Jon Harald Kaspersen

Multimodal Image Fusion in Ultrasound-Based Neuronavigation: Improving Overview and Interpretation by Integrating Preoperative MRI with Intraoperative 3D Ultrasound

Objective: We have investigated alternative ways to integrate intraoperative 3D ultrasound images and preoperative MR images in the same 3D scene for visualizing brain shift and improving overview and interpretation in ultrasound-based neuronavigation. Materials and Methods: A Multi-Modal Volume Visualizer (MMW) was developed that can read data exported from the SonoWand® neuronavigation system and reconstruct the spatial relationship between the volumes available at any given time during an operation, thus enabling the exploration of new ways to fuse pre-and intraoperative data for planning, guidance and therapy control. In addition, the mismatch between MRI volumes registered to the patient and intraoperative ultrasound acquired from the dura was qualified. Results: The results show that image fusion of intraoperative ultrasound images in combination with preoperative MRI will make perception of available information easier by providing updated (real-time) image information and an extended overview of the operating field during surgery. This approach will assess the degree of anatomical changes during surgery and give the surgeon an understanding of how identical structures are imaged using the different imaging modalities. The present study showed that in 50% of the cases there were indications of brain shift even before the surgical procedure had started. Conclusions: We believe that image fusion between intraoperative 3D ultrasound and preoperative MRI might improve the quality of the surgical procedure and hence also improve the patient outcome.

A new method for analysis of motion of carotid plaques from RF ultrasound images

Motion of carotid artery plaques during the cardiac cycle may contribute to plaque disruption and embolism. We have developed a computerized method that objectively analyzes such motion from a sequence of ultrasound (US) radiofrequency (RF) images. A displacement vector map is obtained by 2-D correlation of local areas in consecutive images. From this map, motion dynamics can be quantified and presented as function of time, spatial (image) coordinates or as single numbers. Correct functionality has been verified on laboratory data. Applied to patient data, the method gives temporal results that correlate well with ECG data and the calculated peak systolic velocities of typically 10 mm/s agree well with values reported in the literature. The spatial analysis demonstrates that different plaque regions may exhibit different motion patterns that may cause internal stress, leading to fissures and plaque disruption. Thus, the motion analysis method may provide new and important information about the plaque characteristics and the prospective risk of cerebrovascular events.

Three-dimensional ultrasound-based navigation combined with preoperative CT during abdominal interventions: a feasibility study.

AbstractPurpose: Three-dimensional (3D) intraoperative ultrasound may be easier to interpret when used in combination with less noisy preoperative image data such as CT. The purpose of this study was to evaluate the use of preoperative image data in a 3D ultrasound-based navigation system specially designed for minimally invasive abdominal surgery. A prototype system has been tested in patients with aortic aneurysms undergoing clinical assessment before and after abdominal aortic stent-graft implantation. Methods: All patients were first imaged by spiral CT followed by 3D ultrasound scanning. The CT volume was registered to the patient using fiducial markers. This enabled us to compare corresponding slices from 3D ultrasound and CT volumes. The accuracy of the patient registration was evaluated both using the external fiducial markers (artificial landmarks glued on the patient’s skin) and using intraoperative 3D ultrasound as a measure of the true positioning of anatomic landmarks inside the body. Results: The mean registration accuracy on the surface was found to be 7.1 mm, but increased to 13.0 mm for specific landmarks inside the body. CT and ultrasound gave supplementary information of surrounding structures and position of the patient’s anatomy. Fine-tuning the initial patient registration of the CT data with a multimodal CT to intraoperative 3D ultrasound registration (e.g., mutual information), as well as ensuring no movements between this registration and image guidance, may improve the registration accuracy. Conclusion: Preoperative CT in combination with 3D ultrasound might be helpful for guiding minimal invasive abdominal interventions.

Navigation in laparoscopy--prototype research platform for improved image-guided surgery.

The manipulation of the surgical field in laparoscopic surgery, through small incisions with rigid instruments, reduces free sight, dexterity, and tactile feedback. To help overcome some of these drawbacks, we present a prototype research and development platform, CustusX, for navigation in minimally invasive therapy. The system can also be used for planning and follow‐up studies. With this platform we can import and display a range of medical images, also real‐time data such as ultrasound and X‐ray, during surgery. Tracked surgical tools, such as pointers, video laparoscopes, graspers, and various probes, allow surgeons to interactively control the display of medical images during the procedure. This paper introduces navigation technologies and methods for laparoscopic therapy, and presents our software and hardware research platform. Furthermore, we illustrate the use of the system with examples from two pilots performed during laparoscopic therapy. We also present new developments that are currently being integrated into the system for future use in the operating room. Our initial results from pilot studies using this technology with preoperative images and guidance in the retroperitoneum during laparoscopy are promising. Finally, we shortly describe an ongoing multicenter study using this surgical navigation system platform.

Integrating segmentation methods from the Insight Toolkit into a visualization application.

The Insight Toolkit (ITK) initiative from the National Library of Medicine has provided a suite of state-of-the-art segmentation and registration algorithms ideally suited to volume visualization and analysis. A volume visualization application that effectively utilizes these algorithms provides many benefits: it allows access to ITK functionality for non-programmers, it creates a vehicle for sharing and comparing segmentation techniques, and it serves as a visual debugger for algorithm developers. This paper describes the integration of image processing functionalities provided by the ITK into VolView, a visualization application for high performance volume rendering. A free version of this visualization application is publicly available and is available in the online version of this paper. The process for developing ITK plugins for VolView according to the publicly available API is described in detail, and an application of ITK VolView plugins to the segmentation of Abdominal Aortic Aneurysms (AAAs) is presented. The source code of the ITK plugins is also publicly available and it is included in the online version.

Wavelet-based edge detection in ultrasound images

We introduce a new wavelet-based method for edge detection in ultrasound (US) images. Each beam that is analyzed is first transformed into the wavelet domain using the continuous wavelet transform (CWT). Because the CWT preserves both scale and time information, it is possible to separate the signal into a number of scales. The edge is localized by first determining the scale at which the power spectrum, based on the wavelet transform, has its maximum value. Next, at this scale we find the position of the peak for the squared CWT. This method does not depend on any threshold, after the range of scales have been determined. We suggest a range of scales for US images in general. Sample edge detections are demonstrated in US images of straight and jagged edges of simple structures submerged in water bath, and of an abdominal aorta aneurysm phantom.

Wavelet-based method for burst detection

A method to detect energetic structures based on wavelet analysis is outlined. Combined with a quadrant decomposition the method may provide information about the scale dependency of ejection and sweep events. One advantage of this method compared to previously published algorithms is that there are no thresholds or grouping times involved. The method was applied to a number of zero pressure gradient boundary layer flows covering a large range of Reynolds numbers. It is shown that the duration of the ejections, over the entire boundary layer, scales with inner variables for a wide range of turbulent scales. The time between the events scale with inner variables in the immediate vicinity of the wall, but for y+ greater than about 70, outer scaling proved to give the best collapse for the Re range investigated.

3D visualization of strain in abdominal aortic aneurysms based on navigated ultrasound imaging

The criterion for recommending treatment of an abdominal aortic aneurysm is that the diameter exceeds 50-55 mm or shows a rapid increase. Our hypothesis is that a more accurate prediction of aneurysm rupture is obtained by estimating arterial wall strain from patient specific measurements. Measuring strain in specific parts of the aneurysm reveals differences in load or tissue properties. We have previously presented a method for in vivo estimation of circumferential strain by ultrasound. In the present work, a position sensor attached to the ultrasound probe was used for combining several 2D ultrasound sectors into a 3D model. The ultrasound was registered to a computed-tomography scan (CT), and the strain values were mapped onto a model segmented from these CT data. This gave an intuitive coupling between anatomy and strain, which may benefit both data acquisition and the interpretation of strain. In addition to potentially provide information relevant for assessing the rupture risk of the aneurysm in itself, this model could be used for validating simulations of fluid-structure interactions. Further, the measurements could be integrated with the simulations in order to increase the amount of patient specific information, thus producing a more reliable and accurate model of the biomechanics of the individual aneurysm. This approach makes it possible to extract several parameters potentially relevant for predicting rupture risk, and may therefore extend the basis for clinical decision making.