Gang Gao

Registration of 3D trans-esophageal echocardiography to x-ray fluoroscopy using image-based probe tracking

Two-dimensional (2D) X-ray imaging is the dominant imaging modality for cardiac interventions. However, the use of X-ray fluoroscopy alone is inadequate for the guidance of procedures that require soft-tissue information, for example, the treatment of structural heart disease. The recent availability of three-dimensional (3D) trans-esophageal echocardiography (TEE) provides cardiologists with real-time 3D imaging of cardiac anatomy. Increasingly X-ray imaging is now supported by using intra-procedure 3D TEE imaging. We hypothesize that the real-time co-registration and visualization of 3D TEE and X-ray fluoroscopy data will provide a powerful guidance tool for cardiologists. In this paper, we propose a novel, robust and efficient method for performing this registration. The major advantage of our method is that it does not rely on any additional tracking hardware and therefore can be deployed straightforwardly into any interventional laboratory. Our method consists of an image-based TEE probe localization algorithm and a calibration procedure. While the calibration needs to be done only once, the GPU-accelerated registration takes approximately from 2 to 15s to complete depending on the number of X-ray images used in the registration and the image resolution. The accuracy of our method was assessed using a realistic heart phantom. The target registration error (TRE) for the heart phantom was less than 2mm. In addition, we assess the accuracy and the clinical feasibility of our method using five patient datasets, two of which were acquired from cardiac electrophysiology procedures and three from trans-catheter aortic valve implantation procedures. The registration results showed our technique had mean registration errors of 1.5-4.2mm and 95% capture range of 8.7-11.4mm in terms of TRE.

A subject-specific technique for respiratory motion correction in image-guided cardiac catheterisation procedures

We describe a system for respiratory motion correction of MRI-derived roadmaps for use in X-ray guided cardiac catheterisation procedures. The technique uses a subject-specific affine motion model that is quickly constructed from a short pre-procedure MRI scan. We test a dynamic MRI sequence that acquires a small number of high resolution slices, rather than a single low resolution volume. Additionally, we use prior knowledge of the nature of cardiac respiratory motion by constraining the model to use only the dominant modes of motion. During the procedure the motion of the diaphragm is tracked in X-ray fluoroscopy images, allowing the roadmap to be updated using the motion model. X-ray image acquisition is cardiac gated. Validation is performed on four volunteer datasets and three patient datasets. The accuracy of the model in 3D was within 5mm in 97.6% of volunteer validations. For the patients, 2D accuracy was improved from 5 to 13mm before applying the model to 2-4mm afterwards. For the dynamic MRI sequence comparison, the highest errors were found when using the low resolution volume sequence with an unconstrained model.

Ultrasound calibration using intensity-based image registration: for application in cardiac catheterization procedures

We present a novel method to calibrate a 3D ultrasound probe which has a 2D transducer array. By optically tracking a calibrated 3D probe we are able to produce extended field of view 3D ultrasound images. Tracking also enables us to register our ultrasound images to other tracked and calibrated surgical instruments or to other tracked and calibrated imaging devices. Our method applies rigid intensity-based image registration to three or more ultrasound images. These images can either be of a simple phantom, or could potentially be images of the patient. In this latter case we would have an automated calibration system which required no phantom, no image segmentation and was optimized to the patients ultrasound characteristics i.e. speed of sound. We have carried out experiments using a simple calibration phantom and with ultrasound images of a volunteers liver. Results are compared to an independent gold-standard. These showed our method to be accurate to 1.43mm using the phantom images and 1.56mm using the liver data, which is slightly better than the traditional point-based calibration method (1.7mm in our experiments).

Rapid image registration of three-dimensional transesophageal echocardiography and X-ray fluoroscopy for the guidance of cardiac interventions

The recent availability of three-dimensional (3D) transesophageal echocardiography (TEE) provides cardiologists with real-time 3D imaging of cardiac anatomy. X-ray fluoroscopy is the conventional modalilty that is used for guiding many cardiac interventions. Increasingly this is now supported using intra-procedure 3D TEE imaging. We hypothesize that the real-time co-registration and visualization of 3D TEE and X-ray fluoroscopy data will provide a powerful guidance tool for cardiologists. In this paper, we propose a novel, robust and efficient method for performing this registration. Our method consists of an image-based TEE probe localization algorithm and a calibration procedure. While the calibration needs to be done only once, the registration takes approximately 9.5 seconds to complete. The accuracy of our method was assessed by using both a crosswire phantom and a more realistic heart phantom. The target registration error for the heart phantom was less than 2mm. In addition, the accuracy and the clinical feasiblity of our method was evaluated in two cardiac electrophysiology procedures. The registration results showed in-plane errors of 1.5 and 3mm.

Anisotropic wave propagation and apparent conductivity estimation in a fast electrophysiological model: application to XMR interventional imaging

Cardiac arrhythmias are increasingly being treated using ablation procedures. Development of fast electrophysiological models and estimation of parameters related to conduction pathologies can aid in the investigation of better treatment strategies during Radio-frequency ablations. We present a fast electrophysiological model incorporating anisotropy of the cardiac tissue. A global-local estimation procedure is also outlined to estimate a hidden parameter (apparent electrical conductivity) present in the model. The proposed model is tested on synthetic and real data derived using XMR imaging. We demonstrate a qualitative match between the estimated conductivity parameter and possible pathology locations. This approach opens up possibilities to directly integrate modelling in the intervention room.

Novel System for Real-Time Integration of 3-D Echocardiography and Fluoroscopy for Image-Guided Cardiac Interventions: Preclinical Validation and Clinical Feasibility Evaluation

Real-time imaging is required to guide minimally invasive catheter-based cardiac interventions. While transesophageal echocardiography allows for high-quality visualization of cardiac anatomy, X-ray fluoroscopy provides excellent visualization of devices. We have developed a novel image fusion system that allows real-time integration of 3-D echocardiography and the X-ray fluoroscopy. The system was validated in the following two stages: 1) preclinical to determine function and validate accuracy; and 2) in the clinical setting to assess clinical workflow feasibility and determine overall system accuracy. In the preclinical phase, the system was assessed using both phantom and porcine experimental studies. Median 2-D projection errors of 4.5 and 3.3 mm were found for the phantom and porcine studies, respectively. The clinical phase focused on extending the use of the system to interventions in patients undergoing either atrial fibrillation catheter ablation (CA) or transcatheter aortic valve implantation (TAVI). Eleven patients were studied with nine in the CA group and two in the TAVI group. Successful real-time view synchronization was achieved in all cases with a calculated median distance error of 2.2 mm in the CA group and 3.4 mm in the TAVI group. A standard clinical workflow was established using the image fusion system. These pilot data confirm the technical feasibility of accurate real-time echo-fluoroscopic image overlay in clinical practice, which may be a useful adjunct for real-time guidance during interventional cardiac procedures.

Real-time compounding of three-dimensional transesophageal echocardiographic volumes: The phantom study

3D ultrasound has attracted considerable interest in recent years as a low cost, mobile and real-time imaging modality for interventional cardiac applications. However, the low image quality and small field of view have been two major barriers preventing 3D ultrasound from being widely accepted as a solution to the guidance of cardiac interventions. By using the 3D transesophageal echographic (TEE) probe, it is possible to acquire images with better quality compared to the images acquired from traditional transthoracic probe (TTE). However, the 3D TEE volume has even smaller field of view and is insufficient to cover the whole geometry of the heart. Previously, we have developed a technique to compound 3D TTE volumes in real-time. In this study, we extend this technique to compound 3D TEE volumes by using an electromagnetic tracking system. In this pilot study, two different types of phantoms were used to evaluate our technique. The results suggest our method is accurate and efficient. The compounding error is approximately 2.5mm.

Image-based automatic ablation point tagging system with motion correction for cardiac ablation procedures

X-ray fluoroscopically guided cardiac ablation procedures are commonly carried out for the treatment of cardiac arrhythmias, such as atrial fibrillation (AF). X-ray images have poor soft tissue contrast and, for this reason, overlay of a 3D roadmap derived from pre-procedural volumetric image data can be used to add anatomical information. It is a requirement to determine and record the 3D positions of the ablation catheter tip in the 3D road map during AF ablation. This feature can be used as a guidance and post-procedure analysis tool. The 3D positions of the catheter tip can be calculated from biplane X-ray images and mapped to the 3D roadmap. However, the registration between the 3D roadmap and the 2D X-ray data can be compromised by patient respiratory and cardiac motions. As the coronary sinus (CS) catheter is not routinely altered during the procedure, tracking the CS catheter in real-time can be used as means of motion correction to improve the accuracy of registration between live X-ray images and a 3D roadmap. To achieve a fast and automatic ablation point tagging system from biplane images, we developed a novel tracking method for real-time simultaneous detection of the ablation catheter and the CS catheter from fluoroscopic X-ray images. We tested our tracking method on 1083 fluoroscopy frames from 16 patients and achieved a success rate of 97.5% and an average 2D tracking error of 0.5 mm ± 0.3 mm. In order to achieve tagging using a monoplane X-ray image system, we proposed a novel motion gating method to select a pair of images from two short image sequences acquired from two different views. Both respiratory and cardiac motion phases are matched by selecting the pair of images with the minimum reconstruction error of the CS catheter electrodes. Finally, the 3D position of the ablation catheter tip was calculated using the epipolar constraint from the multiview images. We validated our automatic ablation point tagging strategy by computing the reconstruction error of the ablation catheter tip and achieved an error of 1.1 mm ± 0.5 mm.

A technique for respiratory motion correction in image guided cardiac catheterisation procedures

This paper presents a technique for compensating for respiratory motion and deformation in an augmented reality system for cardiac catheterisation procedures. The technique uses a subject-specific affine model of cardiac motion which is quickly constructed from a pre-procedure magnetic resonance imaging (MRI) scan. Respiratory phase information is acquired during the procedure by tracking the motion of the diaphragm in real-time X-ray images. This information is used as input to the model which uses it to predict the position of structures of interest during respiration. 3-D validation is performed on 4 volunteers and 4 patients using a leave-one-out test on manually identified anatomical landmarks in the MRI scan, and 2-D validation is performed by using the model to predict the respiratory motion of structures of the heart which contain catheters that are visible in X-ray images. The technique is shown to reduce 3-D registration errors due to respiratory motion from up to 15mm down to less than 5mm, which is within clinical requirements for many procedures. 2-D validation showed that accuracy improved from 14mm to 2mm. In addition, we use the model to analyse the effects of different types of breathing on the motion and deformation of the heart, specifically increasing the breathing rate and depth of breathing. Our findings suggest that the accuracy of the model is reduced if the subject breathes in a different way during model construction and application. However, models formed during deep breathing may be accurate enough to be applied to other types of breathing.

Validation of the use of photogrammetry to register pre- procedure MR images to intra-procedure patient position for image-guided cardiac catheterization procedures

A hybrid X-ray and magnetic resonance imaging system (XMR) has been proposed as an interventional guidance for cardiovascular catheterisation procedure. However, very few hospitals can benefit from the XMR system because of its limited availability. In this paper we describe a new guidance strategy for cardiovascular catheterisation procedure. In our technique, intra-operative patient position is estimated by using a chest surface reconstructed from a photogrammetry system. The chest surface is then registered with the same surface derived from pre-procedure magnetic resonance (MR) images. The catheterisation procedure can therefore be guided by a roadmap derived from the MR images. Patients were required to hold the breath at end expiration during MRI acquisition. The surface matching accuracy is improved by using a robust trimmed iterative closest point (ICP) matching algorithm, which is especially designed for incomplete surface matching. Compared to the XMR system, the proposed guidance strategy is low cost and easy to set up. Experimental data were acquired from 6 volunteers and 1 patient. The patient data were collected during an electrophysiology procedure. In 6 out of 7 subjects, the experimental results show our method is accurate in term of reciprocal residual error (range from 1.66m to 3.75mm) and constant (closed-loop TREs range from 1.49mm to 3.55mm). For one subject, trimmed ICP failed to find the optimal transform matrix (residual = 4.89, TRE = 9.32) due to the poor quality of the photogrammetry-reconstructed surface. More studies are being carried on in clinical trials.