Development of a new tool to correlate stroke outcome with infarct topography: a proof-of-concept study

Thanh G. Phan, Jian Chen, Geoffrey Donnan, Velandai Srikanth, Amanda Wood, David C. Reutens

Research output: Contribution to journalArticlepeer-review


Improving the ability to assess potential stroke deficit may aid the selection of patients most likely to benefit from acute stroke therapies. Methods based only on ‘at risk’ volumes or initial neurological condition do predict eventual outcome, but not perfectly. Given the close relationship between anatomy and function in the brain, we performed a proof-of-concept study to examine how well stroke outcome correlated with infarct location and extent. A prospective study of 60 patients with ischemic stroke (38 in the training set and 22 in the validation set), using an implementation of partial least squares with penalized logistic regression (PLS-PLR), was performed. The method yielded a model relating location of infarction (on a voxel-by-voxel basis) and neurological deficits. The area under the receiver operating characteristics curve (AUC) method was used to assess the accuracy of the method for predicting outcome. In the validation phase, this model indicated the presence of neglect (AUC 0.89), aphasia (AUC 0.79), right-arm motor deficit (0.94), and right-leg motor deficit (AUC 0.94) but less accurately indicated left-arm motor deficit (0.52) and left-leg motor deficit (0.69). The model indicated no to mild disability (Rankin ≤ 2) versus moderate to severe disability (Rankin > 2) with AUC 0.78. In this proof-of-concept study, we have demonstrated that stroke outcome correlates well with infarct location raising the possibility of accurate prediction of neurological deficit in the individual stroke patient using only information on infarct location and multivariate regression methods.
Original languageEnglish
Pages (from-to)127-133
Number of pages7
Issue number1
Early online date4 Aug 2009
Publication statusPublished - 1 Jan 2010


  • stroke outcome
  • prediction
  • digital
  • atlas


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