Background: Spontaneous nonsustained ventricular tachycardia (NSVT) on Holter, VT inducibility during electrophysiology study, and late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) have been associated with sustained ventricular arrhythmias (SVAs) in nonischemic dilated cardiomyopathy (DCM). This study aimed to analyze whether these parameters carry independent prognostic value for spontaneous SVA in DCM. Methods: Between 2011 and 2018, patients with the DCM clinical spectrum and documented SVA, suspected SVA, or considered to be at intermediate or high risk for SVA were enrolled in the prospective Leiden Nonischemic Cardiomyopathy Study. Patients underwent a comprehensive evaluation including 24-hour Holter, LGE-CMR, and electrophysiology study. Holters were assessed for the presence of NSVT (≥3 beats; rate, ≥120 bpm; lasting <30 s) and NSVT characteristics (coupling interval, duration, cycle length, morphology, regularity). Patients were followed at 6 to 12 monthly intervals. Results: Of all 115 patients (age, 59±12 years; 77% men; left ventricular ejection fraction, 33±13%; history of SVA, 36%; LGE in 63%; median LGE mass, 13 g; interquartile range, 8–23 g), 62 (54%) had NSVT on Holter, and sustained monomorphic VT was inducible in 34 of 114 patients (30%). NSVT was not associated with LGE on CMR or VT inducibility during electrophysiology study nor were its features (all P >0.05). During 4.0±1.8 years of follow-up, SVA occurred in 39 patients (34%). NSVT (HR, 4.47 [95% CI, 1.87–10.72]; P =0.001) and VT inducibility (HR, 3.08 [95% CI, 1.08–8.81]; P =0.036) were independently associated with SVA during follow-up. A bivariable model including only noninvasively acquired parameters also allowed identification of a high-risk subgroup (ie, those with both NSVT and LGE on CMR). The findings remained similar when only patients without prior SVA were included. Conclusions: In patients with DCM, NSVT on Holter and VT inducibility during electrophysiology study predict SVA during follow-up independent of LGE on CMR. NSVTs may serve as an initiator, and sustained VT inducibility indicates the presence of the substrate for SVA in DCM. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01940081.
Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): The department of cardiology from Leiden University Medical Center receives unrestricted grants from Edwards Lifesciences, Biotronik, Medtronik, Boston Scientific and BioSense Webster. MS was supported by the Research Fellowship of the European Society of Cardiology 2017/2018. Background Cardiac sarcoidosis (CS) with right ventricular (RV) involvement may mimic ARVC. Histopathological differences may result in disease specific RV activation patterns, detectable on the 12-lead electrocardiogram (ECG). Scar in ARVC progresses from epicardium to endocardium and may lead to delayed activation of areas with reduced voltages, translating into terminal activation delay and occasionally an (epsilon) wave with small amplitude on the ECG. On the contrary, patchy transmural RV scar in CS may lead to conduction block, and therefore late activated areas with preserved voltages, reflected as preserved R’-waves in the right precordial leads. Purpose To determine whether the terminal activation patterns in precordial leads V1-V3 distinguish CS with RV involvement from ARVC. Methods This is a multicenter retrospective study including patients with either 1) CS with RV involvement or 2) gene-positive ARVC referred for VT ablation. A non-ventricular paced 12-lead surface ECG prior to ablation was obtained (25mm/s and 10mm/mV). For detailed analysis, Leiden ECG Analysis and Decomposition Software (LEADS) was used. After detection of QRST complexes in the spatial velocity signal, LEADS generates a representative and low-noise averaged beat. Then, measurements per lead were performed using the measurement tool in Adobe Pro DC. Based on the hypothesis that conduction block in CS will lead to late activated areas with preserved voltages, we measured the surface area (SA) of the R’-wave in V1-V3. An R’-wave was defined as any positive deflection from baseline after an S-wave. Results 13 CS patients with RV involvement (54 ± 8years, 62% male) and 23 ARVC patients (37 ± 15years, 78% male) were included. A R’-wave in V1-V3 was present in all CS patients, compared to 11 (48%) of ARVC patients (p = 0.002). The maximum R’-wave SA in lead V1-V3 was 3.55 (IQR:2.18-5.81) mm2 in CS vs. 0.00 (IQR:0.00-0.43) mm2 in ARVC (p < 0.001; Figure A). By ROC-analysis, the maximum R’-wave SA in lead V1-V3 was an excellent discriminator (area under the curve 0.980 [95%CI: 0.945-1.000]). A cutoff of ≥1.65mm2 had a sensitivity of 85% and specificity of 96% for diagnosing CS. An algorithm was created including the presence of an R’-wave in V1-V3 and the SA of this R’-wave (Figure B). This was validated in a second cohort (18 CS and 40 ARVC) with 72% sensitivity and 88% specificity. Conclusion Transmural RV scars in CS may cause localized conduction block, leading to late activated areas with preserved voltages, reflected as large R’-wave on the 12-lead surface ECG. An easily applicable algorithm including the surface area of the largest R’-wave in lead V1-V3 ≥1.65mm2 distinguishes CS from ARVC with good sensitivity and specificity. The QRS terminal activation in precordial leads V1-V2 may reflect disease specific scar patterns (for examples: Figure C). Abstract Figure
Cardiac sarcoidosis (CS) with right ventricular (RV) involvement can mimic arrhythmogenic right ventricular cardiomyopathy (ARVC). Histopathological differences may result in disease-specific RV activation patterns detectable on the 12-lead electrocardiogram. Dominant subepicardial scar in ARVC leads to delayed activation of areas with reduced voltages, translating into terminal activation delay and occasionally (epsilon) waves with a small amplitude. Conversely, patchy transmural RV scar in CS may lead to conduction block and therefore late activated areas with preserved voltages reflected as preserved R' waves.The purpose of this study was to evaluate the distinct terminal activation patterns in precordial leads V1 through V3 as a discriminator between CS and ARVC.Thirteen patients with CS affecting the RV and 23 patients with gene-positive ARVC referred for ventricular tachycardia ablation were retrospectively included in a multicenter approach. A non-ventricular-paced 12-lead surface electrocardiogram was analyzed for the presence and the surface area of the R' wave (any positive deflection from baseline after an S wave) in leads V1 through V3.An R' wave in leads V1 through V3 was present in all patients with CS compared to 11 (48%) patients with ARVC (P = .002). An algorithm including a PR interval of ≥220 ms, the presence of an R' wave, and the surface area of the maximum R' wave in leads V1 through V3 of ≥1.65 mm2 had 85% sensitivity and 96% specificity for diagnosing CS, validated in a second cohort (18 CS and 40 ARVC) with 83% sensitivity and 88% specificity.An easily applicable algorithm including PR prolongation and the surface area of the maximum R' wave in leads V1 through V3 of ≥1.65 mm2 distinguishes CS from ARVC. This QRS terminal activation in precordial leads V1 through V3 may reflect disease-specific scar patterns.
Background: Fragmented QRS (fQRS) has been associated with cardiac death and ventricular arrhythmias in patients (pts) with myocardial infarction. However, the clinical impact of fQRS on recurrent ventricular tachycardia (VT) and cardiac death after radiofrequency catheter ablation (RFCA) in post-infarct pts is unknown. Method: We retrospectively included 160 pts (68 ± 9 years; 138 men; left ventricular ejection fraction 33 ± 12%) who underwent RFCA of post-infarct VT from 2009 to 2015. Pre-procedural 12 lead ECGs were evaluated for fQRS defined as RSR' patterns (>1 R' or notching of R or S wave) in pts with a narrow QRS complex and >2 notches of R or S wave in pts with wide QRS complex, present in ≥2 contiguous leads. The primary endpoint was freedom from any VT recurrence and cardiac death after RFCA. Result: Among 160 pts, fQRS was present in 37 (23%) pts; anterior leads in 20 pts, lateral in 9 pts, inferior in 19 pts. Pts were inducible for 3 (interquartile range [IQR] 2–5) VTs. Procedural success (non-inducibility of any VT) was achieved in 74 pts. During follow-up of 17 (IQR 9–24) months, 44 (34%) pts experienced the primary end point. The presence of fQRS was associated with an increased risk of VT recurrence and cardiac death (P = 0.006 by log-rank test). The significant difference was driven by VT recurrence (p = 0.002) but not by cardiac death (p = 0.361). Considering specific locations only fQRS in anterior leads was associated with the primary endpoint (p = 0.005); not in inferior and lateral leads (p = 0.145 and p = 0.84, respectively). A multivariable Cox regression analysis revealed that the presence of fQRS (hazard ratio [HR] 2.27; 95% CI 1.23–4.21; p = 0.009), left ventricular ejection fraction less than 30% (HR 2.36; 95% CI 1.24–4.48; p = 0.009), and number of induced VT during RFCA (HR 1.25; 95% CI 1.12–1.39; p < 0.001) were independent predictors for the endpoint. Conclusion: An fQRS predicts VT recurrence and cardiac death after RFCA of post-infarct VT.
Purpose: This study aimed to analyze the effect of focal myocardial fibrosis, assessed by late gadolinium enhancement MRI (LGE-MRI), on the occurrence and type of ventricular arrhythmia in patients with nonischemic dilated cardiomyopathy (NIDCM). Methods: We included consecutive patients with NIDCM who underwent LGE-MRI before implantable cardioverter-defibrillator (ICD) implantation at two centers. LGE was defined by signal intensity ≥35% of maximal signal intensity and subdivided into core and border zone (≥50% and 35-50% of maximal signal intensity, respectively), and according to (non)basal location and transmurality. ICD recordings and 12-lead ECGs were reviewed to determine the occurrence and type of ventricular arrhythmia during follow-up. Results: Of all 87 patients (62% male, age 56±13 years, LVEF 29±12%), 55 patients (63%) had LGE (median 6.3g, IQR 0.0-13.8g). During a median follow-up of 45 months (interquartile range, 23-67), monomorphic VT occurred in 18 (21%) patients, and polymorphic VT/VF in 10 (11%). LGE predicted monomorphic VT (Log-rank, p<0.001), but not polymorphic VT/VF (Log-rank, p=0.40). The optimal cut-off value for LGE to predict monomorphic VT was 7.2 grams (area under curve 0.84). Features associated with high risk for monomorphic VT were core extent, location in basal segments and area with 51-75% transmurality. Conclusion: Focal fibrosis assessed by LGE-MRI predicts monomorphic VT, but not polymorphic VT/VF. The risk for monomorphic VT was particularly high when the LGE extent was ≥7.2 grams. The differences in underlying substrate and associated types of arrhythmia may have important implications for risk stratification and therapeutic interventions in patients with NIDCM.
Abstract Background The underlying substrates and mechanisms of non-sustained ventricular tachycardia (NSVT) in nonischemic dilated cardiomyopathy (DCM) are unclear and may be different than those of sustained VT. Purpose To characterize NSVT in DCM and analyze its association with late gadolinium enhancement (LGE) on CMR, inducibility of sustained VT during EP study, and ventricular arrhythmias during follow-up. Methods In the prospective Leiden Nonischemic Cardiomyopathy Study (ClinicalTrials.gov Identifier: NCT01940081) patients with DCM underwent a comprehensive evaluation. For the present study, 24h-Holters were assessed for the presence of NSVT (defined as ≥3 consecutive beats arising below the atrioventricular node with a rate ≥120 bpm and lasting <30 s) and its features (number of episodes, rate, rate variability >10%, duration, coupling interval and morphology). CMRs were assessed for the presence of LGE and EP studies for inducibility of sustained monomorphic VT. Patients were followed and ICDs were programmed with therapy >188-200 bpm or adjusted to clinically documented VT. Results Of all 148 patients, 95 underwent a 24-hour Holter at the Leiden University Medical Center and were included in the present study (age 59 ± 13 years, 76% male, history of sustained VT in 26 [27%], out-of-hospital cardiac arrest in 7 [9%]). NSVT was observed during Holter in 52 patients (55%) and was typically short (median 4 beats, IQR 3-5 beats), relatively slow (median 144 bpm, IQR 134-156 bpm), irregular (median 67%, IQR 43-100% of all episodes per patient) and monomorphic (median 87%, IQR 12-100%). NSVT was not associated with LGE on CMR (p = 0.49) or VT inducibility during EP study (p = 0.96), nor were its features (all p > 0.05). During 4.0 ± 1.7 years follow-up, sustained VT occurred in 25 patients (26%), polymorphic VT/VF in 8 (8%), and any sustained ventricular arrhythmia in 30 (32%). NSVT was associated with a higher rate of sustained VT during follow-up (HR 5.45, p = 0.002) and any sustained ventricular arrhythmia (HR 4.17, p = 0.002), but not with polymorphic VT/VF (p = 0.69). Similarly, inducibility of sustained VT during EP study was also associated with sustained VT during follow-up (HR 5.78, p < 0.001) and any sustained ventricular arrhythmia (HR 4.88, p < 0.001), but not with polymorphic VT/VF (p = 0.13). The findings remained similar when only primary prevention patients were included. In multivariate analysis, NSVT on Holter and inducibility of sustained VT during EP study both remained independently associated with sustained VT and any sustained ventricular arrhythmia during follow-up (all p ≤ 0.001), but not with polymorphic VT/VF. Conclusion In DCM, NSVT on Holter and inducible sustained VT during EP study are not directly interrelated, but both predict the occurrence of sustained VT during follow-up. These data suggest that non-sustained and sustained VT may have different underlying mechanisms and provide complementary information in DCM. Abstract Figure. Sustained VT during follow-up
Noninducibility is frequently used as procedural end point of ventricular tachycardia (VT) ablation after myocardial infarction. We investigated the influence of left ventricular (LV) function on the predictive value of noninducibility for VT recurrence and cardiac mortality.Ninety-one patients (82 men, 67±10 years) with post-myocardial infarction VT underwent ablation between 2009 and 2012. Fifty-nine (65%) had an LV ejection fraction (EF) >30% (mean 41±7) and 32 (35%) an LVEF≤30% (mean 20±5). Thirty patients (51%) with EF>30% and 13 (41%) with EF≤30% were noninducible after ablation (P=0.386). During a median follow-up of 23 (Q1-Q3 16-36) months, 35 patients (38%) experienced VT recurrences and 17 (18%) cardiac death. At 1 year follow-up, survival free from VT recurrence and cardiac death for patients with LVEF>30% was 80% (95% confidence interval [CI], 70-90) compared with 42% (95% CI, 33-51) for those with LVEF≤30% (P=0.001). Noninducible patients with LVEF>30% had a recurrence-free survival from cardiac death of 90% (95% CI, 71-100) compared with 65% (95% CI, 47-83) for inducible patients (P=0.015). In the subgroup of patients with LVEF≤30%, the survival free from VT recurrence and cardiac death was 31% (95% CI, 0%-60%) for noninducible compared with 39% (95% CI, 27-52) for those who remained inducible (P=0.842).Noninducible patients with moderately depressed LV function have a favorable outcome compared with patients who remained inducible after ablation. On the contrary, patients with severely depressed LV function have a poor prognosis independent of the acute procedural outcome.
Introduction: Unipolar endocardial voltage (UEV) at sites with normal bipolar endocardial voltage (BEV) may accurately detect epicardial scar. Currently applied UEV cut-off values for epicardial scar are based on studies that did not correct for the highly variable epicardial fat layer attenuating BV. Method: Consecutive patient who underwent combined endo/epicardial RV electroanatomical mapping (EAM) with integration of CT-derived fat mesh between 2006 and 2015 were included. Epicardial and pericardial contours were semi-automatically traced on short axis views for fat thickness (FT). After EAM epicardial points were exported and superimposed on the corresponding short-axis CT slice to evaluate local FT. 3D coordinates of each point were exported to Matlab and endocardial and epicardial points were linked based on shortest distance. For analysis point pairs with BEV >1.5mV and ≤1mm FT were selected. Receiver operating characteristics curve analysis was performed to determine the optimal cut-off value, for endocardial UV to detect epicardial low BV. Results: Of the 30 pts included (50 ± 15 years, 77% male 23, BMI 25 ± 4 kg/m2), 15 had definite ARVC, 13/15 a pathogenic mutation, 2 borderline ARVC, 3 cardiac sarcoidosis, 1 scar of unknown origin, 8 subepicardial RVOT scar in endurance athletes, and 1 myocarditis. The median FT was 2.9 mm (IQR 1.6 – 5.3 mm). A total of 6750 endocardial points was coupled to the closest epicardial points and 3997 (60%) point pairs had a distance <10mm when corrected for FT. Of these, a total of 351 (5%) point pairs were selected (BEV >1.5mm, FT ≤ 1mm). For endocardial UV, the optimal cut-off value to detect areas with epicardial BV < 1.5mV was 3.92mV (AUC 0.73; sensitivity 0.58, specificity 0.79).This cut- off was more specific for epicardial scar than the previously proposed 4.4mV and 5.5mV (specificity 0.72 and 0.54, respectively). Conclusion: This is the first study to propose an endocardial UV cut off of 3.92mV to detect epicardial scar using CT image integration to correct for epicardial fat thickness. Prior proposed cut-off values overestimate the epicardial scar.
