Abstract

Management of carotid artery disease, towards preventing strokes, currently relies on a simple algorithm, which has proved insufficient for a large number of mostly asymptomatic subjects, posing a significant clinical challenge. Ultrasound imaging in combination with image analysis hold promise for addressing this challenge, through the in vivo estimation of morphological, mechanical and anatomical features of the carotid artery, the artery that takes blood to the brain.

This presentation highlights various advanced image analysis techniques applied on carotid ultrasound, in an attempt to identify novel risk markers and optimise disease management. Texture features, estimated from static images, describe different patterns of tissue allocation, presumably as a consequence of exerted stresses. Mechanical features, estimated from temporal image sequences, characterise tissue elasticity and are more sensitive to early tissue changes due to ageing or disease. Anatomical features, including arterial diameters, wall thickness and lesion size, can be automatically extracted using segmentation tools. These methodologies, along with biochemical and clinical indices, are integrated in a web-based platform, which relies on a semantically-aided architecture and allows for intelligent archival and retrieval of data, thus facilitating and enhancing the entire diagnostic procedure.

In view of the valuable information on lesion composition and stability revealed by ultrasound-image-based features, and the noninvasiveness and low-cost of ultrasound imaging, these approaches are directed towards improved risk stratification, increased patient safety and cost-efficiency. Their clinical usefulness remains to be demonstrated in large trials.

Bio

Spyretta Golemati is Assistant Professor in Biomedical Engineering and a member of the First Intensive Care Unit of the Medical School of the University of Athens.

Dr Golemati holds a Diploma in Mechanical Engineering from the National Technical University of Athens, Greece, and a M.Sc. and a Ph.D. degree in Bioengineering from Imperial College London, UK.

Her research interests include (a) medical image analysis, with emphasis on vascular ultrasound image analysis, (b) biosignal processing, and (c) vascular physiology and pathophysiology. She has co-authored 32 papers published in international scientific peer-reviewed journals, 12 book chapters, and 44 papers published in international scientific peer-reviewed conference proceedings. She has participated in 7 funded national and international research projects (in one, as co-ordinator). Dr Golemati has acted as reviewer of national and international research proposals as well as of papers submitted to international scientific journals and conferences. She is a member of the Institute of Electrical and Electronic Engineers [Engineering in Medicine and Biology Society (IEEE-EMBS), Ultrasonics, Ferroelectrics and Frequency Control (IEEE-UFFC)], the Technical Chamber of Greece, and the Hellenic Atherosclerosis Society. She is Associate Editor of the journal Ultrasonics. She is a grantee of the Fulbright Foundation-Greece for the academic year 2016-2017.