Automated three-dimensional signature model for assessing brain injury in emergent stroke

K. M.A. Welch, V. Nagesh, L. D. D'Olhaberriague, Z. G. Zhang, M. D. Boska, S. Patel, J. P. Windham

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

This presentation will focus on the value of established and newer MR methods that can be applied to the diagnosis and management of ischemic stroke with emphasis on future applications of MR to provide previously unmet needs of the treating clinician and clinical trials. Time alone is an inadequate indicator of the therapeutic window, especially when the time of stroke onset is uncertain. Thus, there is a need to predict the evolution of stroke in a way that more precisely and with greater resolution identifies the progression of cellular damage at the moment of investigation. This also would be of value for thrombolysis when knowledge of the degree and extent of tissue necrosis and the consequent potential for brain hemorrhage is of the utmost importance. To provide this, we perform postprocessing of diffusion-, T1- and T2-weighted images to produce the apparent diffusion coefficient of water, and T1 and T2 maps that are then further processed to provide maps and quantitation of the tissue signatures of ischemic histopathology. By these means, we can accomplish objective volumetric analysis of infarct size and of the proportions of potentially viable and salvageable tissue. We will show how this has the potential to predict long-term stroke outcome and facilitate decision-making in terms of safety of reperfusion strategies and the appropriateness of cytoprotective treatment. The value of our approach is to replace time as the therapeutic window and extend the opportunity of treatment to those patients presenting beyond the stringent time limits employed in current investigative clinical trials. Further, used as a surrogate marker of clinical outcome, this form of stroke analysis may speed proof of principle clinical trials in small numbers of stroke patients.

Original languageEnglish (US)
Pages (from-to)9-14
Number of pages6
JournalCerebrovascular Diseases
Volume11
Issue numberSUPPL. 1
DOIs
StatePublished - 2001

Keywords

  • Apparent diffusion coefficient of water
  • MRI techniques
  • Stroke analysis
  • T-weighted images

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine

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  • Cite this

    Welch, K. M. A., Nagesh, V., D'Olhaberriague, L. D., Zhang, Z. G., Boska, M. D., Patel, S., & Windham, J. P. (2001). Automated three-dimensional signature model for assessing brain injury in emergent stroke. Cerebrovascular Diseases, 11(SUPPL. 1), 9-14. https://doi.org/10.1159/000049120