Synopsis

¹⁷O MRI can be used to quantify metabolic rates of oxygen consumption. The use of ¹⁷O methods is currently still complicated as the SNR of ¹⁷O is very low, and the spatial resolution is limited. Nevertheless, reliable measurements of the cerebral metabolic rate of oxygen consumption have been performed that are in good agreement with values from ¹⁵O PET.

Target Audience

Objectives

Participants of this lecture will

• become acquainted with the fundamental principles of ¹⁷O MRI
• learn methods to determine metabolic rates of oxygen consumption from dynamic ¹⁷O MRI measurements
• be able to identify strengths and weaknesses of these methods
• compare the methods to other techniques such as PET

Introduction

Dynamic Oxygen-17 MRI

To measure metabolic rates with ¹⁷O MRI, several different components must be available: a system to administer the gaseous tracer ¹⁷O, a broadband RF transmit system for RF excitation at the ¹⁷O frequency, a dedicated ¹⁷O Tx/Rx coil, an optimized pulse sequence to acquire a dynamic image series, and a post-processing framework to calculate the metabolic rates using pharmaco-kinetic modeling.

In general, ¹⁷O MRI and MRS is challenging due to the extreme properties of the ¹⁷O nucleus: the natural abundance of ¹⁷O is only 0.037% and the gyromagnetic ratio of the ¹⁷O nucleus is approximately sevenfold lower than that of protons, which results in a relative sensitivity of 1.1·10^-5 compared to ¹H. To overcome this low sensitivity, direct detection of the ¹⁷O MR signal has been predominantly performed at ultra-high magnetic fields (UHFs) of 7 T and 9.4 T. UHF MR systems are unfortunately not widely available, and are not yet used in clinical routine. Recently, feasibility of direct ¹⁷O MRI has been reported in human brain and heart at clinical field strengths of 3 T, so that the implementation MRO₂ quantification at clinical MR systems seems feasible.

To study the oxygen metabolism, isotope-enriched ¹⁷O with up to 70% enrichment factors is inhaled, and the change in ¹⁷O MRI signal is monitored in the target organ (mostly, the brain). In the previous studies, a re-breathing system was implemented for efficient usage of rare and expensive ¹⁷O₂ gas by re-inhalation of the stored ¹⁷O₂ gas in subsequent inhalation cycles. Unfortunately, this delivery method leads to uncertainties in the determination of the ¹⁷O enrichment fraction of the inhaled gas, which in turn can lead to systematic errors in the quantities derived from this enrichment fraction.

Another limitation of ¹⁷O MRI is the short relaxation times of H₂¹⁷O. With a T2* on the order of 2-3 ms, pulse sequences with very short echo times are required. Thus, ¹⁷O MRI is preferably performed with ultra-short TE (UTE) pulse sequences which acquire k-space data radially and which can achieve TEs as low as 40 μs. Radial UTE k-space sampling is often performed in combination with a density compensated gradient encoding scheme to increase the SNR and to optimize the point spread function. Due to the short T1 of only 4-6 ms, UTE data acquisition can be realized with short repetition times and high flip angles (TR = 4-8 ms, α = 30°-70°) without saturating the weak ¹⁷O MR signal.

An advantage of the UTE data acquisition is the possibility to trade the spatial resolution against the temporal resolution. In dynamic UTE acquisitions radial k-space sampling is repeated many times, and with a suitable ordering of the radial k-space spokes (e.g. using a Golden Angle scheme) temporal and spatial resolution can be selected after the acquisition. Typically, a spatial resolution of 8-10 mm is used and a temporal acquisition window of 1-2 min is selected.

Calculation of Metabolic Rates

From the dynamic ¹⁷O MRI experiment the time evolution of the ¹⁷O MR signal is extracted either in a pixel-wise manner or for selected anatomical regions. If TR is not too short, the ¹⁷O MR signal can be assumed to be linearly correlated with the concentration of ¹⁷O due to the short T1. The signal is exclusively representing the H₂¹⁷O concentration, as the ¹⁷O₂ molecules bound to hemoglobin in the blood or in the gas phase cannot be detected. Thus, the observed ¹⁷O MR signal increase after gas inhalation is only proportional to the amount of the metabolized H₂¹⁷O water.

To convert the ¹⁷O MR signal into H₂¹⁷O concentration in µmol per gram tissue, the ¹⁷O signal intensities are normalized to the baseline phase (i.e., before gas inhalation). Using coregistered ¹H image data (e.g., an MPRAGE data set) and the H₂¹⁷O natural abundance of 20.56 µmol/gwater, water partition coefficients and averaged density of brain tissue of 1.038 g/mL, the signal can be converted into absolute concentration values. In a next step the signal-time curves are fitted to a pharmaco-kinetic model. According to the principle of mass conservation, the change of the H₂¹⁷O concentration within a given volume can be caused either by water creation and conversion to other intermediates in the volume, or inward and outward diffusion between neighboring volumes. For the brain, a cerebral MRO₂ (CMRO₂) quantification model was proposed by Atkinson and Thulborn. The model can be modified to account for pulsed supply of ¹⁷O gas that is often used in an experimental setup with a demand oxygen delivery system (DODS).

One fit parameter of the model is CMRO₂. In parameter fitting, practical and structural parameter identifiability needs to be investigated to assess the reliability of the fitting results. For example, practical non-identifiability can arise, if data is too noisy, and structurally non-identifiability is observed if the numerical model does not properly describe the measured data. For the identifiability analysis a profile likelihood (PL) method can be used. In PL, confidence intervals (CI) are not based on Fisher information theory which cannot be applied for nonlinear models as the CMRO₂ quantification model. The PL analysis of the modified Atkinson model shows that CMRO₂ can only be quantified reliably if the ¹⁷O enrichment fraction is used as prior information in the model fit.

In the brain, CMRO₂ values of about 0.8-1.1 µmol/g_tissue/min have been found with ¹⁷O MRI in white brain matter, whereas a higher value of 1.1-1.8 µmol/g_tissue/min was observed in gray brain matter. These results are in good agreement with reference values from ¹⁵O PET which is the only clinically established method for direct oxygen quantification. ¹⁵O PET, however, is difficult to implement clinically due to the short isotope half‑life of only 2 min, which requires costly on-site production. Deviations between the PET and the MR measurement can be explained by partial volume effects which are caused by the low resolution of ¹⁷O MRI and the additional blurring due to signal decay during the UTE readout. To overcome these limitations, partial volume models based on prior ¹H information can be used. With these models, even different compartments can be studied in a lesion such as the necrotic core, the hyperintense rim and the surrounding edema in a glioblastoma.

Acknowledgements

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