Dynamic susceptibility contrast perfusion MRI using phase-based venous output functions: comparison with pseudo-continuous arterial spin labelling and assessment of contrast agent concentration in large veins

Dynamic contrast-enhanced QSM for perfusion imaging: a systematic comparison of ΔR2*- and QSM-based contrast agent concentration time curves in blood and tissue

OBJECTIVE

In dynamic susceptibility contrast MRI (DSC-MRI), an arterial input function (AIF) is required to quantify perfusion. However, estimation of the concentration of contrast agent (CA) from magnitude MRI signal data is challenging. A reasonable alternative would be to quantify CA concentration using quantitative susceptibility mapping (QSM), as the CA alters the magnetic susceptibility in proportion to its concentration.

MATERIAL AND METHODS

AIFs with reasonable appearance, selected on the basis of conventional criteria related to timing, shape, and peak concentration, were registered from both ΔR2* and QSM images and mutually compared by visual inspection. Both ΔR2*- and QSM-based AIFs were used for perfusion calculations based on tissue concentration data from ΔR2*as well as QSM images.

RESULTS

AIFs based on ΔR2* and QSM data showed very similar shapes and the estimated cerebral blood flow values and mean transit times were similar. Analysis of corresponding ΔR2* versus QSM-based concentration estimates yielded a transverse relaxivity estimate of 89 s^-1 mM^-1, for voxels identified as useful AIF candidate in ΔR2* images according to the conventional criteria.

DISCUSSION

Interestingly, arterial concentration time curves based on ΔR2* versus QSM data, for a standard DSC-MRI experiment, were generally very similar in shape, and the relaxivity obtained in voxels representing blood was similar to tissue relaxivity obtained in previous studies.

In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound

Over the past decades, the field of in vivo magnetic resonance (MR) has built up an impressive repertoire of data acquisition and analysis technologies for anatomical, functional, physiological, and molecular imaging, the description of which requires many book volumes. As such it is impossible for a few authors to have an authoritative overview of the field and for a brief article to be inclusive. We will therefore focus mainly on data acquisition and attempt to give some insight into the principles underlying current advanced methods in the field and the potential for further innovation. In our view, the foreseeable future is expected to show continued rapid progress, for instance in imaging of microscopic tissue properties in vivo, assessment of functional and anatomical connectivity, higher resolution physiologic and metabolic imaging, and even imaging of receptor binding. In addition, acquisition speed and information content will continue to increase due to the continuous development of approaches for parallel imaging (including simultaneous multi-slice imaging), compressed sensing, and MRI fingerprinting. Finally, artificial intelligence approaches are becoming more realistic and will have a tremendous effect on both acquisition and analysis strategies. Together, these developments will continue to provide opportunity for scientific discovery and, in combination with large data sets from other fields such as genomics, allow the ultimate realization of precision medicine in the clinic.

Dynamic Susceptibility Contrast MRI at 7 T: Tail-Scaling Analysis and Inferences About Field Strength Dependence

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) following bolus injection of gadolinium contrast agent (CA) is widely used for the estimation of brain perfusion parameters such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) for both clinical and research purposes. Although it is predicted that DSC-MRI will have superior performance at high magnetic field strengths, to the best of our knowledge, there are no reports of 7 T DSC-MRI in the literature. It is plausible that the transfer of DSC-MRI to 7 T may be accompanied by increased R₂* relaxivity in tissue and a larger difference in ΔR₂*-versus-concentration relationships between tissue and large vessels. If not accounted for, this will subsequently result in apparent CBV and CBF estimates that are higher than those reported previously at lower field strengths. The aims of this study were therefore to assess the feasibility of 7 T DSC-MRI and to investigate the apparent field-strength dependence of CBV and CBF estimates. In total, 8 healthy volunteers were examined using DSC-MRI at 7 T. A reduced CA dose of 0.05 mmol/kg was administered to decrease susceptibility artifacts. CBV, CBF, and MTT maps were calculated using standard DSC-MRI tracer-kinetic theory. Subject-specific arterial partial volume correction factors were obtained using a tail-scaling approach. Compared with literature values obtained using the tail-scaling approach at 1.5 T and 3 T, the CBV and CBF values of the present study were found to be further overestimated. This observation is potentially related to an inferred field-strength dependence of transverse relaxivities, although issues related to the CA dose must also be considered.

Assessment of MRI contrast agent concentration by quantitative susceptibility mapping (QSM): application to estimation of cerebral blood volume during steady state

Objective

One major issue in dynamic susceptibility contrast MRI (DSC-MRI) is to accurately determine contrast agent (CA) concentration, since T2* relaxivity in vivo is generally unknown and varies between blood and tissue. In this study, quantitative susceptibility mapping (QSM) was used for quantification of CA concentration.

Materials and methods

A DSC-MRI protocol, including phase data acquisition, was applied to 20 healthy volunteers in a test–retest study. By selecting a CSF reference region of interest (ROI), the values of all QSM images were shifted to show no CA-induced change in CSF. CA concentration and cerebral blood volume (CBV) were estimated using shifted QSM data. CSF reference ROI optimization was evaluated by investigation of CBV repeatability. The CBV age dependence was analysed and tissue T2* relaxivity was estimated.

Results

The best repeatability of CBV, using an optimal CSF reference ROI, showed test-versus-retest correlations of r = 0.81 and r = 0.91 for white and grey matter, respectively. A slight CBV decrease with age was observed, and the estimated in vivo T2* relaxivity was 85 mM⁻¹s⁻¹.

Conclusion

Provided that a carefully selected CSF reference ROI is used to shift QSM image values, susceptibility information can be used to estimate concentration of contrast agent and to calculate CBV.

Electronic supplementary material

The online version of this article (doi:10.1007/s10334-017-0637-9) contains supplementary material, which is available to authorized users.