Christopher Rohkohl

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.

Improving best-phase image quality in cardiac CT by motion correction with MAM optimization.

PURPOSE Research in image reconstruction for cardiac CT aims at using motion correction algorithms to improve the image quality of the coronary arteries. The key to those algorithms is motion estimation, which is currently based on 3-D/3-D registration to align the structures of interest in images acquired in multiple heart phases. The need for an extended scan data range covering several heart phases is critical in terms of radiation dose to the patient and limits the clinical potential of the method. Furthermore, literature reports only slight quality improvements of the motion corrected images when compared to the most quiet phase (best-phase) that was actually used for motion estimation. In this paper a motion estimation algorithm is proposed which does not require an extended scan range but works with a short scan data interval, and which markedly improves the best-phase image quality. METHODS Motion estimation is based on the definition of motion artifact metrics (MAM) to quantify motion artifacts in a 3-D reconstructed image volume. The authors use two different MAMs, entropy, and positivity. By adjusting the motion field parameters, the MAM of the resulting motion-compensated reconstruction is optimized using a gradient descent procedure. In this way motion artifacts are minimized. For a fast and practical implementation, only analytical methods are used for motion estimation and compensation. Both the MAM-optimization and a 3-D/3-D registration-based motion estimation algorithm were investigated by means of a computer-simulated vessel with a cardiac motion profile. Image quality was evaluated using normalized cross-correlation (NCC) with the ground truth template and root-mean-square deviation (RMSD). Four coronary CT angiography patient cases were reconstructed to evaluate the clinical performance of the proposed method. RESULTS For the MAM-approach, the best-phase image quality could be improved for all investigated heart phases, with a maximum improvement of the NCC value by 100% and of the RMSD value by 81%. The corresponding maximum improvements for the registration-based approach were 20% and 40%. In phases with very rapid motion the registration-based algorithm obtained better image quality, while the image quality of the MAM algorithm was superior in phases with less motion. The image quality improvement of the MAM optimization was visually confirmed for the different clinical cases. CONCLUSIONS The proposed method allows a software-based best-phase image quality improvement in coronary CT angiography. A short scan data interval at the target heart phase is sufficient, no additional scan data in other cardiac phases are required. The algorithm is therefore directly applicable to any standard cardiac CT acquisition protocol.

Interventional 4-D C-Arm CT Perfusion Imaging Using Interleaved Scanning and Partial Reconstruction Interpolation

Tissue perfusion measurement during catheter-guided stroke treatment in the interventional suite is currently not possible. In this work, we present a novel approach that uses a C-arm angiography system capable of computed tomography (CT)-like imaging (C-arm CT) for this purpose. With C-arm CT one reconstructed volume can be obtained every 4-6 s which makes it challenging to measure the flow of an injected contrast bolus. We have developed an interleaved scanning (IS) protocol that uses several scan sequences to increase temporal sampling. Using a dedicated 4-D reconstruction approach based on partial reconstruction interpolation (PRI) we can optimally process our data. We evaluated our combined approach (IS-PRI) with simulations and a study in five healthy pigs. In our simulations, the cerebral blood flow values (unit: ml/100 g/min) were 60 (healthy tissue) and 20 (pathological tissue). For one scan sequence the values were estimated with standard deviations of 14.3 and 2.9, respectively. For two interleaved sequences the standard deviations decreased to 3.6 and 1.5, respectively. We used perfusion CT to validate the in vivo results. With two interleaved sequences we achieved promising correlations ranging from r=0.63 to r=0.94. The results suggest that C-arm CT tissue perfusion imaging is feasible with two interleaved scan sequences.

CAVAREV?an open platform for evaluating 3D and 4D cardiac vasculature reconstruction

The 3D reconstruction of cardiac vasculature, e.g. the coronary arteries, using C-arm CT (rotational angiography) is an active and challenging field of research. There are numerous publications on different reconstruction techniques. However, there is still a lack of comparability of achieved results for several reasons: foremost, datasets used in publications are not open to public and thus experiments are not reproducible by other researchers. Further, the results highly depend on the vasculature motion, i.e. cardiac and breathing motion patterns which are also not comparable across publications. We aim to close this gap by providing an open platform, called CAVAREV (CArdiac VAsculature Reconstruction EValuation). It features two simulated dynamic projection datasets based on the 4D XCAT phantom with contrasted coronary arteries which was derived from patient data. In the first dataset, the vasculature undergoes a continuous periodic motion. The second dataset contains aperiodic heart motion by including additional breathing motion. The geometry calibration and acquisition protocol were obtained from a real-world C-arm system. For qualitative evaluation of the reconstruction results, the correlation of the morphology is used. Two segmentation-based quality measures are introduced which allow us to assess the 3D and 4D reconstruction quality. They are based on the spatial overlap of the vasculature reconstruction with the ground truth. The measures enable a comprehensive analysis and comparison of reconstruction results independent from the utilized reconstruction algorithm. An online platform (www.cavarev.com) is provided where the datasets can be downloaded, researchers can manage and publish algorithm results and download a reference C++ and Matlab implementation.

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.

Inverse C-arm Positioning for Interventional Procedures Using Real-Time Body Part Detection

The automation and speedup of interventional therapy and diagnostic workflows is a crucial issue. One way to improve these work-flows is to accelerate the image acquisition procedures by fully automating the patient setup. This paper describes a system that performs this task without the use of markers or other prior assumptions. It returns metric coordinates of the 3-D body shape in real-time for inverse positioning. This is achieved by the application of an emerging technology, called Time-of-Flight (ToF) sensor. A ToF sensor is a cost-efficient, off-the-shelf camera which provides more than 40,000 3-D points in real-time. The first contribution of this paper is the incorporation of this novel imaging technology (ToF) in interventional imaging. The second contribution is the ability of a C-arm system to position itself with respect to the patient prior to the acquisition. We are using the 3-D surface information of the patient to partition the body into anatomical sections. This is achieved by a fast two-stage classification process. The system computes the ISO-center for each detected region. To verify our system we performed several tests on the ISO-center of the head. Firstly, the reproducibility of the head ISO-center computation was evaluated. We achieved an accuracy of (x: 1.73 +/- 1.11 mm/y: 1.87 +/- 1.31 mm/z: 2.91 +/- 2.62 mm). Secondly, a C-arm head scan of a body phantom was setup. Our system automatically aligned the ISO-center of the head with the C-arm ISO-center. Here we achieved an accuracy of +/- 1 cm, which is within the accuracy of the patient table control.

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.

Evaluation of interpolation methods for surface-based motion compensated tomographic reconstruction for cardiac angiographic C-arm data

PURPOSE For interventional cardiac procedures, anatomical and functional information about the cardiac chambers is of major interest. With the technology of angiographic C-arm systems it is possible to reconstruct intraprocedural three-dimensional (3D) images from 2D rotational angiographic projection data (C-arm CT). However, 3D reconstruction of a dynamic object is a fundamental problem in C-arm CT reconstruction. The 2D projections are acquired over a scan time of several seconds, thus the projection data show different states of the heart. A standard FDK reconstruction algorithm would use all acquired data for a filtered backprojection and result in a motion-blurred image. In this approach, a motion compensated reconstruction algorithm requiring knowledge of the 3D heart motion is used. The motion is estimated from a previously presented 3D dynamic surface model. This dynamic surface model results in a sparse motion vector field (MVF) defined at control points. In order to perform a motion compensated reconstruction, a dense motion vector field is required. The dense MVF is generated by interpolation of the sparse MVF. Therefore, the influence of different motion interpolation methods on the reconstructed image quality is evaluated. METHODS Four different interpolation methods, thin-plate splines (TPS), Shepards method, a smoothed weighting function, and a simple averaging, were evaluated. The reconstruction quality was measured on phantom data, a porcine model as well as on in vivo clinical data sets. As a quality index, the 2D overlap of the forward projected motion compensated reconstructed ventricle and the segmented 2D ventricle blood pool was quantitatively measured with the Dice similarity coefficient and the mean deviation between extracted ventricle contours. For the phantom data set, the normalized root mean square error (nRMSE) and the universal quality index (UQI) were also evaluated in 3D image space. RESULTS The quantitative evaluation of all experiments showed that TPS interpolation provided the best results. The quantitative results in the phantom experiments showed comparable nRMSE of ≈0.047 ± 0.004 for the TPS and Shepards method. Only slightly inferior results for the smoothed weighting function and the linear approach were achieved. The UQI resulted in a value of ≈ 99% for all four interpolation methods. On clinical human data sets, the best results were clearly obtained with the TPS interpolation. The mean contour deviation between the TPS reconstruction and the standard FDK reconstruction improved in the three human cases by 1.52, 1.34, and 1.55 mm. The Dice coefficient showed less sensitivity with respect to variations in the ventricle boundary. CONCLUSIONS In this work, the influence of different motion interpolation methods on left ventricle motion compensated tomographic reconstructions was investigated. The best quantitative reconstruction results of a phantom, a porcine, and human clinical data sets were achieved with the TPS approach. In general, the framework of motion estimation using a surface model and motion interpolation to a dense MVF provides the ability for tomographic reconstruction using a motion compensation technique.

Three-dimensional coronary sinus reconstruction-guided left ventricular lead implantation based on intraprocedural rotational angiography: a novel imaging modality in cardiac resynchronization device implantation †

AIMS Rotational angiography (RA) of the coronary sinus (CS) provides more anatomical insights compared with static angiographies. We evaluated intraprocedural three-dimensional (3D) CS reconstruction (RC) based on RA, using syngo(®) DynaCT Cardiac to guide CS lead implantation. METHODS AND RESULTS In 24 patients with indication for cardiac resynchronization therapy, intraprocedural RA and 3D RC of the CS was performed. Lead placement was guided by 3D image integration into real-time fluoroscopy. Rotational angiography and 3D RCs were evaluated regarding visibility of the CS and tributaries, CS-to-target vein angles, and vessel diameters. The target vein for CS lead implantation, identified by RA, was successfully displayed by 3D RC in 20 (91%) of 22 patients with adequate RA. All lead implantations were guided successfully by 3D image integration into real-time fluoroscopy. Cranial or caudal angulations were used in 95% of the procedures without further angiographies. Rotational angiography displayed a mean of 2.9 ± 1.0 second-order side branches compared with 1.8 ± 1.1 in 3D RCs (P< 0.05). The CS-to-target vein angle estimated from static projections (right anterior oblique 20°, left anterior oblique 40°, and even optimal RA view) differed substantially from 3D RCs. Main vessel diameters did not differ significantly between both techniques. CONCLUSION Intraprocedural 3D RC of the CS and 3D image integration-guided lead placement is feasible. Coronary sinus-to-target vein angles seemed to be misestimated even by RA views compared with 3D RC. Thus RA and 3D CS RC should be applied routinely for CS lead implantation.

Automatic extraction of 3d dynamic left ventricle model from 2d rotational angiocardiogram

In this paper, we propose an automatic method to directly extract 3D dynamic left ventricle (LV) model from sparse 2D rotational angiocardiogram (each cardiac phase contains only five projections). The extracted dynamic model provides quantitative cardiac function for analysis. The overlay of the model onto 2D real-time fluoroscopic images provides valuable visual guidance during cardiac intervention. Though containing severe cardiac motion artifacts, an ungated CT reconstruction is used in our approach to extract a rough static LV model. The initialized LV model is projected onto each 2D projection image. The silhouette of the projected mesh is deformed to match the boundary of LV blood pool. The deformation vectors of the silhouette are back-projected to 3D space and used as anchor points for thin plate spline (TPS) interpolation of other mesh points. The proposed method is validated on 12 synthesized datasets. The extracted 3D LV meshes match the ground truth quite well with a mean point-to-mesh error of 0.51 +/- 0.11 mm. The preliminary experiments on two real datasets (included a patient and a pig) show promising results too.