Abstract
Echocardiographic image interpretation is predominantly a subjective process, generally performed using the 'eyeball' technique and thus critically dependent on the reviewer's experience. In the past, software packages for digital image analysis have been limited. Recently, Advanced Technology Laboratories (ATL) has introduced HDI Lab for the analysis of digital images from the A TL HDI 5000 CV ultrasound machine. The purpose of this study was to apply HDI Lab to characterize the normal patterns of echocardiographic contrast uptake into the myocardium. Only by understanding the spatial variation in contrast uptake with normal perfusion can this technique be applied to patients with coronary artery disease. Digital images were obtained from 7 normal volunteers pre and post injection of Optison, microbubbles of albumin containing perfluorocarbon gas. Apical 4 and 2 chamber images were obtained in pulse-inversion harmonic mode, gated to end-diastole of every fourth beat, and stored to either a 3.5″ magneto-optical disk (MOD) on the echo machine or to a remote PC via a network connection. Images were stored in a polar format containing data from individual scan lines and echo density quantified from regions of interest in the basal, mid and apical regions of the inferior, septal, anterior and lateral walls. Multifactorial analysis of variance demonstrated highly significant (p<0.001) increase in echogenicity of all walls indicating definite contrast presence in the myocardium. However, there was considerable variability in contrast effect with a strong (p<0.004) gradient from the base (least intense) to the apex (most intense), perhaps due to attenuation from overlying structures. Such heterogeneity of effect will have to be considered as contrast echocardiography is applied to patients with coronary artery disease.
Original language | English (US) |
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Pages (from-to) | 449-452 |
Number of pages | 4 |
Journal | Computers in Cardiology |
Volume | 0 |
Issue number | 0 |
State | Published - 1998 |
ASJC Scopus subject areas
- Computer Science Applications
- Cardiology and Cardiovascular Medicine