SMARTool: A Tool for Clinical Decision Support for the Management of Patients with Coronary Artery Disease based on Modeling of Atherosclerotic Plaque Process

Antonis Sakellarios1, Georgios Rigas, Kigka Vassiliki1, Panagiotis Siogkas, Panagiota Tsompou2, Georgia Karanasiou3, Themis P. Exarchos, Ioannis Andrikos1, Nikolaos Tachos4, Gualtiero Pelosi5, Oberdan Parodi, Dimitrios I. Fotiadis1

  • 1University of Ioannina
  • 2Unit of Medical Technology and Intelligent Information Systems,
  • 3University of Ioannina, Dept. of Materials Science, Unit of
  • 4Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engin
  • 5Institute of Clinical Physiology, National Research Council, 561

Details

09:15 - 09:30 | Wed 12 Jul | Schmitt Room | WeAT10.6

Session: Models for Clinical Decision Support

Abstract

SMARTool aims to the development of a clinical decision support system (CDSS) for the management and stratification of patients with coronary artery disease (CAD). This will be achieved by performing computational modeling of the main processes of atherosclerotic plaque growth. More specifically, computed tomography coronary angiography (CTCA) is acquired and 3-dimensional (3D) reconstruction is performed for the arterial trees. Then, blood flow and plaque growth modeling is employed simulating the major processes of atherosclerosis, such as the estimation of endothelial shear stress (ESS), the lipids transportation, low density lipoprotein (LDL) oxidation, macrophages migration and plaque development. The plaque growth model integrates information from genetic and biological data of the patients. The SMARTool system enables also the calculation of the virtual functional assessment index (vFAI), an index equivalent to the invasively measured fractional flow reserve (FFR), to provide decision support for patients with stenosed arteries. Finally, it integrates modeling of stent deployment. In this work preliminary results are presented. More specifically, the reconstruction methodology has mean value of Dice Coefficient and Hausdorff Distance is 0.749 and 1.746, respectively, while low ESS and high LDL concentration can predict plaque progression.