Showing papers by "Robert J. Lederman published in 2010"

Robust automatic rigid registration of MRI and X‐ray using external fiducial markers for XFM‐guided interventional procedures

Abstract: Purpose: In X-ray fused with MRI, previously gathered roadmap MRI volume images are overlaid on live X-ray fluoroscopy images to help guide the clinician during an interventional procedure. The incorporation of MRI data allows for the visualization of soft tissue that is poorly visualized under X-ray. The widespread clinical use of this technique will require fully automating as many components as possible. While previous use of this method has required time-consuming manual intervention to register the two modalities, in this article, the authors present a fully automatic rigid-body registration method. Methods: External fiducial markers that are visible under these two complimentary imaging modalities were used to register the X-ray images with the roadmap MR images. The method has three components: (a) The identification of the 3D locations of the markers from a full 3D MR volume, (b) the identification of the 3D locations of the markers from a small number of 2D X-ray fluoroscopy images, and (c) finding the rigid-body transformation that registers the two point sets in the two modalities. For part (a), the localization of the markers from MR data, the MR volume image was thresholded, connected voxels were segmented and labeled, and the centroids of the connected components were computed. For part (b), the X-ray projection images, produced by an image intensifier, were first corrected for distortions. Binary mask images of the markers were created from the distortion-corrected X-ray projection images by applying edge detection, pattern recognition, and image morphological operations. The markers were localized in the X-ray frame using an iterative backprojection-based method which segments voxels in the volume of interest, discards false positives based on the previously computed edge-detected projections, and calculates the locations of the true markers as the centroids of the clusters of voxels that remain. For part (c), a variant of the iterative closest point method was used to find correspondences between and register the two sets of points computed from MR and X-ray data. This knowledge of the correspondence between the two point sets was used to refine, first, the X-ray marker localization and then the total rigid-body registration between modalities. The rigid-body registration was used to overlay the roadmap MR image onto the X-ray fluoroscopy projections. Results: In 35 separate experiments, the markers were correctly registered to each other in 100% of the cases. When half the number of X-ray projections was used (10 X-ray projections instead of 20), the markers were correctly registered in all 35 experiments. The method was also successful in all 35 experiments when the number of markers was (retrospectively) halved (from 16 to 8). The target registration error was computed in a phantom experiment to be less than 2.4 mm. In two in vivo experiments, targets (interventional devices with pointlike metallic structures) inside the heart were successfully registered between the two modalities. Conclusions: The method presented can be used to automatically register a roadmap MR image to X-ray fluoroscopy using fiducial markers and as few as ten X-ray projections.

Interventional MRI using Multiple 3D Angiography Roadmaps with Real-time Imaging

Abstract: Purpose: To enhance real-time magnetic resonance (MR)-guided catheter navigation by overlaying colorized multiphase MR angiography (MRA) and cholangiopancreatography (MRCP) roadmaps in an anatomic context. Materials and Methods: Time-resolved MRA and respiratory-gated MRCP were acquired prior to real-time imaging in a pig model. MRA and MRCP data were loaded into a custom real-time MRI reconstruction and visualization workstation where they were displayed as maximum intensity projections (MIPs) in distinct colors. The MIPs were rendered in 3D together with real-time multislice imaging data using alpha blending. Interactive rotation allowed different views of the combined data. Results: Fused display of the previously acquired MIP angiography data with real-time imaging added anatomical context during endovascular interventions in swine. The use of multiple MIPs rendered in different colors facilitated differentiation of vascular structures, improving visual feedback during device navigation. Conclusion: Interventional real-time MRI may be enhanced by combining with previously acquired multiphase angiograms. Rendered as 3D MIPs together with 2D slice data, this technique provided useful anatomical context that enhanced MRI-guided interventional applications. J. Magn. Reson. Imaging 2010;31:1015–1019. ©2010 Wiley-Liss, Inc.

Visualization of active devices and automatic slice repositioning (“SnapTo”) for MRI‐guided interventions

Abstract: The accurate visualization of interventional devices is crucial for the safety and effectiveness of MRI-guided interventional procedures. In this paper, we introduce an improvement to the visualization of active devices. The key component is a fast, robust method (“CurveFind”) that reconstructs the three-dimensional trajectory of the device from projection images in a fraction of a second. CurveFind is an iterative prediction-correction algorithm that acts on a product of orthogonal projection images. By varying step size and search direction, it is robust to signal inhomogeneities. At the touch of a key, the imaged slice is repositioned to contain the relevant section of the device (“SnapTo”), the curve of the device is plotted in a three-dimensional display, and the point on a target slice, which the device will intersect, is displayed. These features have been incorporated into a real-time MRI system. Experiments in vitro and in vivo (in a pig) have produced successful results using a variety of single- and multichannel devices designed to produce both spatially continuous and discrete signals. CurveFind is typically able to reconstruct the device curve, with an average error of approximately 2 mm, even in the case of complex geometries. Magn Reson Med 63:1070–1079, 2010. © 2010 Wiley-Liss, Inc.

Efficient implementation of hardware-optimized gradient sequences for real-time imaging.

Abstract: This work improves the performance of interactive real-time imaging with balanced steady-state free precession. The method employs hardware-optimized gradient pulses, together with a novel phase-encoding strategy that simplifies the design and implementation of the optimized gradient waveforms. In particular, the waveforms for intermediate phase-encode steps are obtained by simple linear combination, rather than separate optimized waveform calculations. Gradient waveforms are redesigned in real time as the scan plane is manipulated, and the resulting sequence operates at the specified limits of the MRI gradient subsystem for each new scan-plane orientation. The implementation provides 14-25% improvement in the sequence pulse repetition time over the vendor-supplied interactive real-time imaging sequence for similar scan parameters on our MRI scanner.

RT-GROG: parallelized self-calibrating GROG for real-time MRI

Abstract: A real-time implementation of self-calibrating Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) operator gridding for radial acquisitions is presented. Self-calibrating GRAPPA operator gridding is a parallel-imaging-based, parameter-free gridding algorithm, where coil sensitivity profiles are used to calculate gridding weights. Self-calibrating GRAPPA operator gridding’s weight-set calculation and image reconstruction steps are decoupled into two distinct processes, implemented in C11 and parallelized. This decoupling allows the weights to be updated adaptively in the background while image reconstruction threads use the most recent gridding weights to grid and reconstruct images. All possible combinations of two-dimensional gridding weights G m G n are evaluated for m,n 5 {20.5, 20.4, ... , 0, 0.1, ... , 0.5} and stored in a look-up table. Consequently, the per-sample two-dimensional weights calculation during gridding is eliminated from the reconstruction process and replaced by a simple look-up table access. In practice, up to 343 faster reconstruction than conventional (parallelized) self-calibrating GRAPPA operator gridding is achieved. On a 32-coil dataset of size 128 3 64, reconstruction performance is 14.5 frames per second (fps), while the data acquisition is 6.6 fps. Magn Reson Med 64:306–312, 2010. V C 2010 Wiley-Liss, Inc.

Closed chest transthoracic perventricular ventricular septal defect closure under real-time MRI

Abstract: Introduction Muscular ventricular septal defect (VSD) is common, and can be congenital, post-infarction, or post-traumatic. Real-time MRI can provide surgical-grade exposure for non-surgical procedures. One innovative pediatric surgical procedure is device closure of ventricular septal defect using catheter techniques through an open chest. We attempt to conduct this same procedure in a closed chest model using real-time MRI.

An interleaved-navigator projection dual-echo bSSFP sequence for respiratory self-gated imaging

Abstract: Introduction Recently, self-navigation has become an alternative to breath-holding and respiratory navigators for cardiac MR scans [1-3]. Current sequences acquire a high spatial-resolution navigator projection every cardiac phase [i.e. [4]], a lower resolution navigator every TR, or a complete image with lower temporal resolution [2]. Temporal or spatial resolution is sacrificed to minimize the loss of imaging efficiency. Here, we propose a dual-echo balanced SSFPbased imaging sequence that acquires a constant navigator projection during every TR and alternates navigator projection direction for robust motion measurement.

Getting closer for high-resolution vascular MRI.

Abstract: Since the 1980s, investigators have tried to enhance vascular magnetic resonance imaging (MRI) and spectroscopy of deep structures by positioning MRI receiver coils (antennae) inside the body, closer to the tissue of interest ([1,2][1]). Unfortunately, intravascular MRI has been largely