A quantitative analysis of 3-D coronary modeling from two or more projection images

Impact of cardiac and respiratory motion on the 3D accuracy of image-guided interventions on monoplane systems

PURPOSE

Image-guided intervention (IGI) systems have the potential to increase the efficiency in interventional cardiology but face limitations from motion. Even though motion compensation approaches have been proposed, the resulting accuracy has rarely been quantified using in vivo data. The purpose of this study is to investigate the potential benefit of motion-compensation in IGS systems.

METHODS

Patients scheduled for left atrial appendage closure (LAAc) underwent pre- and postprocedural non-contrast-enhanced cardiac magnetic resonance imaging (CMR). According to the clinical standard, the final position of the occluder device was routinely documented using x-ray fluoroscopy (XR). The accuracy of the IGI system was assessed retrospectively based on the distance of the 3D device marker location derived from the periprocedural XR data and the respective location as identified in the postprocedural CMR data.

RESULTS

The assessment of the motion-compensation depending accuracy was possible based on the patient data. With motion synchronization, the measured accuracy of the IGI system resulted similar to the estimated accuracy, with almost negligible distances of the device marker positions identified in CMR and XR. Neglection of the cardiac and/or respiratory phase significantly increased the mean distances, with respiratory motion mainly reducing the accuracy with rather low impact on the precision, whereas cardiac motion decreased the accuracy and the precision of the image guidance.

CONCLUSIONS

In the presented work, the accuracy of the IGI system could be assessed based on in vivo data. Motion consideration clearly showed the potential to increase the accuracy in IGI systems. Where the general decrease in accuracy in non-motion-synchronized data did not come unexpected, a clear difference between cardiac and respiratory motion-induced errors was observed for LAAc data. Since sedation and intervention location close to the large vessels likely impacts the respiratory motion contribution, an intervention-specific accuracy analysis may be useful for other interventions.

A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images

We present a multi-stage neural network approach for 3D reconstruction of coronary artery trees from uncalibrated 2D X-ray angiography images. This method uses several binarized images from different angles to reconstruct a 3D coronary tree without any knowledge of image acquisition parameters. The method consists of a single backbone network and separate stages for vessel centerline and radius reconstruction. The output is an analytical matrix representation of the coronary tree suitable for downstream applications such as hemodynamic modeling of local vessel narrowing (i.e., stenosis). The network was trained using a dataset of synthetic coronary trees from a vessel generator informed by both clinical image data and literature values on coronary anatomy. Our multi-stage network achieved sub-pixel accuracy in reconstructing vessel radius (RMSE = 0.16 ± 0.07 mm) and stenosis radius (MAE = 0.27 ± 0.18 mm), the most important feature used to inform diagnostic decisions. The network also led to 52% and 38% reduction in vessel centerline reconstruction errors compared to a single-stage network and projective geometry-based methods, respectively. Our method demonstrated robustness to overcome challenges such as vessel foreshortening or overlap in the input images. This work is an important step towards automated analysis of anatomic and functional disease severity in the coronary arteries.

Computed tomography angiography/magnetic resonance imaging-based preprocedural planning and guidance in the interventional treatment of structural heart disease

Preprocedural planning and periprocedural guidance based on image fusion are widely established techniques supporting the interventional treatment of structural heart disease. However, these two techniques are typically used independently. Previous works have already demonstrated the benefits of integrating planning details into image fusion but are limited to a few applications and the availability of the proprietary tools used. We propose a vendor-independent approach to integrate planning details into periprocedural image fusion facilitating guidance during interventional treatment. In this work, we demonstrate the feasibility of integrating planning details derived from computer tomography and magnetic resonance imaging into periprocedural image fusion with open-source and commercially established tools. The integration of preprocedural planning details into periprocedural image fusion has the potential to support safe and efficient interventional treatment of structural heart disease.

3D Reconstruction with Coronary Artery Based on Curve Descriptor and Projection Geometry-Constrained Vasculature Matching

This paper presents a novel method based on a curve descriptor and projection geometry constrained for vessel matching. First, an LM (Leveberg–Marquardt) algorithm is proposed to optimize the matrix of geometric transformation. Combining with parameter adjusting and the trust region method, the error between 3D reconstructed vessel projection and the actual vessel can be minimized. Then, CBOCD (curvature and brightness order curve descriptor) is proposed to indicate the degree of the self-occlusion of blood vessels during angiography. Next, the error matrix constructed from the error of epipolar matching is used in point pairs matching of the vascular through dynamic programming. Finally, the recorded radius of vessels helps to construct ellipse cross-sections and samples on it to get a point set around the centerline and the point set is converted to mesh for reconstructing the surface of vessels. The validity and applicability of the proposed methods have been verified through experiments that result in the significant improvement of 3D reconstruction accuracy in terms of average back-projection errors. Simultaneously, due to precise point-pair matching, the smoothness of the reconstructed 3D coronary artery is guaranteed.

The importance of three dimensional coronary artery reconstruction accuracy when computing virtual fractional flow reserve from invasive angiography

Three dimensional (3D) coronary anatomy, reconstructed from coronary angiography (CA), is now being used as the basis to compute 'virtual' fractional flow reserve (vFFR), and thereby guide treatment decisions in patients with coronary artery disease (CAD). Reconstruction accuracy is therefore important. Yet the methods required remain poorly validated. Furthermore, the magnitude of vFFR error arising from reconstruction is unkown. We aimed to validate a method for 3D CA reconstruction and determine the effect this had upon the accuracy of vFFR. Clinically realistic coronary phantom models were created comprosing seven standard stenoses in aluminium and 15 patient-based 3D-printed, imaged with CA, three times, according to standard clinical protocols, yielding 66 datasets. Each was reconstructed using epipolar line projection and intersection. All reconstructions were compared against the real phantom models in terms of minimal lumen diameter, centreline and surface similarity. 3D-printed reconstructions (n = 45) and the reference files from which they were printed underwent vFFR computation, and the results were compared. The average error in reconstructing minimum lumen diameter (MLD) was 0.05 (± 0.03 mm) which was < 1% (95% CI 0.13-1.61%) compared with caliper measurement. Overall surface similarity was excellent (Hausdorff distance 0.65 mm). Errors in 3D CA reconstruction accounted for an error in vFFR of ± 0.06 (Bland Altman 95% limits of agreement). Errors arising from the epipolar line projection method used to reconstruct 3D coronary anatomy from CA are small but contribute to clinically relevant errors when used to compute vFFR.

3D-XGuide: open-source X-ray navigation guidance system

PURPOSE

With the growing availability and variety of imaging modalities, new methods of intraoperative support have become available for all kinds of interventions. The basic principles of image fusion and image guidance have been widely adopted and are commercialized through a number of platforms. Although multimodal systems have been found to be useful for guiding interventional procedures, they all have their limitations. The integration of more advanced guidance techniques into the product functionality is, however, not easy due to the proprietary solutions of the vendors. Therefore, the purpose of this work is to introduce a software system for image fusion, real-time navigation, and working points documentation during transcatheter interventions performed under X-ray (XR) guidance.

METHODS

An interactive software system for cross-modal registration and image fusion of XR fluoroscopy with CT or MRI-derived anatomic 3D models is implemented using Qt application framework and VTK visualization pipeline. DICOM data can be imported in retrospective mode. Live XR data input is realized by a video capture card application interface.

RESULTS

The actual software release offers a graphical user interface with basic functionality including data import and handling, calculation of projection geometry and transformations between related coordinate systems, rigid 3D-3D registration, and template matching-based tracking and motion compensation algorithms in 2D and 3D. The link to the actual software release on GitHub including source code and executable is provided to support independent research and development in the field of intervention guidance.

CONCLUSION

The introduced system provides a common foundation for the rapid prototyping of new approaches in the field of XR fluoroscopic guidance. As a pure software solution, the developed system is potentially vendor-independent and can be easily extended to be used with the XR systems of different manufacturers.

Improved Registration of 3D CT Angiography with X-ray Fluoroscopy for Image Fusion During Transcatheter Aortic Valve Implantation

The fusion of 3D anatomical models derived from high-fidelity pre-interventional computed tomography angiography (CTA), and x-ray (XR) fluoroscopy to facilitate anatomical guidance is of huge interest for complex cardiac interventions like TAVI procedures with cerebral protection. Co-registration of CTA and XR has been introduced either based on additional intraoperative non-/contrast-enhanced cone-beam computed tomography (CBCT) or two separate aortograms. With the related increase of radiation exposure and/or contrast agent (CA) dose, a potential additional risk for the patient is introduced. Here, we propose a modified co-registration approach making use of arteriograms of the iliofemoral arteries, routinely performed during the femoral puncture and sheath introduction. On-the-fly refinement of the co-registration during the on-going procedure enables accurate co-registration without any additional angiograms, thus reducing CA, XR dose and procedure time, while simultaneously improving operator confidence and procedure safety.

Three-dimensional reconstruction and NURBS-based structured meshing of coronary arteries from the conventional X-ray angiography projection images

Despite its two-dimensional nature, X-ray angiography (XRA) has served as the gold standard imaging technique in the interventional cardiology for over five decades. Accordingly, demands for tools that could increase efficiency of the XRA procedure for the quantitative analysis of coronary arteries (CA) are constantly increasing. The aim of this study was to propose a novel procedure for three-dimensional modeling of CA from uncalibrated XRA projections. A comprehensive mathematical model of the image formation was developed and used with a robust genetic algorithm optimizer to determine the calibration parameters across XRA views. The frames correspondences between XRA acquisitions were found using a partial-matching approach. Using the same matching method, an efficient procedure for vessel centerline reconstruction was developed. Finally, the problem of meshing complex CA trees was simplified to independent reconstruction and meshing of connected branches using the proposed nonuniform rational B-spline (NURBS)-based method. Because it enables structured quadrilateral and hexahedral meshing, our method is suitable for the subsequent computational modelling of CA physiology (i.e. coronary blood flow, fractional flow reverse, virtual stenting and plaque progression). Extensive validations using digital, physical, and clinical datasets showed competitive performances and potential for further application on a wider scale.

3D reconstruction of coronary arteries from 2D angiographic projections using non-uniform rational basis splines (NURBS) for accurate modelling of coronary stenoses

OBJECTIVE

Assessment of coronary stenosis severity is crucial in clinical practice. This study proposes a novel method to generate 3D models of stenotic coronary arteries, directly from 2D coronary images, and suitable for immediate assessment of the stenosis severity.

METHODS

From multiple 2D X-ray coronary arteriogram projections, 2D vessels were extracted. A 3D centreline was reconstructed as intersection of surfaces from corresponding branches. Next, 3D luminal contours were generated in a two-step process: first, a Non-Uniform Rational B-Spline (NURBS) circular contour was designed and, second, its control points were adjusted to interpolate computed 3D boundary points. Finally, a 3D surface was generated as an interpolation across the control points of the contours and used in the analysis of the severity of a lesion. To evaluate the method, we compared 3D reconstructed lesions with Optical Coherence Tomography (OCT), an invasive imaging modality that enables high-resolution endoluminal visualization of lesion anatomy.

RESULTS

Validation was performed on routine clinical data. Analysis of paired cross-sectional area discrepancies indicated that the proposed method more closely represented OCT contours than conventional approaches in luminal surface reconstruction, with overall root-mean-square errors ranging from 0.213mm2 to 1.013mm2, and maximum error of 1.837mm2. Comparison of volume reduction due to a lesion with corresponding FFR measurement suggests that the method may help in estimating the physiological significance of a lesion.

CONCLUSION

The algorithm accurately reconstructed 3D models of lesioned arteries and enabled quantitative assessment of stenoses. The proposed method has the potential to allow immediate analysis of the stenoses in clinical practice, thereby providing incremental diagnostic and prognostic information to guide treatments in real time and without the need for invasive techniques.

Reconstruction of coronary arteries from X-ray angiography: A review

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.

Three-dimensional elliptical reconstruction for stereoscopic magnetic resonance angiography

Stereoscopic MRA acquires a pair of blood vessel projections at two different viewing angles. Previously, we have developed two algorithms to reconstruct 3-D blood vessels from stereoscopic MRA. The assumption we made was that blood vessels were tilting circular tubes and the shape of the vessel on every cross-section was an ellipse. Since an ellipse can be represented in either algebraic form or parametric form, our previous algorithms reconstructed the ellipses by representing them in these two forms. In this paper, we further improved the accuracy of our previous algorithms by an order through two enhancements. The first improvement we made was a better method to estimate the rotation angle of the major axis of an ellipse. Instead of using the center of two adjacent ellipses to estimate the rotation angle as in our previous method, the new method used the projection lengths of the two views to estimate the angle. The second improvement we made was the equation to describe the relationship between the major/minor axes and the projection lengths. In our experiments, the average estimation error for the parametric algorithm was improved from 0.471 pixels to 0.066 pixels. The average error for the algebraic algorithm was improved from 0.101 pixels to 0.014 pixels.

Calibration-free device sizing using an inverse geometry x-ray system

PURPOSE

Quantitative coronary angiography (QCA) can be used to support device size selection for cardiovascular interventions. The accuracy of QCA measurements using conventional x-ray fluoroscopy depends on proper calibration using a reference object and avoiding vessel foreshortening. The authors have developed a novel interventional device sizing method using the inverse geometry scanning-beam digital x-ray (SBDX) fluoroscopy system. The proposed method can measure the diameter and length of vessel segments without imaging a reference object and when vessels appear foreshortened.

METHODS

SBDX creates multiple tomosynthetic x-ray images corresponding to planes through the patient volume. The structures that lie in the plane are in focus and the features above and below the plane are blurred. Three-dimensional localization of the vessel edges was performed by examining the degree of blurring at each image plane. A 3D vessel centerline was created and used to determine vessel magnification and angulation relative to the image planes. Diameter measurements were performed using a model-based method and length measurements were calculated from the 3D centerline. Phantom validation was performed by measuring the diameter and length of vessel segments with nominal diameters ranging from 0.5 to 2.8 mm and nominal lengths of 42 mm. The phantoms were imaged at a range of positions between the source and the detector (+/- 16 cm relative to isocenter) and with a range of foreshortening angles (0 degrees-75 degrees).

RESULTS

Changes in vessel phantom position created magnifications ranging from 87% to 118% relative to isocenter magnification. Average diameter errors were less than 0.15 mm. Average length measurements were within 1% (0.3 mm) of the true length. No trends were observed between measurement accuracy and magnification. Changes in vessel phantom orientation resulted in decreased apparent length down to 28% of the original nonforeshortened length. Average diameter errors were less than 0.25 mm across all vessel angulations; errors were less than 0.1 mm for smaller diameter vessels and low to moderate vessel angles. Diameter errors increased with true diameter and vessel angle relative to the image plane. Average length measurement errors were also within 1% (0.3 mm) for each angulation.

CONCLUSIONS

Tomosynthetic imaging with SBDX can accurately measure dimensions of vessels in various magnifications and angulations without calibration. This method may be more accurate and convenient than conventional QCA techniques.

Vascular deformation for vascular interventional surgery simulation

BACKGROUND

Obtaining the expertise to perform minimally vascular interventional surgery (VIS) requires thorough training. Previous VIS simulators have generally assumed that blood vessels are rigid. However, vascular deformation occurs unavoidably in VIS. In this study, the arterial walls were analysed as soft tissue.

METHODS

A mass-spring model (MSM) was applied for vascular deformation simulation. To improve simulation precision, the spring coefficient was derived from a reference model, simulated with a linear finite element method (FEM), which established a link between the spring coefficient and the properties of the vascular materials. In order to evaluate the simulation results, we applied identical external forces to FEM and MSM and calculated their deformations. Additionally, based on the proposed MSM, we designed a VIS simulator to achieve renal artery intervention. Quantitative validation was performed by comparing the simulated catheter position with a reference position, as assessed by 3D rotational angiography imaging.

RESULTS

From the simulation results, we could clearly see that MSM deformation was real-time and very close to the linear FEM reference, and MSM was successfully adopted in our renal artery intervention simulator.

CONCLUSION

MSM with a spring coefficient derived from linear FEM was able to produce a realistic deformation simulation of arterial walls. This method could also be extended to model other organ deformations.

Clinical feasibility of a fully automated 3D reconstruction of rotational coronary X-ray angiograms

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 degrees 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.

Optimization of acquisition trajectories for 3D rotational coronary venography

OBJECTIVE

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.

METHODS

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'.

RESULTS

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.

CONCLUSION

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.

3-D reconstruction of the coronary artery tree from multiple views of a rotational X-ray angiography

To present an efficient and robust method for 3-D reconstruction of the coronary artery tree from multiple ECG-gated views of an X-ray angiography. 2-D coronary artery centerlines are extracted automatically from X-ray projection images using an enhanced multi-scale analysis. For the difficult data with low vessel contrast, a semi-automatic tool based on fast marching method is implemented to allow manual correction of automatically-extracted 2-D centerlines. First, we formulate the 3-D symbolic reconstruction of coronary arteries from multiple views as an energy minimization problem incorporating a soft epipolar line constraint and a smoothness term evaluated in 3-D. The proposed formulation results in the robustness of the reconstruction to the imperfectness in 2-D centerline extraction, as well as the reconstructed coronary artery tree being inherently smooth in 3-D. We further propose to solve the energy minimization problem using α-expansion moves of Graph Cuts, a powerful optimization technique that yields a local minimum in a strong sense at a relatively low computational complexity. We show experimental results on a synthetic coronary phantom, a porcine data set and 11 patient data sets. For the coronary phantom, results obtained using different number of views are presented. 3-D reconstruction error evaluated by the mean plus one standard deviation is below one millimeter when 4 or more views are used. For real data, reconstruction using 4 to 5 views and 256 depth labels averaged around 12 s on a computer with 2.13 GHz Intel Pentium M and achieves a mean 2-D back-projection error of 1.18 mm (ranging from 0.84 to 1.71 mm) in 12 cases. The accuracy for multi-view reconstruction of the coronary artery tree as reported from the phantom and patient studies is promising, and the efficiency is significantly improved compared to other approaches reported in the literature, which range from a few to tens of minutes. Visually good and smooth reconstruction is demonstrated.

Computer assistance for solving imaging problems

Medical imaging has moved into an era of digital files and processing of images to yield three-dimensional models and reconstructions. This development has opened up opportunities to apply computer techniques in traditional imaging tasks. Two of the most common imaging tasks are those to correct the two-dimensional projection problems of foreshortening of lesions and of vessel overlap. This article explores the use of computers to assist in these tasks, to create databases for guiding decision making, to provide graphics to assist the physician, and to simulate cardiovascular procedures.

Novel approach for 3-d reconstruction of coronary arteries from two uncalibrated angiographic images

Three-dimensional reconstruction of vessels from digital X-ray angiographic images is a powerful technique that compensates for limitations in angiography. It can provide physicians with the ability to accurately inspect the complex arterial network and to quantitatively assess disease induced vascular alterations in three dimensions. In this paper, both the projection principle of single view angiography and mathematical modeling of two view angiographies are studied in detail. The movement of the table, which commonly occurs during clinical practice, complicates the reconstruction process. On the basis of the pinhole camera model and existing optimization methods, an algorithm is developed for 3-D reconstruction of coronary arteries from two uncalibrated monoplane angiographic images. A simple and effective perspective projection model is proposed for the 3-D reconstruction of coronary arteries. A nonlinear optimization method is employed for refinement of the 3-D structure of the vessel skeletons, which takes the influence of table movement into consideration. An accurate model is suggested for the calculation of contour points of the vascular surface, which fully utilizes the information in the two projections. In our experiments with phantom and patient angiograms, the vessel centerlines are reconstructed in 3-D space with a mean positional accuracy of 0.665 mm and with a mean back projection error of 0.259 mm. This shows that the algorithm put forward in this paper is very effective and robust.

Determination of optimal viewing regions for X-ray coronary angiography based on a quantitative analysis of 3D reconstructed models

Current expert-recommended views for coronary angiography are based on heuristic experience and have not been scientifically studied. We sought to identify optimal viewing regions for first and second order vessel segments of the coronary arteries that provide optimal diagnostic value in terms of minimizing vessel foreshortening and overlap. Using orthogonal 2D images of the coronary tree, 3D models were created from which patient-specific optimal view maps (OVM) allowing quantitative assessment of vessel foreshortening and overlap were generated. Using a novel methodology that averages 3D-based optimal projection geometries, a universal OVM was created for each individual coronary vessel segment that minimized both vessel foreshortening and overlap. A universal OVM model for each coronary segment was generated based on data from 137 patients undergoing coronary angiography. We identified viewing regions for each vessel segment achieving a mean vessel foreshortening value of 5.8 +/- 3.9% for the left coronary artery (LCA) and 5.6 +/- 3.6% for the right coronary artery (RCA). The overall mean overlap values achieved were 8.7 +/- 7.9% for the LCA and 4.6 +/- 3.2% for the RCA. This scientifically-based OVM evaluation of coronary vessel segments provides the means to facilitate acquisitions during coronary angiography and interventions that minimize imaging inaccuracies related to foreshortening and overlap, improving the accuracy, efficiency, and safety of diagnostic and interventional coronary procedures.

Automatic generation of time resolved motion vector fields of coronary arteries and 4D surface extraction using rotational x-ray angiography

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.

Evaluation of iterative sparse object reconstruction from few projections for 3-D rotational coronary angiography

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 mbiL(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.

Projection-based motion compensation for gated coronary artery reconstruction from rotational x-ray angiograms

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.

Generation of a cardiac shape model from CT data

In this paper we describe the generation of a geometric cardiac shape model based on cardiac CTA data. The model includes the four cardiac chambers and the trunks of the connected vasculature, as well as the coronary arteries and a set of cardiac landmarks. A mean geometric model for the end-diastolic heart has been built based on 27 end-diastolic cardiac CTA datasets and a mean motion model based on 11 multiphase datasets. The model has been evaluated with respect to its capability to estimate the position of cardiac structures. Allowing a similarity transformation to adapt the model to image data, cardiac surface positions can be predicted with an accuracy of below 5 mm.

Usefulness of high-speed rotational coronary venous angiography during cardiac resynchronization therapy

Standard coronary venous angiography (SCVA) provides a static, fixed projection of the coronary venous (CV) tree. High-speed rotational coronary venous angiography (RCVA) is a novel method of mapping CV anatomy using dynamic, multiangle visualization. The purpose of this study was to assess the value of RCVA during cardiac resynchronization therapy. Digitally acquired rotational CV angiograms from 49 patients (mean age 69 +/- 11 years) who underwent left ventricular lead implantation were analyzed. RCVA, which uses rapid isocentric rotation over a 110 degrees arc, acquiring 120 frames/angiogram, was compared with SCVA, defined as 2 static orthogonal views: right anterior oblique 45 degrees and left anterior oblique 45 degrees . RCVA demonstrated that the posterior vein-to-coronary sinus (CS) angle and the left marginal vein-to-CS angle were misclassified in 5 and 11 patients, respectively, using SCVA. RCVA identified a greater number of second-order tributaries with diameters >1.5 mm than SCVA. The CV branch selected for lead placement was initially identified in 100% of patients using RCVA but in only 74% of patients using SCVA. RCVA showed that the best angiographic view for visualizing the CS and its tributaries differed significantly among different areas of the CV tree and among patients. The area of the CV tree that showed less variability was the CS ostium, which had a fairly constant relation with the spine in shallow right anterior oblique and left anterior oblique projections. In conclusion, RCVA provided a more precise map of CV anatomy and the spatial relation of venous branches. It allowed the identification of fluoroscopic views that could facilitate cannulation of the CS. The final x-ray view displaying the appropriate CV branch for left ventricular lead implantation was often different from the conventional left anterior oblique and right anterior oblique views. RCVA identified the target branch for lead implantation more often than SCVA.

Initial clinical experience of selective coronary angiography using one prolonged injection and a 180° rotational trajectory

OBJECTIVE

Evaluate the safety of prolonged coronary injections during a rotational acquisition covering 180 degrees.

BACKGROUND

Rotational angiography has been adapted to coronary angiography and shown to reduce radiation and contrast exposure. Three-dimensional (3D) reconstructions and other advanced applications require imaging over a 180 degrees -arc with a single but longer injection of larger contrast volumes.

METHODS

Thirty patients referred for angiography were enrolled. Blood pressure (BP), heart rate (HR), symptoms, and ectopy were recorded before-and-after injections.

RESULTS

Pre and post-injection HRs for the LCA/RCA were not statistically different (LCA-pre-injection 63+/-13 bpm vs. LCA-post-injection 62+/-11 bpm, P=0.54 and RCA-pre-injection 65+/-12 bpm vs. RCA-post-injection 65+/-10, P=0.88). Central aortic pressure values were not statistically different for the RCA injections (RCA-systolic-pre-injection 118+/-14 mm Hg vs. RCA-systolic-post-injection 112+/-25 mm Hg, P=0.15, and RCA diastolic-pre-injection 69+/-9 mm Hg vs. RCA-diastolic-post-injection 60+/-10 mm Hg, P=0.88) but were statistically significant for the LCA injections (LCA systolic-pre-injection 122+/-19 mm Hg vs. LCA-systolic-post-injection 116+/-17 mm Hg, P=0.0004, and LCA-diastolic-pre-injection 69+/-10 mm Hg vs. LCA-diastolic-post-injection 65+/-9 mm Hg, P=0.0007). There were no symptoms or electrical events documented during or immediately post-injection.

CONCLUSION

This study demonstrates the feasibility and safety of longer coronary injections. There were no significant HR changes, clinically insignificant pressure changes, and no adverse reactions. Additional studies will be needed to assure its safety in a larger and clinically more varied patient population.

A comprehensive shape model of the heart

Domain knowledge about the geometrical properties of cardiac structures is an important ingredient for the segmentation of these structures in medical images or for the simulation of cardiac physiology. So far, a strong focus was put on the left ventricle due to its importance for the general pumping performance of the heart and related functional indices. However, other cardiac structures are of similar importance, e.g., the coronary arteries with respect to diagnosis and treatment of arteriosclerosis or the left atrium with respect to the treatment of atrial fibrillation. In this paper we describe the generation of a geometric cardiac model including the four cardiac chambers and the trunks of the connected vasculature, as well as the coronary arteries and a set of cardiac landmarks. A mean geometric model for the end-diastolic heart has been built based on 27 cardiac CT datasets and has been evaluated with respect to its capability to estimate the position of cardiac structures. Allowing a similarity transformation to adapt the model to image data, cardiac surface positions can be predicted with an accuracy of below 5mm.

Motion-compensated and gated cone beam filtered back-projection for 3-D rotational X-ray angiography

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.

Towards cardiac C-arm computed tomography

Cardiac interventional procedures would benefit tremendously from sophisticated three-dimensional image guidance. Such procedures are typically performed with C-arm angiography systems, and tomographic imaging is currently available only by using preprocedural computed tomography (CT) or magnetic resonance imaging (MRI) scans. Recent developments in C-arm CT (Angiographic CT) allow three-dimensional (3-D) imaging of low contrast details with angiography imaging systems for noncardiac applications. We propose a new approach for cardiac imaging that takes advantage of this improved contrast resolution and is based on intravenous contrast injection. The method is an analogue to multisegment reconstruction in cardiac CT adapted to the much slower rotational speed of C-arm CT. Motion of the heart is considered in the reconstruction process by retrospective electrocardiogram (ECG)-gating, using only projections acquired at a similar heart phase. A series of N almost identical rotational acquisitions is performed at different heart phases to obtain a complete data set at a minimum temporal resolution of 1/N of the heart cycle time. First results in simulation, using an experimental phantom, and in preclinical in vivo studies showed that excellent image quality can be achieved.

Automatic selection of the optimal cardiac phase for gated three-dimensional coronary x-ray angiography

RATIONALE AND OBJECTIVES

For the reconstruction of the coronary arteries from rotational angiography data, a crucial point is the selection of the optimal cardiac phase for data reconstruction. To avoid time-consuming interactive selection of the optimal cardiac phase by visual inspection of multiple high-resolution data sets reconstructed at different cardiac phases, an automatic approach for deriving optimal reconstruction windows is attractive.

MATERIALS AND METHODS

This paper presents a new approach to fully automatic selection of the optimal cardiac phase for image reconstruction. It is based on the analysis of a four-dimensional data set of the region of interest reconstructed at low-spatial resolution utilizing an image quality index, which quantifies the image quality of a single three-dimensional reconstructed volume. The derived image quality index utilizes the histogram information of a single temporal snapshot as a quality measure for the vessel reconstruction. The proposed technique was applied to 16 projection data sets obtained in eight pigs.

RESULTS

Experiments to evaluate the proposed method based on user-defined image quality parameters serving as ground truth, showed a relatively high correlation (>84%) for high-quality (c(phi) > 0.95) images.

CONCLUSION

An image-based technique is introduced, which is able to determine the optimal cardiac phase for 3D-RCA fully automatically. The proposed method was successfully applied to 16 data sets obtained in a total of 8 porcine models.

Reconstruction of coronary arteries from a single rotational X-ray projection sequence

Cardiovascular diseases remain the primary cause of death in developed countries. In most cases, exploration of possibly underlying coronary artery pathologies is performed using X-ray coronary angiography. Current clinical routine in coronary angiography is directly conducted in two-dimensional projection images from several static viewing angles. However, for diagnosis and treatment purposes, coronary artery reconstruction is highly suitable. The purpose of this study is to provide physicians with a three-dimensional (3-D) model of coronary arteries, e.g., for absolute 3-D measures for lesion assessment, instead of direct projective measures deduced from the images, which are highly dependent on the viewing angle. In this paper, we propose a novel method to reconstruct coronary arteries from one single rotational X-ray projection sequence. As a side result, we also obtain an estimation of the coronary artery motion. Our method consists of three main consecutive steps: 1) 3-D reconstruction of coronary artery centerlines, including respiratory motion compensation; 2) coronary artery four-dimensional motion computation; 3) 3-D tomographic reconstruction of coronary arteries, involving compensation for respiratory and cardiac motions. We present some experiments on clinical datasets, and the feasibility of a true 3-D Quantitative Coronary Analysis is demonstrated.

Standardized evaluation methodology for 2-D-3-D registration

In the past few years, a number of two-dimensional (2-D) to three-dimensional (3-D) (2-D-3-D) registration algorithms have been introduced. However, these methods have been developed and evaluated for specific applications, and have not been directly compared. Understanding and evaluating their performance is therefore an open and important issue. To address this challenge we introduce a standardized evaluation methodology, which can be used for all types of 2-D-3-D registration methods and for different applications and anatomies. Our evaluation methodology uses the calibrated geometry of a 3-D rotational X-ray (3DRX) imaging system (Philips Medical Systems, Best, The Netherlands) in combination with image-based 3-D-3-D registration for attaining a highly accurate gold standard for 2-D X-ray to 3-D MR/CT/3DRX registration. Furthermore, we propose standardized starting positions and failure criteria to allow future researchers to directly compare their methods. As an illustration, the proposed methodology has been used to evaluate the performance of two 2-D-3-D registration techniques, viz. a gradient-based and an intensity-based method, for images of the spine. The data and gold standard transformations are available on the internet (http://www.isi.uu.nl/Research/Databases/).