Bayesian Modeling of MR Data: Quantifying Longitudinal Relaxation in Vivo and in Vitro with a Tissue-Water-Relaxation Mimic, Towards Tissue pO2 Measures

Kelsey Meinerz, Department of Physics, Washington University
October 20, 2017 at 4:00 pm
204 Crow
Event Description 

Recently, a number of Magnetic Resonance Imaging (MRI) protocols have been reported that seek to exploit the effect of dissolved oxygen (O2, paramagnetic) on the longitudinal 1H relaxation of tissue water, thus providing image contrast related to tissue oxygen content. Herein, we test and apply cross-linked bovine serum albumin (x-BSA) samples prepared at varying known oxygen concentrations as tissue surrogates/mimics to investigate the fidelity of dissolved oxygen as a contrast agent using “high resolution” NMR spectrometers. As an inanimate longitudinal relaxation (R1) tissue surrogate, x-BSA allows for precise characterization of the influence of physiologically-relevant variations in temperature and macromolecule concentration upon R1-based pO2 measures. Our data suggest that: (i) x-BSA phantoms exhibit the same 1H longitudinal relaxation characteristics as in vivo tissues and, thus, serve as excellent MR tissue surrogates and (ii) x-BSA phantoms are useful in quantif ying the relationship between R1 and pO2. However, tissue water relaxation is dependent on a number of mechanisms, and this raises the issue of how best to model the relaxation data. This problem, the model selection problem, occurs in many branches of science and is optimally addressed by Bayesian probability theory.