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Background Angiography-derived physiological assessment of coronary lesions has emerged as an alternative to wire based assessment aiming at less-invasiveness and shorter procedural time as well as cost effectiveness in physiology-guided decision making. However, current available image-derived physiology software have limitations including the requirement of multiple projections and are time consuming.Methods/Design The ReVEAL iFR (Radiographic imaging Validation and EvALuation for Angio-iFR) trial is a multicenter, multicontinental, validation study which aims to validate the diagnostic accuracy of the Angio-iFR medical software device (Philips, San Diego, US) in patients undergoing angiography for Chronic Coronary Syndrome (CCS). The Angio-iFR will enable operators to predict both the iFR and FFR value within a few seconds from a single projection of cine angiography by using a lumped parameter fluid dynamics model. Approximately 440 patients with at least one de-novo 40% to 90% stenosis by visual angiographic assessment will be enrolled in the study. The primary endpoint is the sensitivity and specificity of the iFR and FFR for a given lesion compared to the corresponding invasive measures. The enrollment started in August 2019, and was completed in March 2021.Summary The Angio-iFR system has the potential of simplifying physiological evaluation of coronary stenosis compared with available systems, providing estimates of both FFR and iFR. The ReVEAL iFR study will investigate the predictive performance of the novel Angio-iFR software in CCS patients. Ultimately, based on its unique characteristics, the Angio-iFR system may contribute to improve adoption of functional coronary assessment and the workflow in the catheter laboratory.

Objective The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTATs) for critical findings in chest radiographs (CXRs). Furthermore, we investigate a method to counteract the effect of false negative predictions by AI—resulting in an extremely and dangerously long RTAT, as CXRs are sorted to the end of the worklist. Methods We developed a simulation framework that models the current workflow at a university hospital by incorporating hospital-specific CXR generation rates and reporting rates and pathology distribution. Using this, we simulated the standard worklist processing “first-in, first-out” (FIFO) and compared it with a worklist prioritization based on urgency. Examination prioritization was performed by the AI, classifying eight different pathological findings ranked in descending order of urgency: pneumothorax, pleural effusion, infiltrate, congestion, atelectasis, cardiomegaly, mass, and foreign object. Furthermore, we introduced an upper limit for the maximum waiting time, after which the highest urgency is assigned to the examination. Results The average RTAT for all critical findings was significantly reduced in all prioritization simulations compared to the FIFO simulation (e.g., pneumothorax: 35.6 min vs. 80.1 min; p p p Conclusion Our simulations demonstrate that smart worklist prioritization by AI can reduce the average RTAT for critical findings in CXRs while maintaining a small maximum RTAT as FIFO. Key Points • Development of a realistic clinical workflow simulator based on empirical data from a hospital allowed precise assessment of smart worklist prioritization using artificial intelligence. • Employing a smart worklist prioritization without a threshold for maximum waiting time runs the risk of false negative predictions of the artificial intelligence greatly increasing the report turnaround time. • Use of a state-of-the-art convolution neural network can reduce the average report turnaround time almost to the upper limit of a perfect classification algorithm (e.g., pneumothorax: 35.6 min vs. 30.4 min).

Excellent image quality is a primary prerequisite for diagnostic non-invasive coronary CT angiography. Artifacts due to cardiac motion may interfere with detection and diagnosis of coronary artery disease and render subsequent treatment decisions more difficult. We propose deep-learning-based measures for coronary motion artifact recognition and quantification in order to assess the diagnostic reliability and image quality of coronary CT angiography images. More specifically, the application, steering and evaluation of motion compensation algorithms can be triggered by these measures. A Coronary Motion Forward Artifact model for CT data (CoMoFACT) is developed and applied to clinical cases with excellent image quality to introduce motion artifacts using simulated motion vector fields. The data required for supervised learning is generated by the CoMoFACT from 17 prospectively ECG-triggered clinical cases with controlled motion levels on a scale of 0–10. Convolutional neural networks achieve an accuracy of 93.3% ± 1.8% for the classification task of separating motion-free from motion-perturbed coronary cross-sectional image patches. The target motion level is predicted by a corresponding regression network with a mean absolute error of 1.12 ± 0.07. Transferability and generalization capabilities are demonstrated by motion artifact measurements on eight additional CCTA cases with real motion artifacts.

Purpose Comparison of radiation doses in patients undergoing angiographic bronchial artery embolization (BAE) before and after a noise reduction imaging technology upgrade. Methods We performed a retrospective study of 70 patients undergoing BAE. Procedures were performed before (n = 32) and after (n = 38) the technology upgrade containing additional filters and improved image-processing. Cumulative air kerma (AK), cumulative dose area product (DAP), number of exposure frames, total fluoroscopy time and amount of contrast agent were recorded. Mean values were calculated and compared using two-tailed t-tests. DSA image quality was assessed independently by two blinded readers and compared using the Wilcoxon signed-rank test. Results Using the new technology resulted in a significant reduction of 59% in DAP (149.2 (103.1–279.1) vs. 54.8 (38.2–100.7) Gy*cm2, p Conclusions The new angiographic noise reduction technology significantly decreases the radiation dose during bronchial artery embolization without compromising image quality or increasing time of fluoroscopy or contrast volume.

Cardiac motion artifacts frequently reduce the interpretability of coronary computed tomography angiography (CCTA) images and potentially lead to misinterpretations or preclude the diagnosis of coronary artery disease (CAD). In this paper, a novel motion compensation approach dealing with Coronary Motion estimation by Patch Analysis in CT data (CoMPACT) is presented. First, the required data for supervised learning is generated by the Coronary Motion Forward Artifact model for CT data (CoMoFACT) which introduces simulated motion to 19 artifact-free clinical CT cases with step-and-shoot acquisition protocol. Second, convolutional neural networks (CNNs) are trained to estimate underlying 2D motion vectors from 2.5D image patches based on the coronary artifact appearance. In a phantom study with computer-simulated vessels, CNNs predict the motion direction and the motion magnitude with average test accuracies of 13.37°±1.21° and 0.77 ± 0.09 mm, respectively. On clinical data with simulated motion, average test accuracies of 34.85°±2.09° and 1.86 ± 0.11 mm are achieved, whereby the precision of the motion direction prediction increases with the motion magnitude. The trained CNNs are integrated into an iterative motion compensation pipeline which includes distance-weighted motion vector extrapolation. Alternating motion estimation and compensation in twelve clinical cases with real cardiac motion artifacts leads to significantly reduced artifact levels, especially in image data with severe artifacts. In four observer studies, mean artifact levels of 3.08 ± 0.24 without MC and 2.28 ± 0.29 with CoMPACT MC are rated in a five point Likert scale.

Metal objects in the human heart such as implanted pacemakers frequently lead to heavy artifacts in reconstructed CT image volumes. Due to cardiac motion, common metal artifact reduction methods which assume a static object during CT acquisition are not applicable. We propose a fully automatic Dynamic Pacemaker Artifact Reduction (DyPAR+) pipeline which is built of three convolutional neural network (CNN) ensembles. In a first step, pacemaker metal shadows are segmented directly in the raw projection data by the SegmentationNets. Second, resulting metal shadow masks are passed to the InpaintingNets which replace metal-affected line integrals in the sinogram for subsequent reconstruction of a metal-free image volume. Third, the metal locations in a pre-selected motion state are predicted by the ReinsertionNets based on a stack of partial angle back-projections generated from the segmented metal shadow mask. We generate the data required for the supervised learning processes by introducing synthetic, moving pacemaker leads into 14 clinical cases without pacemakers. The SegmentationNets and the ReinsertionNets achieve average Dice coefficients of 94.16% ± 2.01% and 55.60% ± 4.79% during testing on clinical data with synthetic metal leads. With a mean absolute reconstruction error of 11.54 HU ± 2.49 HU in the image domain, the InpaintingNets outperform the hand-crafted approaches PatchMatch and inverse distance weighting. Application of the proposed DyPAR+ pipeline to nine clinical test cases with real pacemakers leads to significant reduction of metal artifacts and demonstrates the transferability to clinical practice. Especially the SegmentationNets and InpaintingNets generalize well to unseen acquisition modes and contrast protocols.

Background Vasodilator stress computed tomography perfusion (sCTP) imaging is complementary to coronary CT angiography (CCTA), used to determine the hemodynamic significance of coronary artery disease. However, it requires a separate image acquisition due to motion artifacts caused by higher heart rates during stress, resulting in increased iodine contrast dose and radiation. We sought to determine whether a novel motion correction algorithm applied to stress images would improve the visualization of the coronary arteries to potentially allow CCTA + sCTP evaluation in a single scan. Methods 28 patients referred for clinically indicated CCTA (iCT, Philips) underwent sCTP imaging (retrospective-gating with dose modulation; 100 kVp and 250 mA; 5.2 ± 4.3 mSv) after regadenoson (0.4 mg, Astellas). Stress images were reconstructed using standard filtered back-projection (FBP) and also processed to generate interaction-free coronary motion-compensated back-projection reconstructions (MCR). Each coronary artery from standard FBP and MCR images was viewed side-by-side by a reader blinded to the reconstruction technique, who graded severity of motion artifact by segment (scale 0–5, with 3 as the threshold for diagnostic quality) and to measure signal-to-noise and contrast-to-noise ratios (SNR, CNR). Results Visualization scores were higher with MCR for all coronary segments, including 14/86 (16%) segments deemed as non-diagnostic on FBP images. SNR (7 ± 2) and CNR (15 ± 8) were unchanged by motion-correction (7 ± 3, p = 0.88 and 15 ± 5, p = 0.94, respectively). Conclusions MCR improves the visualization of coronary anatomy on sCTP images without degrading image characteristics. This algorithm is an important step towards the combined assessment of coronary anatomy and myocardial perfusion in a single scan, which will reduce study time, radiation exposure and contrast dose.

OBJECTIVEThe goal of this study was to develop and validate a system for automatic segmentation of the spine, pedicle identification, and screw path suggestion for use with an intraoperative 3D surgical navigation system.METHODSCone-beam CT (CBCT) images of the spines of 21 cadavers were obtained. An automated model-based approach was used for segmentation. Using machine learning methodology, the algorithm was trained and validated on the image data sets. For measuring accuracy, surface area errors of the automatic segmentation were compared to the manually outlined reference surface on CBCT. To further test both technical and clinical accuracy, the algorithm was applied to a set of 20 clinical cases. The authors evaluated the system’s accuracy in pedicle identification by measuring the distance between the user-defined midpoint of each pedicle and the automatically segmented midpoint. Finally, 2 independent surgeons performed a qualitative evaluation of the segmentation to judge whether it was adequate to guide surgical navigation and whether it would have resulted in a clinically acceptable pedicle screw placement.RESULTSThe clinically relevant pedicle identification and automatic pedicle screw planning accuracy was 86.1%. By excluding patients with severe spinal deformities (i.e., Cobb angle > 75° and severe spinal degeneration) and previous surgeries, a success rate of 95.4% was achieved. The mean time (± SD) for automatic segmentation and screw planning in 5 vertebrae was 11 ± 4 seconds.CONCLUSIONSThe technology investigated has the potential to aid surgeons in navigational planning and improve surgical navigation workflow while maintaining patient safety.

Cardiac ablation procedures during electrophysiology interventions are performed under x-ray guidance with a C-arm imaging system. Some procedures require catheter navigation in complex anatomies like the left atrium. Navigation aids like 3D road maps and external tracking systems may be used to facilitate catheter navigation. As an alternative to external tracking a fully automatic method is presented here that enables the calculation of the 3D location of the ablation catheter from individual 2D x-ray projections. The method registers a high resolution, deformable 3D attenuation model of the catheter to a 2D x-ray projection. The 3D localization is based on the divergent beam projection of the catheter. On an individual projection, the catheter tip is detected in 2D by image filtering and a template matching method. The deformable 3D catheter model is adapted using the projection geometry provided by the C-arm system and 2D similarity measures for an accurate 2D/3D registration. Prior to the tracking and registration procedure, the deformable 3D attenuation model is automatically extracted from a separate 3D cone beam CT reconstruction of the device. The method can hence be applied to various cardiac ablation catheters. In a simulation study of a virtual ablation procedure with realistic background, noise, scatter and motion blur an average 3D registration accuracy of 3.8 mm is reached for the catheter tip. In this study four different types of ablation catheters were used. Experiments using measured C-arm fluoroscopy projections of a catheter in a RSD phantom deliver an average 3D accuracy of 4.5 mm.

Objective To compare patient radiation dose in patients undergoing transjugular intrahepatic portosystemic shunt (TIPS) implantation before and after an imaging-processing technology upgrade. Methods In our retrospective single-center-study, cumulative air kerma (AK), cumulative dose area product (DAP), total fluoroscopy time and contrast agent were collected from an age- and BMI-matched collective of 108 patients undergoing TIPS implantation. 54 procedures were performed before and 54 after the technology upgrade. Mean values were calculated and compared using two-tailed t -tests. Two blinded, independent readers assessed DSA image quality using a four-rank likert scale and the Wilcoxcon test. Results The new technology demonstrated a significant reduction of 57% of mean DAP (402.8 vs. 173.3Gycm 2 , p Conclusions In our study the new imaging technology halved radiation dose in patients undergoing TIPS maintaining sufficient image quality without a significant increase in radiation time or contrast consumption.

Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research.

To evaluate the technical feasibility of automatically removing the ribs and spine from C-arm cone-beam computed tomography (CBCT) images acquired during transcatheter arterial chemoembolization (TACE).Fifty-eight patients (45.8 ± 5.0 years) with unresectable hepatocellular carcinoma (HCC) underwent transcatheter arterial chemoembolization and had intraprocedural CBCT imaging. Automatic bone removal was performed using model-based segmentation of the ventral cavity. Two interventional radiologists independently evaluated the performance of bone removal, remaining soft tissue retention, and general usability (where both the bone is appropriately removed while retaining soft tissue) for 3D TACE planning on a four-level (complete/excellent, adequate/good, incomplete/questionable, insufficient/bad) score. The proportion of inter-reader agreement was calculated.For ribs and spine removal, 98.3-100% and 100% of cases showed complete or adequate performance, respectively. In 96.6% of the cases, soft tissue was at least adequately retained. 91.3-93.1% of the cases demonstrated good or excellent general usability for TACE planning. Satisfactory inter-reader agreement proportion was achieved in ribs (93.1%) and spine removal (89.7%), soft tissue retention (84.5%), and general usability for TACE planning (72.4%).Intraprocedural automatic bone removal on CBCT images is technically feasible and offers good removal of ribs and spine while preserving soft tissue. Its clinical value needs further assessment.

Computed tomographic (CT) image resolution and quality were evaluated utilizing varying scan protocols with accelerated image acquisition. A resolution phantom with hole diameters from 0.2 to 1.0 mm was scanned in axial, coronal, and sagittal plane using a 64-slice multidetector CT with varying scan parameters. No relevant differences in image resolution and quality were detected between the fastest scan protocol, with the shortest rotation time and highest pitch, and the slowest protocol. Accelerated CT protocols resulted in diagnostic images with adequate resolution and quality.

A method for motion compensated iterative CT reconstruction of a cardiac region-of-interest is presented. The algorithm is an ordered subset maximum likelihood approach with spherically symmetric basis functions, and it uses an ECG for gating. Since the straightforward application of iterative methods to CT data has the drawback that a field-of-view has to be reconstructed, which covers the complete volume contributing to the absorption, region-of-interest reconstruction is applied here. Despite gating, residual object motion within the reconstructed gating window leads to motion blurring in the reconstructed image. To limit this effect, motion compensation is applied. Hereto, a gated 4D reconstruction at multiple phases is generated for the region-of-interest, and a limited set of vascular landmarks are manually annotated throughout the cardiac phases. A dense motion vector field is obtained from these landmarks by scattered data interpolation. The method is applied to two clinical data sets at strongest motion phases. Comparing the method to standard gated iterative reconstruction results shows that motion compensation strongly improved reconstruction quality. (C) 2009 Elsevier Ltd. All rights reserved.

A fully automated 3D centerline modeling algorithm for coronary arteries is presented. It utilizes a subset of standard rotational X-ray angiography projections that correspond to one single cardiac phase. The algorithm is based on a fast marching approach, which selects voxels in 3D space that belong to the vascular structure and introduces a hierarchical order. The local 3D propagation speed is determined by a combination of corresponding 2D projections filtered with a vessel enhancing kernel. The best achievable accuracy of the algorithm is evaluated on simulated projections of a virtual heart phantom, showing that it is capable of extracting coronary centerlines with an accuracy that is mainly limited by projection and volume quantization (0.25 mm). The algorithm is reasonably insensitive to residual motion, which means that it is able to cope with inconsistencies within the projection data set caused by limited gating accuracy and respiration. Its accuracy on clinical data is evaluated based on expert ratings of extracted models of 17 consecutive clinical cases (10 LCA, 7 RCA). A success rate of 93.5% (i.e. with no or slight deviations) is achieved compared to 58.8% success rate of semi-automatically extracted models.

Rotational coronary angiography provides a multitude of x-ray projections of the contrast agent enhanced coronary arteries along a given trajectory with parallel ECG recording. These data can be used to derive motion information of the coronary arteries including vessel displacement and pulsation. In this paper, a fully automated algorithm to generate 4D motion vector fields for coronary arteries from multi-phase 3D centerline data is presented. The algorithm computes similarity measures of centerline segments at different cardiac phases and defines corresponding centerline segments as those with highest similarity. In order to achieve an excellent matching accuracy, an increasing number of bifurcations is included as reference points in an iterative manner. Based on the motion data, time-dependent vessel surface extraction is performed on the projections without the need of prior reconstruction. The algorithm accuracy is evaluated quantitatively on phantom data. The magnitude of longitudinal errors (parallel to the centerline) reaches approx. 0.50 mm and is thus more than twice as large as the transversal 3D extraction errors of the underlying multi-phase 3D centerline data. It is shown that the algorithm can extract asymmetric stenoses accurately. The feasibility on clinical data is demonstrated on five different cases. The ability of the algorithm to extract time-dependent surface data, e.g. for quantification of pulsating stenosis is demonstrated.

A 3-D reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular disease, compared to 2-D X-ray angiograms. Besides improved roadmapping, quantitative vessel analysis is possible. Due to the heart's motion, rotational coronary angiography typically provides only 5-10 projections for the reconstruction of each cardiac phase, which leads to a strongly undersampled reconstruction problem. Such an ill-posed problem can be approached with regularized iterative methods. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, the minimization of the \mbi L 1 norm of the reconstructed image, favoring spatially sparse images, is a suitable regularization. Additional problems are overlaid background structures and projection truncation, which can be alleviated by background reduction using a morphological top-hat filter. This paper quantitatively evaluates image reconstruction based on these ideas on software phantom data, in terms of reconstructed absorption coefficients and vessel radii. Results for different algorithms and different input data sets are compared. First results for electrocardiogram-gated reconstruction from clinical catheter-based rotational X-ray coronary angiography are presented. Excellent 3-D image quality can be achieved.

This paper presents a three-dimensional method to reconstruct moving objects from cone-beam X-ray projections using an iterative reconstruction algorithm and a given motion vector field. For the image representation, adapted blobs are used, which can be implemented efficiently as basis functions. Iterative reconstruction requires the calculation of line integrals (forward projections) through the image volume, which are compared with the actual measurements to update the image volume. In the existence of a divergent motion vector field, a change in the volumes of the blobs has to be taken into account in the forward and backprojections. An efficient method to calculate the line integral through the adapted blobs is proposed. It solves the problem, how to compensate for the divergence in the motion vector field on a grid of basis functions. The method is evaluated on two phantoms, which are subject to three different known motions. Moreover, a motion-compensated filtered back-projection reconstruction method is used, and the reconstructed images are compared. Using the correct motion vector field with the iterative motion-compensated reconstruction, sharp images are obtained, with a quality that is significantly better than gated reconstructions.

This paper presents a method to reconstruct moving objects from cone beam X-ray projections acquired during a single rotational run using a given motion vector field. The method is applicable to voxel driven cone-beam filtered back-projection reconstruction approaches. Here, a formulation based on the algorithm of Feldkamp, Davis, and Kress (FDK) is presented. The motion correction is applied during the back-projection step by shifting the voxel to be reconstructed according to the motion vector field. The method is applied to three-dimensional (3-D) rotational X-ray angiography. Projections from a beating coronary heart phantom are simulated. Motion-compensated reconstructions with varying accuracy of the applied motion field are carried out for a late diastolic heart phase and compared to the reconstruction obtained with the standard FDK-method from projections of the corresponding motion-free model in the same heart phase. Furthermore, gated reconstructions are calculated by weighting the projections according to their cardiac phase without using a motion vector field. Different gating window widths are applied, and the reconstructions are compared. Using the correct motion field with the motion-compensated reconstruction, the image quality of the standard reconstruction from the corresponding motion-free coronary model can almost be recovered. The reconstructed image quality stays acceptable if the accuracy of the motion field sampling points is better than 1 mm. The gated reconstructions with a window width of 15%-20% of the cardiac cycle lead to superior results compared to nearest neighbor gating, especially for histogram based visualization and analysis. The motion-compensated reconstructions provide sharp images of the coronaries far surpassing the image quality of gated reconstructions.

Low motion phases for cardiac computed tomography reconstructions are currently detected manually in a user-dependent selection process which is often time consuming and suboptimal. The concept of motion maps was recently introduced to achieve automatic phase selection. This pilot study compared the accuracy of motion-map phase selection to that with manual iterative selection. The study included 20 patients, consisting of one group with low and one with high heart rate. The technique automatically derives a motion strength function between multiple low-resolution reconstructions through the cardiac cycle, with periods of lowest difference between neighboring phases indicating minimal cardiac motion. A high level of agreement was found for phase selection achieved with the motion map approach compared with the manual iterative selection process. The motion maps allowed automated quiescent phase detection of the cardiac cycle in 85% of cases, with best results at low heart rates and for the left coronary artery. They can also provide additional information such as the presence of breathing artifacts. Motion maps show promise as a rapid off-line tool to automatically detect quiescent cardiac phases in a variety of patients.

In modern computer tomography (CT) systems, the fast rotating gantry and the increased detector width enable 3D imaging of the heart. Cardiac volume CT has a high potential for non-invasive coronary angiography with high spatial resolution and short scan time. Due to the increased detector width, true cone beam reconstruction methods are needed instead of adapted 2D reconstruction schemes. In this paper, the extended cardiac reconstruction method is introduced. It integrates the idea of retrospectively gated cardiac reconstruction for helical data acquisition into a cone beam reconstruction framework. It leads to an efficient and flexible algorithmic scheme for the reconstruction of single- and multi-phase cardiac volume datasets. The method automatically adapts the number of cardiac cycles used for the reconstruction. The cone beam geometry is fully taken into account during the reconstruction process. Within this paper, results are presented on patient datasets which have been acquired using a 16-slice cone beam CT system.

A method for the determination of the contrast-agent propagation in vessel trees is presented. A standard three-dimensional (3-D) rotational angiography procedure is performed to reconstruct the morphology of the contrast-filled vessel tree in a 3-D volume. An additional fluoroscopy projection series acquired with a fixed projection angle delivers the temporal information of the bolus propagating. The mapping of the propagation information from the two-dimensional projections to the 3-D image data set is the topic of this paper. A symbolic tree structure is built up that represents the vessel tree including bifurcations. Neighborhood relations between vessel pieces are given in three dimensions. This facilitates filtering procedures and plausibility controls of the resulting time dependent 3-D data set. The presented method proved to be accurate with phantom data and gives novel insight in the feeding structure of arterio-venous malformations and aneurysms.

Cardiac C-arm CT imaging delivers a tomographic region-of-interest reconstruction of the patient's heart during image guided catheter interventions. Due to the limited size of the flat detector a volume image is reconstructed, which is truncated in the cone-beam (along the patient axis) and the fan-beam (in the transaxial plane) direction. To practically address this local tomography problem correction methods, like projection extension, are available for first pass image reconstruction. For second pass correction methods, like metal artefact reduction, alternative correction schemes are required when the field of view is limited to a region-of-interest of the patient. In classical CT imaging metal artefacts are corrected by metal identification in a first volume reconstruction and generation of a corrected projection data set followed by a second reconstruction. This approach fails when the metal structures are located outside the reconstruction field of view. When a C-arm CT is performed during a cardiac intervention pacing leads and other cables are frequently positioned on the patients skin, which results in propagating streak artefacts in the reconstruction volume. A first pass approach to reduce this type of artefact is introduced and evaluated here. It makes use of the fact that the projected position of objects outside the reconstruction volume changes with the projection perspective. It is shown that projection based identification, tracking and removal of high contrast structures like cables, only detected in a subset of the projections, delivers a more consistent reconstruction volume with reduced artefact level. The method is quantitatively evaluated based on 50 simulations using cardiac CT data sets with variable cable positioning. These data sets are forward projected using a C-arm CT system geometry and generate artefacts comparable to those observed in clinical cardiac C-arm CT acquisitions. A C-arm CT simulation of every cardiac CT data set without cables served as a ground truth. The 3D root mean square deviation between the simulated data set with and without cables could be reduced for 96% of the simulated cases by an average of 37% (min −9%, max 73%) when using the first pass correction method. In addition, image quality improvement is demonstrated for clinical whole heart C-arm CT data sets when the cable removal algorithm was applied.

In this paper, four approximate cone-beam CT reconstruction algorithms are compared: Advanced single slice rebinning (ASSR) as a representative of algorithms employing a two dimensional approximation, PI, PI-SLANT, and 3-PI which all use a proper three dimensional back-projection. A detailed analysis of the image artifacts produced by these techniques shows that aliasing in the z-direction is the predominant source of artifacts for a 16-row scanner with 1.25 mm nominal slice thickness. For a detector with isotropic resolution of 0.5 mm, we found that ASSR and PI produce different kinds of artifacts which are almost at the same level, while PI-SLANT produces none of these artifacts. It is shown that the use of redundant data in the 3-PI method suppresses aliasing artifacts efficiently for both scanners.

Hybrid reconstruction techniques have been introduced for the volume reconstruction of axially truncated cone-beam computed tomography projection data acquired along a circular source-detector trajectory. The introduction of weighted half-scan techniques into this framework is described in this paper. Due to the cone-beam geometry it is not possible to perform the weighting on the projections as is typically done in conventional single-line computed tomography. Hence, in this paper we present an efficient way to incorporate angular weighting functions, depending on the object point position, into the framework of hybrid cone-beam reconstruction. Four different angular weighting functions are introduced and discussed with respect to their cone-beam artefact behaviour and their influence on the signal-to-noise ratio. As a result, the most effective angular weighting function for hybrid circular cone-beam reconstruction is determined by means of a simulation study based on mathematical phantoms and clinical data sets. This distance-weighted angular weighting scheme yields the best results in terms of high image quality, low computational complexity and signal-to-noise variations in the reconstruction volume.

Reconstruction of the beating heart in 3D + time in the catheter laboratory using only the available C-arm system would improve diagnosis, guidance, device sizing, and outcome control for intracardiac interventions, e.g., electrophysiology, valvular disease treatment, structural or congenital heart disease. To obtain such a reconstruction, the patient's electrocardiogram (ECG) must be recorded during the acquisition and used in the reconstruction. In this paper, the authors present a 4D reconstruction method aiming to reconstruct the heart from a single sweep 10 s acquisition.The authors introduce the 4D RecOnstructiOn using Spatial and TEmporal Regularization (short 4D ROOSTER) method, which reconstructs all cardiac phases at once, as a 3D + time volume. The algorithm alternates between a reconstruction step based on conjugate gradient and four regularization steps: enforcing positivity, averaging along time outside a motion mask that contains the heart and vessels, 3D spatial total variation minimization, and 1D temporal total variation minimization.4D ROOSTER recovers the different temporal representations of a moving Shepp and Logan phantom, and outperforms both ECG-gated simultaneous algebraic reconstruction technique and prior image constrained compressed sensing on a clinical case. It generates 3D + time reconstructions with sharp edges which can be used, for example, to estimate the patient's left ventricular ejection fraction.4D ROOSTER can be applied for human cardiac C-arm CT, and potentially in other dynamic tomography areas. It can easily be adapted to other problems as regularization is decoupled from projection and back projection.

C-arm cone-beam computed tomography (CBCT) is a new imaging technology integrated in modern angiographic systems. Due to its ability to obtain cross-sectional imaging and the possibility to use dedicated planning and navigation software, it provides an informed platform for interventional oncology procedures. In this paper, we highlight the technical aspects and clinical applications of CBCT imaging and navigation in the most common loco-regional oncological treatments.

Tracking the location of medical devices in interventional X-ray data solves different problems. For example the motion information of the devices is used to determine cardiac or respiratory motion during X-ray guided procedures or device features are used as landmarks to register images. In this publication an approach using a 3D deformable catheter model is presented and used to track a coronary sinus (CS) catheter in 3D plus time through a complete rotational angiography sequence. The benefits of using voxel based models with attenuation information for 2D/3D registration are investigated in comparison to binary catheter models. The 2D/3D registration of the model allows to extract a 3D catheter shape from every individual 2D projection. The tracking accuracy is evaluated on simulated and clinical rotational angiography data of the contrast enhanced left atrium. The quantitative evaluation of the experiments delivers an average registration accuracy for all catheter electrodes of 0.23 mm in 2D and 0.95 mm in 3D when using an attenuation model of the catheter. The overall tracking accuracy is lower when using binary catheter models.

Circular scanning with an off-center planar detector is an acquisition scheme that allows to save detector area while keeping a large field of view (FOV). Several filtered back-projection (FBP) algorithms have been proposed earlier. The purpose of this work is to present two newly developed back-projection filtration (BPF) variants and evaluate the image quality of these methods compared to the existing state-of-the-art FBP methods.The first new BPF algorithm applies redundancy weighting of overlapping opposite projections before differentiation in a single projection. The second one uses the Katsevich-type differentiation involving two neighboring projections followed by redundancy weighting and back-projection. An averaging scheme is presented to mitigate streak artifacts inherent to circular BPF algorithms along the Hilbert filter lines in the off-center transaxial slices of the reconstructions. The image quality is assessed visually on reconstructed slices of simulated and clinical data. Quantitative evaluation studies are performed with the Forbild head phantom by calculating root-mean-squared-deviations (RMSDs) to the voxelized phantom for different detector overlap settings and by investigating the noise resolution trade-off with a wire phantom in the full detector and off-center scenario.The noise-resolution behavior of all off-center reconstruction methods corresponds to their full detector performance with the best resolution for the FDK based methods with the given imaging geometry. With respect to RMSD and visual inspection, the proposed BPF with Katsevich-type differentiation outperforms all other methods for the smallest chosen detector overlap of about 15 mm. The best FBP method is the algorithm that is also based on the Katsevich-type differentiation and subsequent redundancy weighting. For wider overlap of about 40-50 mm, these two algorithms produce similar results outperforming the other three methods. The clinical case with a detector overlap of about 17 mm confirms these results.The BPF-type reconstructions with Katsevich differentiation are widely independent of the size of the detector overlap and give the best results with respect to RMSD and visual inspection for minimal detector overlap. The increased homogeneity will improve correct assessment of lesions in the entire field of view.

Imaging modalities utilized in the interventional cardiology suite have seen an impressive evolution and expansion recently, particularly with regard to the recent interest in three-dimensional (3D) imaging. Despite this, the backbone of visualization in the catheterization laboratory remains two-dimensional (2D) X-ray fluoroscopy and cine-angiography. New imaging techniques under development, referred to as three-dimensional rotational angiography (RA) and C-arm CT, hold great promise for improving current device implantation and understanding of cardiovascular anatomy. This paper reviews the evolution of rotational angiography and advanced 3D X-ray imaging applications to interventional cardiology.

In this paper a method which combines iterative computed tomography reconstruction and coronary centerline extraction technique to obtain motion artifact-free reconstructed images of the coronary arteries are proposed and evaluated. The method relies on motion-vector fields derived from a set of coronary centerlines extracted at multiple cardiac phases within the R-R interval. Hereto, start and end points are provided by the user in one time-frame only. Using an elastic image registration, these points are propagated to all the remaining cardiac phases. Consequently, a multi-phase three-dimensional coronary centerline is determined by applying a semi-automatic minimum cost path based extraction method. Corresponding centerline positions are used to determine the relative motion-vector fields from phase to phase. Finally, dense motion-vector fields are achieved by thin-plate-spline interpolation and used to perform a motion-corrected iterative reconstruction of a selected region of interest. The performance of the method is validated on five patients, showing the improved sharpness of cardiac motion-corrected gated iterative reconstructions compared to the results achieved by a classical gated iterative method. The results are also compared to known manual and fully automatic coronary artery motion estimation methods. (C) 2012 Elsevier Ltd. All rights reserved.

Three-dimensional (3-D) reconstruction of the coronary arteries during a cardiac catheter-based intervention can be performed from a C-arm based rotational x-ray angiography sequence. It can support the diagnosis of coronary artery disease, treatment planning, and intervention guidance. 3-D reconstruction also enables quantitative vessel analysis, including vessel dynamics from a time-series of reconstructions.The strong angular undersampling and motion effects present in gated cardiac reconstruction necessitate the development of special reconstruction methods. This contribution presents a fully automatic method for creating high-quality coronary artery reconstructions. It employs a sparseness-prior based iterative reconstruction technique in combination with projection-based motion compensation.The method is tested on a dynamic software phantom, assessing reconstruction accuracy with respect to vessel radii and attenuation coefficients. Reconstructions from clinical cases are presented, displaying high contrast, sharpness, and level of detail.The presented method enables high-quality 3-D coronary artery imaging on an interventional C-arm system.

Cardiac computed tomography is a rapidly emerging technique for noninvasive diagnosis of cardiovascular diseases. Nevertheless, the cardiac motion continues to be a limiting factor. Electrocardiogram-gated cardiac computed tomography reconstruction methods yield excellent results, but these are limited in their temporal resolution due to the mechanical movement of the gantry, and lead to residual motion blurring artifacts. If the motion of the cardiac region of interest is determined, motion compensated gated reconstructions can be applied to reduce motion artifacts. In this paper it is shown that elastic image registration methods can be an accurate solution to determine the cardiac motion. A method, which combines elastic registration and iterative computed tomography reconstruction methods delivering motion-corrected images of a chosen cardiac region of interest, is introduced.Using a gated four-dimensional region of interest image data set, a fully automatic elastic image registration is applied to recover a cardiac displacement field from a reference phase to a number of phases within the RR interval. Here, a stochastic optimizer and multiresolution approach are adopted to speed up the registration process. Subsequently, motion-compensated iterative reconstruction using the determined motion field is carried out. For the image representation volume-adapted spherical basis functions (blobs) are used to take the volume change caused by a divergent motion vector field into account.The method is evaluated on phantom data and on four clinical data sets at a strong cardiac motion phase. Comparing the method to standard gated iterative reconstruction results shows that motion compensation strongly improves the image quality in these phases. A qualitative and quantitative accuracy study is presented for the estimated cardiac motion field. For the first time a blob-volume adaptation is applied on clinical data, and in the case of divergent motion it yields improved image quality.A fully automatic local cardiac motion compensated gated iterative method with volume-adapted blobs is proposed. The method leads to excellent motion-corrected images which outperform nonmotion corrected results in phases of strong cardiac motion. In clinical cases, a volume-dependent blob-footprint adaptation proves to be a good solution to take care of the change in the blob volume caused by a divergent motion field.

Background— Although fixed view x-ray angiography remains the primary technique for anatomic imaging of coronary artery disease, the known shortcomings of 2D projection imaging may limit accurate 3D vessel and lesion definition and characterization. A recently developed method to create 3D images of the coronary arteries uses x-ray projection images acquired during a 180� C-arm rotation and continuous contrast injection followed by ECG-gated iterative reconstruction. This method shows promise for providing high-quality 3D reconstructions of the coronary arteries with no user interaction but requires clinical evaluation. Methods and Results— The reconstruction strategy was evaluated by comparing the reconstructed 3D volumetric images with the 2D angiographic projection images from the same 23 patients to ascertain overall image quality, lesion visibility, and a comparison of 3D quantitative coronary analysis with 2D quantitative coronary analysis. The majority of the resulting 3D volume images were rated as having high image quality (66%) and provided the physician with additional clinical information such as complete visualization of bifurcations and unobtainable views of the coronary tree. True-positive lesion detection rates were high (90 to 100%), whereas false-positive detection rates were low (0 to 8.1%). Finally, 3D quantitative coronary analysis showed significant similarity with 2D quantitative coronary analysis in terms of lumen diameters and provided vessel segment length free from the errors of foreshortening. Conclusions— Fully automated reconstruction of rotational coronary x-ray angiograms is feasible, produces 3D volumetric images that overcome some of the limitations of standard 2D angiography, and is ready for further implementation and study in the clinical environment.

Rotational coronary X-ray imaging on C-arm systems provides a multitude of diagnostic projections from the vascular tree with a single contrast agent bolus. The acquisition trajectory is typically limited to a circular arc with a fixed caudo-cranial angulation. This may cause sub- optimal projection directions for specific vessel segments for all acquired views, e.g., those segments orthogonal to the axis of rotation. In this paper, a method is presented to calculate a patient-independent acquisition trajectory with respect to vessel foreshortening and overlap for multiple vessel segments of the coronary tree. This method can be applied to artery as well as vein anatomy.Rotational coronary venograms of 14 patients have been used to generate three-dimensional mesh representations with a semi-automatic two view modeling algorithm. The venous tree is divided into seven different vessel segments. Foreshortening and overlap of every segment are calculated and combined for all patients in a measure called obstruction value. The weighted obstruction values of all vessel segments define a cost function for the entire two-dimensional angular range of the C-arm system. Viterbi's algorithm is used to calculate an optimal trajectory with respect to this cost function. The method is validated by leave-one-out cross-validation on the 14 rotational venography data sets and on simulated venograms of a segmented computed tomography (CT) data set. Projection images with a foreshortening value below 10% and overlap below 20% are rated 'optimal'.In 12 (85.7%) data sets, 43% more optimal images were acquired using the presented method compared to the standard circular arc trajectory. As well, in 13 (92.8%) data sets 38% more vessel segments can be optimally visualized in the acquired images. The test on the CT data set showed that the resulting average root-mean-square error of the extracted centerline points of the segmented CT data set compared to the error based on the views from the circular arc was reduced from 2.52 to 1.55 mm.In a first test, the method proved to deliver improved image quality by reducing foreshortening and overlap of vessel segments and may therefore also improve the centerline extraction accuracy of the semi-automatic two view modeling method.

Fully automatic generation of a volumetric representation of the coronary artery tree can be achieved by rotational coronary angiography acquisition and three-dimensional tomographic reconstruction. The generated volume datasets can assist the physician during percutaneous coronary interventions by visualizing three-dimensional coronary morphology and offering utility tools to derive various quantitative measurements. These utility tools allow lesion assessment, optimal working-view selection for specific vessel segments, and improved guidance via overlay functionality or follow C-arc. This article gives an overview of reconstruction methods, clinical tools, and present clinical data.

Three-dimensional reconstruction of coronary arteries can be performed during x-ray-guided interventions by gated reconstruction from a rotational coronary angiography sequence. Due to imperfect gating and cardiac or breathing motion, the heart's motion state might not be the same in all projections used for the reconstruction of one cardiac phase. The motion state inconsistency causes motion artefacts and degrades the reconstruction quality. These effects can be reduced by a projection-based 2D motion compensation method. Using maximum-intensity forward projections of an initial uncompensated reconstruction as reference, the projection data are transformed elastically to improve the consistency with respect to the heart's motion state. A fast iterative closest-point algorithm working on vessel centrelines is employed for estimating the optimum transformation. Motion compensation is carried out prior to and independently from a final reconstruction. The motion compensation improves the accuracy of reconstructed vessel radii and the image contrast in a software phantom study. Reconstructions of human clinical cases are presented, in which the motion compensation substantially reduces motion blur and improves contrast and visibility of the coronary arteries.

The motion of the heart is a major challenge for cardiac imaging using CT. A novel approach to decrease motion blur and to improve the signal to noise ratio is motion compensated reconstruction which takes motion vector fields into account in order to correct motion. The presented work deals with the determination of local motion vector fields from high contrast objects and their utilization within motion compensated filtered back projection reconstruction. Image registration is applied during the quiescent cardiac phases. Temporal interpolation in parameter space is used in order to estimate motion during strong motion phases. The resulting motion vector fields are during image reconstruction. The method is assessed using a software phantom and several clinical cases for calcium scoring. As a criterion for reconstruction quality, calcium volume scores were derived from both, gated cardiac reconstruction and motion compensated reconstruction throughout the cardiac phases using low pitch helical cone beam CT acquisitions. The presented technique is a robust method to determine and utilize local motion vector fields. Motion compensated reconstruction using the derived motion vector fields leads to superior image quality compared to gated reconstruction. As a result, the gating window can be enlarged significantly, resulting in increased SNR, while reliable Hounsfield units are achieved due to the reduced level of motion artefacts. The enlargement of the gating window can be translated into reduced dose requirements.

A new method is introduce for the three-dimensional (3D) reconstruction of the coronary stents in-vivo utilizing two-dimensional projection images acquired during rotational angiography (RA). The method is based on the application of motion compensated techniques to the acquired angiograms resulting in a temporal snapshot of the stent within the cardiac cycle. For the first time results of 3D reconstructed coronary stents in vivo, with high spatial resolution are presented. The proposed method allows for a comprehensive and unique quantitative 3D assessment of stent expansion that rivals current x-ray and intravascular ultrasound techniques.

Computer tomography (CT) scanners with an increasing number of detector rows offer the potential of shorter scanning times. Nevertheless, the reconstruction problem becomes more challenging, since cone beam artifacts are likely to enter. Here, we consider helical cardiac CT. We analyze how a relationship can be established between exact reconstruction algorithms and the demand to perform a cardiac gating. Utilizing the redundancies requires the consideration of all kinds of Radon planes. For the reconstruction algorithm proposed here, we separate the data into two parts. The first part contains contributions of Radon planes, which are measured with a large number of redundancies. The second part contains the remaining contributions. As it turns out, the second part contributes rather to the low-frequency contents of trans-axial slices. Therefore, we propose to perform a gated back-projection only for the first part, while the second part is back-projected in an ungated way. Data from the complete source trajectory are employed in the reconstruction process in contrary to conventional helical cardiac reconstruction methods. Moreover, all different types of Radon planes are taken into account in the reconstruction, though an ECG-dependent cardiac gating is applied. The reconstruction results, which we present for clinical and simulated data, demonstrate the high potential of CEnPiT for helical cardiac CT with large cone angle systems.

A calcium-scoring phantom with hydroxyapatite-filled cylindrical holes (0.5 to 4 mm) was used. High-resolution scans were performed for an accuracy baseline. The phantom was mounted to a moving heart phantom. Non-moving data with the implementation of an ECG-signal were acquired for different pitches (0.2/0.3), heart rates (60/80/95 bpm) and collimations (16 x 0.75/16 x 1.5 mm). Images were reconstructed with a cone-beam multi-cycle algorithm at a standard thickness/increment of 3 mm/1.5 mm and the thinnest possible thickness (0.8/0.4 and 2/1). Subsequently, ECG-gated moving calcium-scoring phantom data were acquired. The calcium volume and Agatston score were measured. The temporal resolution and reconstruction cycles were calculated. High-resolution scans determine the calcium volume with a high accuracy (mean overestimation, 0.8%). In the non-moving measurements, the volume underestimation ranged from about 6% (16 x 0.75 mm; 0.8/0.4 mm) to nearly 25% (16 x 1.5 mm; 3/1.5 mm). Moving scans showed increased measurement errors depending on the reconstructed RR interval, collimation, pitch, heart rate and gantry rotation time. Also, a correlation with the temporal resolution could be found. The reliability of calcium-scoring results can be improved with the use of a narrower collimation, a lower pitch and the reconstruction of thinner images, resulting in higher patient doses. The choice of the correct cardiac phase within the RR interval is essential to minimize measurement errors.

This paper presents a framework of non-interactive algorithms for the mapping of blood flow information to vessels in 3D-RA images. With the presented method, mapping of flow information to 3D-RA images is done automatically without user interaction. So far, radiologists had to perform this task by extensive image comparisons and did not obtain visualizations of the results. In our approach, flow information is reconstructed by forward projection of vessel pieces in a 3D-RA image to a two-dimensional projection series capturing the propagation of a short additional contrast agent bolus. For accurate 2D-3D image registration, an efficient patient motion compensation technique is introduced. As an exemplary flow-related quantity, bolus arrival times are reconstructed for the vessel pieces by matching of intensity-time curves. A plausibility check framework was developed which handles projection ambiguities and corrects for noisy flow reconstruction results. It is based on a linear programming approach to model the feeding structure of the vessel. The flow reconstruction method was applied to 12 cases of cerebral stenoses, AVMs and aneurysms, and it proved to be feasible in the clinical environment. The propagation of the injected contrast agent was reconstructed and visualized in three-dimensional images. The flow reconstruction method was able to visualize different types of useful information. In cases of stenosis of the middle cerebral artery (MCA), flow reconstruction can reveal impeded blood flow depending on the severeness of the stenosis. With cases of AVMs, flow reconstruction can clarify the feeding structure. The presented methods handle the problems imposed by clinical demands such as non-interactive algorithms, patient motion compensation, short reconstruction times, and technical requirements such as correction of noisy bolus arrival times and handling of overlapping vessel pieces. Problems occurred mainly in the reconstruction and segmentation of 3D-RA images in cases of complex AVMs. The concentration of injected contrast agent was often not sufficient to provide highly contrasted vessels in 3D-RA images. Another segmentation-related problem is known as 'kissing vessels' [19]. Kissing vessel artifacts introduce artificial vessel junctions and thereby distort the feeding structure of the vessel. This may finally cause implausible flow reconstruction results and inverse flow directions in vessel segments. We are currently planning to validate our reconstruction results using particle imaging velocimetry (PIV). PIV experiments with phantoms, for which the true flow parameters are known, will allow for the assessment of the accuracy of our contrast agent based method. In the context of computational fluid dynamics techniques, the potential of the presented flow reconstruction method is high. Flow reconstruction results based on the presented method could be used both as boundary conditions for simulations and as a reference for the validation of simulation results. Computational fluid dynamics provide useful information such as arterial wall shear stress and complex flow patterns in aneurysms.

To evaluate the effect of heart rate on the quality of coronary angiograms obtained with 16-detector row computed tomography (CT) by using temporally enhanced three-dimensional (3D) approaches.The local ethics committee approved the study, and informed consent was obtained from all patients. Fifty patients underwent coronary CT angiography (heart rate range, 45-103 beats per minute). Raw data from helical CT and electrocardiography (ECG) were saved in a combined data set. Retrospectively ECG-gated images were reconstructed at preselected phases (50% and 80%) of the cardiac cycle. A 3D voxel-based approach with cardiac phase weighting was used for reconstruction. Testing for correlation between heart rate, cardiac phase reconstruction window, and image quality was performed with Kruskal-Wallis analysis. Image quality (freedom from cardiac motion-related artifacts) was referenced against findings at conventional angiography in a secondary evaluation step. Regression analysis was performed to calculate heart rate thresholds for future beta-blocker application.A significant negative correlation was observed between heart rate and image quality (r = 0.80, P.001). Motion artifact-free images were available for 44 (88%) patients and were achieved consistently at a heart rate of 80 or fewer beats per minute (n = 39). Best image quality was achieved at 75 or fewer beats per minute. Segmental analysis revealed that 97% of arterial segments (diameteror = 1.5 mm according to conventional angiography) were assessable at 80 or fewer beats per minute. Premature ventricular contractions and rate-contained arrhythmia did not impede diagnostic assessment of the coronary arteries in 10 (83%) of the 12 patients affected.Motion-free coronary angiograms can be obtained consistently with 16-detector row CT scanners and adaptive multicyclic reconstruction algorithms in patients with heart rates of less than 80 beats per minute.

With the introduction of cone beam (CB) scanners, cardiac volumetric computed tomography (CT) imaging has the potential to become a noninvasive imaging tool in clinical routine for the diagnosis of various heart diseases. Heart rate adaptive reconstruction schemes enable the reconstruction of high-resolution volumetric data sets of the heart. Artifacts, caused by strong heart rate variations, high heart rates and obesity, decrease the image quality and the diagnostic value of the images. The image quality suffers from streak artifacts if suboptimal scan and reconstruction parameters are chosen, demanding improved gating techniques. In this paper, an artifact analysis is carried out which addresses the artifacts due to the gating when using a three-dimensional CB cardiac reconstruction technique. An automatic and patient specific cardiac weighting technique is presented in order to improve the image quality. Based on the properties of the reconstruction algorithm, several assessment techniques are introduced which enable the quantitative determination of the cycle-to-cycle transition smoothness and phase homogeneity of the image reconstruction. Projection data of four patients were acquired using a 16-slice CBCT system in low pitch helical mode with parallel electrocardiogram recording. For each patient, image results are presented and discussed in combination with the assessment criteria.

Measurements of spatial and temporal resolution for ECG-gated scanning of a stationary and moving heart phantom with a 16-row MDCT were performed. A resolution phantom with cylindrical holes from 0.4 to 3.0 mm diameter was mounted to a cardiac phantom, which simulates the motion of a beating heart. Data acquisition was performed with 16×0.75 mm at various heart rates (HR, 60–120 bpm), pitches (0.15–0.30) and scanner rotation times (RT, 0.42 and 0.50 s). Raw data were reconstructed using a multi-cycle real cone-beam reconstruction algorithm at multiple phases of the RR interval. Multi-planar reformations (MPR) were generated and analyzed. Temporal resolution and cardiac cycles used for image reconstruction were calculated. In 97.2% (243/250) of data obtained with the stationary phantom, the complete row of holes with 0.6 mm was visible. These results were independent of heart rate, pitch, scanner rotation time and phase point of reconstruction. For the dynamic phantom, spatial resolution was determined during phases of minimal motion (116/250). In 40.5% (47/116), the resolution was 0.6 mm and in 37.1% (43/116) 0.7 mm. Temporal resolution varied between 63 and 205 ms, using 1.5–4.37 cardiac cycles for image reconstruction.

Cone beam computed tomography scanners in combination with heart rate adaptive reconstruction schemes have the potential to enable cardiac volumetric computed tomography (CT) imaging for a larger number of patients and applications. In this publication, an adaptive scheme for the automatic and patient-specific reconstruction optimization is introduced to improve the temporal resolution and image quality. The optimization method permits the automatic determination of the required amount of gated helical cone beam projection data for the reconstruction volume. It furthermore allows one to optimize subvolume reconstruction yielding an increased temporal resolution. In addition, methods for the assessment of the temporal resolution are given which enable a quantitative documentation of the reconstruction improvements. Results are presented for patient data sets acquired in low pitch helical mode using a 16-slice cone beam CT system with parallel ECG recording.

The entropy method for stacking a series of angiographic images is presented and compared with the maximum opacity method, which is already established. The entropy method comprises calculation of the entropy of the time course for each image pixel. This accentuates image areas where a contrast agent bolus is passing. Quantitative analysis of the contrast-to-noise ratio and qualitative analysis of 11 cases were performed, the latter by eight independent viewers. Results indicate that the entropy images show more vascular detail in small peripheral vessels and increased contrast-to-noise ratio by up to a factor of 1.97 compared with maximum opacity images. © RSNA, 2003

Magnetic resonance (MR) imaging has faced a dramatic increase in real-time capabilities over the last years. However, the application of fast pulse sequences still suffers from low signal-to-noise ratios (SNRs), which can be the limiting factor for the actual acquisition speed. In MR fluoroscopy, filtering along the time and/or spatial domain can be applied to increase the image quality. In this paper, a projection-based noise filter is presented that significantly enhances the SNR in projection reconstruction (PR) fluoroscopy without apparent loss of resolution in the reconstructed images. In contrast to an imaged-based approach, this method allows a very efficient computational implementation. The filter algorithm was implemented on a digital signal processor and was applied to real-time processing during PR fluoroscopy. A quantitative analysis of the improvement in SNR and results for different fluoroscopic MR applications are given. Apart from MR fluoroscopy, the proposed technique has the potential to be applied to low dose computed tomography fluoroscopy.

Sequential cone-beam tomography is a method that uses data of two or more parallel circular trajectories of a cone-beam scanner to reconstruct the object function. We propose a condition for the data acquisition that ensures that all object points between two successive circles are irradiated over an angular span of the x-ray source position of exactly 360 degrees in total as seen along the rotation axis. A fast and efficient approximative reconstruction method for the proposed acquisition is presented which uses data from exactly 360 degrees for every object point. It is based on the Tent-FDK method which was recently developed for single circular cone-beam CT. The measurement geometry does not provide sufficient data for exact reconstruction but it is shown that the proposed reconstruction method provides satisfying image quality for small cone angles.

The reconstruction of three-dimensional (3D) objects from 2D X-ray cone-beam projections using a circular source path is most commonly done with an algorithm according to Feldkamp et al. [Feldkamp LA, Davis LC, Kress JW. Practical cone-beam algorithms. J Opt Soc Am A 1984;6:612-619]. An adaptation of this so-called Feldkamp method to cone-beam projections acquired with a C-arm system is presented here. In a phantom study, reconstruction results obtained along real source-detector trajectories of a C-arm system are compared to reconstruction results obtained from projections acquired from a full-circular trajectory and from one consisting of two full orthogonal circles, which fulfills Tuy's sufficiency condition. The straightforward application of Feldkamp's method adapted to projection data obtained with a C-arm system illustrates the 3D imaging potential of image intensifier based cone-beam computed tomography. Reconstruction results from projection data of different patients acquired with a motorized C-arm system such as vessel structures filled with contrast agent and bones are presented.