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Videodensitometric vs edge-detection quantitative angiography. Insights from intravascular ultrasound imaging
Author(s) -
Fernándo Alfonso
Publication year - 2000
Publication title -
european heart journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.336
H-Index - 293
eISSN - 1522-9645
pISSN - 0195-668X
DOI - 10.1053/euhj.1999.2016
Subject(s) - medicine , intravascular ultrasound , radiology , angiography , coronary angiography , ultrasound , cardiology , myocardial infarction
overlooked in most patients with acute coronary syndromes. On the other, we have learned that the arterial wall is able to experience ‘remodelling’, which further confuses our interpretation of serial angiographic lumen changes. Although many lesions occur in the setting of positive remodelling (which eventually fails to compensate for plaque growth), others are produced by negative remodelling, implying that vessel shrinkage (and not plaque accumulation) accounts for most of the lumen narrowing. Last but not least, visual assessment of coronary angiograms is associated with large interand intraobserver variability. In this context, quantitative coronary angiography has proved to be a valuable technique in providing reliable and reproducible measurements, alleviating the subjectivity and variability of visual assessment. Experimental studies have validated the performance (accuracy and precision) of quantitative coronary angiography derived measurements against true values obtained from phantom stenoses. In the clinical setting, however, vessel foreshortening and overlapping side-branches remain practical limitations. In addition, despite the use of multiple views, angiography may misrepresent the extent of luminal narrowing in eccentric lesions. Furthermore, debate still exists regarding the relative merits of the two quantitative coronary angiography techniques more frequently used, namely edgedetection and videodensitometry. In edgedetection quantitative coronary angiography the boundaries of the selected coronary segment are automatically detected by an algorithm using the weighted sum of the first and second derivative functions of the brightness profile. The reference segment is either selected by the operator or automatically interpolated by the system. The catheter, used as a scaling device, allows absolute measurements. Eventually, lumen cross-sectional areas are ‘calculated’ from orthogonal projections (assuming an elliptic model) or from the worst view (as a circle). Conversely, videodensitometry is based on the relationship between the optical density of the contrast filled lumen and absolute vessel dimensions. The cross-sectional area function is obtained from See page 654 for the article to which this Editorial refers

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