Marcus Prümmer

Cardiac C-Arm CT: A Unified Framework for Motion Estimation and Dynamic CT

Generating 3-D images of the heart during interventional procedures is a significant challenge. In addition to real time fluoroscopy, angiographic C-arm systems can also now be used to generate 3-D/4-D CT images on the same system. One protocol for cardiac CT uses ECG triggered multisweep scans. A 3-D volume of the heart at a particular cardiac phase is then reconstructed by applying Feldkamp (FDK) reconstruction to the projection images with retrospective ECG gating. In this work we introduce a unified framework for heart motion estimation and dynamic cone-beam reconstruction using motion corrections. The benefits of motion correction are 1) increased temporal and spatial resolution by removing cardiac motion which may still exist in the ECG gated data sets and 2) increased signal-to-noise ratio (SNR) by using more projection data than is used in standard ECG gated methods. Three signal-enhanced reconstruction methods are introduced that make use of all of the acquired projection data to generate a 3-D reconstruction of the desired cardiac phase. The first averages all motion corrected back-projections; the second and third perform a weighted averaging according to 1) intensity variations and 2) temporal distance relative to a time resolved and motion corrected reference FDK reconstruction. In a comparison study seven methods are compared: nongated FDK, ECG-gated FDK, ECG-gated, and motion corrected FDK, the three signal-enhanced approaches, and temporally aligned and averaged ECG-gated FDK reconstructions. The quality measures used for comparison are spatial resolution and SNR. Evaluation is performed using phantom data and animal models. We show that data driven and subject-specific motion estimation combined with motion correction can decrease motion-related blurring substantially. Furthermore, SNR can be increased by up to 70% while maintaining spatial resolution at the same level as is provided by the ECG-gated FDK. The presented framework provides excellent image quality for cardiac C-arm CT.

Semi-automatic level-set based segmentation and stenosis quantification of the internal carotid artery in 3D CTA data sets

We present a new level-set based method to segment and quantify stenosed internal carotid arteries (ICAs) in 3D contrast-enhanced computed tomography angiography (CTA). Within these data sets it is a difficult task to evaluate the degree of stenoses deterministically even for the experienced physician because the actual vessel lumen is hardly distinguishable from calcified plaque and there is no sharp border between lumen and arterial wall. According to our knowledge no commercially available software package allows the detection of the boundary between lumen and plaque components. Therefore in the clinical environment physicians have to perform the evaluation manually. This approach suffers from both intra- and inter-observer variability. The limitation of the manual approach requires the development of a semi-automatic method that is able to achieve deterministic segmentation results of the internal carotid artery via level-set techniques. With the new method different kinds of plaques were almost completely excluded from the segmented regions. For an objective evaluation we also studied the methods performance with four different phantom data sets for which the ground truth of the degree of stenosis was known a priori. Finally, we applied the method to 10 ICAs and compared the obtained segmentations with manual measurements of three physicians.

Interventional 4D motion estimation and reconstruction of cardiac vasculature without motion periodicity assumption

Anatomical and functional information of cardiac vasculature is a key component in the field of interventional cardiology. With the technology of C-arm CT it is possible to reconstruct static intraprocedural 3D images from angiographic projection data. Current approaches attempt to add the temporal dimension (4D). In the assumption of periodic heart motion, ECG-gating techniques can be used. However, arrhythmic heart signals and slight breathing motion are degrading image quality frequently. To overcome those problems, we present a reconstruction method based on a 4D time-continuous B-spline motion field. The temporal component of the motion field is parameterized by the acquisition time and does not assume a periodic heart motion. The analytic dynamic FDK-reconstruction formula is used directly for the motion estimation and image reconstruction. In a physical phantom experiment two vessels of size 3.1mm and 2.3mm were reconstructed using the proposed method and an algorithm with periodicity assumption. For a periodic motion both methods obtained an error of 0.1mm. For a non-periodic motion the proposed method was superior, obtaining an error of 0.3mm/0.2mm in comparison to 1.2mm/1.0mm for the algorithm with periodicity assumption. For a clinical test case of a left coronary artery it could be further shown that the method is capable to produce diameter measurements with an absolute error of 0.1mm compared to state-of-the-art measurement tools from orthogonal coronary angiography. Further, it is shown for three different clinical cases (left/right coronary artery, coronary sinus) that the proposed method is able to handle a large variability of vascular structures and motion patterns. The complete algorithm is hardware-accelerated using the GPU requiring a computation time of less than 3min for typical clinical scenarios.

C-arm CT: Reconstruction of dynamic high contrast objects applied to the coronary sinus

For many interventional procedures the 3-D reconstruction of dynamic high contrast objects from C-arm data is desirable. We present a method for compensating artifacts from periodic motions by providing a modified filtered backprojection algorithm. The proposed algorithm comprises three steps: First, the reconstruction of an initial reference volume from a phase-consistent subset of the projection data. Secondly, the selection of proper data for a motion corrected reconstruction using as many projections as possible in the third step. The first step is addressed by gating in combination with a modified backprojection operator which reduces streak artifacts, the second by analysis of the cardiac motion characteristics and the impact on gated reconstruction quality and the third by accumulating gated sub-reconstructions registered with the reference volume. We present first clinical results from real patient data for the reconstruction of the coronary sinus.

Adaptive variational sinogram interpolation of sparsely sampled CT data

We present various kinds of variational PDE based methods to interpolate missing sinogram data for tomographic image reconstruction. Using the observed sinogram data we inpaint the projection data by diffusion. To overcome the problem of contour blurring we consider nonlinear and anisotropic diffusion based regularizes and include optical flow information in order to preserve the sinusoidal traces corresponding to object contours in the reconstructed image. We compare our results to a spectral deconvolution based interpolation and show that the method can easily be extended to 3D

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.

Interventional 4-D Motion Estimation and Reconstruction of Cardiac Vasculature without Motion Periodicity Assumption

Anatomical and functional information of cardiac vasculature is a key component of future developments in the field of interventional cardiology. With the technology of C-arm CT it is possible to reconstruct intraprocedural 3-D images from angiographic projection data. Current approaches attempt to add the temporal dimension (4-D) by ECG-gating in order to distinct physical states of the heart. This model assumes that the heart motion is periodic. However, frequently arrhytmic heart signals are observed in a clinical environment. In addition breathing motion can still occur. We present a reconstruction method based on a 4-D time-continuous motion field which is parameterized by the acquisition time and not the quasi-periodic heart phase. The output of our method is twofold. It provides a motion compensated 3-D reconstruction (anatomic information) and a motion field (functional information). In a physical phantom experiment a vessel of size 3.08 mm undergoing a non-periodic motion was reconstructed. The resulting diameters were 3.42 mm and 1.85 mm assuming non-periodic and periodic motion, respectively. Further, for two clinical cases (coronary arteries and coronary sinus) it is demonstrated that the presented algorithm outperforms periodic approaches and is able to handle realistic irregular heart motion.

OpenCL: a viable solution for high-performance medical image reconstruction?

Reconstruction of 3-D volumetric data from C-arm CT projections is a computationally demanding task. For interventional image reconstruction, hardware optimization is mandatory. Manufacturers of medical equipment use a variety of high-performance computing (HPC) platforms, like FPGAs, graphics cards, or multi-core CPUs. A problem of this diversity is that many different frameworks and (vendor-specific) programming languages are used. Furthermore, it is costly to switch the platform, since the code has to be re-written, verified, and optimized. OpenCL, a relatively new industry standard for HPC, promises to enable portable code. Its key idea is to abstract hardware in a way that allows an efficient mapping onto real CPUs, GPUs, and other hardware. The code is compiled for the actual target by the device driver. In this work we investigated the suitability of OpenCL as a tool to write portable code that runs efficiently across different hardware. The problems chosen are back- and forward-projection, the most time-consuming parts of (iterative) reconstruction. We present results on three platforms, a multi-core CPU system and two GPUs, and compare them against manually optimized native implementations. We found that OpenCL allows to share a common framework in one language across platforms. However, considering differences in the underlying architecture, a hardware-oblivious implementation cannot be expected to deliver maximal performance. By optimizing the OpenCL code for the specific hardware we reached over 90% of native performance for both problems, back- and forward-projection, on all platforms.

Phase-unwrapping of differential phase-contrast data using attenuation information

Phase-contrast imaging approaches suffer from a severe problem which is known in Magnetic Resonance Imaging (MRI) and Synthetic Aperture Radar (SAR) as phase-wrapping. This work focuses on an unwrapping solution for the grating based phase-contrast interferometer with X-rays. The approach delivers three types of information about the x-rayed object - the absorption, differential phase-contrast and dark-field information whereas the observed differential phase values are physically limited to the interval (-π, π]; values higher or lower than the interval borders are mapped (wrapped) back into it. In contrast to existing phase-unwrapping algorithms for MRI and SAR the presented algorithm uses the absorption image as additional information to identify and correct phase-wrapped values. The idea of the unwrapping algorithm is based on the observation that at locations with phase-wrapped values the contrast in the absorption image is high and the behavior of the gradient is similar to the real (unwrapped) phase values. This can be expressed as a cost function which has to be minimized by an integer optimizer. Applied on simulated and real datasets showed that 95.6% of phase-wraps were correctly unwrapped. Based on the results we conclude that it is possible to use the absorption information in order to identify and correct phase-wrapped values.

4D motion animation of coronary arteries from rotational angiography

Time-resolved 3-D imaging of the heart is a major research topic in the medical imaging community. Recent advances in the interventional cardiac 3-D imaging from rotational angiography (C-arm CT) are now also making 4-D imaging feasible during procedures in the catheter laboratory. State-of-the-art reconstruction algorithms try to estimate the cardiac motion and utilize the motion field to enhance the reconstruction of a stable cardiac phase (diastole). The available data offers a handful of opportunities during interventional procedures, e.g. the ECG-synchronized dynamic roadmapping or the computation and analysis of functional parameters. In this paper we will demonstrate that the motion vector field (MVF) that is output by motion compensated image reconstruction algorithms is in general not directly usable for animation and motion analysis. Dependent on the algorithm different defects are investigated. A primary issue is that the MVF needs to be inverted, i.e. the wrong direction of motion is provided. A second major issue is the non-periodicity of cardiac motion. In algorithms which compute a non-periodic motion field from a single rotation the in depth motion information along viewing direction is missing, since this cannot be measured in the projections. As a result, while the MVF improves reconstruction quality, it is insufficient for motion animation and analysis. We propose an algorithm to solve both problems, i.e. inversion and missing in-depth information in a unified framework. A periodic version of the MVF is approximated. The task is formulated as a linear optimization problem where a parametric smooth motion model based on B-splines is estimated from the MVF. It is shown that the problem can be solved using a sparse QR factorization within a clinical feasible time of less than one minute. In a phantom experiment using the publicly available CAVAREV platform, the average quality of a non-periodic animation could be increased by 39% by applying the proposed periodization and inversion method.