title: Strain measurement in coronary arteries using intravascular ultrasound and deformable images.
abstract: Atherosclerotic plaque rupture is responsible for the majority of myocardial infarctions and acute coronary syndromes. Rupture is initiated by mechanical failure of the plaque cap, and thus study of the deformation of the plaque in the artery can elucidate the events that lead to myocardial infarction. Intravascular ultrasound (IVUS) provides high resolution in vitro and in vivo cross-sectional images of blood vessels. To extract the deformation field from sequences of IVUS images, a registration process must be performed to correlate material points between image pairs. The objective of this study was to determine the efficacy of an image registration technique termed Warping to determine strains in plaques and coronary arteries from paired IVUS images representing two different states of deformation. The Warping technique uses pointwise differences in pixel intensities between image pairs to generate a distributed body force that acts to deform a finite element model. The strain distribution estimated by image-based Warping showed excellent agreement with a known forward finite element solution, representing the gold standard, from which the displaced image was created. The Warping technique had a low sensitivity to changes in material parameters or material model and had a low dependency on the noise present in the images. The Warping analysis was also able to produce accurate strain distributions when the constitutive model used for the Warping analysis and the forward analysis was different. The results of this study demonstrate that Warping in conjunction with in vivo IVUS imaging will determine the change in the strain distribution resulting from physiological loading and may be useful as a diagnostic tool for predicting the likelihood of plaque rupture through the determination of the relative stiffness of the plaque constituents.
authors.affiliation: Department of Bioengineering, Department of Radiology, University of Utah, 50 South Central Campus Drive, Room 2480, Salt Lake City, Utah 84112-9202, USA.
authors.forename: Alexander I
authors.initials: AI
authors.lastname: Veress
authors.forename: Jeffrey A
authors.initials: JA
authors.lastname: Weiss
authors.forename: Grant T
authors.initials: GT
authors.lastname: Gullberg
authors.forename: D Geoffrey
authors.initials: DG
authors.lastname: Vince
authors.forename: Richard D
authors.initials: RD
authors.lastname: Rabbitt
mesh_terms: D000465:Algorithms; D001158:Arteries / Q000000981:diagnostic imaging / Q000503:physiopathology; D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D003331:Coronary Vessels / Q000000981:diagnostic imaging / Q000503:physiopathology; D004548:Elasticity; D020342:Finite Element Analysis; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008955:Models, Cardiovascular; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013269:Stochastic Processes; D013314:Stress, Mechanical; D013382:Subtraction Technique; D018084:Ultrasonography, Interventional / Q000379:methods*