Alexander Brost

Respiratory motion compensation by model-based catheter tracking during EP procedures.

In many cases, radio-frequency catheter ablation of the pulmonary veins attached to the left atrium still involves fluoroscopic image guidance. Two-dimensional X-ray navigation may also take advantage of overlay images derived from static pre-operative 3D volumetric data to add anatomical details otherwise not visible under X-ray. Unfortunately, respiratory motion may impair the utility of static overlay images for catheter navigation. We developed a novel approach for image-based 3D motion estimation and compensation as a solution to this problem. It is based on 3D catheter tracking which, in turn, relies on 2D/3D registration. To this end, a bi-plane C-arm system is used to take X-ray images of a special circumferential mapping catheter from two directions. In the first step of the method, a 3D model of the device is reconstructed. Three-dimensional respiratory motion at the site of ablation is then estimated by tracking the reconstructed catheter model in 3D based on bi-plane fluoroscopy. Phantom data and clinical data were used to assess model-based catheter tracking. Our phantom experiments yielded an average 2D tracking error of 1.4mm and an average 3D tracking error of 1.1mm. Our evaluation of clinical data sets comprised 469 bi-plane fluoroscopy frames (938 monoplane fluoroscopy frames). We observed an average 2D tracking error of 1.0 + or - 0.4mm and an average 3D tracking error of 0.8 + or - 0.5mm. These results demonstrate that model-based motion-compensation based on 2D/3D registration is both feasible and accurate.

3-D Respiratory Motion Compensation during EP Procedures by Image-Based 3-D Lasso Catheter Model Generation and Tracking

Radio-frequency catheter ablation of the pulmonary veins attached to the left atrium is usually carried out under fluoroscopy guidance. Two-dimensional X-ray navigation may involve overlay images derived from a static pre-operative 3-D volumetric data set to add anatomical details. However, respiratory motion may impair the utility of static overlay images for catheter navigation. We developed a system for image-based 3-D motion estimation and compensation as a solution to this problem for which no previous solution is yet known. It is based on 3-D catheter tracking involving 2-D/3-D registration. A biplane X-ray C-arm system is used to image a special circumferential (lasso) catheter from two directions. In the first step of the method, a 3-D model of the device is reconstructed. 3-D respiratory motion at the site of ablation is then estimated by tracking the reconstructed model in 3-D from biplane fluoroscopy. In our experiments, the circumferential catheter was tracked in 231 biplane fluoro frames (462 monoplane fluoro frames) with an average 2-D tracking error of 1.0 mm +/- 0.5 mm.

Constrained Registration for Motion Compensation in Atrial Fibrillation Ablation Procedures

Fluoroscopic overlay images rendered from preoperative volumetric data can provide additional anatomical details to guide physicians during catheter ablation procedures for treatment of atrial fibrillation (AFib). As these overlay images are often compromised by cardiac and respiratory motion, motion compensation methods are needed to keep the overlay images in sync with the fluoroscopic images. So far, these approaches have either required simultaneous biplane imaging for 3-D motion compensation, or in case of monoplane X-ray imaging, provided only a limited 2-D functionality. To overcome the downsides of the previously suggested methods, we propose an approach that facilitates a full 3-D motion compensation even if only monoplane X-ray images are available. To this end, we use a training phase that employs a biplane sequence to establish a patient specific motion model. Afterwards, a constrained model-based 2-D/3-D registration method is used to track a circumferential mapping catheter. This device is commonly used for AFib catheter ablation procedures. Based on the experiments on real patient data, we found that our constrained monoplane 2-D/3-D registration outperformed the unconstrained counterpart and yielded an average 2-D tracking error of 0.6 mm and an average 3-D tracking error of 1.6 mm. The unconstrained 2-D/3-D registration technique yielded a similar 2-D performance, but the 3-D tracking error increased to 3.2 mm mostly due to wrongly estimated 3-D motion components in X-ray view direction. Compared to the conventional 2-D monoplane method, the proposed method provides a more seamless workflow by removing the need for catheter model re-initialization otherwise required when the C-arm view orientation changes. In addition, the proposed method can be straightforwardly combined with the previously introduced biplane motion compensation technique to obtain a good trade-off between accuracy and radiation dose reduction.

Accuracy of x-ray image-based 3D localization from two C-arm views: a comparison between an ideal system and a real device

arm X-ray imaging devices are commonly used for minimally invasive cardiovascular or other interventional procedures. Calibrated state-of-the-art systems can, however, not only be used for 2D imaging but also for three-dimensional reconstruction either using tomographic techniques or even stereotactic approaches. To evaluate the accuracy of X-ray object localization from two views, a simulation study assuming an ideal imaging geometry was carried out first. This was backed up with a phantom experiment involving a real C-arm angiography system. Both studies were based on a phantom comprising five point objects. These point objects were projected onto a flat-panel detector under different C-arm view positions. The resulting 2D positions were perturbed by adding Gaussian noise to simulate 2D point localization errors. In the next step, 3D point positions were triangulated from two views. A 3D error was computed by taking differences between the reconstructed 3D positions using the perturbed 2D positions and the initial 3D positions of the five points. This experiment was repeated for various C-arm angulations involving angular differences ranging from 15° to 165°. The smallest 3D reconstruction error was achieved, as expected, by views that were 90° degrees apart. In this case, the simulation study yielded a 3D error of 0.82 mm ± 0.24 mm (mean ± standard deviation) for 2D noise with a standard deviation of 1.232 mm (4 detector pixels). The experimental result for this view configuration obtained on an AXIOM Artis C-arm (Siemens AG, Healthcare Sector, Forchheim, Germany) system was 0.98 mm ± 0.29 mm, respectively. These results show that state-of-the-art C-arm systems can localize instruments with millimeter accuracy, and that they can accomplish this almost as well as an idealized theoretical counterpart. High stereotactic localization accuracy, good patient access, and CT-like 3D imaging capabilities render state-of-the-art C-arm systems ideal devices for X-ray based minimally invasive procedures.

Semi-automatic catheter reconstruction from two views

We propose novel methods for (a) detection of a catheter in fluoroscopic images and (b) reconstruction of this catheter from two views. The novelty of (a) is a reduced user interaction and a higher accuracy. It requires only a single seed point on the catheter in the fluoroscopic image. Using this starting point, possible parts of the catheter are detected using a graph search. An evaluation of the detection using 66 clinical fluoroscopic images yielded an average error of 0.7 mm +/- 2.0 mm. The novelty of (b) is a better ability to deal with highly curved objects as it selects an optimal set of point correspondences from two point sequences describing the catheters in two fluoroscopic images. The selected correspondences are then used for computation of the 3-D reconstruction. The evaluation on 33 clinical biplane images yielded an average backprojection error of 0.4 mm +/- 0.6 mm.

Model-based registration for motion compensation during EP ablation procedures

Radio-frequency catheter ablation (RFCA) has become an accepted treatment option for atrial fibrillation (Afib). RFCA of Afib involves isolation of the pulmonary veins under X-ray guidance. For easier navigation, two-dimensional X-ray imaging may take advantage of overlay images derived from static pre-operative 3-D data set to add anatomical details which, otherwise, would not be visible under X-ray. Unfortunately, respiratory and cardiac motion may impair the utility of static overlay images for catheter navigation. We developed a system for image-based 2-D motion estimation and compensation as a solution to this problem. It is based on 2-D catheter tracking facilitated by model-based registration of an ellipse-shaped model to fluorosocpic images. A mono-plane or a bi-plane X-ray C-arm system can be used. In the first step of the method, a 2-D model of the catheter device is computed. Respiratory and cardiac motion at the site of ablation is then estimated by tracking the catheter device in fluoroscopic images. The cost function of the registration step is based on the average distance of the model to the segmented circumferential mapping catheter using a distance map. In our experiments, the circumferential catheter was successfully tracked in 688 fluoroscopic images with an average 2-D tracking error of 0.59 mm ± 0.25 mm. Our presented method achieves a tracking rate of 10 frames-per-second.

Combined cardiac and respiratory motion compensation for atrial fibrillation ablation procedures

Catheter ablation of atrial fibrillation has become an accepted treatment option if a patient no longer responds to or tolerates drug therapy. A main goal is the electrical isolation of the pulmonary veins attached to the left atrium. Catheter ablation may be performed under fluoroscopic image guidance. Due to the rather low soft-tissue contrast of X-ray imaging, the heart is not visible in these images. To overcome this problem, overlay images from pre-operative 3-D volumetric data can be used to add anatomical detail. Unfortunately, this overlay is compromised by respiratory and cardiac motion. In the past, two methods have been proposed to perform motion compensation. The first approach involves tracking of a circumferential mapping catheter placed at an ostium of a pulmonary vein. The second method relies on a motion estimate obtained by localizing an electrode of the coronary sinus (CS) catheter. We propose a new motion compensation scheme which combines these two methods. The effectiveness of the proposed method is verified using 19 real clinical data sets. The motion in the fluoroscopic images was estimated with an overall average error of 0.55 mm by tracking the circumferential mapping catheter. By applying an algorithm involving both the CS catheter and the circumferential mapping catheter, we were able to detect motion of the mapping catheter from one pulmonary vein to another with a false positive rate of 5.8 %.

Percutaneous Punctures with MR Imaging Guidance: Comparison between MR Imaging–enhanced Fluoroscopic Guidance and Real-time MR Imaging Guidance

PURPOSE To evaluate and compare the technical accuracy and feasibility of magnetic resonance (MR) imaging-enhanced fluoroscopic guidance and real-time MR imaging guidance for percutaneous puncture procedures in phantoms and animals. MATERIALS AND METHODS The experimental protocol was approved by the institutional animal care and use committee. Punctures were performed in phantoms, aiming for markers (20 each for MR imaging-enhanced fluoroscopic guidance and real-time MR imaging guidance), and pigs, aiming for anatomic landmarks (10 for MR imaging-enhanced fluoroscopic guidance and five for MR imaging guidance). To guide the punctures, T1-weighted three-dimensional (3D) MR images of the phantom or pig were acquired. Additional axial and coronal T2-weighted images were used to visualize the anatomy in the animals. For MR imaging-enhanced fluoroscopic guidance, phantoms and pigs were transferred to the fluoroscopic system after initial MR imaging and C-arm computed tomography (CT) was performed. C-arm CT and MR imaging data sets were coregistered. Prototype navigation software was used to plan a puncture path with use of MR images and to superimpose it on fluoroscopic images. For real-time MR imaging, an interventional MR imaging prototype for interactive real-time section position navigation was used. Punctures were performed within the magnet bore. After completion, 3D MR imaging was performed to evaluate the accuracy of insertions. Puncture durations were compared by using the log-rank test. The Mann-Whitney U test was applied to compare the spatial errors. RESULTS In phantoms, the mean total error was 8.6 mm ± 2.8 with MR imaging-enhanced fluoroscopic guidance and 4.0 mm ± 1.2 with real-time MR imaging guidance (P < .001). The mean puncture time was 2 minutes 10 seconds ± 44 seconds with MR imaging-enhanced fluoroscopic guidance and 37 seconds ± 14 with real-time MR imaging guidance (P < .001). In the animal study, a tolerable distance (<1 cm) between target and needle tip was observed for both MR imaging-enhanced fluoroscopic guidance and real-time MR imaging guidance. The mean total error was 7.7 mm ± 2.4 with MR imaging-enhanced fluoroscopic guidance and 7.9 mm ± 4.9 with real-time MR imaging guidance (P = .77). The mean puncture time was 5 minutes 43 seconds ± 2 minutes 7 seconds with MR imaging-enhanced fluoroscopic guidance and 5 minutes 14 seconds ± 2 minutes 25 seconds with real-time MR imaging guidance (P = .68). CONCLUSION Both MR imaging-enhanced fluoroscopic guidance and real-time MR imaging guidance demonstrated reasonable and similar accuracy in guiding needle placement to selected targets in phantoms and animals.

Catheter tracking: filter-based vs. learning-based

Atrial fibrillation is the most common sustained arrhythmia. One important treatment option is radio-frequency catheter ablation (RFCA) of the pulmonary veins attached to the left atrium. RFCA is usually performed under fluoroscopic (X-ray) image guidance. Overlay images computed from pre-operative 3-D volumetric data can be used to add anatomical detail otherwise not visible under X-ray. Unfortunately, current fluoro overlay images are static, i.e., they do not move synchronously with respiratory and cardiac motion. A filter-based catheter tracking approach using simultaneous biplane fluoroscopy was previously presented. It requires localization of a circumferential tracking catheter, though. Unfortunately, the initially proposed method may fail to accommodate catheters of different size. It may also detect wrong structures in the presence of high background clutter. We developed a new learning-based approach to overcome both problems. First, a 3-D model of the catheter is reconstructed. A cascade of boosted classifiers is then used to segment the circumferential mapping catheter. Finally, the 3-D motion at the site of ablation is estimated by tracking the reconstructed model in 3-D from biplane fluoroscopy. We compared our method to the previous approach using 13 clinical data sets and found that the 2-D tracking error improved from 1.0 mm to 0.8 mm. The 3-D tracking error was reduced from 0.8 mm to 0.7 mm.

Multi-frame Super-resolution with Quality Self-assessment for Retinal Fundus Videos

This paper proposes a novel super-resolution framework to reconstruct high-resolution fundus images from multiple low-resolution video frames in retinal fundus imaging. Natural eye movements during an examination are used as a cue for super-resolution in a robust maximum a-posteriori scheme. In order to compensate heterogeneous illumination on the fundus, we integrate retrospective illumination correction for photometric registration to the underlying imaging model. Our method utilizes quality self-assessment to provide objective quality scores for reconstructed images as well as to select regularization parameters automatically. In our evaluation on real data acquired from six human subjects with a low-cost video camera, the proposed method achieved considerable enhancements of low-resolution frames and improved noise and sharpness characteristics by 74%. In terms of image analysis, we demonstrate the importance of our method for the improvement of automatic blood vessel segmentation as an example application, where the sensitivity was increased by 13% using super-resolution reconstruction.