A supervised method for calculating perfusion/diffusion mismatch volume in acute ischemic stroke

Judy R. James, Karmen K. Yoder, Olaniyi Osuntokun, Andrew Kalnin, Askiel Bruno, Evan D. Morris

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Diffusion and perfusion (MR) imaging modalities identify overlapping but not identical areas of tissue as lesion following a stroke. It is thought that the 'mismatch' between modalities may represent tissue that could be recovered with proper (thrombolytic) treatment. We have designed a tool for semi-automated segmentation of the images and calculation of the mismatch volume. We present results from software phantoms and clinical data. Phantom results show our mismatch volume calculations are unbiased at realistic noise levels. Clinical data show that raters using our tool are consistent, fast (15 min per subject) and indistinguishable from an expert using manual segmentation.

Original languageEnglish (US)
Pages (from-to)1268-1287
Number of pages20
JournalComputers in Biology and Medicine
Volume36
Issue number11
DOIs
StatePublished - Nov 2006
Externally publishedYes

Keywords

  • Diffusion
  • Mismatch volume
  • Penumbra
  • Perfusion
  • Segmentation
  • Stroke

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications

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