Abstract
Stress echocardiography is an established and mainstream method for the diagnosis and risk stratification of patients with known or suspected coronary artery disease [1, 2]. While the overall accuracy of stress echocardiography techniques is high, these methods are inherently limited by the subjective, eyeballing nature of image interpretation [3] and the learning curve [4] with relatively wide interinstitutional variability [5], unless conservative reading criteria are developed a priori through consensus [6]. In addition, the diagnosis is based on visual assessment of systolic thickening and endocardial motion, estimating radial function, which is theoretically less sensitive to ischemia than longitudinal and circumferential function [7]. Electrical activation disturbances (such as left bundle branch block or right ventricular pacing), hemodynamic conditions (such as right ventricular overload), or extracardiac factors (such as cardiac surgery or constrictive physiology) may affect wall motion independently of ischemia, making the analysis dependent on evaluation of systolic thickening alone [8]. Tachycardia and an increase in blood pressure may mimic ischemia, inducing a reduction of wall motion and thickening [9] – this is usually global but may be regional. Conversely, ventricular unloading (e.g., caused by mitral insufficiency) may mask ischemic wall motion abnormalities because of hyperkinesis and low wall stress [10]. Our current approach to subjective wall scoring is to evaluate contraction on a transmural basis, without the ability to assess subendocardial function, which is more sensitive to ischemia than the subepicardial layer [8]. Furthermore, the current application of stress echocardiography is certainly “intelligent” (full of useful clinical information), but the results cannot be easily reduced to a “beautiful” graphical display, understandable at a glance also by a non-imaging specialist. The development of an objective, quantitative method for wall motion analysis during stress testing would overcome these limitations, translating the inducible wall motion abnormality from an opinion into a number (Table 23.1).
Keywords
- Wall Motion
- Tissue Doppler Imaging
- Wall Motion Abnormality
- Left Bundle Branch Block
- Stress Echocardiography
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Marwick, T.H., Picano, E. (2015). New Ultrasound Technologies for Quantitative Assessment of Left Ventricular Function. In: Stress Echocardiography. Springer, Cham. https://doi.org/10.1007/978-3-319-20958-6_23
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