2017
DOI: 10.1016/j.ultrasmedbio.2016.12.003
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Non-Invasive Identification of Vulnerable Atherosclerotic Plaques Using Texture Analysis in Ultrasound Carotid Elastography: An In Vivo Feasibility Study Validated by Magnetic Resonance Imaging

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Cited by 28 publications
(13 citation statements)
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“…Preliminary results on principal strain derived values (axis independent strains) was also presented (McCormick et al, 2012). Axis dependent strains have been utilized in in vivo patient studies and all three strain distributions (axial, lateral and shear) have shown successful estimation of quantitative 'strain indices' that correspond to carotid plaque instability (Meshram et al, 2017;Dempsey et al, 2017;Wang et al, 2016;Wang et al, 2014;Naim et al, 2013;Huang et al, 2016;Huang et al, 2017;Roy Cardinal et al, 2017). (Wang et al, 2016) also demonstrated a relationship between elevated values of strain indices to lower cognition scores for both symptomatic and asymptomatic patients with severely stenotic plaque.…”
Section: Introductionmentioning
confidence: 99%
“…Preliminary results on principal strain derived values (axis independent strains) was also presented (McCormick et al, 2012). Axis dependent strains have been utilized in in vivo patient studies and all three strain distributions (axial, lateral and shear) have shown successful estimation of quantitative 'strain indices' that correspond to carotid plaque instability (Meshram et al, 2017;Dempsey et al, 2017;Wang et al, 2016;Wang et al, 2014;Naim et al, 2013;Huang et al, 2016;Huang et al, 2017;Roy Cardinal et al, 2017). (Wang et al, 2016) also demonstrated a relationship between elevated values of strain indices to lower cognition scores for both symptomatic and asymptomatic patients with severely stenotic plaque.…”
Section: Introductionmentioning
confidence: 99%
“…Texture features has been used for identifying other diseased tissues. For example, texture extracted from strain rate images were proposed for vulnerable plaque identification [28]. Recent studies using machine learning (ML) approach is another promising branch in the diagnosis of early disease [30], [31].…”
Section: Introductionmentioning
confidence: 99%
“…A noninvasive method that examines the mechanical properties of soft tissue, called acoustic radiation force impulse (ARFI) imaging, has been developed as a new modality for atherosclerotic plaque characterization using phantoms and atherosclerotic pigs, but the technique has yet to be validated in vivo in humans [10]. Huang et al [11] studied the textural information of strain rate images in ultrasound carotid elastography and evaluated the feasibility of using the textural features in discriminating stable and vulnerable plaques with magnetic resonance imaging. They indicated that the use of texture analysis in plaque classification is feasible and that larger local deformations and higher levels of complexity in deformation patterns are more likely to occur in vulnerable plaques.…”
Section: Introductionmentioning
confidence: 99%