Aims:In patients with Brugada syndrome (BrS), diagnosis relies primarily on the presence of the characteristic type 1 electrocardiographic (ECG) pattern. The aim of this study was to propose an alternative diagnostic method in situations where ECG alone is uncertain.
Methods and results:This study was conducted in two phases: (i) Phase 1: cut-off determination. Controls and BrS patients were analysed to develop a predictive model based on electrocardiographic imaging (ECGi) parameters for the diagnosis of BrS. Patients with right bundle branch block (RBBB) were analysed separately. All patients underwent ajmaline infusion. Concealed BrS patients were evaluated in both the absence and presence of a type 1 ECG pattern. The right and left ventricular ‘epicardium’ maps obtained with ECGi were divided into eight regions, and the mean activation time (ATm) was calculated for each region. The ATm for each area was normalized to QRS length (ATm%); ATm and ATm% were compared across populations. (ii) Phase 2: cut-off validations. A new cohort of control and BrS patients was used to perform a blinded validation of the proposed method. In Phase 1 (cut-off determination), 57 patients affected by BrS, and 10 controls were included. Analysis of ATm and ATm% in right ventricular outflow tract (RVOT) showed significant differences between controls and BrS patients both with either concealed or manifested Pattern 1 ECG (3 721 ± 6.23 vs. 68.33 ± 14.73 ms, P < 0.001; 37.21 ± 6.23 vs. 107.57 ± 21.16 ms, P < 0.001). The relationship between the anterior-RV and the RVOT ATm was used to develop a predictive model to identify a diagnostic threshold for BrS diagnosis. An increase of 45% in anterior-RV ATm was determined to be the optimal predictor of delayed RVOT activation in BrS patients (area under the receiver operating characteristic curve = 0.97, accuracy = 0.92, F-score = 0.95). In RBBB patients, the ATm delay cut-off was reached exclusively in cases with concomitant BrS. In Phase 2, 7 out of 7 control patients exhibited a percentage increase between the anterior-RV and RVOT of <45%. Among BrS patients with concealed pattern (pattern-concealed), 11 out of 20 showed a percentage increase >45% (accuracy 67%). In BrS patients with manifested Pattern 1 (pattern-positive), 19 out of 20 showed a percentage increase of >45% (accuracy 96%).
Conclusion:In BrS, the delay in RVOT activation can be identified using a threshold value of 45% above the mean activation time in the anterior-RV for each patient, offering a reliable diagnostic tool when standard ECG method alone falls short.