Radiomics Features on MRI are Associated with High Risk Intracranial Aneurysms

Risk stratification of unruptured intracranial aneurysms (IAs) is critical for better management and treatment. Engineered tools, like the Rupture Resemblance Score (RRS), use aneurysm morphology and flow characteristics from computational fluid dynamics (CFD) for identification of high-risk IAs. Despite several studies that have demonstrated the potential of such metrics, their potential usefulness is hindered, since the metrics relation to the biological composition of the aneurysm wall, where the rupture event occurs, is unknown. In the current study, we investigated the association between the RRS and radiomics features (RFs) derived from routine magnetic resonance imaging (MRI) that can covey limited information about the biochemistry of the IA tissue. Using 3D image processing software and CFD, we computed the RRS for a series of 25 IAs. From their MRI, we computed 107 RFs from the IA wall of the aneurysms. We identified RFs that were significantly different between high and low-risk aneurysms and evaluated their potential correlation with underlying variables (morphologic and hemodynamic parameters) of RRS. We found 2 RFs were significantly different between high and low-risk aneurysm cases: Flatness and small area low gray level emphasis (SALGLE). Flatness was significantly correlated with the time averaged normalized wall shear stress (WSS) and SALGLE was significantly correlated with size ratio. ROC analysis showed that the Flatness had an AUC of 0.79 and SALGLE had an AUC of 0.72. This preliminary study shows that RFs derived from routine non-invasive MRI imaging could potentially help in risk stratification of newly discovered IAs.