B₁ inhomogeneity-corrected T₁ mapping and quantitative magnetization transfer imaging via simultaneously estimating Bloch-Siegert shift and magnetization transfer effects

Purpose: To introduce a method of inducing Bloch-Siegert shift and magnetization Transfer Simultaneously (BTS) and demonstrate its utilization for measuring binary spin-bath model parameters free pool spin–lattice relaxation ((Figure presented.)), macromolecular fraction ((Figure presented.)), magnetization exchange rate ((Figure presented.)) and local transmit field ((Figure presented.)). Theory and Methods: Bloch-Siegert shift and magnetization transfer is simultaneously induced through the application of off-resonance irradiation in between excitation and acquisition of an RF-spoiled gradient-echo scheme. Applying the binary spin-bath model, an analytical signal equation is derived and verified through Bloch simulations. Monte Carlo simulations were performed to analyze the method's performance. The estimation of the binary spin-bath parameters with (Figure presented.) compensation was further investigated through experiments, both ex vivo and in vivo. Results: Comparing BTS with existing methods, simulations showed that existing methods can significantly bias (Figure presented.) estimation when not accounting for transmit (Figure presented.) heterogeneity and MT effects that are present. Phantom experiments further showed that the degree of this bias increases with increasing macromolecular proton fraction. Multi-parameter fit results from an in vivo brain study generated values in agreement with previous literature. Based on these studies, we confirmed that BTS is a robust method for estimating the binary spin-bath parameters in macromolecule-rich environments, even in the presence of (Figure presented.) inhomogeneity. Conclusion: A method of estimating Bloch-Siegert shift and magnetization transfer effect has been developed and validated. Both simulations and experiments confirmed that BTS can estimate spin-bath parameters ((Figure presented.), (Figure presented.), (Figure presented.)) that are free from (Figure presented.) bias.