Monaco Cinzia, Eltsov Ivan, Del Monte Alvise, Aglietti Filippo, Pannone Luigi, Della Rocca Domenico, Gauthey Anaïs, Bisignani Antonio, Mouram Sahar, Calburean Paul-Adrian, Pappaert Gudrun, Bala Gezim, Sorgente Antonio, Almorad Alexandre, Stroker Erwin, Sieira Juan, Sarkozy Andrea, Chierchia Gian Battista, La Meir Mark, Brugada Pedro, de Asmundis Carlo
Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, European Reference Networks Guard-Heart, Vrije Universiteit Brussel, Universitair Ziekenhuis, Laarbeeklaan 101, Brussel 1090, Belgium.
Cardiac Surgery Department, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium.
Europace. 2025 Jun 3;27(6). doi: 10.1093/europace/euaf093.
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.
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%).
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.
在 Brugada 综合征（BrS）患者中，诊断主要依赖于特征性 1 型心电图（ECG）模式的存在。本研究的目的是在仅依靠心电图不确定的情况下提出一种替代诊断方法。
本研究分两个阶段进行：（i）阶段 1：临界值确定。对对照组和 BrS 患者进行分析，以基于心电图成像（ECGi）参数开发用于诊断 BrS 的预测模型。对右束支传导阻滞（RBBB）患者进行单独分析。所有患者均接受阿义马林静脉注射。对隐匿性 BrS 患者在无 1 型 ECG 模式和有 1 型 ECG 模式时均进行评估。通过 ECGi 获得的右心室和左心室“心外膜”图被分为八个区域，并计算每个区域的平均激活时间（ATm）。将每个区域的 ATm 标准化为 QRS 长度（ATm%）；比较不同人群的 ATm 和 ATm%。（ii）阶段 2：临界值验证。使用一组新的对照组和 BrS 患者对所提出的方法进行盲法验证。在阶段 1（临界值确定）中，纳入了 57 例 BrS 患者和 10 例对照。对右心室流出道（RVOT）的 ATm 和 ATm%分析显示，无论是隐匿性还是显性 1 型 ECG 的对照组和 BrS 患者之间均存在显著差异（37.21±6.23 与 68.33±14.73 ms，P<0.001；37.21±6.23 与 107.57±21.16 ms，P<0.001）。利用前 RV 与 RVOT 的 ATm 之间的关系开发预测模型，以确定 BrS 诊断的诊断阈值。确定前 RV 的 ATm 增加 45%是 BrS 患者 RVOT 激活延迟的最佳预测指标（受试者工作特征曲线下面积 = 0.97，准确率 = 0.92，F 值 = 0.95）。在 RBBB 患者中，仅在合并 BrS 的病例中达到 ATm 延迟临界值。在阶段 2 中，7 例对照患者中有 7 例显示前 RV 与 RVOT 之间的百分比增加<45%。在隐匿性模式（隐匿模式）的 BrS 患者中，20 例中有 11 例显示百分比增加>45%（准确率 67%）。在显性 1 型模式（阳性模式）的 BrS 患者中，20 例中有 19 例显示百分比增加>45%（准确率 96%）。
在 BrS 中，可使用高于每位患者前 RV 平均激活时间 45%的阈值来识别 RVOT 激活延迟，当仅标准 ECG 方法不足时提供一种可靠的诊断工具。
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