3-D/2-D Registration of Cardiac Structures by 3-D Contrast Agent Distribution Estimation
This work addresses the challenge of robust 3-D/2-D registration in cardiac procedures for clinicians, but it is incremental as it builds on existing registration methods with new similarity measures.
The paper tackles the problem of registering a 3-D model of the left atrium to X-ray images for cardiac catheter ablation, particularly when contrast agent is limited, by proposing two similarity measures: explicit apparent edges and contrast agent distribution estimate (CADE). The evaluation on clinical datasets showed errors of 7.9±6.3 mm for well-contrasted cases and 8.8±6.7 mm for low-contrast cases, significantly outperforming a baseline method.
For augmented fluoroscopy during cardiac catheter ablation procedures, a preoperatively acquired 3-D model of the left atrium of the patient can be registered to X-ray images. Therefore the 3D-model is matched with the contrast agent based appearance of the left atrium. Commonly, only small amounts of contrast agent (CA) are used to locate the left atrium. This is why we focus on robust registration methods that work also if the structure of interest is only partially contrasted. In particular, we propose two similarity measures for CA-based registration: The first similarity measure, explicit apparent edges, focuses on edges of the patient anatomy made visible by contrast agent and can be computed quickly on the GPU. The second novel similarity measure computes a contrast agent distribution estimate (CADE) inside the 3-D model and rates its consistency with the CA seen in biplane fluoroscopic images. As the CADE computation involves a reconstruction of CA in 3-D using the CA within the fluoroscopic images, it is slower. Using a combination of both methods, our evaluation on 11 well-contrasted clinical datasets yielded an error of 7.9+/-6.3 mm over all frames. For 10 datasets with little CA, we obtained an error of 8.8+/-6.7 mm. Our new methods outperform a registration based on the projected shadow significantly (p<0.05).