title: A 3-D ultrasound-based framework to characterize the echo morphology of carotid plaques.
abstract: Carotid atherosclerosis is the main cause of brain stroke, which is the most common life-threatening neurological disease. Nearly all methods aiming at assessing the risk of plaque rupture are based on its characterization from 2-D ultrasound images, which depends on plaque geometry, degree of stenosis, and echo morphology (intensity and texture). The computation of these indicators is, however, usually affected by inaccuracy and subjectivity associated with data acquisition and operator-dependent image selection. To circumvent these limitations, a novel and simple method based on 3-D freehand ultrasound is proposed that does not require any expensive equipment except the common scanner. This method comprises the 3-D reconstruction of carotids and plaques to provide clinically meaningful parameters not available in 2-D ultrasound imaging, namely diagnostic views not usually accessible via conventional techniques and local 3-D characterization of plaque echo morphology. The labeling procedure, based on graph cuts, allows us to identify, locate, and quantify potentially vulnerable foci within the plaque. Validation of the characterization method was made with synthetic data. Results of plaque characterization with real data are encouraging and consistent with the results from conventional methods and after inspection of surgically removed plaques.
authors.affiliation: Institute for Systems and Robotics, Instituto Superior Técnico, Lisbon 1049-001, Portugal. jseabra@isr.ist.utl.pt
authors.forename: José C R
authors.initials: JC
authors.lastname: Seabra
authors.forename: Luís M
authors.initials: LM
authors.lastname: Pedro
authors.forename: José Fernandes
authors.initials: JF
authors.lastname: e Fernandes
authors.forename: João M
authors.initials: JM
authors.lastname: Sanches
mesh_terms: D000465:Algorithms; D016893:Carotid Stenosis / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D015203:Reproducibility of Results; D014463:Ultrasonography / Q000379:methods*