Perfusion Quantification in the Human Brain Using DSC MRI - Simulations and Validations at 3T

Gadolinium (Gd) and deoxyhemoglobin (dOHb) are paramagnetic contrast agents capable of inducing changes in T2*-weighted MRI signal, utilized in dynamic susceptibility contrast (DSC) MRI. With multiple contrast agents and analysis choices, there are a variety of questions as to its capability to accurately quantify perfusion values. To address these questions, we developed a novel signal model for DSC MRI that incorporates signal contributions from intravascular and extravascular water proton spins at 3T for arterial, venous, and cerebral tissue voxels. This framework allowed us to model the MRI signal in response to changes in Gd and dOHb concentrations, and the effects that various experimental and tissue parameters have on perfusion quantification. We compared the predictions of the numerical simulations with those obtained from experimental data at 3T on six healthy human subjects using Gd and dOHb boluses as contrast agents. Using standard DSC analysis, we identified perfusion quantification dependencies in the experimental results that were in close agreement with the simulations. We found that a reduced baseline oxygen saturation (base-SaO2), greater susceptibility of applied contrast agent (Gd vs dOHb), and larger magnitude of the hypoxic drop ({Delta}SaO2) reduces overestimation of the cerebral blood volume (rCBV) and flow (rCBF). Furthermore, shortening the bolus duration increases the accuracy and reduces the calculated values of mean transit time (MTT). This study demonstrates that changes in Gd and dOHb can be described by the same unifying theoretical framework, as validated by the experimental results. Based on our work, we suggest practices in DSC MRI that increase accuracy and reduce inter- and intra-subject variability. In uncovering a wide array of quantification dependencies, we argue that caution must be exercised when comparing perfusion values obtained from a standard DSC MRI analysis when employing different experimental paradigms.