Bert Verdonck

3D MRA coronary axis determination using a minimum cost path approach

A method is introduced to automatically find the coronary axis based on two or more user‐defined points, even in the presence of a severe stenosis. The coronary axis is determined by finding a minimum cost path (MCP) in a feature image in which the tubular‐like structures are enhanced. The results of the proposed method were compared with manually drawn central axes to estimate the accuracy. In 32 3D TFE‐EPI acquisitions of patients and volunteers, 14 right coronary arteries (RCAs), 15 left anterior descending arteries (LADs), and eight left circumflex arteries (LCXs) were manually tracked twice by two operators to determine a reference axis and to assess the inter‐ and intra‐user variability. On average, the maximum distance to the reference axis, based on only two user‐defined points, is less than 1.5 mm; the average distance is around 0.65 mm, which is less than the average in‐plane resolution. The results of the method are comparable to those of the manual operators. Magn Reson Med 47:1169–1175, 2002.

Vessel Axis Determination Using Wave Front Propagation Analysis

A method is presented that aims at finding the central vessel axis in two and three dimensional angiographic images based on a single user defined point. After the vessels in the image are enhanced using a special purpose filter, the operator is asked to point out the vessel of interest. Subsequently, a wave front propagation is started based on the response of the filter. By analyzing the evolution of the wave front, points are retrieved that are very likely to be part of the vessel of interest. These points can either be combined to form a connected structure or to retrieve the minimum cost path to the user defined point. In this paper examples of this approach are given that illustrate the performance of this method in different types of images and in situations where there is no or hardly any image evidence of the vessel at hand.

Blood pool contrast-enhanced MRA: improved arterial visualization in the steady state

Blood pool agents (BPAs) for contrast-enhanced magnetic resonance angiography (CE-MRA) allow prolonged imaging during the steady state when the agent is distributed through the complete vascular system. This increases both the spatial resolution and the contrast resolution. However, simultaneous venous and arterial enhancement hampers interpretation. For the pelvic region of the vasculature, it is shown that arterial visualization in this equilibrium phase can be improved if the central arterial axis (CAA) is known. However, manually obtaining this axis is not feasible in clinical practice. Therefore, a method is presented that utilizes images acquired during the first pass of the contrast agent to find the CAA in the steady-state data with minimum user initialization. The accuracy of the resulting CAA is compared with tracings of three observers in six patient datasets. It was found that the mean difference between the semiautomatic method and the manual delineation is 1.32 mm in the steady-state data, and that the resulting CAA was always within the arterial lumen, which is an important prerequisite for both improved visualization and segmentation.

Computer Assisted Quantitative Analysis of Deformities of the Human Spine

Nowadays, conventional X-ray radiographs are still the images of choice for evaluating spinal deformaties such as scoliosis. However, digital translation reconstruction gives easy access to high quality, digital overview images of the entire spine. This work aims at improving the description of the scoliotic deformity by developing semi-automated tools to assist the extraction of anatomical landmarks (on vertebral bodies and pedicles) and the calculation of deformity quantifying parameters. These tools are currently validated in a clinical setting.

3D reconstruction of the encapsulating contour of arteriovenous malformations for radiosurgery using digital subtraction angiography.

PURPOSE Treatment planning for radiosurgery depends on the precise definition of radiation target volumes. For vascular pathologies such as arteriovenous malformations (AVM), the most usual technique remains standard X-ray projection imaging, most often carried out under stereotactic conditions. To further benefit from the advantages of two-dimensional digital subtraction angiography (DSA), the authors have developed a method for determining the three-dimensional shape of arteriovenous malformations from two views. METHODS AND MATERIALS After correction of image intensifier distortion and calibration of both views, the 3D shape of the AVM was determined from two DSA projections using epipolarity geometry. The AVM-encapsulating contour was modeled by triangulation of a stack of almost parallel ellipses. The method was technically validated using artificial targets in a skull phantom. Clinical validation was carried out on 10 patients who were examined using both conventional angiography under stereotactic conditions (SX-ray) and DSA. RESULTS There was excellent agreement between the artificial target volumes measured with SX-ray and with DSA. The correspondence between AVM volumes found for patients was not as good as with the phantom. CONCLUSIONS The different image characteristics of the two modalities lead to some differences in AVM estimations. However, the results were sufficiently satisfactory to justify routine use of this AVM modeling technique for radiosurgery planning.

Image quality and X-ray dose for translation reconstruction overview imaging of the spine, colon and legs

Abstract Overview images of long parts of the human anatomy (spine, colon, legs) can be generated from a translated series of digital image intensifier (II) X-ray images using dedicated match-and-paste algorithms. The purpose of this study is to clarify the relation between the X-ray dose of the overlapping image series and the resulting image quality (contrast and noise) and image geometry of the overview image. We describe the entire acquisition protocol, but focus on the specific optimizations for translation reconstruction.

Blood Pool Agent CE-MRA: Improved Arterial Visualization of the Aortoiliac Vasculature in the Steady-State Using First-Pass Data

Blood pool agent (BPA) contrast-enhanced magnetic resonance angiography (CE-MRA) images have been acquired during the first-pass of the contrast agent and in the steady-state. Arterial visualization, which is hampered in the steady-state owing to simultaneous enhancement of arteries and veins, can be improved if the central arterial axis (CAA) is known. A method is presented that utilizes the first-pass data to find the CAA in the steady-state data with minimum user interaction. The accuracy of the resulting CAA is compared to tracings of two observers in three datasets. It was found that the average error of the method is 0.73 mm in the first-pass data and 1.54 mm in the steady-state data.

Variations in the geometrical distortion of x-ray image intensifiers

The paper investigates the variability of the geometrical deformation in digital X-ray image intensifier images as a function of acquisition parameters and time. We have increased our understanding of the deformation patterns and of how they are influenced by normal clinical use. Our goal is to reduce the frequency of calibration and the complexity of the protocol for diagnostic and interventional procedures so that geometrical distortion correction can become part of daily clinical practice.

Blood pool agent contrast-enhanced MRA: level-set-based artery-vein separation

Blood pool agents (BPAs) for contrast-enhanced magnetic resonance angiography (CE-MRA) allow prolonged imaging times for higher contrast and resolution by imaging during the steady-state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement hampers interpretation. It is shown that arterial and venous segmentation in this equilibrium phase can be achieved if the central arterial axis (CAA) and central venous axis (CVA) are known. Since the CAA can not straightforwardly be obtained from the steady-state data, images acquired during the first-pass of the contrast agent can be utilized to determine the CAA with minimal user initialization. Utilizing the CAA to provide a rough arterial segmentation, the CVA can subsequently be determined from the steady-state dataset. The final segmentations of the arteries and veins are achieved by simultaneously evolving two level-sets in the steady-state dataset starting from the CAA and CVA.

Efficacy of automatic path tracking in virtual colonoscopy

Abstract Virtual colonoscopy is a minimally invasive technique allowing early detection of colorectal polyps. Several visualization techniques exist to inspect this large amount of data on the presence of lesions. The most common ones are slice-by-slice viewing, multiplanar reformatting and perspective volume rendering of the inner colon wall (virtual endoscopy). A path or centerline through the colon can be very useful to perform virtual endoscopy. Frequently, this path has to be tracked manually. Unfortunately, manual path tracking is a very time-consuming task and the resulting path depends a lot on the experience of the operator. This severely limits the applicability of the path-based visualization and inspection methods. We have developed an automatic path tracker for virtual endoscopy based on the minimal cost path algorithm described in Deschamps and Cohen [1] . In this paper, we briefly summarize the minimal cost path method and its implementation into an automatic path tracker tool. We also describe the results of a multiuser study, where we measured the speed and operator dependence of the automated path tracker.