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Automated left ventricular delineation in X‐ray angiograms: A validation study
Author(s) -
Oost Elco,
Oemrawsingh Pranobe,
Reiber Johan H.,
Lelieveldt Boudewijn
Publication year - 2009
Publication title -
catheterization and cardiovascular interventions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.988
H-Index - 116
eISSN - 1522-726X
pISSN - 1522-1946
DOI - 10.1002/ccd.21672
Subject(s) - contouring , medicine , workflow , automated method , artificial intelligence , radiology , computer science , computer graphics (images) , database
Objectives: Recently an automated analysis approach for left ventricular (LV) X‐ray angiographic studies was proposed. This particular study aims to assess the clinical potential of this approach. Background: Over the past 30 years much research has been carried out to develop a technique with automated contour detection of the LV outline in the end‐diastolic (ED) and end‐systolic (ES) phases. Very few have made it into clinical practice. Our latest approach is based on innovative model‐based image processing techniques. Methods: Two expert cardiologists analyzed 30 patient studies both by contouring the LV manually and by using the proposed automated methodology. In the latter procedure the experts were allowed to edit the automatically generated contours manually. The manual, automatic, and edited automatic contours were compared, focusing on accuracy, workflow efficiency, and inter‐ and intra‐observer variabilities. Results: No significant differences between the automatically derived and manual LV volumes were observed. The average patient study analysis time was reduced by 26%, from 4.2 to 3.1 min. When editing was required, 19% of the ED and 25% of the ES contour length needed manual correction. Furthermore, a reduction in inter‐observer variability of 12.4% was observed. Conclusions: Using the proposed automated methodology for X‐ray LV angiographic study analysis, a considerable reduction in required analysis time and manual effort is achieved. Because the acquired results are of clinically acceptable quality and the inter‐ and intra‐observer variabilities are reduced, this automated approach has the potential to optimize the analysis workflow for LV X‐ray angiography in clinical practice. © 2009 Wiley‐Liss, Inc.