Marcus Pfister

3D Imaging with Flat-Detector C-Arm Systems

Three-dimensional (3D) C-arm computed tomography is a new and innovative imaging technique. It uses two-dimensional (2D) X-ray projections acquired with a flat-panel detector C-arm angiography system to generate CT-like images. To this end, the C-arm system performs a sweep around the patient, acquiring up to several hundred 2D views. They serve as input for 3D cone-beam reconstruction. Resulting voxel data sets can be visualized either as cross-sectional images or as 3D data sets using different volume rendering techniques. Initially targeted at 3D high-contrast neurovascular applications, 3D C-arm imaging has been continuously improved over the years and is now capable of providing CT-like soft-tissue image quality. In combination with 2D fluoroscopic or radiographic imaging, information provided by 3D C-arm imaging can be valuable for therapy planning, guidance, and outcome assessment all in the interventional suite.

C-Arm Cone Beam Computed Tomography Needle Path Overlay for Fluoroscopic Guided Vertebroplasty

Study Design. Retrospective review. Objective. To report our early clinical experience using C-arm cone beam computed tomography (C-arm CBCT) with fluoroscopic overlay for needle guidance during vertebroplasty. Summary of Background Data. C-arm CBCT is advanced three-dimensional (3-D) imaging technology that is currently available on state-of-the-art flat panel based angiography systems. The imaging information provided by C-arm CBCT allows for the acquisition and reconstruction of “CT-like” images in flat panel based angiography/interventional suites. As part of the evolution of this technology, enhancements allowing the overlay of cross-sectional imaging information can now be integrated with real time fluoroscopy. We report our early clinical experience with C-arm CBCT with fluoroscopic overlay for needle guidance during vertebroplasty. Methods. This is a retrospective review of 10 consecutive oncology patients who underwent vertebroplasty of 13 vertebral levels using C-arm CBCT with fluoroscopic overlay for needle guidance from November 2007 to December 2008. Procedural data including vertebral level, approach (transpedicular vs. extrapedicular), access (bilateral vs. unilateral) and complications were recorded. Technical success with the overlay technology was assessed based on accuracy which consisted of 4 measured parameters: distance from target to needle tip, distance from planned path to needle tip, distance from midline to needle tip, and distance from the anterior 1/3 of the vertebral body to needle tip. Success within each parameter required that the distance between the needle tip and parameter being evaluated be no more than 5 mm on multiplanar CBCT or fluoroscopy. Results. Imaging data for 12 vertebral levels was available for review. All vertebral levels were treated using unilateral access and 9 levels were treated with an extrapedicular approach. Technical success rates were 92% for both distance from planned path and distance from midline to final needle tip, 100% when distance from needle tip to the anterior 1/3 border of the vertebral body was measured, and 75% when distance from target to needle tip was measured. There were no major complications. Minor complications consisted of 3 cases (25%) of cement extravasation. Conclusion. C-arm CBCT with needle path overlay for fluoroscopic guided vertebroplasty is feasible and allows for reliable unilateral therapy of both lumbar and thoracic vertebral bodies. Extrapedicular approaches were performed safely and with good accuracy of reaching the targets.

Interventional Tool Tracking Using Discrete Optimization

This work presents a novel scheme for tracking of motion and deformation of interventional tools such as guide-wires and catheters in fluoroscopic X-ray sequences. Being able to track and thus to estimate the correct positions of these tools is crucial in order to offer guidance enhancement during interventions. The task of estimating the apparent motion is particularly challenging due to the low signal-to-noise ratio (SNR) of fluoroscopic images and due to combined motion components originating from patient breathing and tool interactions performed by the physician. The presented approach is based on modeling interventional tools with B-splines whose optimal configuration of control points is determined through efficient discrete optimization. Each control point corresponds to a discrete random variable in a Markov random field (MRF) formulation where a set of labels represents the deformation space. In this context, the optimal curve corresponds to the maximum a posteriori (MAP) estimate of the MRF energy. The main motivation for employing a discrete approach is the possibility to incorporate a multi-directional search space which is robust to local minima. This is of particular interest for curve tracking under large deformation. This work analyzes feasibility of employing efficient first-order MRFs for tracking. In particular it shows how to achieve a good compromise between energy approximations and computational efficiency. Experimental results suggest to define both the external and internal energy in terms of pairwise potential functions. The method was successfully applied to the tracking of guide-wires in fluoroscopic X-ray sequences of several hundred frames which requires extremely robust techniques. Comparisons with state-of-the-art guide-wire tracking algorithms confirm the effectiveness of the proposed method.

An efficient graph-based deformable 2D/3D registration algorithm with applications for abdominal aortic aneurysm interventions

2D/3D registration is in general a challenging task due to its ill-posed nature. It becomes even more difficult when deformation between the 3D volume and 2D images needs to be recovered. This paper presents an automatic, accurate and efficient deformable 2D/3D registration method that is formulated on a 3D graph and applied for abdominal aortic aneurysm (AAA) interventions. The proposed method takes the 3D graph generated from a segmentation of the CT volume and the 2D distance map calculated from the 2D X-ray image as the input. The similarity measure consists of a difference measure, a length preservation term and a smoothness regularization term, all of which are defined and efficiently calculated on the graph. A hierarchical registration scheme is further designed specific to the anatomy of abdominal aorta and typical deformations observed during AAA cases. The method was validated using both phantom and clinical datasets, and achieved an average error of > 1mm within 0.1s. The proposed method is of general form and has the potential to be applied for a wide range of applications requiring efficient 2D/3D registration of vascular structures.

Source of Errors and Accuracy of a Two-Dimensional/Three-Dimensional Fusion Road Map for Endovascular Aneurysm Repair of Abdominal Aortic Aneurysm

PURPOSE To evaluate the accuracy and source of errors using a two-dimensional (2D)/three-dimensional (3D) fusion road map for endovascular aneurysm repair (EVAR) of abdominal aortic aneurysm. MATERIALS AND METHODS A rigid 2D/3D road map was tested in 16 patients undergoing EVAR. After 3D/3D manual registration of preoperative multidetector computed tomography (CT) and cone beam CT, abdominal aortic aneurysm outlines were overlaid on live fluoroscopy/digital subtraction angiography (DSA). Patient motion was evaluated using bone landmarks. The misregistration of renal and internal iliac arteries were estimated by 3 readers along head-feet and right-left coordinates (z-axis and x-axis, respectively) before and after bone and DSA corrections centered on the lowest renal artery. Iliac deformation was evaluated by comparing centerlines before and during intervention. A score of clinical added value was estimated as high (z-axis < 3 mm), good (3 mm ≤ z-axis ≤ 5 mm), and low (z-axis > 5 mm). Interobserver reproducibility was calculated by the intraclass correlation coefficient. RESULTS The lowest renal artery misregistration was estimated at x-axis = 10.6 mm ± 11.1 and z-axis = 7.4 mm ± 5.3 before correction and at x-axis = 3.5 mm ± 2.5 and z-axis = 4.6 mm ± 3.7 after bone correction (P = .08), and at 0 after DSA correction (P < .001). After DSA correction, residual misregistration on the contralateral renal artery was estimated at x-axis = 2.4 mm ± 2.0 and z-axis = 2.2 mm ± 2.0. Score of clinical added value was low (n = 11), good (n= 0), and high (n= 5) before correction and low (n = 5), good (n = 4), and high (n = 7) after bone correction. Interobserver intraclass correlation coefficient for misregistration measurements was estimated at 0.99. Patient motion before stent graft delivery was estimated at x-axis = 8 mm ± 5.8 and z-axis = 3.0 mm ± 2.7. The internal iliac artery misregistration measurements were estimated at x-axis = 6.1 mm ± 3.5 and z-axis = 5.6 mm ± 4.0, and iliac centerline deformation was estimated at 38.3 mm ± 15.6. CONCLUSIONS Rigid registration is feasible and fairly accurate. Only a partial reduction of vascular misregistration was observed after bone correction; minimal DSA acquisition is still required.

C-arm Cone Beam Computed Tomographic Needle Path Overlay for Fluoroscopic-Guided Placement of Translumbar Central Venous Catheters

C-arm cone beam computed tomography is an advanced 3D imaging technology that is currently available on state-of-the-art flat-panel-based angiography systems. The overlay of cross-sectional imaging information can now be integrated with real-time fluoroscopy. This overlay technology was used to guide the placement of three percutaneous translumbar inferior vena cava catheters.

Real-Time Respiratory Motion Tracking : Roadmap Correction for Hepatic Artery Catheterizations

Nowadays, hepatic artery catheterizations are performed under live 2D X-ray fluoroscopy guidance, where the visualization of blood vessels requires the injection of contrast agent. The projection of a 3D static roadmap of the complex branches of the liver artery system onto 2D fluoroscopy images can aid catheter navigation and minimize the use of contrast agent. However, the presence of a significant hepatic motion due to patients respiration necessitates a real-time motion correction in order to align the projected vessels. The objective of our work is to introduce dynamic roadmaps into clinical workflow for hepatic artery catheterizations and allow for continuous visualization of the vessels in 2D fluoroscopy images without additional contrast injection. To this end, we propose a method for real-time estimation of the apparent displacement of the hepatic arteries in 2D flouroscopy images. Our approach approximates respiratory motion of hepatic arteries from the catheter motion in 2D fluoroscopy images. The proposed method consists of two main steps. First, a filtering is applied to 2D fluoroscopy images in order to enhance the catheter and reduce the noise level. Then, a part of the catheter is tracked in the filtered images using template matching. A dynamic template update strategy makes our method robust to deformations. The accuracy and robustness of the algorithm are demonstrated by experimental studies on 22 simulated and 4 clinical sequences containing 330 and 571 image frames, respectively.

Multi-modal 2D-3D non-rigid registration

In this paper, we propose a multi-modal non-rigid 2D-3D registration technique. This method allows a non-rigid alignment of a patient pre-operatively computed tomography (CT) to few intra operatively acquired fluoroscopic X-ray images obtained with a C-arm system. This multi-modal approach is especially focused on the 3D alignment of high contrast reconstructed volumes with intra-interventional low contrast X-ray images in order to make use of up-to-date information for surgical guidance and other interventions. The key issue of non-rigid 2D-3D registration is how to define the distance measure between high contrast 3D data and low contrast 2D projections. In this work, we use algebraic reconstruction theory to handle this problem. We modify the Euler-Lagrange equation by introducing a new 3D force. This external force term is computed from the residual of the algebraic reconstruction procedures. In the multi-modal case we replace the residual between the digitally reconstructed radiographs (DRR) and observed X-ray images with a statistical based distance measure. We integrate the algebraic reconstruction technique into a variational registration framework, so that the 3D displacement field is driven to minimize the reconstruction distance between the volumetric data and its 2D projections using mutual information (MI). The benefits of this 2D-3D registration approach are its scalability in the number of used X-ray reference images and the proposed distance that can handle low contrast fluoroscopies as well. Experimental results are presented on both artificial phantom and 3D C-arm CT images.

Toward smart utilization of two X-ray images for 2-D/3-D registration applied to abdominal aortic aneurysm interventions

Minimally invasive abdominal aortic aneurysm stenting can be greatly facilitated by overlaying the pre-operative 3-D model of the abdominal aorta onto the intra-operative 2-D X-ray images. Accurate 2-D/3-D registration in 3-D space makes the 2-D/3-D overlay robust to the change of C-Arm angulations. Typically at least two X-ray images showing the abdominal aorta with contrast medium from different angles are needed for an accurate registration in 3-D space. In this paper, a novel 2-D/3-D registration technique is proposed for using only one image with contrast medium in the abdominal aorta and one native image showing the spine to achieve accurate registration of the abdominal aorta in 3-D. The proposed method utilizes the two X-ray images in an integrated but differentiated way in order to best utilize the complementary information provided by the two types of images. A hierarchical registration scheme is deployed by a sensible partition of the registration parameter space based on the image acquisition protocol. The proposed method was validated using both synthetic and clinical datasets, and achieved significantly improved accuracy and robustness compared to the conventional methods.

Recognition of handwritten digits using structural information

This article presents an off-line method for recognizing handwritten digits. Structural information and quantitative features are extracted from images of isolated numerals to be classified by a hybrid multi-stage recognition system. Feature extraction starts with the raw pixel-image and derives more structured representations like line-drawings and attributed structural graphs. Classification is done in two steps: 1) the structural graph is matched to prototypes; 2) for each prototype there is a neural classifier which has been trained to distinguish digits represented by the same graph-structure. The performance of the described system is evaluated on two large databases (provided by SIEMENS AG and NIST) and is compared to other systems. Finally, the combination of the described system and a time-delay neural network classifier is discussed. The experimental results indicate that there is an advantage in using structural information to enhance an unstructured neural classifier.