Search

Radiographic identification of the cardiac implantable electronic device (CIED) manufacturer facilitates urgent interrogation of an unknown CIED. In the past, we relied on visualizing a manufacturer-specific X-ray logo. Recently, a free smartphone application ("Pacemaker-ID") was made available. A photograph of a chest X-ray was subjected to an artificial intelligence (AI) algorithm that uses manufacturer characteristics (canister shape, battery design) for identification. We sought to externally validate the accuracy of this smartphone application as a point-of-care (POC) diagnostic tool, compare on-axis to off-axis photo accuracy, and compare it to X-ray logo visualization for manufacturer identification. We reviewed operative reports and chest X-rays in 156 pacemaker and 144 defibrillator patients to visualize X-ray logos and to test the application with 3 standard (on-axis) and 4 non-standard (off-axis) photos (20° cranial; caudal, leftward, and rightward). Contingency tables were created and chi-squared analyses (P.05) were completed for manufacturer and CIED type. The accuracy of the application was 91.7% and 86.3% with single and serial application(s), respectively; 80.7% with off-axis photos; and helpful for all manufacturers (range, 85.4%-96.6%). Overall, the application proved superior to the X-ray logo, visualized in 56% overall (P.0001) but varied significantly by manufacturer (range, 7.7%-94.8%; P.00001). The accuracy of the Pacemaker-ID application is consistent with reports from its creators and superior to X-ray logo visualization. The accuracy of the application as a POC tool can be enhanced and maintained with further AI training using recent CIED models. Some manufacturers can enhance their X-ray logos by improving placement and design.

Background: We developed a novel RIVAL system that consists of a CT-based computational simulation to identify VT circuits and an ECG-based automated approach to localize VT exit sites. Objective: Prospectively assess the ability of the RIVAL system to localize VT circuits and exits. Methods: Patients presenting for VT ablation were enrolled into the study. Pre-procedural cardiac CT was performed and used to conduct heart simulations for predicting VT circuits. The patient’s CT geometry with the predicted VT circuits was registered to the electroanatomic shell created during the procedure and imported into the RIVAL program. During the procedure, exit sites of induced VTs are localized in real-time using the 12-lead ECG onto the patient-specific CT surface. Predicted ablation regions obtained by combining RIVAL-predicted VT circuits with exit sites were analyzed offline to assess localization accuracy to the invasive VT ablation procedure. Results: Four patients with ischemic cardiomyopathy undergoing VT ablation had preprocedural cardiac CT. In P1, two VTs were induced during the procedure. The RIVAL predicted 2 VT circuits and achieved a mean localization error of 7.0mm for VT exit site prediction (Fig1). There was a spatial concordance between the predicted ablation areas and the clinical ablation regions. For P2, three VTs were induced during the VT ablation. A large area of scar was associated with 6 RIVAL-predicted VT circuits. The exit site localization accuracy could not be precisely quantitated because the VTs terminated with ablation at a mid-diastolic site. For P3, no VTs were inducible, however substrate modification (SM) was performed in the anterior-apical LV. The RIVAL predicted only one VT circuit located in the area where SM was performed. No VT was induced for P4 and the RIVAL did not predict any VT circuits. Conclusions: The RIVAL predicts the VT circuit and exit accurately, which may improve the precision of ablation therapies and procedure outcomes.

Background: Patients with cardiac sarcoidosis (CS) are at increased risk of life-threatening ventricular arrhythmias (VA). Current approaches to risk stratification have limited predictive value. Objectives: To assess the utility of spatial dispersion analysis of LGE-CMR, as a quantitative measure of myocardial tissue heterogeneity, in risk stratifying patients with CS for ventricular VA and death. Methods: 62 patients with CS underwent LGE-CMR. LGE images were segmented and dispersion maps of the left and right ventricles were generated as follows. Based on signal intensity (SI), each pixel was categorized as abnormal (SI {greater than or equal to}3SD above the mean), intermediate (SI 1-3 SD above the mean) or normal (SI

Background We have previously developed an intraprocedural automatic arrhythmia‐origin localization (AAOL) system to identify idiopathic ventricular arrhythmia origins in real time using a 3‐lead ECG. The objective was to assess the localization accuracy of ventricular tachycardia (VT) exit and premature ventricular contraction (PVC) origin sites in patients with structural heart disease using the AAOL system. Methods and Results In retrospective and prospective case series studies, a total of 42 patients who underwent VT/PVC ablation in the setting of structural heart disease were recruited at 2 different centers. The AAOL system combines 120‐ms QRS integrals of 3 leads (III, V2, V6) with pace mapping to predict VT exit/PVC origin site and projects that site onto the patient‐specific electroanatomic mapping surface. VT exit/PVC origin sites were clinically identified by activation mapping and/or pace mapping. The localization error of the VT exit/PVC origin site was assessed by the distance between the clinically identified site and the estimated site. In the retrospective study of 19 patients with structural heart disease, the AAOL system achieved a mean localization accuracy of 6.5±2.6 mm for 25 induced VTs. In the prospective study with 23 patients, mean localization accuracy was 5.9±2.6 mm for 26 VT exit and PVC origin sites. There was no difference in mean localization error in epicardial sites compared with endocardial sites using the AAOL system (6.0 versus 5.8 mm, P =0.895). Conclusions The AAOL system achieved accurate localization of VT exit/PVC origin sites in patients with structural heart disease; its performance is superior to current systems, and thus, it promises to have potential clinical utility.

Visual servoing is a robotic method that has the potential to assist surgeons with tracking tool tips when attached to optical fibers to create photoacoustic images that are autonomously monitored. Currently, this approach must be tested with multiple image frames and multiple laser energies prior to each surgery in order to identify the minimum required energy that will not cause system failure over the number of frames tested. This study investigates possible integration of the generalized contrast-to-noise ratio (gCNR) into pre-surgical procedures as a method to predict system failure from only a single image frame. Photoacoustic data were acquired from an optical fiber inserted in a plastisol phantom or in the left ventricle of an in vivo swine heart. Raw data were processed with delay-and-sum (DAS) and short-lag spatial coherence (SLSC) beamforming (M = 25). gCNR values were estimated from a 3 mm x 3 mm region of interest (ROI) surrounding the photoacoustic target coordinates provided by the visual servoing algorithm. The prediction function modelled from phantom data was fit with R2 values of 0.992 and 0.991 for DAS and SLSC beamformers, respectively. When applying this fit to the in vivo test data, the RMSE between measured segmentation accuracy and the prediction functions was 9.34% for DAS images and 4.78% for SLSC images. These results indicate that the newly introduced image quality metric gCNR has sufficient robustness to predict the performance of visual servoing segmentation tasks and thereby mitigate the burden, time, and requirements of testing multiple image frames prior to the initiation of a surgery.

Corticosteroids are the mainstay of therapy for cardiac sarcoidosis (CS) ([1][1]); however, long-term exposure may be associated with numerous side effects. Although cardiac 18-fluorodoxyglucose position emission tomography (FDG-PET) is useful in tailoring corticosteroid therapy, the effect of

Cardiac sarcoidosis is a granulomatous disease that may affect any organ, including the heart. Diagnosis of cardiac sarcoidosis is challenging, given the varied and non-specific clinical presentation and limited sensitivity and specificity of available diagnostic tests. With the growing interest and developments in imaging techniques, cardiac magnetic resonance imaging (CMR) and positron emission tomography (PET) have emerged as important tools in the diagnostic evaluation of patients with suspected cardiac sarcoidosis. These modalities have been given increasing emphasis in successive published diagnostic guidelines for CS. This review will provide an update on the recent paradigm shift in diagnostic guidelines for cardiac sarcoidosis, with a focus on the advanced cardiac imaging modalities and their developed role in clinical practice.

Atrial flutter (AFL) is a common form of arrhythmia recurrence after atrial fibrillation (AF) ablation. We aimed to define (1) the incidence of AFL and (2) the clinical factors associated with cavo-tricuspid isthmus dependent (typical) and atypical AFL, after AF ablation. The retrospective cohort consisted of 1,029 patients that underwent initial radiofrequency AF ablation from May 2005 to December 2013 at a single academic center. Patients with missing follow-up data, history of AFL ablation, and those with undocumented AFL were excluded. Atrial volumes were measured using three-dimensional cardiac computed tomography or magnetic resonance imaging. A total of 607 patients were included in the final cohort (age 59.2 ± 10.6 years, 76.0% men, 58.7% paroxysmal AF). During a median follow-up of 845 days (interquartile range 389 to 1,597 days), 122 (20.1%) patients developed AFL. Of these, 17 had typical AFL, 98 had atypical AFL, and 7 patients had both circuits. In the multivariable Cox regression analysis, only right atrial volume index (hazard ratio [HR] 1.25 per 10 ml/m2, confidence interval [CI] 95% 1.10 to 1.42) was associated with incident typical AFL; whereas persistent AF (HR 1.59, CI 95% 1.06 to 2.40), linear lesions (HR 1.58, CI 95% 1.02 to 2.46) and left atrial volume index (HR 1.17 per 10 ml/m2, CI 95% 1.07 to 1.27) were associated with incident atypical AFL. In conclusion, noninvasive measures of right and left atrial remodeling are strongly associated with incident AFL after AF ablation. Strategies to prevent incident AFL using these measures after index ablation warrant further investigation.

Supplemental Digital Content is available in the text., Background: Social influencers of health namely race, ethnicity, and structural inequities are known to affect the incidence of out of hospital sudden death (OHSD). We sought to examine the association between social influencers of health and the incidence of OHSD in the diverse neighborhoods of New York City during the first wave of coronavirus disease 2019 (COVID-19) epidemic. Methods: New York City ZIP stratified data on OHSD were obtained from the Fire Department of New York during the first wave of COVID-19 epidemic (March 1 to April 10, 2019) and the same period in 2020. To assess associates of OHSD, ZIP code-specific sociodemographic characteristics for 8 491 238 New York City residents were obtained via the US Census Bureau’s 2018 American Community Survey and the New York Police Department’s crime statistics. Results: Between March 1 and April 10, 2020, the number of OHSD rose to 4334 from 1112 compared with the year prior. Of the univariate ZIP code level variables evaluated, proportions of Black race, Hispanic/Latino ethnicity, single parent household, unemployed inhabitants, people completing less than high school education, inhabitants with no health insurance, people financially struggling or living in poverty, percent of noncitizens, and population density were associated with increased rates of OHSD within ZIP codes. In multivariable analysis, ZIP codes with higher proportions of inhabitants with less than high school education (P

Combining mechanistic modeling and machine learning, a multivariable sudden cardiac death predictor outperforms clinical metrics., Cardiac sarcoidosis (CS), an inflammatory disease characterized by formation of granulomas in the heart, is associated with high risk of sudden cardiac death (SCD) from ventricular arrhythmias. Current “one-size-fits-all” guidelines for SCD risk assessment in CS result in insufficient appropriate primary prevention. Here, we present a two-step precision risk prediction technology for patients with CS. First, a patient’s arrhythmogenic propensity arising from heterogeneous CS-induced ventricular remodeling is assessed using a novel personalized magnetic-resonance imaging and positron-emission tomography fusion mechanistic model. The resulting simulations of arrhythmogenesis are fed, together with a set of imaging and clinical biomarkers, into a supervised classifier. In a retrospective study of 45 patients, the technology achieved testing results of 60% sensitivity [95% confidence interval (CI): 57-63%], 72% specificity [95% CI: 70-74%], and 0.754 area under the receiver operating characteristic curve [95% CI: 0.710-0.797]. It outperformed clinical metrics, highlighting its potential to transform CS risk stratification.

Sarcoidosis is a systemic disease characterized by granulomatous inflammation. Cardiac involvement is associated with increased morbidity. However, differences in clinical characteristics and outcomes based on initial sarcoidosis organ manifestation in patients with cardiac sarcoidosis (CS) have not been described.A retrospective cohort of 252 patients with CS at an urban, quaternary medical center was studied. Presentation, treatment and outcomes of de novo CS and prior ECS groups were compared. Survival free of primary composite outcome (left ventricular assist device implantation, orthotopic heart transplantation (OHT), or death) was assessed.There were 124 de novo CS patients and 128 with prior ECS at time of CS diagnosis. De novo CS patients were younger at CS diagnosis (p = 0.020). De novo CS patients had a more advanced cardiac presentation: lower left ventricular ejection fraction (LVEF) (p 0.001), more frequent sustained ventricular arrhythmias (VA) (p = 0.001), and complete heart block (p = 0.001). During follow-up, new VA (p 0.001), ventricular tachycardia ablation (p 0.001), and OHT (p = 0.003) were more common in the de novo CS group. Outcome free survival was significantly shorter for de novo CS patients (p = 0.005), with increased hazard of primary composite outcome (p = 0.034) and development of new VA (p = 0.027) when compared to ECS patients. Overall mortality was similar between groups.Patients presenting with CS as their first recognized organ manifestation of sarcoidosis have an increased risk of adverse cardiac outcomes as compared to those with a prior history of ECS. Improved awareness and diagnosis of CS is warranted for earlier recognition.

Background Cardiac sarcoidosis (CS) is a major cause of morbidity and mortality in patients with systemic sarcoidosis. Steroid-sparing agents are increasingly used, despite a lack of randomized trials or published guidelines to direct treatment. Methods and Results This retrospective study included 77 patients with CS treated with prednisone monotherapy (n = 32) or a combination with mycophenolate mofetil (n = 45) between 2003 and 2018. Baseline characteristics and clinical outcomes were evaluated. The mean patient age was 53 ± 11 years at CS diagnosis, 66.2% were male, and 35.1% were Black. The total exposure to maximum prednisone dose (initial prednisone dose × days at dose) was lower in the combination therapy group (1440 mg [interquartile range (IQR), 1200–2760 mg] vs 2710 mg [IQR, 1200–5080 mg]; P = .06). On 18F-fluorodeoxyglucose positron emission tomography scans, both groups demonstrated a significant decrease in the cardiac maximum standardized uptake value after treatment: a median decrease of 3.9 (IQR 2.7–9.0, P = .002) and 2.9 (IQR 0–5.0, P = .001) for prednisone monotherapy and combination therapy, respectively. Most patients experienced improvement or complete resolution in qualitative cardiac 18F-fluorodeoxyglucose uptake (92.3% and 70.4% for the prednisone and combination therapy groups, respectively). Mycophenolate mofetil was well tolerated. Conclusions Mycophenolate mofetil in combination with prednisone for the treatment of CS may minimize corticosteroid exposure and decrease cardiac inflammation without significant adverse effects.

Cardiac sarcoidosis is a component of an often multiorgan granulomatous disease of still uncertain cause. It is being recognized with increasing frequency, mainly as the result of heightened awareness and new diagnostic tests, specifically cardiac magnetic resonance imaging and18F-fluorodeoxyglucose positron emission tomography scans. The purpose of this case-based review is to highlight the potentially life-saving importance of making the early diagnosis of cardiac sarcoidosis using these new tools and to provide a framework for the optimal care of patients with this disease. We will review disease mechanisms as currently understood, associated arrhythmias including conduction abnormalities, and atrial and ventricular tachyarrhythmias, guideline-directed diagnostic criteria, screening of patients with extracardiac sarcoidosis, and the use of pacemakers and defibrillators in this setting. Treatment options, including those related to heart failure, and those which may help clarify disease mechanisms are included.

We developed a novel patient-specific computational model for the numerical simulation of ventricular electromechanics in patients with ischemic cardiomyopathy (ICM). This model reproduces the activity both in sinus rhythm (SR) and in ventricular tachycardia (VT). The presence of scars, grey zones and non-remodeled regions of the myocardium is accounted for by the introduction of a spatially heterogeneous coefficient in the 3D electromechanics model. This 3D electromechanics model is firstly coupled with a 2-element Windkessel afterload model to fit the pressure-volume (PV) loop of a patient-specific left ventricle (LV) with ICM in SR. Then, we employ the coupling with a 0D closed-loop circulation model to analyze a VT circuit over multiple heartbeats on the same LV. We highlight similarities and differences on the solutions obtained by the electrophysiology model and those of the electromechanics model, while considering different scenarios for the circulatory system. We observe that very different parametrizations of the circulation model induce the same hemodynamical considerations for the patient at hand. Specifically, we classify this VT as unstable. We conclude by stressing the importance of combining electrophysiological, mechanical and hemodynamical models to provide relevant clinical indicators in how arrhythmias evolve and can potentially lead to sudden cardiac death.

Background: Infiltrating adipose tissue (inFAT) is a newly recognized proarrhythmic substrate for postinfarct ventricular tachycardias (VT) identifiable on contrast-enhanced computed tomography. This study presents novel digital-heart technology that incorporates inFAT from contrast-enhanced computed tomography to noninvasively predict VT ablation targets and assesses the capability of the technology by comparing its predictions with VT ablation procedure data from patients with ischemic cardiomyopathy. Methods: Digital-heart models reflecting patient-specific inFAT distributions were reconstructed from contrast-enhanced computed tomography. The digital-heart identification of fat-based ablation targeting (DIFAT) technology evaluated the rapid-pacing–induced VTs in each personalized inFAT-based substrate. DIFAT targets that render the inFAT substrate noninducible to VT, including VTs that arise postablation, were determined. DIFAT predictions were compared with corresponding clinical ablations to assess the capabilities of the technology. Results: DIFAT was developed and applied retrospectively to 29 ischemic cardiomyopathy patients with contrast-enhanced computed tomography. DIFAT ablation volumes were significantly less than the estimated clinical ablation volumes (1.87±0.35 versus 7.05±0.88 cm 3 , P Conclusions: DIFAT is a novel digital-heart technology for individualized VT ablation guidance designed to eliminate VT inducibility following initial ablation. DIFAT predictions colocalized well with clinical ablation locations but provided significantly smaller lesions. DIFAT also predicted VTs targeted in redo procedures years later. As DIFAT uses widely accessible computed tomography, its integration into clinical workflows may augment therapeutic precision and reduce redo procedures.

BACKGROUND: We previously developed an intraprocedural automated site of origin localization system to identify the origin of early left ventricular (LV) activation using 12-lead ECGs. However, it has limitations, as it could not identify the site of origin in the right ventricle (RV), and relied on acquiring a complete electroanatomic map (EAM). OBJECTIVE: The objective of this study was to present a new system, the Automatic Arrhythmia Origin Localization (AAOL) system, which utilized incomplete EAM for localization of idiopathic ventricular arrhythmia (IVA) origin on the patient-specific geometry of LV, RV and neighboring vessels. The accuracy of the system in localizing IVA source sites on cardiac structures where pace-mapping is challenging was assessed. METHODS: Twenty patients undergoing IVA catheter ablation had a 12-lead ECG recorded during clinical arrhythmia and during pacing at various locations identified on EAM geometries. The new system combined 3-lead (III, V2, V6) 120-ms QRS integrals and patient-specific EAM geometry with pace mapping to predict the site of earliest ventricular activation. The predicted site was projected onto EAM geometry. RESULTS: Twenty-three IVA origin sites were clinically identified by activation mapping and/or pace mapping (8 RV; 15 LV, including 8 from the posteromedial papillary muscle; 2 from the aortic root; and 1 from the distal coronary sinus). The new system achieved a mean localization accuracy of 3.6 mm for the 23 mapped IVAs. CONCLUSIONS: The new intraprocedural AAOL system achieved accurate localization of IVA origin in ventricles and neighbouring vessels, which could facilitate ablation procedures for patients with IVAs. Key Words: Idiopathic ventricular arrhythmias (IVA); Premature ventricular complexes (PVCs); idiopathic ventricular tachycardia (IVT); Pace mapping; Activation mapping; Radiofrequency (RF) Ablation; ECG.

Introduction: Few intraprocedural localization systems have been developed to predict idiopathic ventricular arrhythmia (IVA) source sites. However, an accurate and bi-ventricular patient-specific automated site of origin localization system remains elusive. To address this issue, we have developed a new automatic arrhythmia origin localization (AAOL) system that determines the sites of earliest activation in both ventricles and provides superior accuracy. Hypothesis: We hypothesized that the AAOL system can use electroanatomic mapping (EAM) geometry and accurately localize IVA source sites on patient-specific geometry of LV, RV and neighboring vessels using 3-lead ECGs. Methods: Twenty patients undergoing IVA catheter ablation had a 12-lead ECG recorded during clinical arrhythmia and during pacing at various locations identified on EAM geometries. The AAOL system combined 3-lead (III, V2, V6) 120-ms QRS integrals and patient-specific EAM geometry with intracardiac pacing to predict the site of earliest ventricular activation. The predicted site was projected onto the EAM geometry using the EAM triangular-mesh site nearest to the tip of the predicted site. Results: Twenty-three IVA source sites were clinically identified by activation mapping and/or pace mapping (8 RV, 15 LV, including 8 from the posteromedial papillary muscle; 2 from the aortic root; and 1 from the distal coronary sinus). The new system achieved a mean localization accuracy of 3.6 mm for the 23 mapped IVAs (Figure 1D), better than that achieved by previous systems. Conclusions: The new AAOL system offers highly accurate localization of IVA source sites in both ventricles and neighboring vessels, which could facilitate ablation procedures for patients with IVAs.

Introduction: We previously developed an LGE-MRI-based virtual-heart arrhythmia ablation targeting (VAAT) methodology to non-invasively determine potential ablation targets for infarct-related VT. However, it is unknown whether VAAT’s predictions correspond with surface ECG predictions. Hypothesis: We hypothesized that the VAAT predicted VT circuits and potential ablation lesions would co-localize with ECG-based VT-exit predictions from a previously validated population-derived automated VT exit localization (PAVEL) system. Methods: We retrospectively enrolled 5 post-infarct patients who underwent LV endocardial VT ablation and had pre-procedural 2D LGE-MRIs. The PAVEL system based on a population-derived statistical method was used to localize VT-exit sites onto one of 238 triangles on the patient-specific virtual-heart LV endocardial surface using 8 independent ECG leads (I, II, V1-V6). The VAAT methodology incorporating patient-specific scar and infarct border zone distributions was used to identify potential VT circuits and find ablation lesions. Results: Eleven induced VTs were analyzed. Ten VT-exit sites were localized onto the patient-specific virtual-heart LV endocardial surface by the PAVEL system, and were used for the comparisons. One VT-exit site was too basal to be localized onto the virtual-heart geometry. The spatial resolution of the 10 predicted VT-exit sites was 13.8 ± 1.8 mm. VAAT-predicted VT circuits and ablation lesions correlated well with all 10 predicted VT-exit sites. Lastly, VAAT ablation lesions fell within the regions ablated clinically. Conclusions: The VAAT-predicted VT circuits and ablation lesions matched VT-exit sites predicted by the surface ECG-based PAVEL system. Combining these two complementary technologies may improve accuracy for non-invasively identifying optimal ablation targets to increase ablation efficacy.

Advances in cardiac magnetic resonance (CMR) techniques and image acquisition have made it an excellent tool in the assessment of atrial myopathy. Remolding of the left atrium is the mainstay of atrial fibrillation (AF) development and its progression. CMR can detect phasic atrial volumes, atrial function, and atrial fibrosis using cine, and contrast-enhanced or non-contrast-enhanced images. These abilities make CMR a versatile and extraordinary tool in management of patients with AF including for risk stratification, ablation prognostication and planning, and assessment of stroke risk. We review the latest advancements in utility of CMR in management of patients with AF.

Abnormalities on cardiac magnetic resonance imaging (CMR) and positron emission tomography (PET) predict ventricular arrhythmias (VA) in patients with cardiac sarcoidosis (CS). Little is known whether concurrent abnormalities on CMR and PET increases the risk of developing VA. Our aim was to compare the additive utility of CMR and PET in predicting VA in patients with CS. We included all patients treated at our institution from 2000 to 2018 who (1) had probable or definite CS and (2) had undergone both CMR and PET. The primary endpoint was VA at follow up, which was defined as sustained ventricular tachycardia, sudden cardiac death, or any appropriate device tachytherapy. Fifty patients were included, 88% of whom had a left ventricular ejection fraction >35%. During a mean follow-up 4.1 years, 7/50 (14%) patients had VA. The negative predictive value of LGE for VA was 100% and the negative predictive value of FDG for VA was 79%. Among groups, VA occurred in 4/21 (19%) subjects in the LGE+/FDG+ group, 3/14 (21%) in the LGE+/FDG- group, and 0/15 (0%) in the FDG+/LGE- group. There were no LGE-/FDG- patients. In conclusion, CMR may be the preferred initial clinical risk stratification tool in patients with CS. FDG uptake without LGE on initial imaging may not add additional prognostic information regarding VA risk.

Background: Characterizing myocardial conduction velocity (CV) in patients with ischemic cardiomyopathy (ICM) and ventricular tachycardia (VT) is important for understanding the patient-specific proarrhythmic substrate of VTs and therapeutic planning. The objective of this study is to accurately assess the relation between CV and myocardial fibrosis density on late gadolinium–enhanced cardiac magnetic resonance imaging (LGE-CMR) in patients with ICM. Methods: We enrolled 6 patients with ICM undergoing VT ablation and 5 with structurally normal left ventricles (controls) undergoing premature ventricular contraction or VT ablation. All patients underwent LGE-CMR and electroanatomic mapping (EAM) in sinus rhythm (2960 electroanatomic mapping points analyzed). We estimated CV from electroanatomic mapping local activation time using the triangulation method that provides an accurate estimate of CV as it accounts for the direction of wavefront propagation. We evaluated the association between LGE-CMR intensity and CV with multilevel linear mixed models. Results: Median CV in patients with ICM and controls was 0.41 m/s and 0.65 m/s, respectively. In patients with ICM, CV in areas with no visible fibrosis was 0.81 m/s (95% CI, 0.59–1.12 m/s). For each 25% increase in normalized LGE intensity, CV decreased by 1.34-fold (95% CI, 1.25–1.43). Dense scar areas have, on average, 1.97- to 2.66-fold slower CV compared with areas without dense scar. Ablation lesions that terminated VTs were localized in areas of slow conduction on CV maps. Conclusions: CV is inversely associated with LGE-CMR fibrosis density in patients with ICM. Noninvasive derivation of CV maps from LGE-CMR is feasible. Integration of noninvasive CV maps with electroanatomic mapping during substrate mapping has the potential to improve procedural planning and outcomes. Visual Overview: A visual overview is available for this article.

Background: Transition zones between healthy myocardium and scar form a spatially complex substrate that may give rise to reentrant ventricular arrhythmias (VAs). We sought to assess the utility of a novel machine learning approach for quantifying 3-dimensional spatial complexity of grayscale patterns on late gadolinium enhanced cardiac magnetic resonance images to predict VAs in patients with ischemic cardiomyopathy. Methods: One hundred twenty-two consecutive ischemic cardiomyopathy patients with left ventricular ejection fraction ≤35% without prior history of VAs underwent late gadolinium enhanced cardiac magnetic resonance images. From raw grayscale data, we generated graphs encoding the 3-dimensional geometry of the left ventricle. A novel technique, adapted to these graphs, assessed global regularity of signal intensity patterns using Fourier-like analysis and generated a substrate spatial complexity profile for each patient. A machine learning statistical algorithm was employed to discern which substrate spatial complexity profiles correlated with VA events (appropriate implantable cardioverter-defibrillator firings and arrhythmic sudden cardiac death) at 5 years of follow-up. From the statistical machine learning results, a complexity score ranging from 0 to 1 was calculated for each patient and tested using multivariable Cox regression models. Results: At 5 years of follow-up, 40 patients had VA events. The machine learning algorithm classified with 81% overall accuracy and correctly classified 86% of those without VAs. Overall negative predictive value was 91%. Average complexity score was significantly higher in patients with VA events versus those without (0.5±0.5 versus 0.1±0.2; P P =0.002). Conclusions: Substrate spatial complexity analysis of late gadolinium enhanced cardiac magnetic resonance images may be helpful in refining VA risk in patients with ischemic cardiomyopathy, particularly to identify low-risk patients who may not benefit from prophylactic implantable cardioverter-defibrillator therapy. Visual Overview: A visual overview is available for this article.

Background: Ablation is a widely used therapy for atrial fibrillation (AF); however, arrhythmia recurrence and repeat procedures are common. Studies examining surrogate markers of genetic susceptibility to AF, such as family history and individual AF susceptibility alleles, suggest these may be associated with recurrence outcomes. Accordingly, the aim of this study was to test the association between AF genetic susceptibility and recurrence after ablation using a comprehensive polygenic risk score for AF. Methods: Ten centers from the AF Genetics Consortium identified patients who had undergone de novo AF ablation. AF genetic susceptibility was measured using a previously described polygenic risk score (N=929 single-nucleotide polymorphisms) and tested for an association with clinical characteristics and time-to-recurrence with a 3 month blanking period. Recurrence was defined as >30 seconds of AF, atrial flutter, or atrial tachycardia. Multivariable analysis adjusted for age, sex, height, body mass index, persistent AF, hypertension, coronary disease, left atrial size, left ventricular ejection fraction, and year of ablation. Results: Four thousand two hundred seventy-six patients were eligible for analysis of baseline characteristics and 3259 for recurrence outcomes. The overall arrhythmia recurrence rate between 3 and 12 months was 44% (1443/3259). Patients with higher AF genetic susceptibility were younger ( P P =0.001). Persistent AF (hazard ratio [HR], 1.39 [95% CI, 1.22–1.58]; P P P =0.008) were associated with increased risk of recurrence. In univariate analysis, higher AF genetic susceptibility trended towards a higher risk of recurrence (HR, 1.08 [95% CI, 0.99–1.18]; P =0.07), which became less significant in multivariable analysis (HR, 1.06 [95% CI, 0.98–1.15]; P =0.13). Conclusions: Higher AF genetic susceptibility was associated with younger age and fewer clinical risk factors but not recurrence. Arrhythmia recurrence after AF ablation may represent a genetically different phenotype compared to AF susceptibility.

Objectives The aim of the current investigation is to examine whether use of high-frequency jet ventilation (HFJV) during pulmonary vein isolation (PVI) performed with force-sensing catheters is associated with improved outcomes. Background Catheter ablation is well established as therapy for symptomatic atrial fibrillation (AF). Reconnection following PVI is commonly observed during repeat ablation procedures. Technologies that may optimize catheter stability and lesion delivery include both force-sensing ablation catheters and HFJV. Methods Patients undergoing PVI at Johns Hopkins Hospital were prospectively enrolled in a registry. The study compared procedural characteristics, adverse event rates, and 1-year procedural outcomes in patients undergoing PVI supported either by standard ventilation or HFJV. Patient and procedural aspects were otherwise constant. Results Eighty-four HFJV patients and 84 matched control patients with 1-year outcome data were identified. Atrial arrhythmia recurrence occurred in 26 of 84 HFJV patients (31%) and 42 of 84 control patients (50%; p = 0.019). In patients with paroxysmal AF, arrhythmia recurrence in HFJV and control patients was 27.3% and 47.3%, respectively (p = 0.045). In patients with persistent AF, arrhythmia recurrence rates were not significantly different (37.9% in HFJV patients, 55.2% in control patients; p = 0.184). On multivariate analysis, HFJV was independently associated with improved freedom from arrhythmia recurrence. Vasopressor use during HFJV cases was significantly higher than during standard ventilation (79.7% vs. 22.4%; p = 0.001). Indices of catheter stability and contact force adequacy were significantly higher in the HFJV patients than in control patients. Complication rates in the 2 groups were similarly low. Conclusions Use of HFJV in patients undergoing PVI with radiofrequency force-sensing catheters is associated with improved outcomes, without appreciable increase in adverse procedural events.

BACKGROUND Pacemaker patients experience battery depletion that activates pacemaker's alert for replacement notification. Automatic reprogramming at replacement notification can result in loss of rate response and atrioventricular (AV) synchrony. OBJECTIVE To determine if relevant symptoms or clinical events may be associated with automatic reprogramming at replacement notification. METHODS Electronic medical record review was undertaken for 298 patients referred for pacemaker generator replacement. Primary endpoints were symptoms or clinical events during replacement notification period. RESULTS Following elimination of duplicate pacemaker replacements (n = 12), "near-replacement notification" or "recalled" (n = 15) and pacemakers at "end of life" (n = 5), 266 subjects were included. Three distinct reprogramming cohorts were identified; those with no change (control) in pacing mode (n = 46), those with loss of rate response (n = 154), and those with loss of AV synchrony ± rate response (n = 66). In total, 83 subjects (31.2%) had symptoms with significant differences seen between groups (control = 4.3%, loss of rate response = 26.0%, loss of AV synchrony ± rate response = 62.1%, P

Background Patients go without pacemaker, defibrillator, and cardiac resynchronization therapies (devices) each year due to the prohibitive costs of devices. Objective We sought to examine data available from studies regarding contemporary risks of reused devices in comparison with new devices. Methods We searched online indexing sites to identify recent studies. Peer-reviewed manuscripts reporting infection, malfunction, premature battery depletion, and device-related death with reused devices were included. The primary study outcome was the composite risk of infection, malfunction, premature battery depletion, and death. Secondary outcomes were the individual risks. Results Nine observational studies (published 2009-2017) were identified totaling 2,302 devices (2,017 pacemakers, 285 defibrillators). Five controlled trials were included in meta-analysis (2,114 devices; 1,258 new vs 856 reused). All device reuse protocols employed interrogation to confirm longevity and functionality, disinfectant therapy, and, usually, additional biocidal agents, packaging, and ethylene oxide gas sterilization. Demographic characteristics, indications for pacing, and median follow-up were similar. There were no device-related deaths reported and no statistically significant difference in risk between new versus reused devices for the primary outcome (2.23% vs 3.86% respectively, P = 0.807, odds ratio = 0.76). There were no significant differences seen in the secondary outcomes for the individual risks of infection, malfunction, and premature battery depletion. Conclusions Device reuse utilizing modern protocols did not significantly increase risk of infection, malfunction, premature battery depletion, or device-related death in observational studies. These data provide rationale for proceeding with a prospective multicenter noninferiority randomized control trial.

The P-wave terminal force in lead V1 (PTFV1) on the 12-lead electrocardiogram (ECG) quantifies left atrial (LA) structural and electrophysiologic abnormalities. We aimed to evaluate the association between PTFV1 and cerebrovascular accident (CVA) as well as LA structure and function in patients with atrial fibrillation (AF). We conducted a cross-sectional study of 229 patients with AF (60 ± 10years, 72% men) with (n = 21) and without (n = 208) a history of CVA, who underwent preablation ECG and cardiac magnetic resonance in sinus rhythm. PTFV1 was defined as the duration (in milliseconds) of the downward deflection of the P wave in lead V1 multiplied by the absolute value of its amplitude (in microvolts) on ECG. PTFV1 is associated with LA minimum volume (Vmin) and left ventricular ejection fraction but not associated with the extent of LA fibrosis quantified by cardiac magnetic resonance late gadolinium enhancement. In addition, PTFV1 is associated with CVA independent of the CHA2DS2-VASc score and LA Vmin (odds ratio 1.23; 95% confidence interval 1.08 to 1.40; p = 0.002). Furthermore, PTFV1 has an incremental value over the CHA2DS2-VASc score as a marker of CVA (p

BACKGROUND Implantable defibrillators (ICD) are an important therapy for arrhythmogenic right ventricular cardiomyopathy (ARVC) patients at high risk of sudden death. Given the high appropriate ICD therapy rate, some have argued that the mere act of implanting an ICD inflates the malignant arrhythmia rate in ARVC. OBJECTIVE To report the arrhythmic course of ARVC patients without ICDs at the fulfillment of the 2010 Task Force Criteria and explore predictors of malignant ventricular arrhythmias. METHODS We included 131 definite ARVC patients (age 32 ± 15 years, male 39%, proband 50%) either without ICDs (N = 47) or receiving an ICD at least 6 months after the fulfillment of the diagnostic criteria. The primary outcome was a composite of cardiac arrest (both resuscitated successfully and unsuccessfully) and sustained ventricular tachyarrhythmias (cycle length

AIMS Prior studies identified a relationship between epicardial bipolar and endocardial unipolar voltage. Whether the relationship is valid with smaller multielectrode mapping catheters has not been reported. We explored the association of right ventricular (RV) endocardial unipolar voltage mapping with epicardial bipolar voltage mapping using a multielectrode mapping catheter. METHODS Electrograms from patients who underwent multielectrode endocardial and epicardial RV electroanatomical mapping during ablation procedures were analyzed. Each endocardial mapping point was matched to the corresponding nearest epicardial point. The correlation between unipolar endocardial voltage and epicardial bipolar voltage was determined. The optimal unipolar threshold to detect epicardial low voltage (

Objectives The aim of this study was to examine atrial fibrillation (AF) substrate using different modalities (point-by-point [PBP], fast anatomic mapping [FAM], and late gadolinium enhancement [LGE] magnetic resonance imaging [MRI] mapping) in patients presenting for AF ablation. Background Bipolar voltage mapping, as part of AF ablation, is traditionally performed in a PBP approach using single-tip ablation catheters. Alternative techniques for fibrosis delineation include FAM with multi-electrode circular catheters and LGE MRI. The correlation between PBP, FAM, and LGE-MRI fibrosis assessment is unknown. Methods LGE MRI was performed pre-ablation in 26 patients (73% men, mean age 63 ± 8 years). Local image intensity ratio (IIR) was used to normalize myocardial intensities. PBP and FAM voltage maps were acquired, in sinus rhythm, prior to ablation and coregistered with LGE MRI. Results The mean bipolar voltage for all 19,087 FAM voltage points was 0.88 ± 1.27 mV, and the average IIR was 1.08 ± 0.18. In an adjusted mixed-effects model, each unit increase in local IIR was associated with a 57% decrease in bipolar voltage (p 0.74 corresponded to a bipolar voltage Conclusions LGE-MRI, FAM, and PBP mapping showed good correlation in delineating electroanatomic AF substrate. Each approach has fundamental technical characteristics, the awareness of which allows proper assessment of atrial fibrosis.

All contemporary pacemakers undergo automatic reprogramming upon reaching elective replacement indication due to battery depletion. The majority of such reprogramming will result in changes to both pacing mode and pacing rate. The exact software reprogramming varies considerably among pacemaker manufacturers and may even vary among models of the same manufacturer. Accordingly, it is essential for healthcare providers managing pacemaker patients to have a detailed understanding of the automatic reprogramming seen at elective replacement indication as well as their potential physiological and clinical consequences.

Many cardiac interventional procedures (e.g., radiofrequency ablation) require fluoroscopy to navigate catheters in veins toward the heart. However, this image guidance method lacks depth information and increases the risks of radiation exposure for both patients and operators. To overcome these challenges, we developed a robotic visual servoing system that maintains visualization of segmented photoacoustic signals from a cardiac catheter tip. This system was tested in two in vivo cardiac catheterization procedures with ground truth position information provided by fluoroscopy and electromagnetic tracking. The 1D root mean square localization errors within the vein ranged 1.63 − 2.28 mm for the first experiment and 0.25 − 1.18 mm for the second experiment. The 3D root mean square localization error for the second experiment ranged 1.24 − 1.54 mm. The mean contrast of photoacoustic signals from the catheter tip ranged 29.8 − 48.8 dB when the catheter tip was visualized in the heart. Results indicate that robotic-photoacoustic imaging has promising potential as an alternative to fluoroscopic guidance. This alternative is advantageous because it provides depth information for cardiac interventions and enables enhanced visualization of the catheter tips within the beating heart.

BACKGROUND Pacemaker battery depletion triggers alert for replacement notification and results in automatic reprogramming, which has been shown to be associated with relevant cardiorespiratory symptoms and adverse clinical events. OBJECTIVE Determine if electrocardiogram (ECG) pacing features may be predictive of pacemaker battery depletion and clinical risk. METHODS This is an ECG substudy of a cohort analysis of 298 subjects referred for pacemaker generator replacement from 2006 to 2017. Electronic medical record review was performed; clinical, ECG, and pacemaker characteristics were abstracted. We applied two ECG prediction rules for pacemaker battery depletion that are relevant to all major pacemaker manufacturers except Boston Scientific and MicroPort: (1) atrial pacing not at a multiple of 10 and (2) nonsynchronous ventricular pacing not at a multiple of 10, to determine diagnostic sensitivity, specificity, and risk in applicable ECG subjects. RESULTS We excluded 32 subjects not at replacement notification or duplicate surgeries. Overall, 176 of 266 subjects (66.2%) demonstrated atrial pacing or nonsynchronous ventricular pacing on preoperative ECG. When utilizing both rules, 139 of 176 preoperative ECGs and 12 of 163 postoperative ECGs met criteria for battery depletion yielding reasonable sensitivity (79.0%), high specificity (92.6%), and a positive likelihood ratio of 11.6:1. These rules were associated with significant increase in cardiorespiratory symptoms (P

BACKGROUND Patients with cardiac sarcoidosis (CS) may present with arrhythmic events (AE): atrioventricular block (AVB) and/ or ventricular arrhythmias (VA). We sought to: (a) use regional analysis of cardiac magnetic resonance imaging (CMR) to describe anatomic and functional phenotypes of patients with CS and AE; (b) Assess the association of regional CMR abnormalities with the combined endpoint of death, heart transplantation (HT) and AE; and (c) use machine learning (ML) to predict the combined endpoint based on CMR features. METHODS we included 76 patients with CS and CMR. We analyzed cine images to determine regional longitudinal (LS) and radial strain (RS); and late gadolinium enhancement imaging to determine regional scar burden (%scar). RESULTS Patients with AVB (n = 7), compared with those without, had higher %scar in the anterior (21.8 ± 27.4 vs 5.1 ± 8.9; P = 0.0005) and anteroseptal (19.3 ± 24.5 vs 3.5 ± 5.5; P

Ventricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients with myocardial infarction. Catheter-based radiofrequency ablation of cardiac tissue has achieved only modest efficacy, owing to the inaccurate identification of ablation targets by current electrical mapping techniques, which can lead to extensive lesions and to a prolonged, poorly tolerated procedure. Here we show that personalized virtual-heart technology based on cardiac imaging and computational modelling can identify optimal infarct-related VT ablation targets in retrospective animal (5 swine) and human studies (21 patients) and in a prospective feasibility study (5 patients). We first assessed in retrospective studies (one of which included a proportion of clinical images with artifacts) the capability of the technology to determine the minimum-size ablation targets for eradicating all VTs. In the prospective study, VT sites predicted by the technology were targeted directly, without relying on prior electrical mapping. The approach could improve infarct-related VT ablation guidance, where accurate identification of patient-specific optimal targets could be achieved on a personalized virtual heart prior to the clinical procedure.