Association between MR-derived oxygen extraction fraction and neurological improvement at 24–72 h after successful reperfusion

Oxygen Extraction Fraction (OEF) reflects metabolic changes in cerebral tissue resulting from ischemia and serves as a biomarker of tissue viability in hyperacute stroke. This study evaluated the association between infarct OEF and neurological improvement in ischemic stroke patients following successful endovascular reperfusion therapy, defined by the modified Thrombolysis in Cerebral Infarction (mTICI) score. Infarct OEF index values were extracted from OEF maps using manually delineated infarct regions, 24-72 h post-reperfusion in fifty ischemic stroke patients. Multivariable linear regression analyses analysed the association between neurological improvement defined as improvement in the National Institutes of Health Stroke Scale (ΔNIHSS) and infarct OEF. Linear regression showed a non-significant association between infarct OEF index and ΔNIHSS (β = -0.369, 95 % CI = -3.265-2.526, p = 0.796), and a significant interaction of infarct OEF index and reperfusion status (β = 4.288, 95 %CI: 0.377-8.199, p = 0.033) with ΔNIHSS. A subgroup analysis of the patients with full angiographic reperfusion (mTICI 3) showed a significant association between infarct OEF index and ΔNIHSS (β = 4.937, 95 %CI: 0.188-9.685, p = 0.043). The results demonstrate that post-thrombectomy, OEF in conjunction with reperfusion status could be a surrogate marker of tissue viability in acute post-reperfusion period. Clinical trial registration number for Post-Reperfusion Pathophysiology in Acute Ischemic Stroke (PRAISE): ACTRN12624000629538.

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Journal
European Journal of Radiology
Published
2025-11-20
DOI
https://doi.org/10.1016/j.ejrad.2025.112523
Primary Topic
Advanced MRI Techniques and Applications
Type
article
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article

Association between MR-derived oxygen extraction fraction and neurological improvement at 24–72 h after successful reperfusion

Vijay Venkatraman, Patricia Desmond, Victoria Mercy Kataike, Christopher Steward et al.
European Journal of Radiology
Advanced MRI Techniques and Applications
article

Association between MR-derived oxygen extraction fraction and neurological improvement at 24–72 h after successful reperfusion

Vijay Venkatraman, Patricia Desmond, Victoria Mercy Kataike, Christopher Steward, Felix Ng, Peter Mitchell, Bruce C.V. Campbell
article en

Abstract

Oxygen Extraction Fraction (OEF) reflects metabolic changes in cerebral tissue resulting from ischemia and serves as a biomarker of tissue viability in hyperacute stroke. This study evaluated the association between infarct OEF and neurological improvement in ischemic stroke patients following successful endovascular reperfusion therapy, defined by the modified Thrombolysis in Cerebral Infarction (mTICI) score. Infarct OEF index values were extracted from OEF maps using manually delineated infarct regions, 24-72 h post-reperfusion in fifty ischemic stroke patients. Multivariable linear regression analyses analysed the association between neurological improvement defined as improvement in the National Institutes of Health Stroke Scale (ΔNIHSS) and infarct OEF. Linear regression showed a non-significant association between infarct OEF index and ΔNIHSS (β = -0.369, 95 % CI = -3.265-2.526, p = 0.796), and a significant interaction of infarct OEF index and reperfusion status (β = 4.288, 95 %CI: 0.377-8.199, p = 0.033) with ΔNIHSS. A subgroup analysis of the patients with full angiographic reperfusion (mTICI 3) showed a significant association between infarct OEF index and ΔNIHSS (β = 4.937, 95 %CI: 0.188-9.685, p = 0.043). The results demonstrate that post-thrombectomy, OEF in conjunction with reperfusion status could be a surrogate marker of tissue viability in acute post-reperfusion period. Clinical trial registration number for Post-Reperfusion Pathophysiology in Acute Ischemic Stroke (PRAISE): ACTRN12624000629538.

European Journal of RadiologyVol. 194
The Royal Melbourne Hospital (AU), The University of Melbourne (AU)
Openalex Percentile: Top 50%
Advanced MRI Techniques and Applications
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