  The volume of stroke lesion is the gold standard for predicting the clinical
outcome of stroke patients. However, the presence of stroke lesion may cause
neural disruptions to other brain regions, and these potentially damaged
regions may affect the clinical outcome of stroke patients. In this paper, we
introduce the tractographic feature to capture these potentially damaged
regions and predict the modified Rankin Scale (mRS), which is a widely used
outcome measure in stroke clinical trials. The tractographic feature is built
from the stroke lesion and average connectome information from a group of
normal subjects. The tractographic feature takes into account different
functional regions that may be affected by the stroke, thus complementing the
commonly used stroke volume features. The proposed tractographic feature is
tested on a public stroke benchmark Ischemic Stroke Lesion Segmentation 2017
and achieves higher accuracy than the stroke volume and the state-of-the-art
feature on predicting the mRS grades of stroke patients. In addition, the
tractographic feature also yields a lower average absolute error than the
commonly used stroke volume feature.
