Automated left ventricular delineation in X-ray angiograms: a validation study.
OBJECTIVE
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.
Oost
Elco
E
Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands.
Oemrawsingh
Pranobe
P
Reiber
Johan H
JH
Lelieveldt
Boudewijn
B
D000465:Algorithms; D000790:Angiocardiography; D001331:Automation; D019992:Databases as Topic; D006352:Heart Ventricles / Q000000981:diagnostic imaging* / Q000503:physiopathology; D006801:Humans; D015588:Observer Variation; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D012984:Software; D013318:Stroke Volume; D016277:Ventricular Function, Left