CAROTID - A web-based platform for optimal personalized management of atherosclerotic patients

Aimilia Gastounioti, Vasileios Kolias, Spyretta Golemati, Nikolaos N. Tsiaparas, Aikaterini Matsakou, John S. Stoitsis, Nikolaos P.E. Kadoglou, Christos Gkekas, John D. Kakisis, Christos D. Liapis, Petros Karakitsos, Ioannis Sarafis, Pantelis Angelidis, Konstantina S. Nikita

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Carotid atherosclerosis is the main cause of fatal cerebral ischemic events, thereby posing a major burden for public health and state economies. We propose a web-based platform named CAROTID to address the need for optimal management of patients with carotid atherosclerosis in a twofold sense: (a) objective selection of patients who need carotid-revascularization (i.e., high-risk patients), using a multifaceted description of the disease consisting of ultrasound imaging, biochemical and clinical markers, and (b) effective storage and retrieval of patient data to facilitate frequent follow-ups and direct comparisons with related cases. These two services are achieved by two interconnected modules, namely the computer-aided diagnosis (CAD) tool and the intelligent archival system, in a unified, remotely accessible system. We present the design of the platform and we describe three main usage scenarios to demonstrate the CAROTID utilization in clinical practice. Additionally, the platform was evaluated in a real clinical environment in terms of CAD performance, end-user satisfaction and time spent on different functionalities. CAROTID classification of high- and low-risk cases was 87%; the corresponding stenosis-degree-based classification would have been 61%. Questionnaire-based user satisfaction showed encouraging results in terms of ease-of-use, clinical usefulness and patient data protection. Times for different CAROTID functionalities were generally short; as an example, the time spent for generating the diagnostic decision was 5. min in case of 4-s ultrasound video. Large datasets and future evaluation sessions in multiple medical institutions are still necessary to reveal with confidence the full potential of the platform.

Original languageEnglish
Pages (from-to)183-193
Number of pages11
JournalComputer Methods and Programs in Biomedicine
Issue number2
StatePublished - Apr 2014


  • Biomarkers
  • Carotid atherosclerosis
  • Computer-aided diagnosis
  • Data management
  • Image analysis
  • Web-based platform


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