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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.

Mechanical ventilation may contribute to the impairment of the pulmonary surfactant system, which is one of the mechanisms leading to the progression of acute lung injury. To investigate the potential protective effects of pulmonary surfactant in a rat model of ventilator-induced lung injury, the surfactant powder was aerosolized using an in-house made device designed to deliver the aerosolized powder to the inspiratory line of a rodent ventilator circuit. Rats were randomized to (i) administration of aerosolized recombinant surfactant protein C based pulmonary surfactant, (ii) intratracheally instillation of the same surfactant re-constituted in saline, and (iii) no treatment. Animals were monitored during 2 h of high-tidal volume mechanical ventilation, after which rats were sacrificed, and further analysis of lung mechanics and surfactant function were completed. Blood gas measurements during ventilation showed extended maintenance of oxygen levels above 400 mmHg in aerosol treated animals over non-treated and instilled groups, while total protein analysis showed reduced levels in the aerosol compared to non-treated groups. Dynamic captive bubble surface tension measurements showed the activity of surfactant recovered from aerosol treated animals is maintained below 1 mN/m. The prophylactic treatment of aerosolized surfactant powder reduced the severity of lung injury in this model.

Long-bone fractures such as femur fractures are very common in trauma centers. Robotic assisted fracture surgery (RAFS) can facilitate the minimally invasive surgery which reduces scarring, infection risk and long hospital stays. One important step in RAFS is to establish the coordinate system link between patient joint (rigidly connected with the robotic system) and an external tracking system. As X-ray fluoroscopic images are routinely used during the procedure, an automatic method is proposed to detect and localize landmarks on the tracking tool using live X-ray image. The proposed method uses combination of block detection, geometric model matching and principle component analysis. A successful rate of 91.3% is achieved after testing on 650 X-ray images and accuracy is within 0.5 mm.

The motion and deformation of catheters that lie inside cardiac structures can provide valuable information about the motion of the heart. In this paper we describe the formation of a novel statistical model of the motion of a coronary sinus (CS) catheter based on principal component analysis of tracked electrode locations from standard mono-plane x-ray fluoroscopy images. We demonstrate the application of our model for the purposes of retrospective cardiac and respiratory gating of x-ray fluoroscopy images in normal dose x-ray fluoroscopy images, and demonstrate how a modification of the technique allows application to very low dose scenarios. We validated our method on ten mono-plane imaging sequences comprising a total of 610 frames from ten different patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. For normal dose images we established systole, end-inspiration and end-expiration gating with success rates of 100%, 92.1% and 86.9%, respectively. For very low dose applications, the method was tested on the same ten mono-plane x-ray fluoroscopy sequences without noise and with added noise at signal to noise ratio (SNR) values of √50, √10, √8, √6, √5, √2 and √1 to simulate the image quality of increasingly lower dose x-ray images. The method was able to detect the CS catheter even in the lowest SNR images with median errors not exceeding 2.6 mm per electrode. Furthermore, gating success rates of 100%, 71.4% and 85.7% were achieved at the low SNR value of √2, representing a dose reduction of more than 25 times. Thus, the technique has the potential to extract useful information whilst substantially reducing the radiation exposure.

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. Methods: An acute hemodynamic study was attempted in 20 patients. In each patient, we assessed AHR in a number of CS veins and along a significant proportion of each CS branch using three different bipolar configurations. We compared the AHR achieved when pacing using each different vector and also the highest AHR achieved in any position within the same patient with the lowest achieved in that patient. Results: Sixty-four different CS positions in 19 patients were successfully assessed. No significant difference in AHR was found overall between the three vectors tested. The mean percentage difference in AHR between the CS branch vectors with the lowest and highest dP/dt(max) was +6.5 +/- 5.4% (P

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 d P /d t max was recorded using a pressure wire during stimulation at LV1, LV2, and both sites simultaneously (LV1 + 2). Patients were deemed acute responders if ΔLV d P /d t max 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 d P /d t max 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.

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. (PACE 2011; 34:226–234)

We present a feasibility study on hybrid echocardiography (echo) and x-ray image guidance for cardiac catheterization procedures. A self-tracked, remotely operated robotic arm with haptic feedback was developed that attached to a standard x-ray table. This was used to safely manipulate a three-dimensional (3D) trans-thoracic echo probe during simultaneous x-ray fluoroscopy and echo acquisitions. By a combination of calibration and tracking of the echo and x-ray systems, it was possible to register the 3D echo images with the 2D x-ray images. Visualization of the combined data was achieved by either overlaying triangulated surfaces extracted from segmented echo data onto the x-ray images or by overlaying volume rendered 3D echo data. Furthermore, in order to overcome the limited field of view of the echo probe, it was possible to create extended field of view (EFOV) 3D echo images by co-registering multiple tracked echo data to generate larger roadmaps for procedure guidance. The registration method was validated using a cross-wire phantom and showed a 2D target registration error of 3.5 mm. The clinical feasibility of the method was demonstrated during two clinical cases for patients undergoing cardiac pacing studies. The EFOV technique was demonstrated using two healthy volunteers.

Echocardiography is a potential alternative to X-ray fluoroscopy in cardiac catheterization given its richness in soft tissue information and its lack of ionizing radiation. However, its small field of view and acoustic artifacts make direct automatic segmentation of the catheters very challenging. In this study, a fast catheter segmentation framework for echocardiographic imaging guided by the segmentation of corresponding X-ray fluoroscopic imaging is proposed. The complete framework consists of: 1) catheter initialization in the first X-ray frame; 2) catheter tracking in the rest of the X-ray sequence; 3) fast registration of corresponding X-ray and ultrasound frames; and 4) catheter segmentation in ultrasound images guided by the results of both X-ray tracking and fast registration. The main contributions include: 1) a Kalman filter-based growing strategy with more clinical data evalution; 2) a SURF detector applied in a constrained search space for catheter segmentation in ultrasound images; 3) a two layer hierarchical graph model to integrate and smooth catheter fragments into a complete catheter; and 4) the integration of these components into a system for clinical applications. This framework is evaluated on five sequences of porcine data and four sequences of patient data comprising more than 3000 X-ray frames and more than 1000 ultrasound frames. The results show that our algorithm is able to track the catheter in ultrasound images at 1.3 s per frame, with an error of less than 2 mm. However, although this may satisfy the accuracy for visualization purposes and is also fast, the algorithm still needs to be further accelerated for real-time clinical applications.

For most cardiac catheterization interventions, X-ray imaging is currently used as a standard imaging technique. However, lack of 3D soft tissue information and harmful radiation mean that X-ray imaging is not an ideal modality. In contrast, 3D echocardiography can overcome these disadvantages. In this paper, we propose a fast catheter tracking strategy for 3D ultrasound sequences. The main advantage of our strategy is low use of X-ray imaging, which significantly decreases the radiation exposure. In addition, 3D soft tissue imaging can be introduced by using ultrasound. To enable the tracking procedure, initialization is carried out on the first ultrasound frame. Given the location of the catheter in the previous frame, which is in the form of a set of ordered landmarks, 3D Speeded-Up Robust Feature SURF responses are calculated for candidate voxels in the surrounding region of each landmark on the next frame. One candidate is selected among all voxels for each landmark based on Fast Primal-Dual optimization Fast-PD. As a result, a new set of ordered landmarks is extracted, corresponding to the potential location of the catheter on the next frame. In order to adapt the tracking to the changing length of the catheter in the view, landmarks which may not be located on the catheter are ruled out. Then a catheter growing strategy is performed to extend the tracked part of the catheter to the untracked part. Based on 10 ultrasound phantom sequences and two clinical sequences, comprising more than 1300 frames, our experimental results show that the tracking system can track catheters with an error of less than 2.5mm and a speed of more than 3 fps.

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.

Although X-ray imaging has played a dominant role in cardiac catheter-based interventions, sometimes 3D soft tissue information, which X-ray images cannot provide, may be required. In contrast, 3D echocardiographic imaging is able to visualise soft tissue. In this paper, we propose a real-time catheter tracking strategy in echocardiographic sequences based on catheter tracking in 2D X-ray images and registration between these two modalities. The catheter tracking in X-ray images can be divided into catheter initialization and tracking. For initialization, an extraction algorithm based on SURF features, patch analysis and Kalman filtering is used to locate the catheter in the first X-ray image. Following this, a tracking algorithm based on patch analysis and Fast-PD optimization is used to track the catheter in the following images. The tracking result of each X-ray frame, as well as the transformation between X-ray and ultrasound images obtained from registration, is used to reduce the search space in the echo volume to only a curved surface. Using a graphical model and shortest path optimization, the position of the catheters in each echo frame can be estimated. Based on 10 pairs of X-ray and US sequences, comprising more than 800 frames, our experimental results show that the tracking system can track catheters with an average error of less than 1mm in X-ray images and less than 2mm in US. Also, our strategy for tracking in X-ray outperforms previous methods using only Fast-PD. The speed in total can reach 1.5 fps.

Cardiac electrophysiology procedures are routinely used to treat patients with rhythm disorders. The success rates of ablation procedures and cardiac resynchronization therapy are still sub-optimal. Recent advances in medical imaging, image processing and cardiac biophysical modeling have the potential to improve patient outcome. This manuscript provides an overview of how these advances have been translated into the clinical environment.

Cardiac resynchronization therapy (CRT) is an effective procedure for patients with heart failure but 30% of patients do not respond. This may be due to sub-optimal placement of the left ventricular (LV) lead. It is hypothesized that the use of cardiac anatomy, myocardial scar distribution and dyssynchrony information, derived from cardiac magnetic resonance imaging (MRI), may improve outcome by guiding the physician for optimal LV lead positioning. Whole heart MR data can be processed to yield detailed anatomical models including the coronary veins. Cine MR data can be used to measure the motion of the LV to determine which regions are late-activating. Finally, delayed Gadolinium enhancement imaging can be used to detect regions of scarring. This paper presents a complete platform for the guidance of CRT using pre-procedural MR data combined with live x-ray fluoroscopy. The platform was used for 21 patients undergoing CRT in a standard catheterization laboratory. The patients underwent cardiac MRI prior to their procedure. For each patient, a MRI-derived cardiac model, showing the LV lead targets, was registered to x-ray fluoroscopy using multiple views of a catheter looped in the right atrium. Registration was maintained throughout the procedure by a combination of C-arm/x-ray table tracking and respiratory motion compensation. Validation of the registration between the three-dimensional (3D) roadmap and the 2D x-ray images was performed using balloon occlusion coronary venograms. A 2D registration error of 1.2 ± 0.7 mm was achieved. In addition, a novel navigation technique was developed, called Cardiac Unfold, where an entire cardiac chamber is unfolded from 3D to 2D along with all relevant anatomical and functional information and coupled to real-time device detection. This allowed more intuitive navigation as the entire 3D scene was displayed simultaneously on a 2D plot. The accuracy of the unfold navigation was assessed off-line using 13 patient data sets by computing the registration error of the LV pacing lead electrodes which was found to be 2.2 ± 0.9 mm. Furthermore, the use of Unfold Navigation was demonstrated in real-time for four clinical cases.

X-ray fluoroscopically-guided cardiac catheterization procedures are commonly carried out for the treatment of cardiac arrhythmias, such as atrial fibrillation (AF) and cardiac resynchronization therapy (CRT). X-ray images have poor soft tissue contrast and, for this reason, overlay of a 3D roadmap derived from pre-procedure volumetric image data can be used to add anatomical information. However, current overlay technologies have the limitation that 3D information is displayed on a 2D screen. Therefore, it is not possible for the cardiologist to appreciate the true positional relationship between anatomical/functional data and the position of the interventional devices. We prose a navigation methodology, called cardiac unfold, where an entire cardiac chamber is unfolded from 3D to 2D along with all relevant anatomical and functional information and coupled to real-time device tracking. This would allow more intuitive navigation since the entire 3D scene is displayed simultaneously on a 2D plot. A real-time unfold guidance platform for CRT was developed, where navigation is performed using the standard AHA 16-segment bull's-eye plot for the left ventricle (LV). The accuracy of the unfold navigation was assessed in 13 patient data sets by computing the registration errors of the LV pacing lead electrodes and was found to be 2.2 ± 0.9 mm. An unfold method was also developed for the left atrium (LA) using trimmed B-spline surfaces. The method was applied to 5 patient data sets and its utility was demonstrated for displaying information from delayed enhancement MRI of patients that had undergone radio-frequency ablation.

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.

Optimal left ventricular (LV) lead placement via the coronary sinus (CS) is a critical factor in defining response to cardiac resynchronization therapy (CRT). Using novel MR image acquisition, segmentation, overlay and registration software we set out to guide lead placement by avoiding scar and targeting the LV region with the latest mechanical activation. We previously reported clinical results for 7 patients and now present updated results. 17 patients underwent cardiac magnetic resonance (CMR) scans. 3D whole heart images were segmented to produce high-fidelity anatomical models of the cardiac chambers and coronary veins. Four-chamber and short-axis cine images were processed using Tomtec software to give a 16-segment time volume-dyssynchrony map. In patients with myocardial scar, the Gadolinium late enhancement images were manually segmented and registered to the anatomical model along with the dyssynchrony map. The 3 latest mechanically acti- vated segments with

Cardiac MRI (CMR) is recognized as an important imaging modality for assessing patients with heart failure. With improved segmentation and image registration tools, data acquired using CMR can help with planning and intraprocedural guidance as well as with defining etiology of heart failure and ventricular function. Here, we describe a successful CRT implantation where segmented CMR images were registered with the fluoroscopic images during the procedure to guide device implantation. A 23-year-old man with a history of repair of hemianomalous pulmonary venous drainage and biventricular noncompaction (Figure 1A and B) presented with a 3-month history of reduced exercise tolerance and peripheral edema. Despite optimal medical therapy, he remained in New York Heart Association class 3. His ECG showed sinus rhythm with a PR interval of 154 milliseconds (ms), QRS duration of 134 ms, and left bundle branch block (LBBB) morphology. Transthoracic echocardiography showed a dilated left ventricle with severe global impairment, an ejection fraction of 23%, and an end-systolic volume of 141 mL. The patient had significant intraventricular dyssynchrony, with 3D echo assessment giving a systolic dyssynchrony index (SDI) of 16.7%. A CMR examination was performed to assess cardiac function and …

We present an initial evaluation of a robotic arm for positioning a 3D echo probe during cardiac catheterization procedures. By tracking the robotic arm, X-ray table and X-ray C-arm, we are able to register the 3D echo images with live 2D X-ray images. In addition, we can also use tracking data from the robotic arm combined with system calibrations to create extended field of view 3D echo images. Both these features can be used for roadmapping to guide cardiac catheterization procedures. We have carried out a validation experiment of our registration method using a cross-wire phantom. Results show our method to be accurate to 3.5 mm. We have successfully demonstrated the creation of the extended field of view data on 2 healthy volunteers and the registration of echo and X-ray data on 1 patient undergoing a pacing study.

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 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.

This paper presents the evaluation of the use of multimodality skin markers for the registration of cardiac magnetic resonance (MR) image data to x-ray fluoroscopy data for the guidance of cardiac electrophysiology procedures. The approach was validated using a phantom study and 3 patients undergoing pulmonary vein (PV) isolation for the treatment of paroxysmal atrial fibrillation. In the patient study, skin markers were affixed to the patients' chest and used to register pre-procedure cardiac MR image data to intra-procedure fluoroscopy data. Registration errors were assessed using contrast angiograms of the left atrium that were available in 2 out of 3 cases. A clinical expert generated "gold standard" registrations by adjusting the registration manually. Target registration errors (TREs) were computed using points on the PV ostia. Ablation locations were computed using biplane x-ray imaging. Registration errors were further assessed by computing the distances of the ablation points to the registered left atrial surface for all 3 patients. The TREs were 6.0 & 3.1mm for patients 1 & 2. The mean ablation point errors were 6.2, 3.8, & 3.0mm for patients 1, 2, & 3. These results are encouraging in the context of a 5mm clinical accuracy requirement for this type of procedure. We conclude that multimodality skin markers have the potential to provide anatomical image integration for x-ray guided cardiac electrophysiology procedures, especially if coupled with an accurate respiratory motion compensation strategy.

Purpose: Image-guided cardiac interventions involve the use of fluoroscopic images to guide the insertion and movement of interventional devices. Cardiorespiratory gating can be useful for 3D reconstruction from multiple x-ray views and for reducing misalignments between 3D anatomical models overlaid onto fluoroscopy. Methods: The authors propose a novel and potentially clinically useful retrospective cardiorespiratory gating technique. The principal component analysis (PCA) statistical method is used in combination with other image processing operations to make our proposed masked-PCA technique suitable for cardiorespiratory gating. Unlike many previously proposed techniques, our technique is robust to varying image-content, thus it does not require specific catheters or any other optically opaque structures to be visible. Therefore, it works without any knowledge of catheter geometry. The authors demonstrate the application of our technique for the purposes of retrospective cardiorespiratory gating of normal and very low dose x-ray fluoroscopy images. Results: For normal dose x-ray images, the algorithm was validated using 28 clinical electrophysiology x-ray fluoroscopy sequences (2168 frames), from patients who underwent radiofrequency ablation (RFA) procedures for the treatment of atrial fibrillation and cardiac resynchronization therapy procedures for heart failure. The authors established end-systole, end-expiration, and end-inspiration success rates of 97.0%, 97.9%, and 97.0%, respectively. For very low dose applications, the technique was tested on ten x-ray sequences from the RFA procedures with added noise at signal to noise ratio (SNR) values of√50 √10 √8 √6 √5 √2 and √1 to simulate the image quality of increasingly lower dose x-ray images. Even at the low SNR value of √2, representing a dose reduction of more than 25 times, gating success rates of 89.1%, 88.8%, and 86.8% were established. Conclusions: The proposed technique can therefore extract useful information from interventional x-ray images while minimizing exposure to ionizing radiation.

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.

X-ray fluoroscopic images are widely used for image guidance in cardiac electrophysiology (EP) procedures to diagnose or treat cardiac arrhythmias based on catheter ablation. However, the main disadvantage of fluoroscopic imaging is the lack of soft tissue information and harmful radiation. In contrast, ultrasound (US) has the advantages of low-cost, non-radiation, and high contrast in soft tissue. In this paper we propose a framework to extract the catheter from both X-ray and US images in real time for cardiac interventions. The catheter extraction from X-ray images is based on SURF features, local patch analysis and Kalman filtering to acquire a set of sorted key points representing the catheter. At the same time, the transformation between the X-ray and US images can be obtained via 2D/3D rigid registration between a 3D model of the US probe and its projection on X-ray images. By backprojecting the information about the catheter location in the X-ray images to the US images the search space can be drastically reduced. The extraction of the catheter from US is based on 3D SURF feature clusters, graph model building, A* algorithm and B-spline smoothing. Experiments show the overall process can be achieved in 2.72 seconds for one frame and the reprojected error is 1.99 mm on average.

Cardiac resynchronization therapy (CRT) can be an effective procedure for patients with heart failure but 30% of patients do not respond. This may be partially caused by the sub-optimal placement of the left ventricular (LV) lead. Detailed cardiac anatomy and dyssynchrony information could improve optimal LV lead placement. As a pre-interventional imaging modality, cardiac magnetic resonance (MR) imaging has the potential to provide all the relevant information. Whole heart MR image data can be processed to yield detailed anatomical models including the coronary veins. Cine MR data can be used to measure the motion of the LV to determine which regions are late-activating. Finally, late Gadolinium enhancement imaging can be used to detect regions of scarring. This paper presents a complete software solution for the guidance of CRT using pre-procedural MR data combined with live X-ray fluoroscopy. The platform was evaluated using 7 live CRT cases. For each patient, a detailed cardiac model was generated and registered to the X-ray fluoroscopy using multiple views of a catheter looped in the right atrium. There was complete freedom of movement of the X-ray system and respiratory motion compensation was achieved by tracking the diaphragm. The registration was validated using balloon occlusion coronary venograms. The mean 2D target registration error for 7 patients was 1.3 ± 0.68 mm. All patients had a successful left lead implant.