Radiomics using non-contrast CT to predict hemorrhagic transformation risk in stroke patients undergoing revascularization

ConclusionsThe radiomics model can predict hemorrhagic transformation using NCCT in stroke patients. Low Hounsfield unit was a strong predictor of hemorrhagic transformation, while textural features alone can predict hemorrhagic transformation.Clinical relevance statementUsing radiomic features extracted from initial non-contrast computed tomography, early prediction of hemorrhagic transformation has the potential to improve patient care and outcomes by aiding in personalized treatment decision-making and early identification of at-risk patients.Key Points• Predicting hemorrhagic transformation following thrombolysis in stroke is challenging since multiple factors are associated.• Radiomics features of infarcted tissue on initial non-contrast CT are associated with hemorrhagic transformation.• Textural features on non-contrast CT are associated with the frailty of the infarcted tissue.
Source: European Radiology - Category: Radiology Source Type: research