The interpretation of the 12‑lead ECG is notoriously difficult and requires experts to distinguish normal from abnormal ECG waveforms. ECG waveforms depend on body build and electrode positions, both often different in males and females. To relate the ECG waveforms to cardiac anatomical structures is even more difficult. The novel CineECG algorithm enables a direct projection of the 12‑lead ECG to the cardiac anatomy by computing the mean location of cardiac activity over time. The aim of this study is to investigate the cardiac locations of the CineECG derived from standard 12‑lead ECGs of normal subjects. In this study we used 6525 12‑lead ECG tracings labelled as normal obtained from the certified Physionet PTB XL Diagnostic ECG Database to construct the CineECG. All 12 lead ECGs were analyzed, and then divided by age groups (18-29,30-39,40-49,50-59,60-69,70-100 years) and by gender (male/female). For each ECG, we computed the CineECG within a generic 3D heart/torso model. Based on these CineECG's, the average normal cardiac location and direction for QRS, STpeak, and TpeakTend segments were determined. The CineECG direction for the QRS segment showed large variation towards the left free wall, whereas the STT segments were homogeneously directed towards the septal/apical region. The differences in the CineECG location for the QRS, STpeak, and TpeakTend between the age and gender groups were relatively small (maximally 10 mm at end T-wave), although between the gender groups minor differences were found in the 4 chamber direction angles (QRS 4°, STpeak 5°, and TpeakTend 8°) and LAO (QRS 1°, STpeak 13°, and TpeakTend 30°). CineECG demonstrated to be a feasible and pragmatic solution for ECG waveform interpretation, relating the ECG directly to the cardiac anatomy. The variations in depolarization and repolarization CineECG were small within this group of normal healthy controls, both in cardiac location as well as in direction. CineECG may enable an easier discrimination between normal and abnormal QRS and T-wave morphologies, reducing the amount of expert training. Further studies are needed to prove whether novel CineECG can significantly contribute to the discrimination of normal versus abnormal ECG tracings.

Background: In Brugada syndrome (BrS), diagnosed in presence of a spontaneous or ajmaline-induced type-1 pattern, ventricular arrhythmias originate from the right ventricle outflow tract (RVOT). We developed a novel CineECG method, obtained by inverse electrocardiogram (ECG) from standard 12-lead ECG, to localize the electrical activity pathway in patients with BrS. Methods: The CineECG enabled the temporospatial localization of the ECG waveforms, deriving the mean temporospatial isochrone from standard 12-lead ECG. The study sample included (1) 15 patients with spontaneous type-1 Brugada pattern, and (2) 18 patients with ajmaline-induced BrS (at baseline and after ajmaline), in whom epicardial potential duration maps were available; (3) 17 type-3 BrS pattern patients not showing type-1 BrS pattern after ajmaline (ajmaline-negative); (4) 47 normal subjects; (5) 18 patients with right bundle branch block (RBBB). According to CineECG algorithm, each ECG was classified as Normal, Brugada, RBBB, or Undetermined. Results: In patients with spontaneous or ajmaline-induced BrS, CineECG localized the terminal mean temporospatial isochrone forces in the RVOT, congruent with the arrhythmogenic substrate location detected by epicardial potential duration maps. The RVOT location was never observed in normal, RBBB, or ajmaline-negative patients. In most patients with ajmaline-induced BrS (78%), the RVOT location was already evident at baseline. The CineECG classified all normal subjects and ajmaline-negative patients at baseline as Normal or Undetermined, all patients with RBBB as RBBB, whereas all patients with spontaneous and ajmaline-induced BrS as Brugada. Compared with standard 12-lead ECG, CineECG at baseline had a 100% positive predictive value and 81% negative predictive value in predicting ajmaline test results. Conclusions: In patients with spontaneous and ajmaline-induced BrS, the CineECG localized the late QRS activity in the RVOT, a phenomenon never observed in normal, RBBB, or ajmaline-negative patients. The possibility to identify the RVOT as the location of the arrhythmogenic substrate by the noninvasive CineECG, based on the standard 12-lead ECG, opens new prospective for diagnosing patients with BrS.

The standard 12-lead electrocardiogram (ECG) is a diagnostic tool to asses cardiac electrical activity. The vectorcardiogram is a related tool that represents that activity as the direction of a vector. In this work we investigate CineECG, a new 12-lead ECG based analysis method designed to directly estimate the average cardiac anatomical location of activation over time. We describe CineECG calculation and a novel comparison parameter, the average isochrone position (AIP). In a model study, fourteen different activation sequences were simulated and corresponding 12-lead ECGs were computed. The CineECG was compared to AIP in terms of location and direction. In addition, 67-lead body surface potential maps from ten patients were used to study the sensitivity of CineECG to electrode mispositioning and anatomical model selection. Epicardial activation maps from four patients were used for further evaluation. The average distance between CineECG and AIP across the fourteen sequences was 23.7 ± 2.4 mm, with significantly better agreement in the terminal (27.3 ± 5.7 mm) versus the initial QRS segment (34.2 ± 6.1 mm). Up to four cm variation in electrode positioning produced an average distance of 6.5 ± 4.5 mm between CineECG trajectories, while substituting a generic heart/torso model for a patient-specific one produced an average difference of 6.1 ± 4.8 mm. Dominant epicardial activation map features were recovered. Qualitatively, CineECG captured significant features of activation sequences and was robust to electrode misplacement. CineECG provides a realistic representation of the average cardiac activation in normal and diseased hearts. In particular, the terminal segment of the CineECG might be useful to detect pathology.

Aims: Ventricular conduction disorders can induce arrhythmias and impair cardiac function. Bundle branch blocks (BBBs) are diagnosed by 12-lead electrocardiogram (ECG), but discrimination between BBBs and normal tracings can be challenging. CineECG computes the temporo-spatial trajectory of activation waveforms in a 3D heart model from 12-lead ECGs. Recently, in Brugada patients, CineECG has localized the terminal components of ventricular depolarization to right ventricle outflow tract (RVOT), coincident with arrhythmogenic substrate localization detected by epicardial electro-anatomical maps. This abnormality was not found in normal or right BBB (RBBB) patients. This study aimed at exploring whether CineECG can improve the discrimination between left BBB (LBBB)/RBBB, and incomplete RBBB (iRBBB). Methods and results: We utilized 500 12-lead ECGs from the online Physionet-XL-PTB-Diagnostic ECG Database with a certified ECG diagnosis. The mean temporo-spatial isochrone trajectory was calculated and projected into the anatomical 3D heart model. We established five CineECG classes: ‘Normal’, ‘iRBBB’, ‘RBBB’, ‘LBBB’, and ‘Undetermined’, to which each tracing was allocated. We determined the accuracy of CineECG classification with the gold standard diagnosis. A total of 391 ECGs were analysed (9 ECGs were excluded for noise) and 240/266 were correctly classified as ‘normal’, 14/17 as ‘iRBBB’, 55/55 as ‘RBBB’, 51/51 as ‘LBBB’, and 31 as ‘undetermined’. The terminal mean temporal spatial isochrone contained most information about the BBB localization. Conclusion: CineECG provided the anatomical localization of different BBBs and accurately differentiated between normal, LBBB and RBBB, and iRBBB. CineECG may aid clinical diagnostic work-up, potentially contributing to the difficult discrimination between normal, iRBBB, and Brugada patients.