Rui Liao

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.

Automatic Aorta Segmentation and Valve Landmark Detection in C-Arm CT for Transcatheter Aortic Valve Implantation

Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure to treat severe aortic valve stenosis. As an emerging imaging technique, C-arm computed tomography (CT) plays a more and more important role in TAVI on both pre-operative surgical planning (e.g., providing 3-D valve measurements) and intra-operative guidance (e.g., determining a proper C-arm angulation). Automatic aorta segmentation and aortic valve landmark detection in a C-arm CT volume facilitate the seamless integration of C-arm CT into the TAVI workflow and improve the patient care. In this paper, we present a part-based aorta segmentation approach, which can handle structural variation of the aorta in case that the aortic arch and descending aorta are missing in the volume. The whole aorta model is split into four parts: aortic root, ascending aorta, aortic arch, and descending aorta. Discriminative learning is applied to train a detector for each part separately to exploit the rich domain knowledge embedded in an expert-annotated dataset. Eight important aortic valve landmarks (three hinges, three commissures, and two coronary ostia) are also detected automatically with an efficient hierarchical approach. Our approach is robust under all kinds of variations observed in a real clinical setting, including changes in the field-of-view, contrast agent injection, scan timing, and aortic valve regurgitation. Taking about 1.1 s to process a volume, it is also computationally efficient. Under the guidance of the automatically extracted patient-specific aorta model, the physicians can properly determine the C-arm angulation and deploy the prosthetic valve. Promising outcomes have been achieved in real clinical applications.

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.

System to guide transcatheter aortic valve implantations based on interventional c-arm CT imaging

Transcatheter aortic valve implantation is an emerging technique to be applied in patients with aortic valve defects. Angiographic and fluoroscopic X-ray imaging with a C-arm system is crucial in these minimally invasive procedures. We describe a prototypical system based on the ability to acquire a 3D C-arm CT image during transcatheter aortic valve implantations. It supports the physician in measuring critical anatomical parameters, finding an optimum C-arm angulation, and guiding the positioning and deployment of the prosthesis by 3D overlay with fluoroscopic images. To yield high acceptance by the physicians in the operating room, our approach is fast, fully integrated into an angiographic C-arm system, and designed to minimize the necessary user interaction. We evaluate the accuracy of our system on 20 clinical cases.

Image guidance of intracardiac ultrasound with fusion of pre-operative images

This paper presents a method for registering 3D intracardiac echo (ICE) to pre-operative images. A magnetic tracking sensor is integrated on the ICE catheter tip to provide the 3D location and orientation. The user guides the catheter into the patient heart to acquire a series of ultrasound images covering the anatomy of the heart chambers. An automatic intensity-based registration algorithm is applied to align these ultrasound images with pre-operative images. One of the important applications is to help electrophysiology doctors to treat complicated atrial fibrillation cases. After registration, the doctor can see the position and orientation of the ICE catheter and other tracked catheters inside the heart anatomy in real time. The image guidance provided by this technique may increase the ablation accuracy and reduce the amount of time for the electrophysiology procedures. We show successful image registration results from animal experiments.

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.

A hybrid method for 2-D/3-D registration between 3-D volumes and 2-D angiography for trans-catheter aortic valve implantation (TAVI)

Minimally invasive trans-catheter aortic valve implantation (TAVI) procedure can be greatly facilitated using smart visualization and guidance technology involving the 3-D model of the aorta. In this paper, a hybrid method is proposed for contrast-based registration between the 3-D model and angiography of the aorta during TAVI procedures. By integrating the information of aorta segmentation and aortic landmark detection into intensity-based registration, the proposed method combines the merits of intensity-based registration and feature/landmark-based registration. In addition, the challenging task of explicit feature/landmark extraction on 2-D images is avoided. Experiments on 9 real clinical data achieved an average registration error of 2.14±0.49 pixels, demonstrating the efficacy of the proposed method.

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.

Learning-Based 2d/3d rigid registration using jensen-shannon divergence for image-guided surgery

Registration of 3D volumetric data to 2D X-ray images has many applications in image-guided surgery, varying from verification of patient position to working projection searching. In this work, we propose a learning-based method that incorporates the prior information on the expected joint intensity histogram for robust real-time 2D/3D registration. Jensen-Shannon divergence (JSD) is used to quantify the statistical (dis)similarity between the observed and expected joint histograms, and is shown to be superior to Kullback-Leibler divergence (KLD) in its symmetry, being theoretically upper-bounded, and well-defined with histogram non-continuity. A nonlinear histogram mapping technique is proposed to handle the intensity difference between the observed data and the training data so that the learned prior can be used for registration of a wide range of data subject to intensity variations. We applied the proposed method on synthetic, phantom and clinical data. Experimental results demonstrated that a combination of the prior knowledge and the low-level similarity measure between the images being registered led to a more robust and accurate registration in comparison with the cases where either of the two factors was used alone as the driving force for registration.

Automatic and efficient contrast-based 2-D/3-D fusion for trans-catheter aortic valve implantation (TAVI)

Trans-catheter aortic valve implantation (TAVI) is a new breakthrough in the field of minimally invasive surgery applied on high-risk patients with aortic valve defects. 2-D X-ray angiographic and fluoroscopic images are typically used to guide TAVI procedures, for which contrast agent needs to be injected from time to time in order to make the anatomy of the aortic root visible under X-ray. Advanced visualization and guidance technology involving patient-specific 3-D models of the aorta can greatly facilitate the relatively complex TAVI procedures by providing a more realistic anatomy of the aortic root and more accurate C-Arm angulation. In this paper, a fully automatic and efficient system for contrast-based 2-D/3-D fusion for TAVI is presented. Contrast agent injection into the aortic root is automatically detected based on histogram analysis and a likelihood ratio test on the X-ray images. A hybrid method is then applied for contrast-based 2-D/3-D registration between the 3-D model and the detected angiographic frame. By integrating the information of aorta segmentation and aortic landmark detection into intensity-based registration, the proposed method combines the merits of intensity-based registration and feature/landmark-based registration. Experiments on 34 clinical data sets from TAVI patients achieve 100% correct detection on the contrast-enhanced frame, and a mean registration error of 0.66±0.47mm for 2-D/3-D registration. The proposed method is furthermore highly efficient with an average processing time of 2.5s after the most contrast-enhanced frame is available, demonstrating the efficacy of the proposed method to be adopted in a clinical setup.