Untitled

Abstract

Intracoronary ultrasound (ICUS) provides high-resolution transmural images of the arterial wall. By performing a pullback of the ICUS transducer and three-dimensional reconstruction of the images, an advanced assessment of the lumen and vessel wall morphology can be obtained. To reduce the analysis time and the subjectivity of boundary tracing, automated segmentation of the image sequence must be performed. The Quantitative Coronary Ultrasound-Clinical Measurement Solutions (QCU-CMS) (semi)automated analytical software package uses a combination of transversal and longitudinal model- and knowledge-guided contour detection techniques. On multiple longitudinal sections through the pullback stack, the external vessel contours are detected simultaneously, allowing mutual guidance of the detection in difficult areas. Subsequently, luminal contours are detected on these longitudinal sections. Vessel and luminal contour points are transformed to the individual cross-sections, where they guide the vessel and lumen contour detection on these transversal images. The performance of the software was validated stepwise. A set of phantoms was used to determine the systematic and random errors of the contour detection of external vessel and lumen boundaries. Subsequently, the results of the contour detection as obtained in in vivo image sets were compared with expert manual tracing, and finally the contour detection in in vivo image sequences was compared with results obtained from another previously validated ICUS quantification system. The phantom lumen diameters were underestimated by 0.1 mm, equally by the QCU-CMS software and by manual tracing. Comparison of automatically detected contours and expert manual contours, showed that lumen contours correspond very well (systematic and random radius difference: -0.025 +/- 0.067 mm), while automatically detected vessel contours slightly overestimated the expert manual contours (radius difference: 0.061 +/- 0.037 mm). The cross-sectional vessel and lumen areas as detected with our system and with the second computerized system showed a high correlation (r = 0.995 and 0.978, respectively). Thus, use of the new QCU-CMS analytical software is feasible and the validation data suggest its application for the analysis of clinical research.

In vivo comparison of arterial lumen dimensions assessed by co-registered three-dimensional (3D) quantitative coronary angiography, intravascular ultrasound and optical coherence tomography

“…As a result, the comparisons reflected the systematic difference between 3D QCA and IVUS or OCT. For IVUS images, only frames that corresponded to the ED phase in the cardiac cycle were considered, since 3D QCA was performed also at the ED phase. A well validated algorithm integrated in a commercial software package (QIvus 2.1, Medis medical imaging systems bv, Leiden, the Netherlands) [11] was used for the IVUS segmentation and quantitative analysis. For quantitative OCT analysis, a new mincost algorithm was directly integrated in the registration software to automatically detect the lumen-intima interface from OCT images.…”

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction

“…In addition, they may have high variability among operators due to different initializations. Therefore, automatic segmentation methods are a more adequate and practical tool for both modalities [32,33,41]. In addition, since IVUS is older than IVOCT, engineers can find from the literature a much wider variety of methods for enhancing, or implementing solutions to create extra tools or to embed in new IVUS equipment.…”

Focus on the research utility of intravascular ultrasound - comparison with other invasive modalities

“…To facilitate its application in research a number of tools were developed that provided fast and reliable IVUS processing and quantitative analysis [6-8]. This allowed the use of IVUS in numerous studies which helped us to explain the mechanisms of atherosclerotic process and affected the evolution in interventional cardiology.…”