Individualized quantification of the benefit from reperfusion therapy using stroke predictive models

Recent imaging developments have shown the potential of voxel‐based models in assessing infarct growth after stroke. Many models have been proposed but their relevance in predicting the benefit of a reperfusion therapy remains unclear. We searched for a predictive model whose volumetric predictions would identify stroke patients who are to benefit from tissue plasminogen activator (t‐PA)‐induced reperfusion.