Modeling and Registration for Electrophysiology Procedures Based on Three-Dimensional Imaging

Image-based view-angle independent cardiorespiratory motion gating and coronary sinus catheter tracking for x-ray-guided cardiac electrophysiology procedures

Determination of the cardiorespiratory phase of the heart has numerous applications during cardiac imaging. In this article we propose a novel view-angle independent near-real time cardiorespiratory motion gating and coronary sinus (CS) catheter tracking technique for x-ray fluoroscopy images that are used to guide cardiac electrophysiology procedures. The method is based on learning CS catheter motion using principal component analysis and then applying the derived motion model to unseen images taken at arbitrary projections, using the epipolar constraint. This method is also able to track the CS catheter throughout the x-ray images in any arbitrary subsequent view. We also demonstrate the clinical application of our model on rotational angiography sequences. We validated our technique in normal and very low dose phantom and clinical datasets. For the normal dose clinical images we established average systole, end-expiration and end-inspiration gating success rates of 100%, 85.7%, and 92.3%, respectively. For very low dose applications, the technique was able to track the CS catheter with median errors not exceeding 1 mm for all tracked electrodes. Average gating success rates of 80.3%, 71.4%, and 69.2% were established for the application of the technique on clinical datasets, even with a dose reduction of more than 10 times. In rotational sequences at normal dose, CS tracking median errors were within 1.2 mm for all electrodes, and the gating success rate was 100%, for view angles from RAO 90° to LAO 90°. This view-angle independent technique can extract clinically useful cardiorespiratory motion information using x-ray doses significantly lower than those currently used in clinical practice.

Synchronization and Registration of Cine Magnetic Resonance and Dynamic Computed Tomography Images of the Heart

The synchronization and registration of dynamic computed tomography (CT) and magnetic resonance images (MRI) of the heart is required to perform a combined analysis of their complementary information. We propose a novel method that synchronizes and registers intrapatient dynamic CT and cine-MRI short axis view (SAX). For the synchronization step, a normalized cross-correlation curve is computed from each image sequence to describe the global cardiac dynamics. The time axes of these curves are then warped using an adapted dynamic time warping (DTW) procedure. The adaptation constrains the time deformation to obtain a coherent warping function. The registration step then computes the rigid transformation that maximizes the multiimage normalized mutual information of DTW-synchronized images. The DTW synchronization and the multiimage registration were evaluated using dynamic CT and cine-SAX acquisitions from nine patients undergoing cardiac resynchronization therapy. The distance between the end-systolic phases after DTW was used to evaluate the synchronization. Mean errors, expressed as a percentage of the RR-intervals, were 3.9% and 3.7% after adapted DTW synchronization against 10.8% and 11.3% after linear synchronization, for dynamic CT and cine-SAX, respectively. This suggests that the adapted DTW synchronization leads to a coherent warping of cardiac dynamics. The multiimage registration was evaluated using fiducial points. Compared to a monoimage and a two-image registration, the multiimage registration of DTW-synchronized images obtained the lowest mean fiducial error showing that the use of dynamic voxel intensity information improves the registration.

Multimodal registration and data fusion for cardiac resynchronization therapy optimization

Cardiac resynchronization therapy (CRT) has been shown to improve cardiovascular function in specific patients suffering from heart failure. This procedure still needs to be optimized to overcome the high rate of implanted patients that do not respond to this therapy. We propose in this work a better characterization of the electro-mechanical (EM) coupling of each region of the left ventricle (LV) that could be useful to precise the best implantation site. A new descriptor is proposed with the extraction of local electro-mechanical delays. Their measurement is based on the fusion of anatomical, functional and electrical data acquired using computed tomography (CT), speckle tracking echocardiography (STE), and electro-anatomical mappings (EAM). We propose a workflow to place multimodal data in the same geometrical referential system and to extract local electro-mechanical descriptors. It implies the fusion of electrical and mechanical data on a 3D+ t anatomical model of the LV. It mainly consists in four steps: 1) the modeling of the endocardium using a dynamic surface estimated from CT images; 2) the semi-interactive registration of EAM data and CT images; 3) the automatic registration of STE data on the dynamic model, using a metric based on Fourier descriptors and dynamic time warping; 4) the temporal alignment between EAM and STE and the estimation of local electro-mechanical delays. The proposed process has been applied to real data corresponding to five patients undergoing CRT. Results show that local electro-mechanical delays provide meaningful information on the local characterization of the LV and may be useful for the optimal pacing site selection in CRT.

Increasing the automation of a 2D-3D registration system

Routine clinical use of 2D-3D registration algorithms for Image Guided Surgery remains limited. A key aspect for routine clinical use of this technology is its degree of automation, i.e., the amount of necessary knowledgeable interaction between the clinicians and the registration system. Current image-based registration approaches usually require knowledgeable manual interaction during two stages: for initial pose estimation and for verification of produced results. We propose four novel techniques, particularly suited to vertebra-based registration systems, which can significantly automate both of the above stages. Two of these techniques are based upon the intraoperative "insertion" of a virtual fiducial marker into the preoperative data. The remaining two techniques use the final registration similarity value between multiple CT vertebrae and a single fluoroscopy vertebra. The proposed methods were evaluated with data from 31 operations (31 CT scans, 419 fluoroscopy images). Results show these methods can remove the need for manual vertebra identification during initial pose estimation, and were also very effective for result verification, producing a combined true positive rate of 100% and false positive rate equal to zero. This large decrease in required knowledgeable interaction is an important contribution aiming to enable more widespread use of 2D-3D registration technology.