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 deoxyhaemoglobin (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 grey 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.
Quantitative functional BOLD (qfBOLD): A combined gradient-echo and spin-echo framework for oxygen extraction fraction (OEF) mapping with functional MRI
Chiarelli A. M.;Chalet L.;Pomante S.;Di Censo D.;Caporale A.;Biondetti E.;Rocco G.;Carriero M.;Graziano F.;Fear E. J.;Wise R. G.;
2026-01-01
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 deoxyhaemoglobin (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 grey 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
