Quantification of Oxygen Saturation of Venous Vessels Using Susceptibility Mapping

Abstract

<p>Quantitatively measuring oxygen saturation is important to characterize the physiological or pathological state of tissue function. In this thesis, we demonstrate the possibility of using susceptibility mapping to noninvasively estimate the venous blood oxygen saturation level. Accurate susceptibility quantification is the key to oxygen saturation quantification. Two approaches are presented in this thesis to generate accurate and artifact free susceptibility maps (SM): a regularized inverse filter and a k-space iterative method. Using the regularized inverse filter, with sufficient resolution, major veins in the brain can be visualized. We found that different sized vessels show a different level of contrast depending on their partial volume effects; larger vessels show a bias toward a reduced susceptibility approaching 90% of the expected value. Also, streaking artifacts associated with high susceptibility structures such as veins are obvious in the reconstructed SM. To further improve susceptibility quantification and reduce the streaking artifacts in the SMs, we proposed a threshold-based k-space iterative approach that used geometric information from the SM itself as a constraint to overcome the ill-posed nature of the inverse filter. Both simulations and in vivo results show that most streaking artifacts inside the SM were suppressed by the iterative approach. In simulated data, the bias toward lower mean susceptibility values inside vessels has been shown to decrease from around 10% to 2% when choosing an appropriate threshold value for the proposed iterative method, which brings us one step closer to a practical means to map out oxygen saturation in the brain.</p>