NMR in biomedicine, 2018
Schweser, F., & Zivadinov, R. (2018). Quantitative susceptibility mapping (QSM) with an extended physical model for MRI frequency contrast in the brain: a proof‐of‐concept of quantitative susceptibility and residual (QUASAR) mapping. NMR in Biomedicine.
Schweser, F., and R. Zivadinov. “Quantitative Susceptibility Mapping (QSM) with an Extended Physical Model for MRI Frequency Contrast in the Brain: a Proof‐of‐Concept of Quantitative Susceptibility and Residual (QUASAR) Mapping.” NMR in biomedicine (2018).
Schweser, F., and R. Zivadinov. “Quantitative Susceptibility Mapping (QSM) with an Extended Physical Model for MRI Frequency Contrast in the Brain: a Proof‐of‐Concept of Quantitative Susceptibility and Residual (QUASAR) Mapping.” NMR in Biomedicine, 2018.
Quantitative susceptibility mapping (QSM) aims to calculate the tissue's magnetic susceptibility distribution from its perturbing effect on the MRI static main magnetic field. The method is increasingly being applied to study iron and myelin in clinical and preclinical settings. However, recent experimental and theoretical findings have challenged the fundamental theoretical assumptions that form the basis of current numerical implementations of QSM algorithms. The present work introduces a new class of susceptibility mapping algorithms, termed quantitative susceptibility and residual mapping (QUASAR), which takes into account frequency contributions not related to the spatial variation of bulk magnetic susceptibility in the Lorentz sphere model. We present a simple proof‐of‐concept QUASAR algorithm that, unlike most of the QSM algorithms currently used widely, results in an improved anatomical accuracy of the susceptibility distribution without any a priori assumptions about the susceptibility distribution during the field‐to‐source inversion. The algorithm was evaluated both in silico and in vivo in the preclinical setting. Our preliminary application of QUASAR in rodents provides the first in vivo evidence that the susceptibility‐field model traditionally used in the QSM field cannot fully explain the frequency contrast in brain tissues. Only when an additional local frequency contribution is added to the physical model can the frequency contrast in the brain be related properly to the underlying anatomy.