Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/22885
DC FieldValueLanguage
dc.contributor.authorGiannopoulos, Argyrios A.-
dc.contributor.authorKyriacou, Efthyvoulos C.-
dc.contributor.authorGriffin, Maura-
dc.contributor.authorPattichis, Constantinos S.-
dc.contributor.authorMichael, Joanna-
dc.contributor.authorRichards, Toby-
dc.contributor.authorGeroulakos, George-
dc.contributor.authorNicolaides, Andrew N.-
dc.date.accessioned2021-08-26T05:56:55Z-
dc.date.available2021-08-26T05:56:55Z-
dc.date.issued2021-05-
dc.identifier.citationJournal of Vascular Surgery, 2021, vol. 73, no. 5, pp. 1630-1638en_US
dc.identifier.issn07415214-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/22885-
dc.description.abstractObjective Dynamic image analysis of carotid plaques has demonstrated that during systole and early diastole, all plaque components will move in the same direction (concordant motion) in some plaques. However, in others, different parts of the plaque will move in different directions (discordant motion). The aim of our study was (1) to determine the prevalence of discordant motion in symptomatic and asymptomatic plaques, (2) to develop a measurement of the severity of discordant motion, and (3) to determine the correlation between the severity of discordant motion and symptom prevalence. Methods A total of 200 patients with 204 plaques resulting in 50% to 99% stenosis (112 asymptomatic and 92 symptomatic plaques) had video recordings available of the plaque motion during 10 cardiac cycles. Video tracking was performed using Farneback's method, which relies on frame comparisons. In our study, these were performed at 0.1-second intervals. The maximum angular spread (MAS) of the motion vectors at 10-pixel intervals in the plaque area was measured in degrees. Plaques were classified as concordant (MAS, <70°), moderately discordant (MAS, 70°-120°), and discordant (MAS, >120°). Results Motion was discordant in 89.1% of the symptomatic plaques but only in 17.9% of asymptomatic plaques (P < .001). The prevalence of symptoms increased with increasing MAS. For a MAS >120°, the hazard ratio for the presence of symptoms was 47.7 (95% confidence interval, 18.1-125.6) compared with the rest of the plaques after adjustment for the degree of stenosis and mean pixel motion. The area under the receiver operating characteristic curve for the prediction of the presence of symptoms using the MAS was 0.876 (95% confidence interval, 0.823-0.929). The use of the median MAS (120°) as a cutoff point classified 86% of the plaques correctly (sensitivity, 81.4%; specificity, 91.2%; positive predictive value, 90.2%; and negative predictive value, 83.0%). Conclusions The use of the MAS value to identify asymptomatic plaques at increased risk of developing symptoms and, in particular, stroke should be tested in prospective studies.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Vascular Surgeryen_US
dc.rights© Elsevieren_US
dc.subjectAtherosclerotic carotid plaqueen_US
dc.subjectConcordanten_US
dc.subjectDiscordanten_US
dc.subjectMotion analysisen_US
dc.subjectUltrasounden_US
dc.titleDynamic carotid plaque imaging using ultrasonographyen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationImperial College Londonen_US
dc.collaborationUniversity College London Hospitalen_US
dc.collaborationFrederick Universityen_US
dc.collaborationVascular Screening and Diagnostic Centreen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationUniversity of Western Australiaen_US
dc.collaborationNational and Kapodistrian University of Athensen_US
dc.collaborationUniversity of Nicosiaen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.subject.categoryClinical Medicineen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.subject.fieldMedical and Health Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1016/j.jvs.2020.10.021en_US
dc.identifier.pmid33091515-
dc.identifier.scopus2-s2.0-85100394790-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85100394790-
dc.relation.issue5en_US
dc.relation.volume73en_US
cut.common.academicyear2020-2021en_US
dc.identifier.spage1630en_US
dc.identifier.epage1638en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextNo Fulltext-
crisitem.journal.journalissn0741-5214-
crisitem.journal.publisherElsevier-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-4589-519X-
crisitem.author.parentorgFaculty of Engineering and Technology-
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