Impact of a new metal artefact reduction algorithm in the noninvasive follow-up of intracranial clips, coils, and stents with flat-panel angiographic CTA: initial results.

INTRODUCTION: Flat-panel angiographic CT after intravenous contrast agent application (ivACT) is increasingly used as a follow-up examination after coiling, clipping, or stenting. The purpose of this study was to evaluate the feasibility of a new metal artefact reduction algorithm (MARA) in patients treated for intracranial aneurysms and stenosis. METHODS: IvACT was performed on a flat-panel detector angiography system after intravenous application of 80 ml contrast media. The uncorrected raw images were transferred to a prototype reconstruction workstation where the MARA was applied. Two experienced neuroradiologists examined the corrected and uncorrected images on a commercially available workstation. RESULTS: Artefacts around the implants were detected in all 16 uncorrected cases, while eight cases showed remaining artefacts after correction with the MARA. In the cases without correction, there were 11 cases with "extensive" artefacts and five cases with "many" artefacts. After correction, seven cases showed "few" and only one case "many" artefacts (Wilcoxon test, P < 0.001). Parent vessels were characterized as "not identifiable" in 62% of uncorrected images, while the delineation of parent vessels were classified as "excellent" in 50% of the cases after correction (Wilcoxon test, P = 0.001). CONCLUSIONS: Use of the MARA in our study significantly reduced artefacts around metallic implants on ivACT images and allowed for the delineation of surrounding structures.

Comparing performance of many-core CPUs and GPUs for static and motion compensated reconstruction of C-arm CT data.

PURPOSE: Interventional reconstruction of 3-D volumetric data from C-arm CT projections is a computationally demanding task. Hardware optimization is not an option but mandatory for interventional image processing and, in particular, for image reconstruction due to the high demands on performance. Several groups have published fast analytical 3-D reconstruction on highly parallel hardware such as GPUs to mitigate this issue. The authors show that the performance of modern CPU-based systems is in the same order as current GPUs for static 3-D reconstruction and outperforms them for a recent motion compensated (3-D+time) image reconstruction algorithm. METHODS: This work investigates two algorithms: Static 3-D reconstruction as well as a recent motion compensated algorithm. The evaluation was performed using a standardized reconstruction benchmark, RABBITCT, to get comparable results and two additional clinical data sets. RESULTS: The authors demonstrate for a parametric B-spline motion estimation scheme that the derivative computation, which requires many write operations to memory, performs poorly on the GPU and can highly benefit from modern CPU architectures with large caches. Moreover, on a 32-core Intel Xeon server system, the authors achieve linear scaling with the number of cores used and reconstruction times almost in the same range as current GPUs. CONCLUSIONS: Algorithmic innovations in the field of motion compensated image reconstruction may lead to a shift back to CPUs in the future. For analytical 3-D reconstruction, the authors show that the gap between GPUs and CPUs became smaller. It can be performed in less than 20 s (on-the-fly) using a 32-core server.

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.

Motion compensation in the region of the coronary arteries based on partial angle reconstructions from short-scan CT data.

PURPOSE: In order to mitigate motion-induced artifacts, several motion compensation (MoCo) methods have been developed, which are either able to (a) compensate for severe artifacts, but utilize the data for the reconstruction of several cardiac phases, or (b) improve image quality of a single reconstruction with only moderate motion artifacts. We propose a method combining both benefits: dose efficiency by utilizing only the data needed for a single short-scan reconstruction while still being able to compensate for severe artifacts. METHODS: We introduce a MoCo method, which we call PAMoCo, to improve the visualization of the coronary arteries of a standard coronary CT angiography exam by reducing motion artifacts. As a first step, we segment a region of interest covering a chosen coronary artery. We subdivide a volume covering the whole heart into several stacks, which are sub-volumes, reconstructed from phase-correlated short-scan data acquired during different heart cycles. Motion-compensated reconstruction is performed for each stack separately, based on partial angle reconstructions, which are derived by dividing the data corresponding to the segmented stack volume into several double-overlapping sectors. We model motion along the coronary artery center line obtained from segmentation and the temporal dimension by a low-degree polynomial and create a dense 3D motion vector field (MVF). The parameters defining the MVF are estimated by optimizing an image artifact measuring cost function and we employ a semi-global optimization routine by re-initializing the optimization multiple times. The algorithm was evaluated on the basis of a phantom measurement and clinical data. For the phantom measurement an artificial vessel equipped with calcified lesions mounted on a moving robot arm was measured, where typical coronary artery motion patterns for 70 bpm and 90 bpm have been applied. For analysis, we calculated the calcified volume V inside an ROI and measured the maximum vessel diameter d based on cross-sectional views to compare the performances of standard reconstructions obtained via filtered backprojection (FBP) and PAMoCo reconstructions between 20% and 80% of the cardiac cycle. Further, the new algorithm was applied to six clinical cases of patients with heart rates between 50 bpm and 74 bpm. Standard FBP, PAMoCo reconstructions were performed and compared to best phase FBP reconstructions and another MoCo algorithm, which is based on motion artifact metrics (MAM), via visual inspection. RESULTS: In case of the phantom measurement we found a strong dependence of V and d on the cardiac phase in case of the FBP reconstructions. When applying PAMoCo, V and d became almost constant due to a better discrimination from calcium to vessel and water background and values close to the ground truth have been derived. In the clinical study we chose reconstructions showing strong motion artifacts and observed a substantially improved delineation of the coronary arteries in PAMoCo reconstructions compared to the standard FBP reconstructions and also the MAM images, confirming the findings of the phantom measurement. CONCLUSIONS: Due to the fast reconstruction of PAMoCo images and the introduction of a new motion model, we were able to re-initialize the optimization routine at pre-selected parameter sets and thereby increase the potential of the MAM algorithm. From the phantom measurement we conclude that PAMoCo performed almost equally well in all cardiac phases and suggest applying the PAMoCo algorithm for single source systems in case of patients with high or irregular heart rates.

Patient-individualized boundary conditions for CFD simulations using time-resolved 3D angiography.

PURPOSE: Hemodynamic simulations are of increasing interest for the assessment of aneurysmal rupture risk and treatment planning. Achievement of accurate simulation results requires the usage of several patient-individual boundary conditions, such as a geometric model of the vasculature but also individualized inflow conditions. METHODS: We propose the automatic estimation of various parameters for boundary conditions for computational fluid dynamics (CFD) based on a single 3D rotational angiography scan, also showing contrast agent inflow. First the data are reconstructed, and a patient-specific vessel model can be generated in the usual way. For this work, we optimize the inflow waveform based on two parameters, the mean velocity and pulsatility. We use statistical analysis of the measurable velocity distribution in the vessel segment to estimate the mean velocity. An iterative optimization scheme based on CFD and virtual angiography is utilized to estimate the inflow pulsatility. Furthermore, we present methods to automatically determine the heart rate and synchronize the inflow waveform to the patient's heart beat, based on time-intensity curves extracted from the rotational angiogram. This will result in a patient-individualized inflow velocity curve. RESULTS: The proposed methods were evaluated on two clinical datasets. Based on the vascular geometries, synthetic rotational angiography data was generated to allow a quantitative validation of our approach against ground truth data. We observed an average error of approximately [Formula: see text] for the mean velocity, [Formula: see text] for the pulsatility. The heart rate was estimated very precisely with an average error of about [Formula: see text], which corresponds to about 6 ms error for the duration of one cardiac cycle. Furthermore, a qualitative comparison of measured time-intensity curves from the real data and patient-specific simulated ones shows an excellent match. CONCLUSION: The presented methods have the potential to accurately estimate patient-specific boundary conditions from a single dedicated rotational scan.

Rotational angiography with motion compensation: first-in-man use for the 3D evaluation of transcatheter valve prostheses.

AIMS: We evaluated a novel motion-compensating 3D reconstruction technique applied to rotational angiography (R-angio) which produces MSCT-like images for evaluation of implanted TAVI prostheses without requiring rapid pacing. METHODS AND RESULTS: Fifty-one consecutive patients were retrospectively identified who were evaluated with rotational angiography (R-angio) using the Siemens Artis zee angiographic C-arm system after TAVI with a Medtronic CoreValve prosthesis. A novel 3D image reconstruction technique was applied which corrects for cardiac motion. CoreValve frame geometry was evaluated according to the same protocol for MSCT and R-angio at the level of: 1) the inflow, 2) the nadirs, 3) central coaptation, and 4) the commissures. The native aortic annulus dimensions were measured at the nadirs of the three leaflets. Sizing ratio, prosthesis expansion and frame ellipticity were assessed. Good quality 3D reconstructions were obtained in 43 patients (84%) and failure was predictable prior to reconstruction in six of the other seven patients (superposition of radiographically dense object n=4, obesity n=2). Prosthesis inflow ellipticity and expansion were correlated with implantation depth (respectively r=-0.46, p<0.01, and r=0.61, p<0.001). Aortic regurgitation grade ≥2 was associated with greater prosthesis ellipticity at the level of central coaptation (median [25th-75th percentile]: 1.15 [1.10-1.20] vs. 1.08 [1.06-1.12], p=0.009). The inter-observer, inter-modality (MSCT, R-angio) variability in measurement at the level of coaptation for minimum diameter, maximum diameter and area were all low (respectively, mean ±SD:1.2% ±1.2; 1.7% ±1.8 and 2.0% ±1.3). CONCLUSIONS: R-angio with motion-compensated reconstruction offers new possibilities for evaluation of the post-implantation geometry of percutaneous structural heart prostheses and the potential clinical effects.

Interventional heart wall motion analysis with cardiac C-arm CT systems.

Today, quantitative analysis of three-dimensional (3D) dynamics of the left ventricle (LV) cannot be performed directly in the catheter lab using a current angiographic C-arm system, which is the workhorse imaging modality for cardiac interventions. Therefore, myocardial wall analysis is completely based on the 2D angiographic images or pre-interventional 3D/4D imaging. In this paper, we present a complete framework to study the ventricular wall motion in 4D (3D+t) directly in the catheter lab. From the acquired 2D projection images, a dynamic 3D surface model of the LV is generated, which is then used to detect ventricular dyssynchrony. Different quantitative features to evaluate LV dynamics known from other modalities (ultrasound, magnetic resonance imaging) are transferred to the C-arm CT data. We use the ejection fraction, the systolic dyssynchrony index a 3D fractional shortening and the phase to maximal contraction (ϕi, max) to determine an indicator of LV dyssynchrony and to discriminate regionally pathological from normal myocardium. The proposed analysis tool was evaluated on simulated phantom LV data with and without pathological wall dysfunctions. The LV data used is publicly available online at https://conrad.stanford.edu/data/heart. In addition, the presented framework was tested on eight clinical patient data sets. The first clinical results demonstrate promising performance of the proposed analysis tool and encourage the application of the presented framework to a larger study in clinical practice.

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.

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), Shepard's 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 Shepard's 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.

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.

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.

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.

ECG-gated interventional cardiac reconstruction for non-periodic motion.

The 3-D reconstruction of cardiac vasculature using C-arm CT is an active and challenging field of research. In interventional environments patients often do have arrhythmic heart signals or cannot hold breath during the complete data acquisition. This important group of patients cannot be reconstructed with current approaches that do strongly depend on a high degree of cardiac motion periodicity for working properly. In a last year's MICCAI contribution a first algorithm was presented that is able to estimate non-periodic 4-D motion patterns. However, to some degree that algorithm still depends on periodicity, as it requires a prior image which is obtained using a simple ECG-gated reconstruction. In this work we aim to provide a solution to this problem by developing a motion compensated ECG-gating algorithm. It is built upon a 4-D time-continuous affine motion model which is capable of compactly describing highly non-periodic motion patterns. A stochastic optimization scheme is derived which minimizes the error between the measured projection data and the forward projection of the motion compensated reconstruction. For evaluation, the algorithm is applied to 5 datasets of the left coronary arteries of patients that have ignored the breath hold command and/or had arrhythmic heart signals during the data acquisition. By applying the developed algorithm the average visibility of the vessel segments could be increased by 27%. The results show that the proposed algorithm provides excellent reconstruction quality in cases where classical approaches fail. The algorithm is highly parallelizable and a clinically feasible runtime of under 4 minutes is achieved using modern graphics card hardware.

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.

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.