Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/32376
DC FieldValueLanguage
dc.contributor.authorNicolaides, Andrew-
dc.contributor.authorKakkos, Stavros K.-
dc.contributor.authorGriffin, Maura-
dc.contributor.authorKyriacou, Efthyvoulos C.-
dc.date.accessioned2024-03-21T12:02:08Z-
dc.date.available2024-03-21T12:02:08Z-
dc.date.issued2022-09-01-
dc.identifier.citationNoninvasive Vascular Diagnosis, 2022, pp. 183-209en_US
dc.identifier.issn9783030606251-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/32376-
dc.description.abstractIn recent years, it has become apparent that the severity of an asymptomatic carotid stenosis is not sufficient to assess the risk of stroke. Although the risk of stroke increases with increasing grades of stenosis, and as a result a stenosis of ≥80% is used by many surgeons as an indication for surgery, this subgroup does not contain the majority of strokes that will subsequently occur. In addition, because the severity of stenosis cannot identify subgroups with stroke risk higher than 2.5%, a very large number of operations (approximately 90) with an asymptomatic stenosis of ≥80% would need to undergo carotid endarterectomy to prevent one stroke for 1 year of follow-up. The aim of this chapter is to present the rationale and practical development of image analysis of ultrasonic plaque images for the identification of texture features that can be used to stratify patients according to stroke risk. Two important advances contributed to the success of this approach. First, image analysis has enabled us to obtain reproducible measurements of gray scale from the same plaques irrespective of equipment and gain used. Second was the realization that, similar to plaque histology, not a single feature on imaging could by itself detect all the structural abnormality characteristic of potentially unstable and high-risk plaques. The ability of a combination of texture features to identify unstable plaques and stratify patients according to stroke risk was tested in both cross-sectional studies and validated in a large prospective cohort (ACSRS study).en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© Springer Natureen_US
dc.subjectultrasounden_US
dc.subjectimage analysisen_US
dc.subjectcarotiden_US
dc.subjectcharacterisationen_US
dc.titleUltrasonic Characterization of Carotid Plaques and Its Clinical Implicationsen_US
dc.typeBook Chapteren_US
dc.linkhttps://link.springer.com/referenceworkentry/10.1007/978-3-030-60626-8_8en_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationVascular Screening and Diagnostic Centreen_US
dc.collaborationUniversity of Patras Medical Schoolen_US
dc.collaborationVascular Noninvasive Diagnostic Centreen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.countryUnited Kingdomen_US
dc.countryGreeceen_US
dc.subject.fieldMedical and Health Sciencesen_US
dc.publicationPeer Revieweden_US
cut.common.academicyear2022-2023en_US
dc.identifier.spage183en_US
dc.identifier.epage209en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_3248-
item.openairetypebookPart-
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
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-
Appears in Collections:Κεφάλαια βιβλίων/Book chapters
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