Why the study?
Does a novel tissue-tracking system accurately quantify left ventricular systolic wall thickening compared to manual measurement in human subjects?
Does a novel tissue-tracking system accurately quantify left ventricular systolic wall thickening compared to manual measurement in human subjects?
The novel tissue-tracking system provides an accurate and reproducible automated method for quantifying human left ventricular systolic wall thickening from standard 2-D echocardiography, particularly when image quality is good.
Supports automated LV wall thickening quantification by tissue tracking; leaves open prospective validation before clinical adoption.
Background. A novel tissue-tracking system (TTS) that enables automatic assessment of two-dimensional (2-D) strain of left ventricle (LV) segments simultaneously from gray-scale digital echocardiography images has been validated in an animal study at our institution. We sought to define the application of TTS for automatic quantification of systolic wall thickening (WT) with a study in humans.Methods. We assessed 202 LV segments from 101 good and fair quality digital echo images acquired from 35 subjects. Radial strain was automatically derived from displacement between two points of interest placed at the epi- and endocardial borders of each segment. Peak radial strain at each segment was compared with manually measured systolic wall thickening.Results. There were good correlation and agreement between 2-D radial strain assessed by TTS and manually measured systolic WT in overall subjects (r = 0.89, p < 0.001). The correlation and agreements were better in good quality images (r = 0.94, p < 0.001) rather than that in fair quality images (r = 0.82, p < 0.001).Conclusion. The novel TTS provides a method for automatic quantification of human LV systolic wall thickening.
No takes yet. Share an insight, caveat, or question.
Sukmawan et al. (2005) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: