NMR Simulation Analysis of Statistical Effects on Quantifying Cerebrovascular Parameters

Determining tissue structure and composition from the behavior of the NMR transverse relaxation during free induction decay and spin echo formation has seen significant advances in recent years. In particular, the ability to quantify cerebrovascular network parameters such as blood volume and deoxyhemoglobin concentration from the NMR signal dephasing has seen intense focus. Analytical models have been described, based on statistical averaging of randomly oriented cylinders in both the static and slow diffusion regimes. However, the error in estimates obtained from these models when applied to systems in which the statistical assumptions of many, randomly oriented perturbers are violated has not been systematically investigated. Using a deterministic simulation that can include diffusion, we find that the error in estimated venous blood volume fraction and deoxyhemoglobin concentration obtained using a static dephasing regime statistical model is inversely related to the square root of number of blood vessels. The most important implication of this is that the minimum imaging resolution for accurate deoxyhemoglobin and blood volume estimation is not bound by hardware limitations, but rather by the underlying tissue structure.