Systolic Stretch Characterizes the Electromechanical Substrate Responsive to Cardiac Resynchronization Therapy

Area of Science:

• Cardiology
• Medical Imaging
• Heart Failure Management

Background:

• Cardiac resynchronization therapy (CRT) response is variable.
• Current guidelines recommend specific electrocardiographic criteria (LBBB, QRS ≥150 ms) for CRT patient selection.
• There is a clinical need to refine patient selection, particularly for those with QRS width 120-149 ms or non-LBBB.

Purpose of the Study:

• To evaluate the systolic stretch index (SSI), derived from echocardiographic strain imaging, as a predictor of outcomes after CRT.
• To determine if SSI can characterize the electromechanical substrate predictive of CRT success.
• To assess the additional prognostic value of global longitudinal strain (GLS) beyond SSI.

Main Methods:

• 442 patients with heart failure (NYHA class III-IV, EF ≤35%, QRS ≥120 ms) from the Adaptive CRT trial were studied.
• A novel computer program calculated SSI from strain curves, quantifying myocardial stretch during the cardiac cycle.
• Primary endpoint: hospitalization for heart failure (HF) or death; Secondary endpoint: death over 2 years post-CRT.

Main Results:

• High longitudinal SSI (≥ group median) was significantly associated with freedom from HF hospitalization or death (HR for low SSI: 2.17) and reduced risk of death (HR for low SSI: 4.06).
• In patients with QRS 120-149 ms or non-LBBB, high SSI predicted fewer HF hospitalizations/deaths (HR for low SSI: 2.08) and longer survival (HR for low SSI: 5.08), similar to patients with LBBB ≥150 ms.
• Circumferential SSI showed similar outcome associations, and GLS provided additive prognostic value to SSI (p=0.001).

Conclusions:

• Echocardiographic systolic stretch imaging effectively characterizes the myocardial substrate and predicts favorable CRT response.
• SSI is valuable for predicting CRT outcomes, including in the subgroup with QRS width 120-149 ms or non-LBBB.
• Global longitudinal strain offers additive prognostic information when combined with SSI for CRT outcome prediction.