Cardiac magnetic resonance and electroanatomical mapping of acute and chronic atrial ablation injury: a histological validation study.

AIMS: To provide a comprehensive histopathological validation of cardiac magnetic resonance (CMR) and endocardial voltage mapping of acute and chronic atrial ablation injury. METHODS AND RESULTS: 16 pigs underwent pre-ablation T2-weighted (T2W) and late gadolinium enhancement (LGE) CMR and high-density voltage mapping of the right atrium (RA) and both were repeated after intercaval linear radiofrequency ablation. Eight pigs were sacrificed following the procedure for pathological examination. A further eight pigs were recovered for 8 weeks, before chronic CMR, repeat RA voltage mapping and pathological examination. Signal intensity (SI) thresholds from 0 to 15 SD above a reference SI were used to segment the RA in CMR images and segmentations compared with real lesion volumes. The SI thresholds that best approximated histological volumes were 2.3 SD for LGE post-ablation, 14.5 SD for T2W post-ablation and 3.3 SD for LGE chronically. T2-weighted chronically always underestimated lesion volume. Acute histology showed transmural injury with coagulative necrosis. Chronic histology showed transmural fibrous scar. The mean voltage at the centre of the ablation line was 3.3 mV pre-ablation, 0.6 mV immediately post-ablation, and 0.3 mV chronically. CONCLUSION: This study presents the first histopathological validation of CMR and endocardial voltage mapping to define acute and chronic atrial ablation injury, including SI thresholds that best match histological lesion volumes. An understanding of these thresholds may allow a more informed assessment of the underlying atrial substrate immediately after ablation and before repeat catheter ablation for atrial arrhythmias.

Patient-specific modeling of atrial fibrosis increases the accuracy of sinus rhythm simulations and may explain maintenance of atrial fibrillation.

Left atrial fibrosis is thought to contribute to the manifestation of atrial fibrillation (AF). Late Gadolinium enhancement (LGE) MRI has the potential to image regions of low perfusion, which can be related to fibrosis. We show that a simulation with a patient-specific model including left atrial regional fibrosis derived from LGE-MRI reproduces local activation in the left atrium more precisely than the regular simulation without fibrosis. AF simulations showed a spontaneous termination of the arrhythmia in the absence of fibrosis and a stable rotor center in the presence of fibrosis. The methodology may provide a tool for a deeper understanding of the mechanisms maintaining AF and eventually also for the planning of substrate-guided ablation procedures in the future.

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.

A Tensor-Based Catheter and Wire Detection and Tracking Framework and Its Clinical Applications.

OBJECTIVE: Catheters and wires are used extensively in cardiac catheterization procedures. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications such as motion compensation and co-registration between 2D and 3D imaging modalities. Detecting the complete length of a catheter or wire object as well as electrode positions on the catheter or wire is a challenging task. METHOD: In this paper, an automatic detection framework for catheters and wires is developed. It is based on path reconstruction from image tensors, which are eigen direction vectors generated from a multiscale vessel enhancement filter. A catheter or a wire object is detected as the smooth path along those eigen direction vectors. Furthermore, a real-time tracking method based on a template generated from the detection method was developed. RESULTS: The proposed framework was tested on a total of 7,754 X-ray images. Detection errors for catheters and guidewires are 0.56 ± 0.28 mm and 0.68 ± 0.33 mm, respectively. The proposed framework was also tested and validated in two clinical applications. For motion compensation using catheter tracking, the 2D target registration errors (TRE) of 1.8 mm ± 0.9 mm was achieved. For co-registration between 2D X-ray images and 3D models from MRI images, a TRE of 2.3 ± 0.9 mm was achieved. CONCLUSION: A novel and fully automatic detection framework and its clinical applications are developed. SIGNIFICANCE: The proposed framework can be applied to improve the accuracy of image-guidance systems for cardiac catheterization procedures.

Edge-enhancement densenet for X-ray fluoroscopy image denoising in cardiac electrophysiology procedures.

PURPOSE: Reducing X-ray dose increases safety in cardiac electrophysiology procedures but also increases image noise and artifacts which may affect the discernibility of devices and anatomical cues. Previous denoising methods based on convolutional neural networks (CNNs) have shown improvements in the quality of low-dose X-ray fluoroscopy images but may compromise clinically important details required by cardiologists. METHODS: In order to obtain denoised X-ray fluoroscopy images whilst preserving details, we propose a novel deep-learning-based denoising framework, namely edge-enhancement densenet (EEDN), in which an attention-awareness edge-enhancement module is designed to increase edge sharpness. In this framework, a CNN-based denoiser is first used to generate an initial denoising result. Contours representing edge information are then extracted using an attention block and a group of interacted ultra-dense blocks for edge feature representation. Finally, the initial denoising result and enhanced edges are combined to generate the final X-ray image. The proposed denoising framework was tested on a total of 3262 clinical images taken from 100 low-dose X-ray sequences acquired from 20 patients. The performance was assessed by pairwise voting from five cardiologists as well as quantitative indicators. Furthermore, we evaluated our technique's effect on catheter detection using 416 images containing coronary sinus catheters in order to examine its influence as a pre-processing tool. RESULTS: The average signal-to-noise ratio of X-ray images denoised with EEDN was 24.5, which was 2.2 times higher than that of the original images. The accuracy of catheter detection from EEDN denoised sequences showed no significant difference compared with their original counterparts. Moreover, EEDN received the highest average votes in our clinician assessment when compared to our existing technique and the original images. CONCLUSION: The proposed deep learning-based framework shows promising capability for denoising interventional X-ray fluoroscopy images. The results from the catheter detection show that the network does not affect the results of such an algorithm when used as a pre-processing step. The extensive qualitative and quantitative evaluations suggest that the network may be of benefit to reduce radiation dose when applied in real time in the catheter laboratory.

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. METHODS: Twelve patients (11 male, 59 ± 16.8 years) undergoing CRT had three-dimensional (3D) whole-heart imaging (six CT, six CMR). Eight patients had at least one previously failed LV lead implant. Using segmentation software, anatomical models of the cardiac chambers, CS, and its branches were overlaid onto the live fluoroscopy using a prototype version of the Philips EP Navigator software to guide lead implantation. RESULTS: We achieved high-fidelity segmentations of cardiac chambers, coronary vein anatomy, and accurate registration between the 3D anatomical models and the live fluoroscopy in all 12 patients confirmed by balloon occlusion angiography. The CS was cannulated successfully in every patient and in 11, an LV lead was implanted successfully. (One patient had no acceptable lead values due to extensive myocardial scar). CONCLUSION: Using overlaid 3D segmentations of the CS and cardiac chambers, it is feasible to guide CRT implantation in real time by fusing advanced imaging and fluoroscopy. This enabled successful CRT in a group of patients with previously failed implants. This technology has the potential to facilitate CRT and improve implant success.

Real-time registration of 3D echo to x-ray fluoroscopy based on cascading classifiers and image registration.

Three-dimensional (3D) transesophageal echocardiography (TEE) is one of the most significant advances in cardiac imaging. Although TEE provides real-time 3D visualization of heart tissues and blood vessels and has no ionizing radiation, x-ray fluoroscopy still dominates in guidance of cardiac interventions due to TEE having a limited field of view and poor visualization of surgical instruments. Therefore, fusing 3D echo with live x-ray images can provide a better guidance solution. This paper proposes a novel framework for image fusion by detecting the pose of the TEE probe in x-ray images in real-time. The framework does not require any manual initialization. Instead it uses a cascade classifier to compute the position and in-plane rotation angle of the TEE probe. The remaining degrees of freedom are determined by fast marching against a template library. The proposed framework is validated on phantoms and patient data. The target registration error for the phantom was 2.1 mm. In addition, 10 patient datasets, seven of which were acquired from cardiac electrophysiology procedures and three from trans-catheter aortic valve implantation procedures, were used to test the clinical feasibility as well as accuracy. A mean registration error of 2.6 mm was achieved, which is well within typical clinical requirements.

Echocardiography to magnetic resonance image registration for use in image-guided cardiac catheterization procedures.

We present a robust method to register three-dimensional echocardiography (echo) images to magnetic resonance images (MRI) based on anatomical features, which is designed to be used in the registration pipeline for overlaying MRI-derived roadmaps onto two-dimensional live x-ray images during cardiac catheterization procedures. The features used in image registration are the endocardial surface of the left ventricle and the centre line of the descending aorta. The MR-derived left ventricle surface is generated using a fully automated algorithm, and the echo-derived left ventricle surface is produced using a semi-automatic segmentation method provided by the QLab software (Philips Healthcare) that it is routinely used in clinical practice. We test our method on data from six volunteers and four patients. We validated registration accuracy using two methods: the first calculated a root mean square distance error using expert identified anatomical landmarks, and the second method used catheters as landmarks in two clinical electrophysiology procedures. Results show a mean error of 4.1 mm, which is acceptable for our clinical application, and no failed registrations were observed. In addition, our algorithm works on clinical data, is fast and only requires a small amount of manual input, and so it is applicable for use during cardiac catheterization procedures.

A novel real-time computational framework for detecting catheters and rigid guidewires in cardiac catheterization procedures.

PURPOSE: Catheters and guidewires are used extensively in cardiac catheterization procedures such as heart arrhythmia treatment (ablation), angioplasty, and congenital heart disease treatment. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications, for example, motion compensation, coregistration between 2D and 3D imaging modalities, and 3D object reconstruction. METHODS: For the generalized framework, a multiscale vessel enhancement filter is first used to enhance the visibility of wire-like structures in the X-ray images. After applying adaptive binarization method, the centerlines of wire-like objects were extracted. Finally, the catheters and guidewires were detected as a smooth path which is reconstructed from centerlines of target wire-like objects. In order to classify electrode catheters which are mainly used in electrophysiology procedures, additional steps were proposed. First, a blob detection method, which is embedded in vessel enhancement filter with no additional computational cost, localizes electrode positions on catheters. Then the type of electrode catheters can be recognized by detecting the number of electrodes and also the shape created by a series of electrodes. Furthermore, for detecting guiding catheters or guidewires, a localized machine learning algorithm is added into the framework to distinguish between target wire objects and other wire-like artifacts. The proposed framework were tested on total 10,624 images which are from 102 image sequences acquired from 63 clinical cases. RESULTS: Detection errors for the coronary sinus (CS) catheter, lasso catheter ring and lasso catheter body are 0.56 ± 0.28 mm, 0.64 ± 0.36 mm, and 0.66 ± 0.32 mm, respectively, as well as success rates of 91.4%, 86.3%, and 84.8% were achieved. Detection errors for guidewires and guiding catheters are 0.62 ± 0.48 mm and success rates are 83.5%. CONCLUSION: The proposed computational framework do not require any user interaction or prior models and it can detect multiple catheters or guidewires simultaneously and in real-time. The accuracy of the proposed framework is sub-mm and the methods are robust toward low-dose X-ray fluoroscopic images, which are mainly used during procedures to maintain low radiation dose.

LV function validation of computer-assisted interventional system for cardiac resyncronisation therapy.

PURPOSE: Cardiac resynchronisation therapy (CRT) is an established treatment for symptomatic patients with heart failure, a prolonged QRS duration, and impaired left ventricular (LV) function; however, non-response rates remain high. Recently proposed computer-assisted interventional platforms for CRT provide new routes to improving outcomes. Interventional systems must process information in an accurate, fast and highly automated way that is easy for the interventional cardiologists to use. In this paper, an interventional CRT platform is validated against two offline diagnostic tools to demonstrate that accurate information processing is possible in the time critical interventional setting. METHODS: The study consisted of 3 healthy volunteers and 16 patients with heart failure and conventional criteria for CRT. Data analysis included the calculation of end-diastolic volume, end-systolic volume, stroke volume and ejection fraction; computation of global volume over the cardiac cycle as well as time to maximal contraction expressed as a percentage of the total cardiac cycle. RESULTS: The results showed excellent correlation ([Formula: see text] values of [Formula: see text] and Pearson correlation coefficient of [Formula: see text]) with comparable offline diagnostic tools. CONCLUSION: Results confirm that our interventional system has good accuracy in everyday clinical practice and can be of clinical utility in identification of CRT responders and LV function assessment.

3D/2D Registration with superabundant vessel reconstruction for cardiac resynchronization therapy.

A key component of image guided interventions is the registration of preoperative and intraoperative images. Classical registration approaches rely on cross-modality information; however, in modalities such as MRI and X-ray there may not be sufficient cross-modality information. This paper proposes a fundamentally different registration approach which uses adjacent anatomical structures with superabundant vessel reconstruction and dynamic outlier rejection. In the targeted clinical scenario of cardiac resynchronization therapy (CRT) delivery, preoperative, non contrast-enhanced, MRI is registered to intraoperative, contrasted X-ray fluoroscopy. The adjacent anatomical structures are the left ventricle (LV) from MRI and the coronary veins reconstructed from two contrast-enhanced X-ray images. The novel concept of superabundant vessel reconstruction is introduced to bypass the standard reconstruction problem of establishing one-to-one correspondences. Furthermore, a new dynamic outlier rejection method is proposed, to enable globally optimal point set registration. The proposed approach has been qualitatively and quantitatively evaluated on phantom, clinical CT angiography with ground truth and clinical CRT data. A novel evaluation method is proposed for clinical CRT data based on previously implanted artificial aortic and mitral valves. The registration accuracy in 3D was 2.94 mm for the aortic and 3.86 mm for the mitral valve. The results are below the required accuracy identified by clinical partners to be the half-segment size (16.35 mm) of a standard American Heart Association (AHA) 16 segment model of the LV.

Standardized unfold mapping: a technique to permit left atrial regional data display and analysis.

PURPOSE: Left atrial arrhythmia substrate assessment can involve multiple imaging and electrical modalities, but visual analysis of data on 3D surfaces is time-consuming and suffers from limited reproducibility. Unfold maps (e.g., the left ventricular bull's eye plot) allow 2D visualization, facilitate multimodal data representation, and provide a common reference space for inter-subject comparison. The aim of this work is to develop a method for automatic representation of multimodal information on a left atrial standardized unfold map (LA-SUM). METHODS: The LA-SUM technique was developed and validated using 18 electroanatomic mapping (EAM) LA geometries before being applied to ten cardiac magnetic resonance/EAM paired geometries. The LA-SUM was defined as an unfold template of an average LA mesh, and registration of clinical data to this mesh facilitated creation of new LA-SUMs by surface parameterization. RESULTS: The LA-SUM represents 24 LA regions on a flattened surface. Intra-observer variability of LA-SUMs for both EAM and CMR datasets was minimal; root-mean square difference of 0.008 ± 0.010 and 0.007 ± 0.005 ms (local activation time maps), 0.068 ± 0.063 gs (force-time integral maps), and 0.031 ± 0.026 (CMR LGE signal intensity maps). Following validation, LA-SUMs were used for automatic quantification of post-ablation scar formation using CMR imaging, demonstrating a weak but significant relationship between ablation force-time integral and scar coverage (R 2 = 0.18, P < 0.0001). CONCLUSIONS: The proposed LA-SUM displays an integrated unfold map for multimodal information. The method is applicable to any LA surface, including those derived from imaging and EAM systems. The LA-SUM would facilitate standardization of future research studies involving segmental analysis of the LA.

ECG imaging of ventricular tachycardia: evaluation against simultaneous non-contact mapping and CMR-derived grey zone.

ECG imaging is an emerging technology for the reconstruction of cardiac electric activity from non-invasively measured body surface potential maps. In this case report, we present the first evaluation of transmurally imaged activation times against endocardially reconstructed isochrones for a case of sustained monomorphic ventricular tachycardia (VT). Computer models of the thorax and whole heart were produced from MR images. A recently published approach was applied to facilitate electrode localization in the catheter laboratory, which allows for the acquisition of body surface potential maps while performing non-contact mapping for the reconstruction of local activation times. ECG imaging was then realized using Tikhonov regularization with spatio-temporal smoothing as proposed by Huiskamp and Greensite and further with the spline-based approach by Erem et al. Activation times were computed from transmurally reconstructed transmembrane voltages. The results showed good qualitative agreement between the non-invasively and invasively reconstructed activation times. Also, low amplitudes in the imaged transmembrane voltages were found to correlate with volumes of scar and grey zone in delayed gadolinium enhancement cardiac MR. The study underlines the ability of ECG imaging to produce activation times of ventricular electric activity-and to represent effects of scar tissue in the imaged transmembrane voltages.

Dynamic mapping of ventricular function from cardiovascular magnetic resonance imaging.

Heart failure is associated with substantial mortality and morbidity and remains the most common diagnosis in older patients. Based on experimental electrophysiologic studies, cardiac resynchronization therapy (CRT) for heart failure results in a maximum resynchronization effect when applied to the most delayed left ventricular (LV) site. Current clinical practice is to identify the optimal site using separate visualisation of scar and activation information. These must be mentally mapped into 3D, which is challenging and time-consuming for the electrophysiologist. The aim of this work is to improve patient planning for CRT by mapping propagation of mechanical activation from cardiac magnetic resonance (CMR) onto a three-dimensional plus time (3D+t) model map to assist the cardiologist in determining the optimal LV pacing site. Automatic motion analysis of the 16-segment patient-specific LV anatomical model, automatically segmented from cine MR data, was done and regional volume change curves as a function of the cardiac cycle along with intraventricular dyssynchrony indices were extracted. The regional volume information computed was then mapped onto all phases of the 3D+t CMR data, which provides a 3D+t mechanical activation map over the whole cardiac cycle. This workflow was tested on 7 patients and 3 healthy volunteers. This mapping of the regional change of volume across the LV during ventricular pacing could facilitate the selection of the optimum pacing segment at the planning stage of the procedure, and consequently decrease the number of inadequate responders to CRT.

Novel approaches to the measurement of arterial blood flow from dynamic digital X-ray images.

We have developed two new algorithms for the measurement of blood flow from dynamic X-ray angiographic images. Both algorithms aim to improve on existing techniques. First, a model-based (MB) algorithm is used to constrain the concentration-distance curve matching approach. Second, a weighted optical flow algorithm (OP) is used to improve on point-based optical flow methods by averaging velocity estimates along a vessel with weighting based on the magnitude of the spatial derivative. The OP algorithm was validated using a computer simulation of pulsatile blood flow. Both the OP and the MB algorithms were validated using a physiological blood flow circuit. Dynamic biplane digital X-ray images were acquired following injection of iodine contrast medium into a variety of simulated arterial vessels. The image data were analyzed using our integrated angiographic analysis software SARA to give blood flow waveforms using the MB and OP algorithms. These waveforms were compared to flow measured using an electromagnetic flow meter (EMF). In total 4935 instantaneous measurements of flow were made and compared to the EMF recordings. It was found that the new algorithms showed low measurement bias and narrow limits of agreement and also out-performed the concentration-distance curve matching algorithm (ORG) and a modification of this algorithm (PA) in all studies.

A system for real-time XMR guided cardiovascular intervention.

The hybrid magnetic resonance (MR)/X-ray suite (XMR) is a recently introduced imaging solution that provides new possibilities for guidance of cardiovascular catheterization procedures. We have previously described and validated a technique based on optical tracking to register MR and X-ray images obtained from the sliding table XMR configuration. The aim of our recent work was to extend our technique by providing an improved calibration stage, real-time guidance during cardiovascular catheterization procedures, and further off-line analysis for mapping cardiac electrical data to patient anatomy. Specially designed optical trackers and a dedicated calibration object have resulted in a single calibration step that can be efficiently checked and updated before each procedure. An X-ray distortion model has been implemented that allows for distortion correction for arbitrary c-arm orientations. During procedures, the guidance system provides a real-time combined MR/X-ray image display consisting of live X-ray images with registered recently acquired MR derived anatomy. It is also possible to reconstruct the location of catheters seen during X-ray imaging in the MR derived patient anatomy. We have applied our registration technique to 13 cardiovascular catheterization procedures. Our system has been used for the real-time guidance of ten radiofrequency ablations and one aortic stent implantation. We demonstrate the real-time guidance using two exemplar cases. In a further two cases we show how off-line analysis of registered image data, acquired during electrophysiology study procedures, has been used to map cardiac electrical measurements to patient anatomy for two different types of mapping catheters. The cardiologists that have used the guidance system suggest that real-time XMR guidance could have substantial value in difficult interventional and electrophysiological procedures, potentially reducing procedure time and delivered radiation dose. Also, the ability to map measured electrical data to patient specific anatomy provides improved visualization and a path to investigation of cardiac electromechanical models.

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.

Repeat left atrial catheter ablation: cardiac magnetic resonance prediction of endocardial voltage and gaps in ablation lesion sets.

BACKGROUND: Studies have reported an inverse relationship between late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) signal intensity and left atrial (LA) endocardial voltage after LA ablation. However, there is controversy regarding the reproducibility of atrial LGE CMR and its ability to identify gaps in ablation lesions. Using systematic and objective techniques, this study examines the correlation between atrial CMR and endocardial voltage. METHODS AND RESULTS: Twenty patients who had previous ablation for atrial fibrillation and represented with paroxysmal atrial fibrillation or atrial tachycardia underwent preablation LGE CMR. During the ablation procedure, high-density point-by-point Carto voltage maps were acquired. Three-dimensional CMR reconstructions were registered with the Carto anatomies to allow comparison of voltage and LGE signal intensity. Signal intensities around the left and right pulmonary vein antra and along the LA roof and mitral lines on the CMR-segmented LA shells were extracted to examine differences between electrically isolated and reconnected lesions. There were a total of 6767 data points across the 20 patients. Only 119 (1.8%) of the points were ≤ 0.05 mV. There was only a weak inverse correlation between either unipolar (r = -0.18) or bipolar (r = -0.17) voltage and LGE CMR signal intensities with low voltage occurring across a large range of signal intensities. Signal intensities were not statistically different for electrically isolated and reconnected lesions. CONCLUSIONS: This study demonstrates that there is only a weak point-by-point relationship between LGE CMR and endocardial voltage in patients undergoing repeat LA ablation. Using an objective method of assessing gaps in ablation lesions, LGE CMR is unable to reliably predict sites of electrical conduction.

Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets.

Knowledge of left atrial (LA) anatomy is important for atrial fibrillation ablation guidance, fibrosis quantification and biophysical modelling. Segmentation of the LA from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images is a complex problem. This manuscript presents a benchmark to evaluate algorithms that address LA segmentation. The datasets, ground truth and evaluation code have been made publicly available through the http://www.cardiacatlas.org website. This manuscript also reports the results of the Left Atrial Segmentation Challenge (LASC) carried out at the STACOM'13 workshop, in conjunction with MICCAI'13. Thirty CT and 30 MRI datasets were provided to participants for segmentation. Each participant segmented the LA including a short part of the LA appendage trunk and proximal sections of the pulmonary veins (PVs). We present results for nine algorithms for CT and eight algorithms for MRI. Results showed that methodologies combining statistical models with region growing approaches were the most appropriate to handle the proposed task. The ground truth and automatic segmentations were standardised to reduce the influence of inconsistently defined regions (e.g., mitral plane, PVs end points, LA appendage). This standardisation framework, which is a contribution of this work, can be used to label and further analyse anatomical regions of the LA. By performing the standardisation directly on the left atrial surface, we can process multiple input data, including meshes exported from different electroanatomical mapping systems.

Registration and tracking to integrate X-ray and MR images in an XMR facility.

We describe a registration and tracking technique to integrate cardiac X-ray images and cardiac magnetic resonance (MR) images acquired from a combined X-ray and MR interventional suite (XMR). Optical tracking is used to determine the transformation matrices relating MR image coordinates and X-ray image coordinates. Calibration of X-ray projection geometry and tracking of the X-ray C-arm and table enable three-dimensional (3-D) reconstruction of vessel centerlines and catheters from bi-plane X-ray views. We can, therefore, combine single X-ray projection images with registered projection MR images from a volume acquisition, and we can also display 3-D reconstructions of catheters within a 3-D or multi-slice MR volume. Registration errors were assessed using phantom experiments. Errors in the combined projection images (two-dimensional target registration error--TRE) were found to be 2.4 to 4.2 mm, and the errors in the integrated volume representation (3-D TRE) were found to be 4.6 to 5.1 mm. These errors are clinically acceptable for alignment of images of the great vessels and the chambers of the heart. Results are shown for two patients. The first involves overlay of a catheter used for invasive pressure measurements on an MR volume that provides anatomical context. The second involves overlay of invasive electrode catheters (including a basket catheter) on a tagged MR volume in order to relate electrophysiology to myocardial motion in a patient with an arrhythmia. Visual assessment of these results suggests the errors were of a similar magnitude to those obtained in the phantom measurements.