An intravascular coronary plaque elasticity reconstruction method using limited depth penetration ultrasound signals
Year: 2015
Type: article
Abstract: Vulnerable atherosclerotic plaque (VP) rupture is the leading cause of acute coronary syndrome, myocardial infarction andstroke in the Western world (Go et al. 2013). Although past studies have identified fibrous cap thickness (Capthick) as theprimary predictor of coronary plaque rupture (Virmani et al. 2006), biomechanical studies have recognized peak cap stress(PCS) as an additional key predictor of plaque disruption (Ohayon et al. 2008). Quantification of PCS amplitude requiresnot only an accurate description of plaque morphology but also a precise knowledge of the mechanical properties of plaquecomponents. An early and accurate determination of these properties remains an essential step to implement preventivetherapeutic strategies.A previous approach (named iMOD for imaging modulography) has been conducted by our group to reconstructthe Young’s modulus map (i.e. modulogram) from intravascular ultrasound (IVUS) strain-elastogram (Le Floc’h et al. 2009). However,one major limitation of such a method is the need to accurately estimate the strain field in the entire lesion, which may beoften difficult when using HD-IVUS techniques with limited depth penetration signals (Kobayashi et al. 2014). Therefore, an extendediMOD approach (E-iMOD), based on the continuum mechanics theory prescribing the strain field in the limited atheroscleroticendoluminal region, was designed and successfully applied to coronary lesions of patients imaged in vivo with IVUS.
Institutions: Centre National de la Recherche Scientifique, Université Joseph Fourier, Translational Innovation in Medicine and Complexity, Université de Montpellier, Laboratoire de Mécanique et Génie Civil, Université Montpellier 2, Inserm, Hospices Civils de Lyon, University of Rochester, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Université Savoie Mont Blanc
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2185025547