ANALYSIS OF RELATIONSHIPS BETWEEN HETEROGENEOUS RADIOMIC FEATURES OF THROMBUS IN ACUTE ISCHEMIC STROKE

Abstract

Ischemic stroke is one of the most widely recognised cerebral pathologies. Its diagnosis starts with computed tomography (CT). However, a comprehensive understanding of the characteristics of the thrombus is necessary to establish an appropriate and less hazardous treatment. This study focusses on the analysis of thrombus heterogeneity in CT images of patients with acute ischemic stroke (AIS). The radiomic features of the thrombus were used to obtain the voxel distribution in the new feature space. It was then reduced using Principal Component Analysis (PCA) and subjected to visualisation techniques such as t-distributed Stochastic Neighbour Embedding (tSNE) and Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP). By evaluating the morphological structure of the clusters created within patients, it was possible to determine the number of thrombus components. This information could help the physician predict the burden on the patient during thrombectomy, such as the number of attempts required for recanalization.