YingLiang Ma

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.

Multi-site left ventricular pacing as a potential treatment for patients with postero-lateral scar: insights from cardiac magnetic resonance imaging and invasive haemodynamic assessment.

AIMS Multi-site left ventricular (LV) pacing may be superior to single-site stimulation in correcting dyssynchrony and avoiding areas of myocardial scar. We sought to characterize myocardial scar using cardiac magnetic resonance imaging (CMR). We aimed to quantify the acute haemodynamic response to single-site and multi-site LV stimulation and to relate this to the position of the LV leads in relation to myocardial scar. METHODS Twenty patients undergoing cardiac resynchronization therapy had implantation of two LV leads. One lead (LV1) was positioned in a postero-lateral vein, the second (LV2) in a separate coronary vein. LV dP/dtmax was recorded using a pressure wire during stimulation at LV1, LV2, and both sites simultaneously (LV1 + 2). Patients were deemed acute responders if ΔLV dP/dtmax was ≥ 10%. Cardiac magnetic resonance imaging was performed to assess dyssynchrony as well as location and burden of scar. Scar anatomy was registered with fluoroscopy to assess LV lead position in relation to scar. RESULTS LV dP/dtmax increased from 726 ± 161 mmHg/s in intrinsic rhythm to 912 ± 234 mmHg/s with LV1, 837 ± 188 mmHg/s with LV2, and 932 ± 201 mmHg/s with LV1 and LV2. Nine of 19 (47%) were acute responders with LV1 vs. 6/19 (32%) with LV2. Twelve of 19 (63%) were acute responders with simultaneous LV1 + 2. Two of three patients benefitting with multi-site pacing had the LV1 lead positioned in postero-lateral scar. CONCLUSION Multi-site LV pacing increased acute response by 16% vs. single-site pacing. This was particularly beneficial in patients with postero-lateral scar identified on CMR.

Real-time respiratory motion correction for cardiac electrophysiology procedures using image-based coronary sinus catheter tracking

X-ray fluoroscopically guided cardiac electrophysiological procedures are routinely carried out for diagnosis and treatment of cardiac arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of static 3D roadmaps derived from pre-procedural volumetric data can be used to add anatomical information. However, the registration between the 3D roadmap and the 2D X-ray data can be compromised by patient respiratory motion. We propose a novel method to correct for respiratory motion using real-time image-based coronary sinus (CS) catheter tracking. The first step of the proposed technique is to use a blob detection method to detect all possible catheter electrodes in the Xray data. We then compute a cost function to select one CS catheter from all catheter-like objects. For correcting respiratory motion, we apply a low pass filter to the 2D motion of the CS catheter and update the 3D roadmap using this filtered motion. We tested our CS catheter tracking method on 1048 fluoroscopy frames from 15 patients and achieved a success rate of 99.3% and an average 2D tracking error of 0.4 mm +/- 0.2 mm. We also validated our respiratory motion correction strategy by computing the 2D target registration error (TRE) at the pulmonary veins and achieved a TRE of 1.6 mm +/- 0.9 mm.

Advanced image fusion to overlay coronary sinus anatomy with real-time fluoroscopy to facilitate left ventricular lead implantation in CRT.

Background: Failure rate for left ventricular (LV) lead implantation in cardiac resynchronization therapy (CRT) is up to 12%. The use of segmentation tools, advanced image registration software, and high‐fidelity images from computerized tomography (CT) and cardiac magnetic resonance (CMR) of the coronary sinus (CS) can guide LV lead implantation. We evaluated the feasibility of advanced image registration onto live fluoroscopic images to allow successful LV lead placement.

Clinical Evaluation of Respiratory Motion Compensation for Anatomical Roadmap Guided Cardiac Electrophysiology Procedures

X-ray fluoroscopically guided cardiac electrophysiological procedures are routinely carried out for diagnosis and treatment of cardiac arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of static 3-D roadmaps derived from preprocedural volumetric data can be used to add anatomical information. However, the registration between the 3-D roadmap and the 2-D X-ray image can be compromised by patient respiratory motion. Three methods were designed and evaluated to correct for respiratory motion using features in the 2-D X-ray images. The first method is based on tracking either the diaphragm or the heart border using the image intensity in a region of interest. The second method detects the tracheal bifurcation using the generalized Hough transform and a 3-D model derived from 3-D preoperative volumetric data. The third method is based on tracking the coronary sinus (CS) catheter. This method uses blob detection to find all possible catheter electrodes in the X-ray image. A cost function is applied to select one CS catheter from all catheter-like objects. All three methods were applied to X-ray images from 18 patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. The 2-D target registration errors (TRE) at the pulmonary veins were calculated to validate the methods. A TRE of 1.6 mm ± 0.8 mm was achieved for the diaphragm tracking; 1.7 mm ± 0.9 mm for heart border tracking, 1.9 mm ± 1.0 mm for trachea tracking, and 1.8 mm ± 0.9 mm for CS catheter tracking. We present a comprehensive comparison between the techniques in terms of robustness, as computed by tracking errors, and accuracy, as computed by TRE using two independent approaches.

Registering Preprocedure Volumetric Images With Intraprocedure 3-D Ultrasound Using an Ultrasound Imaging Model

For many image-guided interventions there exists a need to compute the registration between preprocedure image(s) and the physical space of the intervention. Real-time intraprocedure imaging such as ultrasound (US) can be used to image the region of interest directly and provide valuable anatomical information for computing this registration. Unfortunately, real-time US images often have poor signal-to-noise ratio and suffer from imaging artefacts. Therefore, registration using US images can be challenging and significant preprocessing is often required to make the registrations robust. In this paper we present a novel technique for computing the image-to-physical registration for minimally invasive cardiac interventions using 3-D US. Our technique uses knowledge of the physics of the US imaging process to reduce the amount of preprocessing required on the 3-D US images. To account for the fact that clinical US images normally undergo significant image processing before being exported from the US machine our optimization scheme allows the parameters of the US imaging model to vary. We validated our technique by computing rigid registrations for 12 cardiac US/magnetic resonance imaging (MRI) datasets acquired from six volunteers and two patients. The technique had mean registration errors of 2.1-4.4 mm, and 75% capture ranges of 5-30 mm. We also demonstrate how the same approach can be used for respiratory motion correction: on 15 datasets acquired from five volunteers the registration errors due to respiratory motion were reduced by 45%-92%.

Real‐time x‐ray fluoroscopy‐based catheter detection and tracking for cardiac electrophysiology interventions

PURPOSE X-ray fluoroscopically guided cardiac electrophysiology (EP) procedures are commonly carried out to treat patients with arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of a three-dimensional (3D) roadmap derived from preprocedural volumetric images can be used to add anatomical information. It is useful to know the position of the catheter electrodes relative to the cardiac anatomy, for example, to record ablation therapy locations during atrial fibrillation therapy. Also, the electrode positions of the coronary sinus (CS) catheter or lasso catheter can be used for road map motion correction. METHODS In this paper, the authors present a novel unified computational framework for image-based catheter detection and tracking without any user interaction. The proposed framework includes fast blob detection, shape-constrained searching and model-based detection. In addition, catheter tracking methods were designed based on the customized catheter models input from the detection method. Three real-time detection and tracking methods are derived from the computational framework to detect or track the three most common types of catheters in EP procedures: the ablation catheter, the CS catheter, and the lasso catheter. Since the proposed methods use the same blob detection method to extract key information from x-ray images, the ablation, CS, and lasso catheters can be detected and tracked simultaneously in real-time. RESULTS The catheter detection methods were tested on 105 different clinical fluoroscopy sequences taken from 31 clinical procedures. Two-dimensional (2D) detection errors of 0.50 ± 0.29, 0.92 ± 0.61, and 0.63 ± 0.45 mm as well as success rates of 99.4%, 97.2%, and 88.9% were achieved for the CS catheter, ablation catheter, and lasso catheter, respectively. With the tracking method, accuracies were increased to 0.45 ± 0.28, 0.64 ± 0.37, and 0.53 ± 0.38 mm and success rates increased to 100%, 99.2%, and 96.5% for the CS, ablation, and lasso catheters, respectively. Subjective clinical evaluation by three experienced electrophysiologists showed that the detection and tracking results were clinically acceptable. CONCLUSIONS The proposed detection and tracking methods are automatic and can detect and track CS, ablation, and lasso catheters simultaneously and in real-time. The accuracy of the proposed methods is sub-mm and the methods are robust toward low-dose x-ray fluoroscopic images, which are mainly used during EP procedures to maintain low radiation dose.

The acute hemodynamic response to LV pacing within individual branches of the coronary sinus using a quadripolar lead.

Background:  It is not clear whether there is a large difference in acute hemodynamic response (AHR) to left ventricle (LV) pacing in different regions of the same coronary sinus (CS) vein. Using the four electrodes available on a Quartet LV lead, we evaluated the AHR to pacing within individual branches of the CS.

Evaluation of a real-time hybrid three-dimensional echo and x-ray imaging system for guidance of cardiac catheterisation procedures

Minimally invasive cardiac surgery is made possible by image guidance technology. X-ray fluoroscopy provides high contrast images of catheters and devices, whereas 3D ultrasound is better for visualising cardiac anatomy. We present a system in which the two modalities are combined, with a trans-esophageal echo volume registered to and overlaid on an X-ray projection image in real-time. We evaluate the accuracy of the system in terms of both temporal synchronisation errors and overlay registration errors. The temporal synchronisation error was found to be 10% of the typical cardiac cycle length. In 11 clinical data sets, we found an average alignment error of 2.9 mm. We conclude that the accuracy result is very encouraging and sufficient for guiding many types of cardiac interventions. The combined information is clinically useful for placing the echo image in a familiar coordinate system and for more easily identifying catheters in the echo volume.