Computed tomography angiography (CTA) is a procedure gaining usage in the diagnosis of aneurysms located in the aorta, carotid arteries, and in other locations and has also shown promise in the planning of stent placement procedures. Recently, automatic vessel segmentation programs have been developed that can extract the entire aortic vessel tree and provide information to the user regarding the size, length, and tortuosity of the blood vessels. This study was designed to determine if using the full width at half maximum (FWHM) value is an accurate method of determining the diameter of contrast-enhanced blood vessels. A phantom used to simulate vessels of various diameters was filled with a nonionic iodine solution and scanned using a 16-detector CT scanner (Mx8000IDT, Philips Medical Systems, Inc.). The phantom was scanned with varying concentrations of contrast solution to emulate the variation of enhancement that may be seen clinically. The data was analyzed using an application on a workstation (MxView, Philips Medical Systems, Inc.), which allowed for the calculation of FWHM of a user-defined region of interest. The results indicate that the full width at half maximum is an accurate method of calculating the diameter of a blood vessel, regardless of contrast concentration. The full width at half maximum is an easily calculated value, which could potentially be used in an automatic segmentation algorithm to determine the diameters of extracted vessels.
Liver resection and transplantation surgeries require careful planning and accurate knowledge of the vascular and gross anatomy of the liver. This study aims to create a semi-automatic method for segmenting the liver, along with its entire venous vessel tree from multi-detector computed tomograms. Using fast marching and region-growth techniques along with morphological operations, we have developed a software package which can isolate the liver and the hepatic venous network from a user-selected seed point. The user is then presented with volumetric analysis of the liver and a 3-Dimensional surface rendering. Software tools allow the user to then analyze the lobes of the liver based upon venous anatomy, as defined by Couinaud. The software package also has utilities for data management, key image specification, commenting, and reporting. Seven patients were scanned with contrast on the Mx8000 CT scanner (Philips Medical Systems), the data was analyzed using our method and compared with results found using a manual method. The results show that the semi-automated method utilizes less time than manual methods, with results that are consistent and similar. Also, display of the venous network along with the entire liver in three dimensions is a unique feature of this software.
The abdominal aorta is the most common site for an aneurysm, which may lead to hemorrhage and death, to develop. The aim of this study was to develop a semi-automated method to de-lineate the vessels and detect the center-line of these vessels to make measurements necessary for stent design from multi-detector computed tomograms. We developed a robust method of tracking the aortic vessel tree with branches from a user selected seed point along the vessel path using scale space approaches, central transformation measures, vessel direction findings, iterative corrections and a priori information in determining the vessel branches. Fifteen patients were scanned with contrast on Mx8000 CT scanner (Philips Medical Systems), with a 3.2 mm thickness, 1.5 mm slice spacing, and a stack of 512x512x320 volume data sets were reconstructed. The algorithm required an initial user input to locate the vessel seen in axial CT slice. Next, the automated image processing took approximately two minutes to compute the centerline and borders of the aortic vessel tree. The results between the manually and automatically generated vessel diameters were compared and statistics were computed. We observed our algorithm was consistent (less than 0.01 S.D) and similar (less than 0.1 S.D) to manual results.