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DEVELOPMENTS IN CARDIAC INTERVENTIONS
Image Improvement, Reconstruction, Guidance, and Navigation
Jörn Borgert1, Raoul Florent2, Sascha Krueger1, Sherif Makram-Ebeid2, Babak Movassaghi3, Holger Timinger1 and Volker Rasche4
1Philips Research, Hamburg, Germany; 2Philips Medical Systems, Paris, France;
3Philips Research, Briarckiff Manor, NY, USA; 4University Hospital Ulm, Ulm, Germany
Abstract: Over the last decades, X-ray imaging technology in the catheterization laboratory (cath lab) has dramatically evolved. On latest X-ray equipment, new functionalities such as low-dose imaging, three-dimensional imaging and improved navigation technology aiming for further improvement of existing interventional procedures as well as enabling future procedures are on the verge. This contribution provides a brief overview on some new technologies, which have recently been introduced into clinical practice. Furthermore, some representative examples of ongoing research activities are presented.
Keywords: 3D coronary angiography, stent boosting, noise reduction, motion- compensated navigation
1. INTRODUCTION
The guidance of cardiac interventional procedures such as PTCA and stent deployment has been the domain of X-ray fluoroscopy for the last decades. The introduction of new technologies has significantly improved the imaging performance of the X-ray imaging equipment. For example, the recent commercial availability of flat detector X-ray imaging systems has
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© 2006 Springer. Printed in the Netherlands.
dramatically improved image quality while further reducing radiation dose.
(cath lab) typically provide multiple degrees of freedom enabling the acquisition of X-ray projections from multiple angulations without moving
1).
the patient, while maintaining sufficient patient accessibility (see Figure 11-
G. Spekowius and T. Wendler (Eds.), Advances in Healthcare Technology,
Recent X-ray system geometries for cardiac catheterization laboratories
On the other side, almost 50 years after Mason Sones (1919-1985) acquired the first coronary angiogram, the basic principle of selective angiography has not changed with the introduction of modern X-ray systems. Considering the two-dimensional projective nature of conventional angiography, some limitations such as superposition of vascular structures and vessel foreshortening are obvious. Quantitative measurements of the vessels properties such as length, cross-sectional area, and orientation cannot precisely be retrieved from the two-dimensional projections and there is always the risk that the target lesion is visualized foreshortened or superimposed by other structures. Furthermore, new complex procedures such as interventional multi-vessel disease treatment, patent foramen ovalis (PFO) closures1, transluminal valve repair and replacement2, and the injection of biological material in the myocardial wall3 are currently on the verge.
Figure 11-1. Recent bi-plane cardiovascular X-ray system.
Recent technical developments for improving the interventional guidance focus on a further reduction of the X-ray dose, on providing three- technologies.
This contribution will focus on some specific recent developments for dose reduction by means of image processing, three-dimensional dimensional information, and on the integration of advanced navigation
motion-compensated navigation.
2. IMAGE NOISE REDUCTION
Interventional cardiovascular procedures still involve considerable X-ray dose to the patient and staff, for which the accumulated dose received is still a great concern. Increasing workloads and case complexity will likely place further pressure on X-ray dose levels, which makes X-ray dose reduction an important topic in the field of X-ray-guided interventions.
To reduce X-ray dose, different approaches, such as the use of high power X-ray tubes in combination with heavy filtration of the X-ray beam, have been applied. Although these techniques may provide a reduction of the X-ray dose, the possible maximal reduction is still limited by image noise.
Recently, dedicated filters were introduced, which could significantly for example edges. The proposed cardiac enhancement filter (CEF) was initially developed for conventional ultrasound imaging4,5 and later modified to be used specifically for X-ray projections. As depicted in Figure 11-2, the filter utilizes a multi-resolution Laplacian Pyramid decomposition as defined by Burt and Adelson in their 1983 paper6.
Figure 11-2. Block diagram showing the processing in X-ray noise reduction filtering.
reconstruction from projection data, enhancement of stent visualization, and
reduce X-ray image noise while preserving important image characteristics,
Figure 11-3. Low-dose X-ray projection images before (left) and after (right) filtering by the dedicated cardiac enhancement filter.
Each slice image is decomposed into a succession of sub-bands representing different levels of resolution from coarse to fine. Within each sub-band, pixels are segmented into high contrast regions (edges and ridges) and weakly textured regions. Highly anisotropic filtering is applied to the high contrast regions using adaptive smoothing kernels that are elongated along the ridges and edges and that may optionally provide some enhancement in the direction normal to those ridges and edges. In this way edges and ridges are not blurred and can even be slightly enhanced. In the weakly textured regions, slight isotropic filtering is applied to reduce high frequency random noise without appreciably altering the texture. These operations are applied to each of the individual sub-bands before recomposing the pyramid. As outlined in the figure, the processing at each resolution includes an analysis phase in which each sub-band is segmented into high contrast and weakly textured regions. In the analysis phase, the edge and ridge feature orientations are computed for determining the required filter kernels size and anisotropy. In the subsequent filtering phase, pixel adaptive filtering is implemented.
The described multi-resolution filter technique allows a significant improvement of the signal-to-noise and the contrast-to-noise ratios and enables the application of significantly reduced X-ray doses (see Figure 11- 3), while maintaining the clinical value of the images.
3. VOLUME RECONSTRUCTION FROM PROJECTION DATA
Stent deployment is the preferred vascular interventional procedure for coronary stenosis treatment, making coronary angiography and angioplasty two of the most widespread diagnostic and interventional procedures performed worldwide. These procedures are currently carried out based on information provided by two-dimensional (2D) projection angiograms of the coronary arteries. However, the projective nature of the acquisition results in vessel foreshortening and vessel overlap, which still are major obstacles in X-ray guided fluoroscopic procedures. There is a strong demand for adding three-dimensional morphological and functional data for improving the assessment of the degree and relevance of a certain stenosis or even to enable quantitative three-dimensional assessment of vessel properties.
moving the gantry at high speed around the patient. This so-called Rotational information on the vascular morphology during the intervention.
3.1 Rotational angiography
In Rotational Angiography, projection data are acquired along a planar trajectory by rotating the C-arm gantry around the patient either in head or lateral position. The target anatomic area is positioned in the center-of- rotation. During the rotation, contrast agent (Iodine, 300mg/ml, 1.5 – 3 ml/s flow rate) is selectively injected into the root of the vascular structure under investigation. In applying RA to the coronary arteries, projections are normally taken from RAO 55º to LAO 55º, providing projective information on the coronary arteries over a huge angular range from a cine data acquisition using a single contrast injection only. Several studies by investigators7,8 using X-ray systems from multiple vendors have documented the safety and clinical utility of this approach. In fact, some of these studies demonstrated that in clinical practice by utilizing RA, the overall amount of contrast injected and the X-ray dose can be significantly reduced in comparison to the traditional non-rotational technique. Figure 11-4 shows an Angiography (RA) functionality is utilized for providing more detailed Recent X-ray systems offers the ability to acquire data while constantly
example of multiple projections obtained from a single rotational acquisition.
a)
c) d)
b) a)
c) d)
b)
Figure 11-4. Example of coronary rotational angiograms, where a-c) show three different views of the LCA obtained during a single rotational run, and d) shows a single projection of the RCA selected to ensure minimal foreshortening of the medial section.
3.2 Coronary modeling
To further improve the value of X-ray imaging during cardiovascular interventions, in recent years much work has been performed to expand the current 2D imaging modality into 3D, utilizing a number of 2D X-ray projection images obtained during a single rotational angiography data acquisition. Current methods9-11 generate a three-dimensional representation of the coronary arteries by means of so-called ‘coronary modeling techniques’. In 3D modeling, the 2D projected center- and borderline of the vascular tree are extracted in at least two projections. In combination with the accurate knowledge of the projection geometry, the knowledge of the 2D
projected center- and borderline can be used for generation of a 3D representation of the vascular tree (see Figure 11-5). The resulting 3D representation of the coronary artery tree enables an accurate assessment of the three-dimensional structure of the anatomy of the coronary tree and can be applied for localization of lesions. Besides volumetric quantitative analysis of the degree of stenosis, the 3D representation enables the automatic generation of optimal view-maps for the extraction of those projection directions providing minimal foreshortening and vessel overlap for a specific segment of the vascular tree (see Figure 11-5).
Figure 11-5. 3D model of a left coronary artery tree (left) and the respective optimal view map (right), obtained for the yellow-colored vessel branch. Green indicates little foreshortening and vessel overlap, whereas red indicates severe foreshortening and vessel overlap, depending on the angulation (y-axis) and the rotation (x-axis) of the X-ray gantry.
3.3 Three-dimensional reconstruction
From a user’s perspective, a major limitation of 3D modeling is the required user-interaction for guiding the segmentation of the center- and borderlines in the 2D projections. Either a significant reduction in the amount of user interaction or perhaps even a fully automated generation of a three-dimensional coronary reconstruction may be beneficial in expediting the generation of 3D images for diagnostic and therapeutic purposes. In recent years, three-dimensional reconstructions at high spatial resolution have been demonstrated for non-moving vascular structures based on calibrated 2D X-ray projection data acquired during a rotational run. The
application of these acquisition and reconstruction methods to the coronary arteries requires additional correction procedures for cardiac and respiratory motion. Initial studies have been performed in which breath-hold data acquisition techniques have been combined with ECG-gated13 and motion- compensated techniques14,15.
In ECG-gated techniques, projection data acquired in the same cardiac phase are used for performing a full three-dimensional reconstruction. To obtain sufficient projections from a single rotational data acquisition and to ensure enough angular coverage for the reconstruction, the acquisition protocols have been modified to cover an angular range of about 220º in about 8s. The acquisition protocol was tested in eight pigs. It was well tolerated by all animals and neither a significant venous enhancement nor an obvious hypoxia-induced change in the contraction pattern or heart rate could be observed. After acquisition, the projections were clustered based on delays relative to the R-peaks of the ECG signal. Three-dimensional back-projection was done using a slightly modified Feldkamp algorithm16 considering the real projection geometry and compensating for the non- equidistant angular sampling. Reconstructions were performed using a spatial resolution between 0.13 mm3 and 0.43 mm3 as shown in Figure 11-6.
Figure 11-6. ECG-gated three-dimensional reconstruction of a LAD (left) and RCA (right).
Data courtesy of Prof. Dr. A. Buecker, RWTH Aachen, Germany.
3 3
4. STENT BOOST FLUOROSCOPIC IMAGING
During conventional coronary stenting procedures, the assessment of the stent after deployment is crucial for ensuring optimal outcome. The applicability of conventional X-ray fluoroscopy imaging is limited by the contrast between the stent and the background. Stent boost fluoroscopic imaging (StentBoost) is a new technique, in which a motion-compensated sum over several successive X-ray fluoroscopic projections is formed for improving the visibility of the stent in the final image.
Figure 11-7. Raw X-ray fluoroscopy images (left) and corresponding StentBoost X-ray fluoroscopy images (right).
The motion compensation is based on fully automated tracking of the positions of the markers on the balloon catheter used for deployment of the stent. The tracked positions are utilized for generation of a motion vector field describing the motion of the markers over time. Assuming that the stent moves similar to the balloon markers, the derived motion vector field is used for performing a motion-compensated summation of temporally successive
projections. By motion-compensated summation, all structures moving synchronously with the balloon markers are enhanced, while other structures are smeared off, thereby increasing the visibility of the stent (see Figure 11- 7). The summation produces a highly augmented image of the deployed stent in coronary arteries – while the catheter is still in place. The StentBoost image helps clinicians to make a thorough check of stent expansion, and see the position of stents in relation to other objects, e.g. other stents, without the use of extra contrast agent or intra-vascular imaging modalities.
fluoroscopy images (mid) and IVUS image (right). Data courtesy of Prof. AD Michaels, UCSF, California, USA.
Figure 11-9. Comparison of stent diameter measurements between QCA and IVUS (left) and between StentBoost and IVUS (right).
Figure 11-8. Raw X-ray fluoroscopy images (left), corresponding StentBoost X-ray
Comparison of quantitative coronary angiography (QCA), intravascular
17 for the determination of adequate stent expansion revealed that in direct comparison Stent Boost provided a significantly better correlation of stent diameter measurements (n = 47; r =
for StentBoost where for QCA a mean difference of 0.21mm (95% CI 0.12
5. MOTION COMPENSATED NAVIGATION FOR CARDIOVASCULAR APPLICATIONS
The general aim of motion compensated navigation using virtual roadmaps and non-line-of-sight (NLOS) localization technology for navigation and guidance in interventional procedures is to reduce contrast agent and dose burden to both patient and physician while at the same time conserving or improving the accuracy of the guidance. Tracking systems used for the NLOS localization task perform spatial measurements of position and orientation. However, for the correlation of the position and orientation information to static virtual roadmaps, the measurements have to be compensated for internal organ motion due to heartbeat and respiration.
NLOS localization is normally done by means of magnetic tracking systems (MTS), which is a technology allowing for real-time position measurements of medical devices without line-of-sight restrictions. It has therefore been used to track interventional devices like catheters, needles or endoscopes inside the human18-23.
One of the most prominent challenges of applying MTS for the tracking of medical devices is the presence of large amounts of conductive or ferromagnetic materials, which cause a distortion of the magnetic field. In cases where the magnetic environment remains constant, registration between the imaging modality and the NLOS system can be established.
Focusing on the conventional interventional equipment including an X-ray system, a registration will only be valid for one given orientation of the gantry. Whenever the gantry rotates or the detector is shifted, this registration will become inaccurate due to changes in the magnetic environment. To avoid magnetic field variation due to movement of the gantry, the MTS can be attached to the gantry21 to ensure a static situation between MTS and gantry.
The problem of organ motion has widely been investigated in the field of motion-compensated image reconstruction. Such motion compensation strategies include, among others, gated acquisition protocols or the use of 0.77; p < 0.001) than QCA (n = 47; r = 0.69; p < 0.001). Bland-Altman ultrasound (IVUS) and StentBoost
analysis showed a mean difference of -0.09mm (95% CI -0.19 to +0.01mm) to 0.31mm) resulted when compared to IVUS (see Figure 11-8 and 11-9).
parameterized motion models, which are driven by the ECG or a respiratory sensor signal, inspired by motion compensated MR image acquisition, where rigid or affine parameterized motion models are commonly used24,25. Here, the parameterization is accomplished by means of a respiratory sensor signal, which is derived from diaphragm tracking using 1D-pencil beams acquired by the MR scanner. A similar idea was used for tracking the diaphragm for motion compensation in 2D X-ray projection images26. These techniques can also be applied to motion compensated interventional navigation.
Figure 11-10. Example of sensing the respiratory position by monitoring the position of the diaphragm in an U/S image. The image on the left depicts a typical U/S image with superimposed navigator box applied for the diaphragm position extraction. The image on the right shows the involved steps for deriving the diaphragm position from the U/S navigator box signal.
The motion model itself can be considered as a parameterized elastic deformation field, which assigns a correction vector to the catheter position measured in a known respiratory and cardiac phase in order to compensate for organ motion. Such a deformation field could be determined using a non- patient specific motion model of the coronaries or can be acquired directly by measurements using the MTS. The beauty of learning the motion from MTS measurements is that no additional images have to be acquired and the motion model can be updated and refined during the intervention itself. The motion model and thus the motion compensation can locally and temporally be refined and enhanced by adding new or replacing old sample points during the intervention in real-time. This feature is especially valuable when approaching complex structures where increased accuracy is advantageous
or when motion patterns change at a point in time, which would render the previous model partially inaccurate.
In phantom studies, the elastic motion model is driven by a simulated ECG signal and a respiratory sensor signal derived from ultrasonic diaphragm tracking as shown in Figure 11-10. For U/S based diaphragm tracking, a small ‘navigator’ window is located in the ultrasound B-mode image. The diaphragm position is then determined using image processing techniques.
Typical results from phantom studies using ECG together with QRS detection and U/S based diaphragm tracking to drive an MTS-determined elastic, refinable motion model are outlined in Figure 11-11. The used phantom28 comprises a pneumatically driven dynamic heart phantom, which can simulate the motion of the left ventricle and the left coronary arteries due to heartbeat and respiration. It includes the possibility of selecting different heart rates and respiratory cycle length. The three-dimensional roadmap of the coronary arteries was obtained by gated 3D-rotational coronary angiography.
Figure 11-11. Motion-compensated 3D/2D image overlay of the tracked device (red circle) on the 3D roadmap and the X-ray fluoroscopy image at different gantry orientations.
In phantom studies29, the accuracy of the navigation could be significantly improved. Residual motion turned out to be in the area of 1mm, enabling the unique identification of the vessel under examination.
6. SUMMARY AND DISCUSSION
Over decades, the main target in the cardiac catheterization laboratory has been the diagnosis and therapy of coronary artery disease. The main imaging modality applied for guidance has been and still is X-ray fluoroscopy. Although highly efficient, some major drawbacks arise from the ionizing radiation and especially from the two-dimensional projective
nature of X-ray fluoroscopy, which might cause vessel foreshortening and vessel overlap. The ongoing trends of performing more complex transcatheter procedures such as treatment of multi-vessel diseases in the cath lab and the rise of new complex procedures such as PFO closures and valve repair and replacement demand improved guidance principles, preferably at lower dose levels.
exposure protocols in combination with dedicated image processing techniques enabling noise-enhancement while conserving structures in the X-ray image or enabling local enhancement of structures by means of motion-compensation.
More complex procedures will be enabled by complementing X-ray fluoroscopy by three-dimensional morphological and functional imaging, likely in combination with advanced catheter localization and navigation techniques, which will utilize available images e.g. for roadmap based guidance. New interventional instruments providing intra-vascular and intra- cardiac imaging, while localizable by non line-of-sight localization techniques, will enter the field for improved interventional imaging and guidance.
Considering the current developments in medical imaging, due to the real-time and spatial resolution demands in intervention guidance, X-ray fluoroscopy will play a major role for the foreseeable future. However, new the procedures. Besides importing three-dimensional pre-interventional data, it is likely that the flexibility of recent X-ray system will be utilized for providing geometrically exact morphological information of the vessel lumen in 3D at high isotropic spatial resolution during the intervention. This information will improve the quantitative assessment of lesion dimensions and will enable the prediction of optimal projection angles providing minimal foreshortening and vessel overlap for a certain lesion. Roadmap- based techniques, either for dose reduction or improvement of the accuracy and efficacy of the procedures, will likely be introduced at a later stage, when the more complex procedures are clinically established and reliable registration and motion-compensation techniques will be available.
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