A significant cause of coronary artery disease is the coronary atherosclerosis which leads to stenosis of coronary arteries.
It has been shown in recent studies, using intravascular ultrasound and contrast-enhanced CT, that early atherosclerosis
causes positive coronary artery remodeling, defined as increases in the cross-sectional area. It is hypothesized that
detection of artery remodeling using non-contrast CT can be an important factor in sub-clinical assessment of cardiac
risk for asymptomatic subjects. However, measuring remodeling in coronary arteries in non-contrast CT images is a
challenging task because coronary arteries are small and the intensity of coronary arteries is similar to that of
surrounding tissues. Automatic segmentation algorithms that have been successful in segmenting coronary arteries in
contrast-enhanced images do not perform well. To overcome these difficulties, we developed an interactive application
to enable effective measurement of coronary artery remodeling in non-contrast CT images. This application is an
extension to the 3D Slicer image analysis platform. It allows users to visualize and trace the centerline of arteries in cross
sectional views. The artery centerlines are displayed in a three dimensional view overlaid on the original image volume
and color-coded according to the artery labels. Using this 3D artery model, the user can sample the cross-sectional area
of the arteries at selected points for remodeling assessment. Initial validation has demonstrated the effectiveness of this
method. A pilot study also showed positive correlation of large coronary artery remodeling with highest lifetime risks.
Further evaluation is underway using larger study size and more measurement points.
Most colon CAD (computer aided detection) software products, especially commercial products, are designed for use by
radiologists in a clinical environment. Therefore, those features that effectively assist radiologists in finding polyps are
emphasized in those tools. However, colon CAD researchers, many of whom are engineers or computer scientists, are
working with CT studies in which polyps have already been identified using CT Colonography (CTC) and/or optical
colonoscopy (OC). Their goal is to utilize that data to design a computer system that will identify all true polyps with no
false positive detections. Therefore, they are more concerned with how to reduce false positives and to understand the
behavior of the system than how to find polyps. Thus, colon CAD researchers have different requirements for tools not
found in current CAD software. We have implemented a module in 3D Slicer to assist these researchers. As with clinical
colon CAD implementations, the ability to promptly locate a polyp candidate in a 2D slice image and on a 3D colon
surface is essential for researchers. Our software provides this capability, and uniquely, for each polyp candidate, the
prediction value from a classifier is shown next to the 3D view of the polyp candidate, as well as its CTC/OC finding.
This capability makes it easier to study each false positive detection and identify its causes. We describe features in our
colon CAD system that meets researchers' specific requirements. Our system uses an open source implementation of a
3D Slicer module, and the software is available to the pubic for use and for extension