Manipulation of cortical gray matter oxygenation by hyperoxic respiratory challenge: field dependence of R(2) * and MR signal response

Dependency of the blood oxygen level dependent-response to hyperoxic challenges on the order of gas administration in intracranial malignancies

PURPOSE

Literature reports contradicting results on the response of brain tumors to vascular stimuli measured in T2*-weighted MRI. Here, we analyzed the potential dependency of the MRI-response to (hypercapnic) hyperoxia on the order of the gas administration.

METHODS

T2* values were quantified at 3 Tesla in eight consenting patients at rest and during inhalation of hyperoxic/hypercapnic gas mixtures. Patients were randomly divided into two groups undergoing different gas administration protocols (group A: medical air-pure oxygen-carbogen; group B: medical air-carbogen-pure oxygen). Mann-Whitney U test and Wilcoxon signed rank test have been used to proof differences in T2* regarding respiratory challenge or different groups, respectively.

RESULTS

T2* values at rest for gray and white matter were 50.3 ± 2.6 ms and 46.1 ± 2.0 ms, respectively, and slightly increased during challenge. In tumor areas, T2* at rest were: necrosis = 74.1 ± 10.1 ms; edema = 60.3 ± 17.6 ms; contrast-enhancing lesions = 48.6 ± 20.7 ms; and solid T2-hyperintense lesions = 45.0 ± 3.0 ms. Contrast-enhancing lesions strongly responded to oxygen (+ 20.7%) regardless on the gas protocol (p = 0.482). However, the response to carbogen significantly depended on the order of gas administration (group A, + 18.6%; group B, - 6.4%, p = 0.042). In edemas, a different trend between group was found when breathing oxygen (group A, - 9.9%; group B, + 19.5%, p = 0.057).

CONCLUSION

Preliminary results show a dependency of the T2* response of contrast-enhancing brain tumor lesions on the order of the gas administration. The gas administration protocol is an important factor in the interpretation of the T2*-response in areas of abnormal vascular growth.

Multiparametric measurement of cerebral physiology using calibrated fMRI

The ultimate goal of calibrated fMRI is the quantitative imaging of oxygen metabolism (CMRO₂), and this has been the focus of numerous methods and approaches. However, one underappreciated aspect of this quest is that in the drive to measure CMRO₂, many other physiological parameters of interest are often acquired along the way. This can significantly increase the value of the dataset, providing greater information that is clinically relevant, or detail that can disambiguate the cause of signal variations. This can also be somewhat of a double-edged sword: calibrated fMRI experiments combine multiple parameters into a physiological model that requires multiple steps, thereby providing more opportunity for error propagation and increasing the noise and error of the final derived values. As with all measurements, there is a trade-off between imaging time, spatial resolution, coverage, and accuracy. In this review, we provide a brief overview of the benefits and pitfalls of extracting multiparametric measurements of cerebral physiology through calibrated fMRI experiments.

Field strength dependence of grey matter R2* on venous oxygenation

The relationship between venous blood oxygenation and change in transverse relaxation rate (ΔR2*) plays a key role in calibrated BOLD fMRI. This relationship, defined by the parameter β, has previously been determined using theoretical simulations and experimental measures. However, these earlier studies have been confounded by the change in venous cerebral blood volume (CBV) in response to functional tasks. This study used a double-echo gradient echo EPI scheme in conjunction with a graded isocapnic hyperoxic sequence to assess quantitatively the relationship between the fractional venous blood oxygenation (1−Y_v) and transverse relaxation rate of grey matter (ΔR2⁢GM*), without inducing a change in vCBV.

The results demonstrate that the relationship between ΔR2* and fractional venous oxygenation at all magnet field strengths studied was adequately described by a linear relationship. The gradient of this relationship did not increase monotonically with field strength, which may be attributed to the relative contributions of intravascular and extravascular signals which will vary with both field strength and blood oxygenation.

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We assess the relationship between grey matter R2* and venous oxygenation.

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Isocapnic hyperoxia prevented confounding changes in cerebral blood volume.

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A linear dependency is an appropriate assumption at 1.5, 3 and 7 T.

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Intravascular/extravascular signal ratios will vary with both B0 and oxygenation.

In vivo quantification of cerebral r2*-response to graded hyperoxia at 3 tesla

Objectives:

This study aims to quantify the response of the transverse relaxation rate of the magnetic resonance (MR) signal of the cerebral tissue in healthy volunteers to the administration of air with step-wise increasing percentage of oxygen.

Materials and Methods:

The transverse relaxation rate (R2*) of the MR signal was quantified in seven volunteers under respiratory intake of normobaric gas mixtures containing 21, 50, 75, and 100% oxygen, respectively. End-tidal breath composition, arterial blood saturation (SaO₂), and heart pulse rate were monitored during the challenge. R2* maps were computed from multi-echo, gradient-echo magnetic resonance imaging (MRI) data, acquired at 3.0T. The average values in the segmented white matter (WM) and gray matter (GM) were tested by the analysis of variance (ANOVA), with Bonferroni post-hoc correction. The GM R2*-reactivity to hyperoxia was modeled using the Hill's equation.

Results:

Graded hyperoxia resulted in a progressive and significant (P < 0.05) decrease of the R2* in GM. Under normoxia the GM-R2* was 17.2 ± 1.1 s^-1. At 75% O₂ supply, the R2* had reached a saturation level, with 16.4 ± 0.7 s^-1 (P = 0.02), without a significant further decrease for 100% O₂. The R2*-response of GM correlated positively with CO₂ partial pressure (R = 0.69 ± 0.19) and negatively with SaO₂ (R = -0.74 ± 0.17). The WM showed a similar progressive, but non-significant, decrease in the relaxation rates, with an increase in oxygen intake (P = 0.055). The Hill's model predicted a maximum R2* response of the GM, of 3.5%, with half the maximum at 68% oxygen concentration.

Conclusions:

The GM-R2* responds to hyperoxia in a concentration-dependent manner, suggesting that monitoring and modeling of the R2*-response may provide new oxygenation biomarkers for tumor therapy or assessment of cerebrovascular reactivity in patients.

Quantitative blood oxygenation level-dependent (BOLD) response of the left ventricular myocardium to hyperoxic respiratory challenge at 1.5 and 3.0 T

The aim of this study was to quantify the response of the myocardial transverse relaxation times (ΔT2*) to hyperoxic respiratory challenge (HRC) at different field strengths in an intra-individual comparison of healthy volunteers and in a patient with coronary artery disease. Blood oxygenation level-dependent (BOLD) cardiovascular MR (CMR) data were acquired in 10 healthy volunteers (five women, five men; mean age, 29 ± 3 years; range, 22-35 years) at 1.5 and 3.0 T. Medical air (21% O2 ), pure oxygen and carbogen (95% O2 , 5% CO2 ) were administered in a block-design temporal pattern to induce normoxia, hyperoxia and hyperoxic hypercapnia, respectively. Average T2* times were derived from measurements by two independent and blind readers in 16 standard myocardial segments on three short-axis slices per patient. Inter- and intra-reader correlations of T2* measurements were good [intra-class correlation coefficient (ICC) = 0.75 and ICC = 0.79, both p < 0.001]. During normoxia, the mean T2* times were 29.9 ± 6.1 ms at 1.5 T and 27.1 ± 6.6 ms at 3.0 T. Both hyperoxic gases induced significant (all p < 0.01) T2* increases (∆T2* hyperoxia: 1.5 T, 12.7%; 3.0 T, 11.2%; hyperoxic hypercapnia: 1.5 T, 13.1%; 3.0 T, 17.7%). Analysis of variance (ANOVA) results indicated a significant (both p < 0.001) effect of the inhaled gases on the T2* times at both 1.5 T (F = 17.74) and 3.0 T (F = 39.99). With regard to the patient imaged at 1.5 T, HRC induced significant T2* increases during hyperoxia and hyperoxic hypercapnia in normal myocardial segments, whereas the T2* response was not significant in ischemic segments (p > 0.23). The myocardial ∆T2* response to HRC can reliably be imaged and quantified with BOLD CMR at both 1.5 and 3.0 T. During HRC, hyperoxia and hyperoxic hypercapnia induce a significant increase in T2*, with ∆T2* being largest at 3.0 T and during hyperoxic hypercapnia in normal myocardial segments.