Quantification of whole-brain oxygenation extraction fraction and cerebral metabolic rate of oxygen consumption in adults with sickle cell anemia using individual T2 -based oxygenation calibrations

Abstract

Purpose: To evaluate different T₂ -oxygenation calibrations for estimating venous oxygenation in people with sickle cell anemia (SCA).

Methods: Blood T₂ values were measured at 3 T in the internal jugular veins of 12 healthy volunteers and 11 SCA participants with no history of stroke, recent transfusion, or renal impairment. T₂ -oxygenation relationships of both sickled and normal blood samples were calibrated individually and compared with values generated from published models. After converting venous T₂ values to venous oxygenation, whole-brain oxygen extraction fraction and cerebral metabolic rate of oxygen were calculated.

Results: Sickle blood samples' oxygenation values calculated from our individual calibrations agreed well with measurements using a blood analyzer, whereas previous T₂ calibrations based on normal blood samples showed 13%-19% underestimation. Meanwhile, oxygenation values calculated from previous grouped T₂ calibration for sickle blood agreed well with experimental measurement on averaged values, but showed up to 20% variation for several individual samples. Using individual T₂ calibrations, the whole-brain oxygen extraction fraction and cerebral metabolic rate of oxygen of SCA participants were 0.38 ± 0.08 and 172 ± 42 µmol/min/100 g, respectively, which were comparable to those values measured on healthy volunteers.

Conclusion: Our results confirm that sickle blood T₂ values not only depend on the hematocrit and oxygenation values, but also on other hematological factors. The individual T₂ calibrations minimized the effect of heterogeneity of sickle blood between different SCA populations and improved the accuracy of T₂ -based oximetry. The measured oxygen extraction fraction and cerebral metabolic rate of oxygen of this group of SCA participants were found to not differ significantly from those of healthy individuals.

Keywords: CMRO2; HbS; OEF; T2 oximetry; blood T2; sickle cell disease.

Figure 1.

In vivo and in vitro experiments to determine blood T₂ for one SCA participant. A representative image at the shortest TE_corr (a) in a slice through the IJV and (b) on a blood sample drawn from the same participant. The average intensities of each ROI (red) were fitted as a function of TE_corr using a single exponential decay function, I = A×exp(−TE_corr/T₂), for the in vivo (c) and in vitro (d) experiments.

Figure 2.

The individual fittings (black lines) of sickle blood R₂ (black dots) as a function of oxygenations in samples from different SCA volunteers. The R₂-(1-Y) curves calculated using Bush-Wood’s grouped calibration model from sickle blood (blue lines), Bush Wood’s grouped calibration from normal blood (red lines) and Lu’s grouped calibration from normal blood (magenta lines) are also shown.

Figure 3.

The correlation and agreement (Bland-Altman) plots between the measured Y_Observe of sickled blood samples from the blood analyzer and predicted Y_cal from four T₂-Y calibrations: (a) the individual calibration developed in this study; (b) Bush-Wood’s group calibration for sickle blood c) Bush-Wood’s group calibration for normal blood; (d) Lu’s group calibration for normal blood; The average $\overline{\text{Δ}}$ and standard deviation (σ_Δ) of the difference between predicted and measured Y are labeled in the plots. The dashed lines in the agreement plot represent two times the standard deviation from the mean difference.

Figure 4.

The correlation of the coefficients A₁ (a,c) and A₂ (b,d) in the individual calculation (Eq. 1) with Hct and the percentage of sickle hemoglobin relative to the total hemoglobin (HbS%). The black dots represent A₁ and A₂ of each individual calibration from healthy volunteers, while the red dots represent A₁ and A₂ of each individual calibration from participants with SCA. The solid lines represent the linear fitting of the data and the correlation coefficients (r) are also given in the plot.

Figure 5:

Hct dependence of a) CBF, b) DO₂, c) OEF, and d) CMRO₂ for SCA participants (red) and healthy volunteers (black). In contrast to inverse correlations between Hct and CBF (a), no significant correlation between Hct and DO₂ (b), OEF (c), CMRO₂ (d) were observed. Linear fitting results were shown as solid lines for SCA participants (red) and healthy volunteers (black) in (a) while mean values of DO₂ (b), OEF (c) and CMRO₂ (d) were shown as solid lines with 95% confidence intervals (+/−1.96 standard deviation) as dash lines.