EXPRESS: Quantitative functional BOLD (qfBOLD): A Combined Gradient-Echo and Spin-Echo Framework for Oxygen Extraction Fraction (OEF) Mapping with functional MRI

We present a novel framework for OEF mapping with MRI, based on temporal variations in Gradient Echo (GE) and Spin-Echo (SE) BOLD signals induced by isometabolic modulations in CBF. This approach, termed quantitative functional BOLD (qfBOLD), exploits dynamic variations in relaxation times rather than measuring baseline values as in qBOLD, thereby isolating deoxyhemoglobin (dHb) effects. The interaction between dHb-induced extravascular field distortions and water diffusion allows for decoupling OEF and dHb-sensitive cerebral blood volume with a single modulation in brain physiology. Furthermore, the method avoids functional CBF measures via Arterial Spin Labelling which is required by calibrated (c)fMRI. This advancement may enhance signal-to-noise ratio and spatiotemporal resolution, making qfBOLD applicable to both gray matter (GM) and white matter (WM). Monte Carlo simulations were used to investigate the method. In vivo feasibility assessment using a hypercapnic breath-holding task yielded OEF values of 37.0±2.9% and 41.6±2.9% in GM and WM, respectively, and significant correlations with cfMRI in GM (qfBOLD vs. cfMRI r=0.71, p<10-3) and with relaxometry-based measures in the superior sagittal sinus (GM qfBOLD vs. TRUST r=0.51, p<0.05, WM qfBOLD vs. TRUST r=0.61, p<0.01). Future efforts will aim to improve the method's accuracy by attenuating intravascular signals and by refining WM modelling.

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Publication Details

Journal
Journal of Cerebral Blood Flow & Metabolism
Published
2026-05-28
DOI
https://doi.org/10.1177/0271678x261453807
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

EXPRESS: Quantitative functional BOLD (qfBOLD): A Combined Gradient-Echo and Spin-Echo Framework for Oxygen Extraction Fraction (OEF) Mapping with functional MRI

Antonio Maria Chiarelli, Domenico Zacà, Giulia Rocco, Emma Biondetti et al.
Journal of Cerebral Blood Flow & Metabolism
Advanced MRI Techniques and Applications
article

EXPRESS: Quantitative functional BOLD (qfBOLD): A Combined Gradient-Echo and Spin-Echo Framework for Oxygen Extraction Fraction (OEF) Mapping with functional MRI

Antonio Maria Chiarelli, Domenico Zacà, Giulia Rocco, Emma Biondetti, Lucie Chalet, Davide Di Censo, Alessandra Caporale, Manuela Carriero, Sara Pomante, Fabrizio Fasano, Elizabeth J Fear, Richard G Wise, Francesca Graziano, Maria Eugenia Caligiuri, Michael Germuska
article en

Abstract

We present a novel framework for OEF mapping with MRI, based on temporal variations in Gradient Echo (GE) and Spin-Echo (SE) BOLD signals induced by isometabolic modulations in CBF. This approach, termed quantitative functional BOLD (qfBOLD), exploits dynamic variations in relaxation times rather than measuring baseline values as in qBOLD, thereby isolating deoxyhemoglobin (dHb) effects. The interaction between dHb-induced extravascular field distortions and water diffusion allows for decoupling OEF and dHb-sensitive cerebral blood volume with a single modulation in brain physiology. Furthermore, the method avoids functional CBF measures via Arterial Spin Labelling which is required by calibrated (c)fMRI. This advancement may enhance signal-to-noise ratio and spatiotemporal resolution, making qfBOLD applicable to both gray matter (GM) and white matter (WM). Monte Carlo simulations were used to investigate the method. In vivo feasibility assessment using a hypercapnic breath-holding task yielded OEF values of 37.0±2.9% and 41.6±2.9% in GM and WM, respectively, and significant correlations with cfMRI in GM (qfBOLD vs. cfMRI r=0.71, p<10-3) and with relaxometry-based measures in the superior sagittal sinus (GM qfBOLD vs. TRUST r=0.51, p<0.05, WM qfBOLD vs. TRUST r=0.61, p<0.01). Future efforts will aim to improve the method's accuracy by attenuating intravascular signals and by refining WM modelling.

Journal of Cerebral Blood Flow & Metabolism
Magna Graecia University (IT), University of Chieti-Pescara (IT), Siemens (Italy) (IT), Siemens Healthcare (United States) (US), Siemens Healthineers (Germany) (DE), University of California Davis Medical Center (US)
Wellcome Trust, European Commission, Engineering and Physical Sciences Research Council
Clean water and sanitation
Openalex Percentile: Top 6%
Advanced MRI Techniques and Applications
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