applied to interactive, image-guided surgery, the registration of image space with physical space allows the current location of a surgical tool to be indicated on a computer display of patient-specific preoperative images. This intrasurgical guidance information is particularly valuable in surgery within the brain, where visual feedback is limited. The accuracy of the mapping between physical and image space depends upon the accuracy with which the fiducial markers were located in each coordinate system. To effect accurate space registration for interactive, image-guided neurosurgery, the use of permanent fiducial markers implanted into the surface of the skull is proposed in this paper. These small cylindrical markers are composed of materials that make them visible in the image sets. The challenge lies in locating the subcutaneous markers in physical space. This paper presents an ultrasonic technique for transcutaneously detecting the location of these markers. The technique incorporates an algorithm based on detection of characteristic properties of the reflected A-mode ultrasonic waveform. The results demonstrate that ultrasound is an appropriate technique for accurate transcutaneous marker localization. The companion paper to this article describes an automatic, enhanced implementation of the marker-localization theory described in this article.