The use of DSC-MRI for the assessment of tumor perfusion can be confounded when the blood brain barrier is disrupted, which can result in additional extravascular T₁ and T₂^*contrast agent (CA) leakage effects [1,2]. Unless corrected for leakage effects confound the reliable measure of cerebral blood volume (CBV) [1]. One strategy to reduce T₁ leakage effects is through the use of a pre-load of contrast agent. Numerous pre-load dosing schemes have been used with varying contrast agent doses (up to 2.5 times the recommended dose) and times between the pre-load and primary bolus injection. Given the recent reports of toxicity and prolonged accumulation of Gd-based CAs there is a push to minimize the total dose a patient receives. All of these factors make it challenging to standardize DSC-MRI methods because the reliability of the CBV measures derived from different pre-load dosing schemes is unknown and practically difficult to assess in vivo. The goal of this study is to leverage our recently proposed DSC-MRI simulation toolbox to investigate the influence of pre-load dosing dosing schemes on the reliability of DSC-MRI data. To replicate in vivo DSC-MRI signal from a representative tumor ROI we used an efficient computational approach termed the Finite Perturber Finite Difference Method (FPFDM) based on a 3D tissue structure composed of packed ellipsoids and a fractal based vascular tree [3]. Representative in vivo physical and physiological parameters data such as, v_e ,CBV (v_p), CBF, K^trans along with simulated AIF were used as an input in pharmacokinetic two compartmental model to compute the vascular and extravascular extracellular space CA concentration (C_p and C_e) time curves. The resulting C_p and C_e curves, the simulated tissue structures were then used to compute simulated ΔR₂^* time curves using the FPFDM. The DSC-MRI signal was then calculated using the computed ΔR₁ and ΔR₂^* time curves [3]. The Weisskoff method is then applied to correct for T₁ and T₂^* leakage effects [1]. The corrected ΔR₂^* time curves were used to calculate CBV values and compared with CBV values calculated for tissues with no CA leakage (K^trans = 0). To demonstrate the influence of CA dosing scheme the simulation was repeated for five pre-load and bolus injection combinations (full dose followed by full dose, half dose followed by full dose, no pre-load followed by full dose, half dose followed by half dose and a quarter dose followed by three quarter dose). Figure 1A shows an example model tissue consisting of packed ellipsoid cells and fractal vascular tree. Figure 1B shows FPFDM computed ΔR₂^* time series without T₁ effects for each dose combination. These curves illustrate that increasing the pre-load and total dose yields greater T₂^* leakage effects. Figure 1C shows the computed DSC-MRI signals, reflecting both the T₁ and T₂^* changes. As expected the no pre load case (0-1) exhibits a significant T₁ leakage effect as indicated by the signal over shot whereas the T₁ effect is reduced and T₂^* effects are enhanced as the pre-load concentration increases (e.g. 1-1). Figure 1D shows the ΔR₂^* time curves computed using these signals. Figure 1E shows ΔR₂^* time curves corrected for leakage effects using the Weisskoff model. Corrected curves exhibit the expected decrease in leakage effects. The corrected ΔR₂^* time curves are used to calculate CBV values for each case and were compared with the respective CBV values calculated from ΔR₂^* time curves with no leakage effects (Figure 1F). This preliminary analysis indicates that a dosing scheme using a full pre load followed by a full dose bolus injection yield the most accurate CBV values (-4.8%) whereas the no pre-load approach leads to the least accurate CBV estimate (-63.5%). For a fixed physiological, physical and pulse sequence parameters as well as CA leakage correction techniques, the preliminary computational results presented herein indicate that DSC-MRI data is significantly influence by CA dosing scheme. We are currently performing a systematic investigation across a wide range of physical, physiological and pulse sequence parameters in order to fully characterize which dosing scheme yields the most accurate DSC-MRI data.