A general linear relaxometry model of R 1 using imaging data

Purpose The longitudinal relaxation rate (R 1 ) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R 1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort. Methods Maps of magnetization transfer (MT) and effective transverse relaxation rate (R 2 *) were used as surrogates for macromolecular and iron content, respectively. Spatial variations in these parameters reflected variations in underlying tissue microstructure. A linear model was applied to the whole brain, including gray/white matter and deep brain structures, to determine the global model coefficients. Synthetic R 1 values were then calculated using these coefficients and compared with the measured R 1 maps. Results The model's validity was demonstrated by correspondence between the synthetic and measured R 1 values and by high stability of the model coefficients across a large cohort. Conclusion A single set of global coefficients can be used to relate R 1 , MT, and R 2 * across the whole brain. Our population study demonstrates the robustness and stability of the model. Magn Reson Med, 2014. © 2014 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. Magn Reson Med 73:1309–1314, 2015. © 2014 Wiley Periodicals, Inc.