Diagnostic value of layer-specific global longitudinal strain during adenosine stress in patients suspected of coronary artery disease.
June Anita EjlersenSteen H PoulsenJesper MortensenOle MayPublished in: The international journal of cardiovascular imaging (2016)
Speckle tracking global longitudinal strain (GLS) from dobutamine stress echocardiography (SE) predicts coronary artery disease (CAD). The diagnostic value of GLS from vasodilator SE and the additional value of layer-specific speckle tracking analysis are unclear. We explored the usefulness of layer-specific GLS and non-layer-specific strain (automated functional imaging, AFI) from adenosine SE. The included 132 patients (67% male, 62.6 (9.0) years), of which 46 (35%) had CAD defined as ≥1 stenosis ≥70% (≥50% in the left main), underwent adenosine SE and invasive coronary angiography. Resting AFI and layer-specific GLS were similar in patients with or without CAD (p > 0.05). The stress-rest difference (Δvalue = stress-value - rest-value) in patients with CAD was less pronounced compared to patients without proved CAD (Δendocardial GLS: -1.2 (3.5)% vs. -5.0 (3.2)%; Δmidventricular GLS: -0.95 (3.0)% vs. -4.2 (2.7)%; Δepicardial GLS: -0.7 (2.5)% vs. -3.4 (2.3)%; ΔAFI: -0.8 (2.9)% vs. -3.6 (3.1)%, p < 0.00001 for all comparisons). The diagnostic value of the three layer-specific GLS values and AFI were statistically similar (p = 0.19). The four Δvalues provided independent predictive value to the risk assessment given by gender, age, wall motion and ΔEF (p = 0.002, AFI and p < 0.0001, layer-specific GLS). The accuracies were acceptable (71-80%) with modest sensitivities (54-65%) and high specificities (80-91%). The deformation response to vasodilator infusion was associated with the presence of CAD. Endocardial, midventricular and epicardial GLS and AFI from adenosine SE had similar diagnostic values. The specificities were high, but the modest sensitivities are a limitation to the clinical application.
Keyphrases
- human health
- risk assessment
- coronary artery disease
- end stage renal disease
- chronic kidney disease
- ejection fraction
- newly diagnosed
- percutaneous coronary intervention
- prognostic factors
- cardiovascular events
- machine learning
- computed tomography
- mass spectrometry
- high resolution
- cardiovascular disease
- blood pressure
- pulmonary hypertension
- deep learning
- high throughput
- atrial fibrillation
- protein kinase
- acute coronary syndrome
- aortic stenosis
- transcatheter aortic valve replacement
- heat stress
- fluorescence imaging
- data analysis