Dispersion in ventricular repolarization in the human, canine and porcine heart

Dispersion in repolarization is important for the genesis of the T wave, and for the induction of reentrant arrhtyhmias. Because the T wave differs across species our intent here is to review the epicardial, endocardial and transmural repolarization patterns contributing to repolarization in whole hearts from man, dog and pig. The major points we emphasize are: transmural repolarization time gradients are small and are directed from endocardium (early) to epicardium (late) in dog and human and from epicardium to endocardium in pig; the right ventricle tends to repolarize before the left ventricle and this difference is larger in dog than in pig; a negative relation between the activation times and the repolarization times is rare in man, and absent in dog and pig. Given the above, a large dispersion in repolarization between two myocardial areas does not lead to arrhythmias without a premature beat. Moreover, an arrhythmic substrate can be identified by a metric composed of activation times and repolarization times, the reentry vulnerability index, RVI.

Evaluation of the reentry vulnerability index to predict ventricular tachycardia circuits using high-density contact mapping

Background

Identifying arrhythmogenic sites to improve ventricular tachycardia (VT) ablation outcomes remains unresolved. The reentry vulnerability index (RVI) combines activation and repolarization timings to identify sites critical for reentrant arrhythmia initiation without inducing VT.

Objective

The purpose of this study was to provide the first assessment of RVI’s capability to identify VT sites of origin using high-density contact mapping and comparison with other activation-repolarization markers of functional substrate.

Methods

Eighteen VT ablation patients (16 male; 72% ischemic) were studied. Unipolar electrograms were recorded during ventricular pacing and analyzed offline. Activation time (AT), activation–recovery interval (ARI), and repolarization time (RT) were measured. Vulnerability to reentry was mapped based on RVI and spatial distribution of AT, ARI, and RT. The distance from sites identified as vulnerable to reentry to the VT site of origin was measured, with distances <10 mm and >20 mm indicating accurate and inaccurate localization, respectively.

Results

The origins of 18 VTs (6 entrainment, 12 pace-mapping) were identified. RVI maps included 1012 (408–2098) (median, 1st–3rd quartiles) points per patient. RVI accurately localized 72.2% VT sites of origin, with median distance of 5.1 (3.2–10.1) mm. Inaccurate localization was significantly less frequent for RVI than AT (5.6% vs 33.3%; odds ratio 0.12; P = .035). Compared to RVI, distance to VT sites of origin was significantly larger for sites showing prolonged RT and ARI and were nonsignificantly larger for sites showing highest AT and ARI gradients.

Conclusion

RVI identifies vulnerable regions closest to VT sites of origin. Activation-repolarization metrics may improve VT substrate delineation and inform novel ablation strategies.

Effects of genetic background, sex, and age on murine atrial electrophysiology

AIMS

Genetically altered mice are powerful models to investigate mechanisms of atrial arrhythmias, but normal ranges for murine atrial electrophysiology have not been robustly characterized.

METHODS AND RESULTS

We analyzed results from 221 electrophysiological (EP) studies in isolated, Langendorff-perfused hearts of wildtype mice (114 female, 107 male) from 2.5 to 17.7 months (mean 7 months) with different genetic backgrounds (C57BL/6, FVB/N, MF1, 129/Sv, Swiss agouti). Left atrial monophasic action potential duration (LA-APD), interatrial activation time (IA-AT), and atrial effective refractory period (ERP) were summarized at different pacing cycle lengths (PCLs). Factors influencing atrial electrophysiology including genetic background, sex, and age were determined. LA-APD70 was 18 ± 0.5 ms, atrial ERP was 27 ± 0.8 ms, and IA-AT was 17 ± 0.5 ms at 100 ms PCL. LA-APD was longer with longer PCL (+17% from 80 to 120 ms PCL for APD70), while IA-AT decreased (-7% from 80 to 120 ms PCL). Female sex was associated with longer ERP (+14% vs. males). Genetic background influenced atrial electrophysiology: LA-APD70 (-20% vs. average) and atrial ERP (-25% vs. average) were shorter in Swiss agouti background compared to others. LA-APD70 (+25% vs. average) and IA-AT (+44% vs. average) were longer in 129/Sv mice. Atrial ERP was longer in FVB/N (+34% vs. average) and in younger experimental groups below 6 months of age.

CONCLUSION

This work defines normal ranges for murine atrial EP parameters. Genetic background has a profound effect on these parameters, at least of the magnitude as those of sex and age. These results can inform the experimental design and interpretation of murine atrial electrophysiology.

Electromechanical factors associated with favourable outcome in cardiac resynchronization therapy

AIMS

Electromechanical coupling in patients receiving cardiac resynchronization therapy (CRT) is not fully understood. Our aim was to determine the best combination of electrical and mechanical substrates associated with effective CRT.

METHODS AND RESULTS

Sixty-two patients were prospectively enrolled from two centres. Patients underwent 12-lead electrocardiogram (ECG), cardiovascular magnetic resonance (CMR), echocardiography, and anatomo-electromechanical mapping (AEMM). Remodelling was measured as the end-systolic volume (ΔESV) decrease at 6 months. CRT was defined effective with ΔESV ≤ -15%. QRS duration (QRSd) was measured from ECG. Area strain was obtained from AEMM and used to derive systolic stretch index (SSI) and total left-ventricular mechanical time. Total left-ventricular activation time (TLVAT) and transeptal time (TST) were derived from AEMM and ECG. Scar was measured from CMR. Significant correlations were observed between ΔESV and TST [rho = 0.42; responder: 50 (20-58) vs. non-responder: 33 (8-44) ms], TLVAT [-0.68; 81 (73-97) vs. 112 (96-127) ms], scar [-0.27; 0.0 (0.0-1.2) vs. 8.7 (0.0-19.1)%], and SSI [0.41; 10.7 (7.1-16.8) vs. 4.2 (2.9-5.5)], but not QRSd [-0.13; 155 (140-176) vs. 167 (155-177) ms]. TLVAT and SSI were highly accurate in identifying CRT response [area under the curve (AUC) > 0.80], followed by scar (AUC > 0.70). Total left-ventricular activation time (odds ratio = 0.91), scar (0.94), and SSI (1.29) were independent factors associated with effective CRT. Subjects with SSI >7.9% and TLVAT <91 ms all responded to CRT with a median ΔESV ≈ -50%, while low SSI and prolonged TLVAT were more common in non-responders (ΔESV ≈ -5%).

CONCLUSION

Electromechanical measurements are better associated with CRT response than conventional ECG variables. The absence of scar combined with high SSI and low TLVAT ensures effectiveness of CRT.

Spatiotemporal approximation of cardiac activation and recovery isochrones

BACKGROUND

The sequence of myocardial activation and recovery can be studied in detail by invasive catheter recordings of cardiac electrograms (EGMs), or noninvasive inverse reconstructions thereof with electrocardiographic imaging (ECGI). Local activation and recovery times are obtained from a unipolar EGM by the moment of maximum downslope of the QRS complex or maximum upslope of the T wave, respectively. However, both invasive and noninvasive recordings of intracardiac EGMs may suffer from noise and fractionation, making reliable detection of these deflections nontrivial.

METHODS

Here, we introduce a novel method that benefits from the spatial coupling of these processes, and incorporate not only the temporal EGM deflection, but also the spatial gradients. We validated this approach in computer simulations, in animal data with ECGI and invasive electrode recordings, and illustrated its use in a clinical case.

RESULTS

In the simulated data, the spatiotemporal approach was able to incorporate spatial information to better select the correct deflection in artificially fractionated EGMs and outperformed the traditional temporal-only method. In experimental data, the accuracy of time estimation from ECGI compared to invasive recordings significantly increased from R = 0.73 (activation) and R = 0.58 (recovery) with the temporal-only method to R = 0.79 (activation) and R = 0.72 (recovery) with the novel approach. Localization of the pacing origin of paced beats improved significantly from 36 mm mean error with the temporal-only approach to 23 mm with the spatiotemporal approach.

CONCLUSION

The spatiotemporal method to compute activation and recovery times from EGMs outperformed the traditional temporal-only approach in which spatial information was not taken into account.

Uniqueness of local myocardial strain patterns with respect to activation time and contractility of the failing heart: a computational study

Background

Myocardial deformation measured by strain is used to detect electro-mechanical abnormalities in cardiac tissue. Estimation of myocardial properties from regional strain patterns when multiple pathologies are present is therefore a promising application of computer modelling. However, if different tissue properties lead to indistinguishable strain patterns (‘degeneracy’), the applicability of any such method will be limited. We investigated whether estimation of local activation time (AT) and contractility from myocardial strain patterns is theoretically possible.

Methods

For four different global cardiac pathologies local myocardial strain patterns for 1025 combinations of AT and contractility were simulated with a computational model (CircAdapt). For each strain pattern, a cohort of similar patterns was found within estimated measurement error using the sum of least-squared differences. Cohort members came from (1) the same pathology only, and (2) all four pathologies. Uncertainty was calculated as accuracy and precision of cohort members in parameter space. Connectedness within the cohorts was also studied.

Results

We found that cohorts drawn from one pathology had parameters with adjacent values although their distribution was neither constant nor symmetrical. In comparison cohorts drawn from four pathologies had disconnected components with drastically different parameter values and accuracy and precision values up to three times higher.

Conclusions

Global pathology must be known when extracting AT and contractility from strain patterns, otherwise degeneracy occurs causing unacceptable uncertainty in derived parameters.

Electronic supplementary material

The online version of this article (10.1186/s12938-018-0614-1) contains supplementary material, which is available to authorized users.

Helicopter emergency medical services in Eastern Iran: a 4-year cross-sectional study of time intervals and mission profiles

BACKGROUND

Air medical transport services play a significant role in emergency situations by providing timely transfers of critically ill patients to medical facilities. This study aimed to investigate the mission characteristics of helicopter emergency medical services (HEMS) and the associated time intervals in a geographically remote region of eastern Iran. We also compared the prehospital times of HEMS and ground transportation to determine whether dispatching a helicopter is time-efficient.

METHODS

This retrospective cross-sectional study was conducted at the prehospital emergency medical center in Gonabad, a remote area in eastern Iran. Data were collected using standardized electronic forms developed by the Ministry of Health and Medical Education (MOHME) in Iran. We analyzed the mission profiles and prehospital time intervals for all Gonabad HEMS missions conducted between 2021 and 2024. The mean activation time was compared to the national benchmark of three minutes, and the prehospital time intervals of air ambulances were compared to those of ground ambulances.

RESULTS

From 2021 to 2024, there were 252 HEMS missions, transporting 265 patients. Of all 252 missions, 95 (37.7%) were primary missions, and 157 (62.3%) were secondary missions. The most frequent reasons for air ambulance dispatch were trauma, acute coronary syndrome, and strokes. The mean ± SD for HEMS activation time was 9.14 ± 3.63 min, significantly exceeding the national benchmark of three minutes. HEMS prehospital time was 49.73 ± 9.67 min. The comparison of prehospital time intervals indicated that air emergency services are more time-efficient than ground ambulances.

CONCLUSION

This study found that the mean activation time of air ambulances exceeded the national benchmark of three minutes. When comparing prehospital times for air ambulance and ground ambulance services, HEMS was faster than both ground scenarios. The current benchmark for helicopter activation time in Iran may need clarification and revision.

Transition of EMS workflow from radio to bell signals to shorten activation time in multiple casualty incident

Multiple casualty incident (MCI) are critical situations mandating an immediate response. Traditionally, members of emergency medical services (EMS) are notified about MCI through radio signals. However, communication failures can lead to delays in activation time of EMS operations. The use of bell signals is proposed as a solution to address these issues. This study uses a retrospective pre-post design evaluating the impact of the bell and radio signal on activation times for EMS operation in MCI. Data were collected from January 2020 to December 2023 and divided into two phases: radio signal use during 2020-2021 (pre-design), and bell signal use during 2022-2023 (post-design). In the event of MCI, the bell or radio is used primarily to alert medical personnel. After the MCI was recognized during the pre-design phase, the dispatcher utilized the radio signal, calling out all EMS personnel twice via radio at 171.425 MHz, with a one-minute interval between communication to notify them of the incident. The ED staff would be informed of these incidents through radio or telephone communication by EMS personnel. In the post-design phase, the dispatcher utilized the bell signal, ringing it three times to alert all staff. Activation time and equipment used by EMS during MCI operations was recorded for both phases. A total of 105 MCI with EMS operations were recorded. In the bell signal group, 52.1% (n = 199) of the participants were male. Mass transportation incidents accounted for the most of the MCI, comprising 73.6% in the bell signal group and 73.1% in the radio signal group. The average activation time was significantly shorter for the bell signal (1.54 min) compared to the radio signal (3.60 min) (P < 0.001). The average response time for the bell signal was 13.20 min, while the radio signal response time averaged 16.10 min (P = 0.042). Early activation time (less than 2 min after EMS dispatch) was significantly more likely in the Bell signal group (adjusted odds ratio, 1.25; 95% confidence interval, 1.10-2.45) than in the Radio signal group. The activation and response times for EMS operations during MCI were significantly reduced by using bell signals to alert EMS staff.