June 17, 2009 Ultrasound examination of the carotid artery is a patient-friendly and inexpensive method for assessing atherosclerosis and thereby predicting the risk of cardiovascular diseases. Peter Holdfeldt, who recently defended his doctoral thesis at Chalmers University of Technology in Sweden, has developed new analytical methods for ultrasound images that can provide more reliable and more exact assessments of atherosclerosis.
Cardiovascular diseases brought on by hardening of the arteries are the most common cause of death in the Western world. Hardening of the arteries means a thickening of the walls of blood vessels and the appearance of so-called atherosclerotic plaque, which consist of stored fat, among other things.
With the aid of ultrasound images, it is possible to find individuals who are at risk by measuring the thickness of the walls in the carotid artery. Another ultrasound method is to analyze whether the character of various types of plaque can predict the risk of cardiovascular diseases.
Peter Holdfeldt has developed new and more refined methods of image analysis that are based on dynamic programming.
"Measurements of the thickness of the walls of the carotid require the detection of boundaries between different layers of tissue in the blood vessel," he says. "Previously dynamic programming has been used to automatically detect boundaries in still images. But the new method uses dynamic programming for detection in image sequences of one and the same blood vessel instead."
Examining an entire image sequence instead of a single image provides a more correct result, since it is possible to make use of the similarity between the images in the sequence - a boundary ought to be found in roughly the same place in two images in a row. The method comprises two steps. First, several alternative locations of the boundary are determined in each image. Then one of the alternatives is selected from each image, and it is in this step that the program factors in the movement of boundaries between images.
"This has proven to provide more correct detections of boundaries than what you can get from a program that detects boundaries on the basis of a single image," says Peter Holdfeldt.
He has also developed a method to automatically classify atherosclerotic plaque. This plaque can burst and form blood clots that cause heart attacks or strokes. In ultrasound images it is possible with the naked eye to see the type of plaque that often leads to stroke, but such an assessment is subjective and is influenced by disturbances in the image. The new automatic method entails a technological advancement of ultrasound technology that can lead to more objective and quantifiable analysis.
Peter Holdfeldt's research has been part of a collaborative project between Chalmers and the Wallenberg Laboratory for Cardiovascular Research at Sahlgrenska University Hospital in Gothenburg. Björn Fagerberg, a physician and professor of cardiovascular research, is responsible for the clinical evaluation of the new methods together with the doctoral candidate Ulrica Prahl.
"We're now busy testing the new automatic method for plaque classification in patient groups," he says. "In its final form it should be an excellent aid in identifying high-risk patients."
Measurement of the carotid artery is already in use today in cardiovascular research. There are other methods of measurement, but they are not as well validated as the method that has been developed by the researchers at Chalmers and Sahlgrenska.
"Dynamic image analysis is an exciting new method that will no doubt offer great potential for elaboration," says Björn Fagerberg. "The advantage of using ultrasound is that is practical, inexpensive, and patient-friendly."
The dissertation "Dynamic Programming for Ultrasound Image Analysis of Atherosclerosis" was defended on May 15.
Other social bookmarking and sharing tools:
Note: Materials may be edited for content and length. For further information, please contact the source cited above.
Note: If no author is given, the source is cited instead.