Feasibility of transthoracic echocardiographic guidance for multicatheter electrophysiological mapping studies in horses.

BACKGROUND: Improved characterization of arrhythmias is based on minimally invasive catheterizations. However, these catheterizations have been poorly explored in horses because apart from 3-dimensional (3D) mapping systems, continuous guidance of the catheter's position with adequate detail is difficult using current imaging modalities. HYPOTHESIS: Position multiple electrophysiology catheters simultaneously at predetermined strategical positions in the heart using transthoracic echocardiographic guidance. ANIMALS: Eight adult healthy horses. METHODS: Observational study. Two electrophysiological studies were performed: 1 procedure with catheters positioned in the right heart in the standing sedated horse and 1 procedure under general anesthesia with catheters positioned in the left heart. Except for the coronary sinus catheter, each catheter positioning was simultaneously guided by right-parasternal transthoracic echocardiography and 3D electro-anatomical mapping. RESULTS: For each catheter position, a central imaging plane was taken as the starting point, after which the imaging probe was shifted, rotated, and angulated to visualize the catheter over its entire length, including its distal electrode. Catheter positionings in the right heart and left ventricle were successfully guided in the majority of the horses whereas catheter positionings in the left atrium, and especially the pulmonary veins, were challenging to guide echocardiographically. CONCLUSIONS AND CLINICAL IMPORTANCE: Ultrasound guidance of catheters to specific positions useful for electrophysiological mapping was feasible in the right heart and left ventricle but challenging for the left atrium. This approach creates a perspective for minimally invasive arrhythmia diagnosis without the need for a 3D mapping system. Left parasternal views and intracardiac echocardiography might provide better guidance for left atrial positions.

Utility of CT and MRI in Cardiac Electrophysiology.

Cardiac electrophysiology involves the diagnosis and management of arrhythmias. CT and MRI play an increasingly important role in cardiac electrophysiology, primarily in preprocedural planning of ablation procedures but also in procedural guidance and postprocedural follow-up. The most common applications include ablation for atrial fibrillation (AF), ablation for ventricular tachycardia (VT), and for planning cardiac resynchronization therapy (CRT). For AF ablation, preprocedural evaluation includes anatomic evaluation and planning using CT or MRI as well as evaluation for left atrial fibrosis using MRI, a marker of poor outcomes following ablation. Procedural guidance during AF ablation is achieved by fusing anatomic data from CT or MRI with electroanatomic mapping to guide the procedure. Postprocedural imaging with CT following AF ablation is commonly used to evaluate for complications such as pulmonary vein stenosis and atrioesophageal fistula. For VT ablation, both MRI and CT are used to identify scar, representing the arrhythmogenic substrate targeted for ablation, and to plan the optimal approach for ablation. CT or MR images may be fused with electroanatomic maps for intraprocedural guidance during VT ablation and may also be used to assess for complications following ablation. Finally, functional information from MRI may be used to identify patients who may benefit from CRT, and cardiac vein mapping with CT or MRI may assist in planning access. ©RSNA, 2024 Supplemental material is available for this article.

Electrophysiological Cardiovascular Magnetic Resonance (EP-CMR)-Guided Interventional Procedures: Challenges and Opportunities.

PURPOSE OF REVIEW: Cardiovascular magnetic resonance (CMR) imaging excels in providing detailed three-dimensional anatomical information together with excellent soft tissue contrast and has already become a valuable tool for diagnostic evaluation, electrophysiological procedure (EP) planning, and therapeutical stratification of atrial or ventricular rhythm disorders. CMR-based identification of ablation targets may significantly impact existing concepts of interventional electrophysiology. In order to exploit the inherent advantages of CMR imaging to the fullest, CMR-guided ablation procedures (EP-CMR) are justly considered the ultimate goal. RECENT FINDINGS: Electrophysiological cardiovascular magnetic resonance (EP-CMR) interventional procedures have more recently been introduced to the CMR armamentarium: in a single-center series of 30 patients, an EP-CMR guided ablation success of 93% has been reported, which is comparable to conventional ablation outcomes for typical atrial flutter and procedure and ablation time were also reported to be comparable. However, moving on from already established workflows for the ablation of typical atrial flutter in the interventional CMR environment to treatment of more complex ventricular arrhythmias calls for technical advances regarding development of catheters, sheaths and CMR-compatible defibrillator equipment. CMR imaging has already become an important diagnostic tool in the standard clinical assessment of cardiac arrhythmias. Previous studies have demonstrated the feasibility and safety of performing electrophysiological interventional procedures within the CMR environment and fully CMR-guided ablation of typical atrial flutter can be implemented as a routine procedure in experienced centers. Building upon established workflows, the market release of new, CMR-compatible interventional devices may finally enable targeting ventricular arrhythmias.

Deep learning based ECG segmentation for delineation of diverse arrhythmias.

Accurate delineation of key waveforms in an ECG is a critical step in extracting relevant features to support the diagnosis and treatment of heart conditions. Although deep learning based methods using segmentation models to locate P, QRS, and T waves have shown promising results, their ability to handle arrhythmias has not been studied in any detail. In this paper we investigate the effect of arrhythmias on delineation quality and develop strategies to improve performance in such cases. We introduce a U-Net-like segmentation model for ECG delineation with a particular focus on diverse arrhythmias. This is followed by a post-processing algorithm which removes noise and automatically determines the boundaries of P, QRS, and T waves. Our model has been trained on a diverse dataset and evaluated against the LUDB and QTDB datasets to show strong performance, with F1-scores exceeding 99% for QRS and T waves, and over 97% for P waves in the LUDB dataset. Furthermore, we assess various models across a wide array of arrhythmias and observe that models with a strong performance on standard benchmarks may still perform poorly on arrhythmias that are underrepresented in these benchmarks, such as tachycardias. We propose solutions to address this discrepancy.

Arrhythmic Mitral Valve Prolapse Phenotype: An Unsupervised Machine Learning Analysis Using a Multicenter Cardiac MRI Registry.

Purpose To use unsupervised machine learning to identify phenotypic clusters with increased risk of arrhythmic mitral valve prolapse (MVP). Materials and Methods This retrospective study included patients with MVP without hemodynamically significant mitral regurgitation or left ventricular (LV) dysfunction undergoing late gadolinium enhancement (LGE) cardiac MRI between October 2007 and June 2020 in 15 European tertiary centers. The study end point was a composite of sustained ventricular tachycardia, (aborted) sudden cardiac death, or unexplained syncope. Unsupervised data-driven hierarchical k-mean algorithm was utilized to identify phenotypic clusters. The association between clusters and the study end point was assessed by Cox proportional hazards model. Results A total of 474 patients (mean age, 47 years ± 16 [SD]; 244 female, 230 male) with two phenotypic clusters were identified. Patients in cluster 2 (199 of 474, 42%) had more severe mitral valve degeneration (ie, bileaflet MVP and leaflet displacement), left and right heart chamber remodeling, and myocardial fibrosis as assessed with LGE cardiac MRI than those in cluster 1. Demographic and clinical features (ie, symptoms, arrhythmias at Holter monitoring) had negligible contribution in differentiating the two clusters. Compared with cluster 1, the risk of developing the study end point over a median follow-up of 39 months was significantly higher in cluster 2 patients (hazard ratio: 3.79 [95% CI: 1.19, 12.12], P = .02) after adjustment for LGE extent. Conclusion Among patients with MVP without significant mitral regurgitation or LV dysfunction, unsupervised machine learning enabled the identification of two phenotypic clusters with distinct arrhythmic outcomes based primarily on cardiac MRI features. These results encourage the use of in-depth imaging-based phenotyping for implementing arrhythmic risk prediction in MVP. Keywords: MR Imaging, Cardiac, Cardiac MRI, Mitral Valve Prolapse, Cluster Analysis, Ventricular Arrhythmia, Sudden Cardiac Death, Unsupervised Machine Learning Supplemental material is available for this article. © RSNA, 2024.

Hierarchical online contrastive anomaly detection for fetal arrhythmia diagnosis in ultrasound.

Arrhythmia is a major cardiac abnormality in fetuses. Therefore, early diagnosis of arrhythmia is clinically crucial. Pulsed-wave Doppler ultrasound is a commonly used diagnostic tool for fetal arrhythmia. Its key step for diagnosis involves identifying adjacent measurable cardiac cycles (MCCs). As cardiac activity is complex and the experience of sonographers is often varied, automation can improve user-independence and diagnostic-validity. However, arrhythmias pose several challenges for automation because of complex waveform variations, which can cause major localization bias and missed or false detection of MCCs. Filtering out non-MCC anomalies is difficult because of large intra-class and small inter-class variations between MCCs and non-MCCs caused by agnostic morphological waveform variations. Moreover, rare arrhythmia cases are insufficient for classification algorithms to adequately learn discriminative features. Using only normal cases for training, we propose a novel hierarchical online contrastive anomaly detection (HOCAD) framework for arrhythmia diagnosis during test time. The contribution of this study is three-fold. First, we develop a coarse-to-fine framework inspired by hierarchical diagnostic logic, which can refine localization and avoid missed detection of MCCs. Second, we propose an online learning-based contrastive anomaly detection with two new anomaly scores, which can adaptively filter out non-MCC anomalies on a single image during testing. With these complementary efforts, we precisely determine MCCs for correct measurements and diagnosis. Third, to the best of our knowledge, this is the first reported study investigating intelligent diagnosis of fetal arrhythmia on a large-scale and multi-center ultrasound dataset. Extensive experiments on 3850 cases, including 266 cases covering three typical types of arrhythmias, demonstrate the effectiveness of the proposed framework.

Interventricular septal thickness on cardiac computed tomography as a novel risk factor for conduction disturbances in patients undergoing transcatheter aortic valve replacement.

AIMS: We examined whether thickness of the basal muscular interventricular septum (IVS), as measured by pre-procedural computed tomography (CT), could be used to identify the risk of conduction disturbances following transcatheter aortic valve replacement (TAVR). The IVS is a pivotal region of the electrical conduction system of the heart where the atrioventricular conduction axis is located. METHODS AND RESULTS: Included were 78 patients with severe aortic stenosis who underwent CT imaging prior to TAVR. The thickness of muscular IVS was measured in the coronal view, in systolic phases, at 1, 2, 5, and 10 mm below the membranous septum (MS). The primary endpoint was a composite of conduction disturbance following TAVR. Conduction disturbances occurred in 24 out of 78 patients (30.8%). Those with conduction disturbances were significantly more likely to have a thinner IVS than those without conduction disturbances at every measured IVS level (2.98 ± 0.52 mm vs. 3.38 ± 0.52 mm, 4.10 ± 1.02 mm vs. 4.65 ± 0.78 mm, 6.11 ± 1.12 mm vs. 6.88 ± 1.03 mm, and 9.72 ± 1.95 mm vs. 10.70 ± 1.55 mm for 1, 2, 5 and 10 mm below MS, respectively, P < 0.05 for all). Multivariable logistic regression analysis showed that pre-procedural IVS thickness (<4 mm at 2 mm below the MS) was a significant independent predictor of post-procedural conduction disturbance (adjOR 7.387, 95% CI: 2.003-27.244, P = 0.003). CONCLUSION: Pre-procedural CT assessment of basal IVS thickness is a novel predictive marker for the risk of conduction disturbances following TAVR. The IVS thickness potentially acts as an anatomical barrier protecting the underlying conduction system from mechanical compression during TAVR.

Risk profiles for ventricular arrhythmias in hypertrophic cardiomyopathy through clustering analysis including left ventricular strain.

AIMS: The prediction of ventricular arrhythmia (VA) in hypertrophic cardiomyopathy (HCM) remains challenging. We sought to characterize the VA risk profile in HCM patients through clustering analysis combining clinical and conventional imaging parameters with information derived from left ventricular longitudinal strain analysis (LV-LS). METHODS: A total of 434 HCM patients (65% men, mean age 56 years) were included from two referral centers and followed longitudinally (mean duration 6 years). Mechanical and temporal parameters were automatically extracted from the LV-LS segmental curves of each patient in addition to conventional clinical and imaging data. A total of 287 features were analyzed using a clustering approach (k-means). The principal endpoint was VA. RESULTS: 4 clusters were identified with a higher rhythmic risk for clusters 1 and 4 (VA rates of 26%(28/108), 13%(13/97), 12%(14/120), and 31%(34/109) for cluster 1,2,3 and 4 respectively). These 4 clusters differed mainly by LV-mechanics with a severe and homogeneous decrease of myocardial deformation for cluster 4, a small decrease for clusters 2 and 3 and a marked deformation delay and temporal dispersion for cluster 1 associated with a moderate decrease of the GLS (p < 0.0001 for GLS comparison between clusters). Patients from cluster 4 had the most severe phenotype (mean LV mass index 123 vs. 112 g/m2; p = 0.0003) with LV and left atrium (LA) remodeling (LA-volume index (LAVI) 46.6 vs. 41.5 ml/m2, p = 0.04 and LVEF 59.7 vs. 66.3%, p < 0.001) and impaired exercise capacity (% predicted peak VO2 58.6 vs. 69.5%; p = 0.025). CONCLUSION: Processing LV-LS parameters in HCM patients 4 clusters with specific LV-strain patterns and different rhythmic risk levels are identified. Automatic extraction and analysis of LV strain parameters improves the risk stratification for VA in HCM patients.

Impact of abdominal compression on heart and stomach motion for stereotactic arrhythmia radioablation.

PURPOSE: To evaluate the effectiveness of abdominal compression (AC) as a respiratory motion management method for the heart and stomach during stereotactic arrhythmia radioablation (STAR). METHODS: 4D computed tomography (4DCT) scans of patients imaged with AC or without AC (free-breathing: FB) were obtained from ventricular-tachycardia (VT) (n = 3), lung cancer (n = 18), and liver cancer (n = 18) patients. Patients treated for VT were imaged both FB and with AC. Lung and liver patients were imaged once with FB or with AC, respectively. The heart, left ventricle (LV), LV components (LVCs), and stomach were contoured on each phase of the 4DCTs. Centre of mass (COM) translations in the left/right (LR), ant/post (AP), and sup/inf (SI) directions were measured for each structure. Minimum distances between LVCs and the stomach over the respiratory cycle were also measured on each 4DCT phase. Mann-Whitney U-tests were performed between AC and FB datasets with a significance of α = 0.05. RESULTS: No statistical difference (all p values were >0.05) was found in COM translations between FB and AC patient datasets for all contoured cardiac structures. A reduction in COM translation with AC relative to FB was patient, direction, and structure specific for the three VT patients. A significant decrease in the AP range of motion of the stomach was observed under AC compared to FB. No statistical difference was found between minimum distances to the stomach and LVCs between FB and AC. CONCLUSIONS: AC was not a consistent motion management method for STAR, nor does not uniformly affect the separation distance between LVCs and the stomach. If AC is employed in future STAR protocols, the motion of the target volume and its relative distance to the stomach should be compared on two 4DCTs: one while the patient is FB and one under AC.

Prognostic significance of echocardiographic deformation imaging in adult congenital heart disease.

BACKGROUND: Due to medical and surgical advancements, the population of adult patients with congenital heart disease (ACHD) is growing. Despite successful therapy, ACHD patients face structural sequalae, placing them at increased risk for heart failure and arrhythmias. Left and right ventricular function are important predictors for adverse clinical outcomes. In acquired heart disease it has been shown that echocardiographic deformation imaging is of superior prognostic value as compared to conventional parameters as ejection fraction. However, in adult congenital heart disease, the clinical significance of deformation imaging has not been systematically assessed and remains unclear. METHODS: According to the Preferred Reporting Items for Systematic Reviews checklist, this systematic review included studies that reported on the prognostic value of echocardiographic left and/or right ventricular strain by 2-dimensional speckle tracking for hard clinical end-points (death, heart failure hospitalization, arrhythmias) in the most frequent forms of adult congenital heart disease. RESULTS: In total, 19 contemporary studies were included. Current data shows that left ventricular and right ventricular global longitudinal strain (GLS) predict heart failure, transplantation, ventricular arrhythmias and mortality in patients with Ebstein's disease and tetralogy of Fallot, and that GLS of the systemic right ventricle predicts heart failure and mortality in patients post atrial switch operation or with a congenitally corrected transposition of the great arteries. CONCLUSIONS: Deformation imaging can potentially impact the clinical decision making in ACHD patients. Further studies are needed to establish disease-specific reference strain values and ranges of impaired strain that would indicate the need for medical or structural intervention.

MRI Accurately Visualizes RF Ablation Delivery Targeted to MRI-Defined Arrhythmia Substrates in the Left Ventricle.

OBJECTIVE: Investigate the capacity of MRI to evaluate efficacy of radiofrequency (RF) ablations delivered to MRI-defined arrhythmogenic substrates. METHODS: Baseline MRI was performed at 3 T including 3D LGE in a swine model of chronic myocardial infarct (N = 8). MRI-derived maps of scar and heterogeneous tissue channels (HTCs) were generated using ADAS 3D. Animals underwent electroanatomic mapping and ablation of the left ventricle in CARTO3, guided by MRI-derived scar maps. Post-ablation MRI (in vivo at 3 T in 5/8 animals; ex vivo at 1.5 T in 3/8) included 3D native T1-weighted IR-SPGR (TI = 700-800 ms) to visualize RF lesions. T1-derived RF lesions were compared against excised tissue. The locations of T1-derived RF lesions were compared against CARTO ablation tags, and segment-wise sensitivity and specificity of lesion detection were calculated within the AHA 17-segment model. RESULTS: RF lesions were clearly visualized in HTCs, scar, and myocardium. Ablation patterns delivered in CARTO matched T1-derived RF lesion patterns with high sensitivity (88.9%) and specificity (94.7%), and were closely matched in registered MR-EP data sets, with a displacement of 5.4 ±3.8 mm (N = 152 ablation tags). CONCLUSION: Integrating MRI into ablative procedures for RF lesion assessment is feasible. Patterns of RF lesions created using a standard 3D EAM system are accurately reflected by MRI visualization in healthy myocardium, scar, and HTCs comprising the MRI-defined arrhythmia substrate. SIGNIFICANCE: MRI visualization of RF lesions can provide near-immediate ( 24 h) assessment of ablation, potentially indicating whether critical MRI-defined ventricular tachycardia substrates have been adequately ablated.

Cardiac Magnetic Resonance and Cardiac Implantable Electronic Devices: Are They Truly Still "Enemies"?

The application of cardiac magnetic resonance (CMR) imaging in clinical practice has grown due to technological advancements and expanded clinical indications, highlighting its superior capabilities when compared to echocardiography for the assessment of myocardial tissue. Similarly, the utilization of implantable cardiac electronic devices (CIEDs) has significantly increased in cardiac arrhythmia management, and the requirements of CMR examinations in patients with CIEDs has become more common. However, this type of exam often presents challenges due to safety concerns and image artifacts. Until a few years ago, the presence of CIED was considered an absolute contraindication to CMR. To address these challenges, various technical improvements in CIED technology, like the reduction of the ferromagnetic components, and in CMR examinations, such as the introduction of new sequences, have been developed. Moreover, a rigorous protocol involving multidisciplinary collaboration is recommended for safe CMR examinations in patients with CIEDs, emphasizing risk assessment, careful monitoring during CMR, and post-scan device evaluation. Alternative methods to CMR, such as computed tomography coronary angiography with tissue characterization techniques like dual-energy and photon-counting, offer alternative potential solutions, although their diagnostic accuracy and availability do limit their use. Despite technological advancements, close collaboration and specialized staff training remain crucial for obtaining safe diagnostic CMR images in patients with CIEDs, thus justifying the presence of specialized centers that are equipped to handle these type of exams.

A new approach for heart disease detection using Motif transform-based CWT's time-frequency images with DenseNet deep transfer learning methods.

OBJECTIVES: Electrocardiogram (ECG) signals are extensively utilized in the identification and assessment of diverse cardiac conditions, including congestive heart failure (CHF) and cardiac arrhythmias (ARR), which present potential hazards to human health. With the aim of facilitating disease diagnosis and assessment, advanced computer-aided systems are being developed to analyze ECG signals. METHODS: This study proposes a state-of-the-art ECG data pattern recognition algorithm based on Continuous Wavelet Transform (CWT) as a novel signal preprocessing model. The Motif Transformation (MT) method was devised to diminish the drawbacks and limitations inherent in the CWT, such as the issue of boundary effects, limited localization in time and frequency, and overfitting conditions. This transformation technique facilitates the formation of diverse patterns (motifs) within the signals. The patterns (motifs) are constructed by comparing the amplitudes of each individual sample value in the ECG signals in terms of their largeness and smallness. In the subsequent stage, the obtained one-dimensional signals from the MT transformation were subjected to CWT to obtain scalogram images. In the last stage, the obtained scalogram images were subjected to classification using DenseNET deep transfer learning techniques. RESULTS AND CONCLUSIONS: The combined approach of MT + CWT + DenseNET yielded an impressive success rate of 99.31 %.

Imaging Features of Arrhythmogenic Cardiomyopathies.

Arrhythmogenic cardiomyopathy (ACM) is a genetic disease characterized by replacement of ventricular myocardium with fibrofatty tissue, predisposing the patient to ventricular arrhythmias and/or sudden cardiac death. Most cases of ACM are associated with pathogenic variants in genes that encode desmosomal proteins, an important cell-to-cell adhesion complex present in both the heart and skin tissue. Although ACM was first described as a disease predominantly of the right ventricle, it is now acknowledged that it can also primarily involve the left ventricle or both ventricles. The original right-dominant phenotype is traditionally diagnosed using the 2010 task force criteria, a multifactorial algorithm divided into major and minor criteria consisting of structural criteria based on two-dimensional echocardiographic, cardiac MRI, or right ventricular angiographic findings; tissue characterization based on endomyocardial biopsy results; repolarization and depolarization abnormalities based on electrocardiographic findings; arrhythmic features; and family history. Shortfalls in the task force criteria due to the modern understanding of the disease have led to development of the Padua criteria, which include updated criteria for diagnosis of the right-dominant phenotype and new criteria for diagnosis of the left-predominant and biventricular phenotypes. In addition to incorporating cardiac MRI findings of ventricular dilatation, systolic dysfunction, and regional wall motion abnormalities, the new Padua criteria emphasize late gadolinium enhancement at cardiac MRI as a key feature in diagnosis and imaging-based tissue characterization. Conditions to consider in the differential diagnosis of the right-dominant phenotype include various other causes of right ventricular dilatation such as left-to-right shunts and variants of normal right ventricular anatomy that can be misinterpreted as abnormalities. The left-dominant phenotype can mimic myocarditis at imaging and clinical examination. Additional considerations for the differential diagnosis of ACM, particularly for the left-dominant phenotype, include sarcoidosis and dilated cardiomyopathy. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Role of Computed Tomography in Cardiac Electrophysiology.

With the increasing prevalence of arrhythmias, the use of electrophysiology (EP) procedures has increased. Recent advancements in computed tomography (CT) technology have expanded its use in pre-assessments and post-assessments of EP procedures. CT provides high-resolution images, is noninvasive, and is widely available. This article highlights the strengths and weaknesses of cardiac CT in EP.

Intracardiac echocardiography in paediatric and congenital cardiac ablation shortens procedure duration and improves success without complications.

AIMS: Common to adult electrophysiology studies (EPSs), intracardiac echocardiography (ICE) use in paediatric and congenital heart disease (CHD) EPS is limited. The purpose of this study was to assess the efficacy of ICE use and incidence of associated complications in paediatric and CHD EPS. METHODS AND RESULTS: This single-centre retrospective matched cohort study reviewed EPS between 2013 and 2022. Demographics, CHD type, and EPS data were collected. Intracardiac echocardiography cases were matched 1:1 to no ICE controls to assess differences in complications, ablation success, fluoroscopy exposure, procedure duration, and arrhythmia recurrence. Cases and controls with preceding EPS within 5 years were excluded. Intracardiac echocardiography cases without an appropriate match were excluded from comparative analyses but included in the descriptive cohort. We performed univariable and multivariable logistic regression to assess associations between variables and outcomes. A total of 335 EPS were reviewed, with ICE used in 196. The median age of ICE cases was 15 [interquartile range (IQR) 12-17; range 3-47] years, and median weight 57 [IQR 45-71; range 15-134] kg. There were no ICE-related acute or post-procedural complications. There were 139 ICE cases matched to no ICE controls. Baseline demographics and anthropometrics were similar between cases and controls. Fluoroscopy exposure (P = 0.02), procedure duration (P = 0.01), and arrhythmia recurrence (P = 0.01) were significantly lower in ICE cases. CONCLUSION: Intracardiac echocardiography in paediatric and CHD ablations is safe and reduces procedure duration, fluoroscopy exposure, and arrhythmia recurrence. However, not every arrhythmia substrate requires ICE use. Thoughtful selection will ensure the judicious and strategic application of ICE to enhance outcomes.

SCMR expert consensus statement for cardiovascular magnetic resonance of patients with a cardiac implantable electronic device.

Cardiovascular magnetic resonance (CMR) is a proven imaging modality for informing diagnosis and prognosis, guiding therapeutic decisions, and risk stratifying surgical intervention. Patients with a cardiac implantable electronic device (CIED) would be expected to derive particular benefit from CMR given high prevalence of cardiomyopathy and arrhythmia. While several guidelines have been published over the last 16 years, it is important to recognize that both the CIED and CMR technologies, as well as our knowledge in MR safety, have evolved rapidly during that period. Given increasing utilization of CIED over the past decades, there is an unmet need to establish a consensus statement that integrates latest evidence concerning MR safety and CIED and CMR technologies. While experienced centers currently perform CMR in CIED patients, broad availability of CMR in this population is lacking, partially due to limited availability of resources for programming devices and appropriate monitoring, but also related to knowledge gaps regarding the risk-benefit ratio of CMR in this growing population. To address the knowledge gaps, this SCMR Expert Consensus Statement integrates consensus guidelines, primary data, and opinions from experts across disparate fields towards the shared goal of informing evidenced-based decision-making regarding the risk-benefit ratio of CMR for patients with CIEDs.