Although global circumferential strain (stress-GCS) measured during vasodilator stress cardiovascular magnetic resonance (CMR) has incremental prognostic value for prediction of major adverse cardiovascular events (MACE) above traditional stress CMR factors, no study has investigated the optimal cut-off of stress-GCS for MACE.

To determine the optimal cut-off point of stress-GCS for predicting MACE in a consecutive cohort of patients with normal stress CMR.

Between 2017 and 2018, all consecutive patients with normal stress CMR defined by the absence of inducible ischemia and late gadolinium enhancement (LGE) were recruited retrospectively. Stress-GCS was measured using a fully automated machine-learning algorithm based on featured-tracking imaging from short-axis cine images. The primary composite outcome was MACE defined by cardiovascular death or nonfatal myocardial infarction. The survival tree method was used to identify the optimal cut-off for stress-GCS.

In 1,321 patients (65 ± 12 years, 67% men), 52 (3.9%) experienced a MACE after a median follow-up of 5.1 (4.8–5.4) years. The best cut-off of stress-GCS to predict MACE was −10%. After adjustment for traditional risk factors and stress CMR findings (LVEF), stress-GCS ≥ −10% was independently associated with MACE (adjusted HR, 12.4 [95% CI, 5.89–26.1], p < 0.001, Fig. 1A ). The annualized rate of MACE in patients with stress-GCS ≥ –10% was significantly higher than patients with stress-GCS < −10% ( Fig. 1B ). An increased stress-GCS ≥ −10% showed the best improvement in model discrimination and reclassification above traditional and stress CMR findings (C-statistic improvement: 0.14; NRI = 0.430; IDI = 0.089, all p < 0.001; LR-test p < 0.001).

Using the optimal cut-off of stress-GCS, a stress-GCS value ≥ −10% is independently associated with MACE in patients with normal stress CMR, with an incremental prognostic value over traditional risk factors and stress CMR findings.