Asymptomatic carotid stenosis and risk stratification
File(s)
Author(s)
Giannopoulos, Argyrios
Type
Thesis
Abstract
Carotid endarterectomy in patients with asymptomatic carotid stenosis (ACS) is controversial. Researchers focus on identification of the vulnerable carotid plaque to improve patients’ selection for surgery. However, there is no consensus on a specific
algorithm. Also, most studies analyse static plaque measurements, despite carotid plaques being dynamic structures.
The aims of this thesis were to determine the association of clinical parameters and ultrasonic plaque characteristics with stroke and mortality risk; also, stroke risk in terms of time. The final endpoint was to provide new methods of stroke and mortality stratification
and assess new features of plaque instability, in patients with ACS. In a natural history study of 1121 patients with ACS, a high-risk subgroup with annual stroke risk of 7.2%, based on clinical parameters, was identified. Independent stroke
predictors were creatinine, severity of stenosis, history of contralateral neurological events and progression of stenosis. A model based on six computer-extracted plaque texture features, predicting cerebrovascular events in the first two years, was developed. Finally, a subgroup of patients with 100% 5-year cardiovascular mortality was identified. Independent predictors of cardiovascular mortality were male gender, age, diabetes, stenosis >80%, not taking aspirin, cardiac failure and left ventricular hypertrophy.
In the final part of the thesis, quantification of discordant plaque motion and its relationship to symptoms was evaluated. In a cross-sectional study, involving 116 patients (58 symptomatic and 58 asymptomatic), discordant motion was associated with a high
prevalence of symptomatic carotid plaques. A method of objective computerised measurements for identification and quantification of discordant plaque motion was developed. The optimal predictor and a cut-off point for discordant motion were found.
Plaque motion analysis is a potential tool in stroke risk stratification. It should be tested, in combination with other plaque features, in prospective studies of patients with ACS.
algorithm. Also, most studies analyse static plaque measurements, despite carotid plaques being dynamic structures.
The aims of this thesis were to determine the association of clinical parameters and ultrasonic plaque characteristics with stroke and mortality risk; also, stroke risk in terms of time. The final endpoint was to provide new methods of stroke and mortality stratification
and assess new features of plaque instability, in patients with ACS. In a natural history study of 1121 patients with ACS, a high-risk subgroup with annual stroke risk of 7.2%, based on clinical parameters, was identified. Independent stroke
predictors were creatinine, severity of stenosis, history of contralateral neurological events and progression of stenosis. A model based on six computer-extracted plaque texture features, predicting cerebrovascular events in the first two years, was developed. Finally, a subgroup of patients with 100% 5-year cardiovascular mortality was identified. Independent predictors of cardiovascular mortality were male gender, age, diabetes, stenosis >80%, not taking aspirin, cardiac failure and left ventricular hypertrophy.
In the final part of the thesis, quantification of discordant plaque motion and its relationship to symptoms was evaluated. In a cross-sectional study, involving 116 patients (58 symptomatic and 58 asymptomatic), discordant motion was associated with a high
prevalence of symptomatic carotid plaques. A method of objective computerised measurements for identification and quantification of discordant plaque motion was developed. The optimal predictor and a cut-off point for discordant motion were found.
Plaque motion analysis is a potential tool in stroke risk stratification. It should be tested, in combination with other plaque features, in prospective studies of patients with ACS.
Date Issued
2019-01
Date Awarded
2018-07
Copyright Statement
Creative Commons Attribution NonCommercial NoDerivatives Licence
Advisor
Davies, Alun
Geroulakos, George
Sponsor
London North West University Healthcare NHS Trust
Publisher Department
Department of Surgery and Cancer
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)