Separation of perfusion signals from diffusion-weighted image series enabled by independent component analysis

J Neuroimaging. 2011 Oct;21(4):384-94. doi: 10.1111/j.1552-6569.2010.00514.x. Epub 2010 Oct 26.

Abstract

Background and purpose: An important task in diagnostic imaging of acute ischemic stroke is to identify the so-called diffusion-perfusion mismatch area. We aimed to investigate the possibility of facilitating the identification process by combining independent component analysis (ICA) and diffusion-weighted MRI (DWI), with the expectation that this would eliminate the need for additional perfusion imaging to delineate perfusion lesion.

Methods: Simulations were performed to confirm the utility of an intuitively determined sequence of 14 b-factors ranging from 0 to 1,000 seconds/mm(2) for ICA separation of perfusion lesion. Corresponding DWI data from 2 stroke patients, 1 in the acute and 1 in the subacute phase, were decomposed into independent component (IC) maps, and their b-dependent amplitude decay profiles were subjected to multiexponential fitting.

Results: Low-perfusion areas were successfully delineated on IC maps in both patients. Comparison with the areas of diffusion lesion identifiable on relatively high b-factor images in the DWI data, for example, those at b= 1,000 seconds/mm(2) , allowed the mismatch to be identified.

Conclusion: This study demonstrates that combining ICA and DWI enables noninvasive mapping of sluggish perfusion provided an appropriate b-sequence is applied, and that it thereby facilitates the identification of diffusion-perfusion mismatch.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Brain / pathology*
  • Brain Ischemia / pathology
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Middle Aged
  • Neuroimaging / methods*
  • Stroke / pathology