Abstract

Penumbral biomarkers promise to individualize treatment windows in acute ischemic stroke. We used a novel magnetic resonance imaging approach that measures oxygen metabolic index (OMI), a parameter closely related to positron emission tomography-derived cerebral metabolic rate of oxygen utilization (CMRO2), to derive a pair of ischemic thresholds: (1) an irreversible-injury threshold that differentiates ischemic core from penumbra and (2) a reversible-injury threshold that differentiates penumbra from tissue not-at-risk for infarction. Forty patients with acute ischemic stroke underwent magnetic resonance imaging at 3 time points after stroke onset: <4.5 hours (for OMI threshold derivation), 6 hours (to determine reperfusion status), and 1 month (for infarct probability determination). A dynamic susceptibility contrast method measured cerebral blood flow, and an asymmetrical spin echo sequence measured oxygen extraction fraction, to derive OMI (OMI=cerebral blood flow×oxygen extraction fraction). Putative ischemic threshold pairs were iteratively tested using a computation-intensive method to derive infarct probabilities in 3 tissue groups defined by the thresholds (core, penumbra, and not-at-risk tissue). An optimal threshold pair was chosen based on its ability to predict infarction in the core, reperfusion-dependent survival in the penumbra, and survival in not-at-risk tissue. The predictive abilities of the thresholds were then tested within the same cohort using a 10-fold cross-validation method. The optimal OMI ischemic thresholds were found to be 0.28 and 0.42 of normal values in the contralateral hemisphere. Using the 10-fold cross-validation method, median infarct probabilities were 90.6% for core, 89.7% for nonreperfused penumbra, 9.95% for reperfused penumbra, and 6.28% for not-at-risk tissue. OMI thresholds, derived using voxel-based, reperfusion-dependent infarct probabilities, delineated the ischemic penumbra with high predictive ability. These thresholds will require confirmation in an independent patient sample.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.