The Road to a Realistic 3D Model for Estimating R 2 and R 2 Relaxation Versus Gd‐DTPA Concentration in Whole Blood and Brain Tumor Vasculature

Dynamic susceptibility contrast (DSC) MRI is commonly part of brain tumor imaging. For quantitative analysis, measurement of the arterial input function and tissue concentration time curve is required. Usually, a linear relationship between the MR signal changes and contrast agent concentration ([Gd]) is assumed, even though this is a known simplification. The aim of this study was to develop a realistic 3D simulation model as an efficient method to assess the relationship between Δ R 2 (*) and [Gd] both in whole blood and brain tissue. We modified an open‐source 3D simulation model to study different red blood cell configurations for assessing whole‐blood Δ R 2 (*) versus [Gd]. The results were validated against previously obtained 2D data and in vitro data. Furthermore, hematocrit levels (30%–50%) and field strengths (1.5–3.0–7.0 T) were varied. Subsequently, realistic tumor vascular networks were derived from intraoperative high framerate Doppler ultrasound data to study the influence of vascular structure and orientation with respect to the main magnetic field (1.5–3.0–7.0 T) for the calculation of Δ R 2 (*) versus [Gd] in brain tissue. For whole blood, good agreement of the 3D model was found with in vitro and 2D simulation data when red blood cells were aligned with the blood flow. For brain tissue, minor differences were found between the vascular networks. The effect of vessel direction with respect to B 0 was apparent in case of clear directionality of the main vessels. The dependency on field strength agreed with previous reports. In conclusion, we have shown that the relationship between Δ R 2 (*) and [Gd] is affected by the organization of red blood cells and orientation of blood vessels with respect to the main magnetic field, as well as the field strength. These findings are important for further optimization of the realistic 3D model that could eventually be used to improve the estimation of hemodynamic parameters from DSC‐MRI. Quantitative DSC perfusion MRI requires knowledge of the relationship between R 2 (*) relaxation and the concentration of contrast agent. This relationship depends on both physiological and MR parameters, as well as the structure and orientation of the vascular network with respect to the main magnetic field. Our realistic 3D model provides an efficient method to investigate this relationship, and by further optimizing the vascular segmentations, the model could eventually be used to improve the estimation of hemodyna