Myelin, a thin layer of sheath-like cell, provides an important role in protecting nerve axon and accelerating neural impulse transmission. Recently a quantitative MR method called multicomponent-driven equilibrium single-component observation of T1 and T2 (mcDESPOT) has shown promising results for assessing myelin content using rapid steady-state sequences (1). In this method, a bicomponent water exchange system is used to characterize myelin water and non-myelin water. Yet this simplified bicomponent model is practically useful, the lack of consideration of interaction between non-aqueous macromolecular proton and mobile water through magnetization transfer (MT) renders the complication of interpretation for MWF values (2-4). Recent studies show that the steady-state sequence signal could be strongly biased by MT under certain imaging conditions (5,6). In our previous study, we proposed a new method called multicomponent relaxation imaging using steady-state signal evolution (mcRISE) in cartilage imaging to account for MT effect while preserve the advantageous acquisition of mcDESPOT (7). In this study, we optimized and applied the mcRISE method to the neural tissue and investigate the feasibility of assessing myelin content with MT-insensitive MWF as well as additional MT parameters.In mcRISE, a macromolecular proton pool in exchange with mcDESPOT water pools was introduced to explicitly model MT exchange between macromolecular proton, myelin and non-myelin water. A combined mcDESPOT and quantitative magnetization transfer imaging (qMTI) (8) method is proposed to resolve this three compartmental system. Simultaneous fitting for all parameters of this system is not feasible. Hence, an incremental fitting approach was introduced. First, the macromolecular bound pool fraction f and exchange rate k was estimated using balanced steady-state free precession (bSSFP) based estimation of the MT parameters (8), where varying RF pulse width (bSSFPv) was applied for exploring on-resonance MT effect. Then, these values as fixed parameters were implemented in the full model fit with additional varying flip angle spoiled gradient echo (SPGR) and bSSFP, which involves the mutually exchanging slow and rapid relaxing water compartments and the bound proton pool. The detailed processing pipeline is shown in Figure 1.A brain scan was performed on a healthy adult volunteer using a GE MR750 3.0T scanner. The mcRISE parameters included: 1) SPGR scans with TR/TE=4.1/1.5ms over a range of flip angles (α=3, 4, 5, 6, 7, 9, 13, 18°); 2) Two bSSFP scans with RF phase cycling on (bSSFP₁₈₀) and off (bSSFP₀), with TR/TE=3.0/1.4ms over a range of flip angles (α=2, 5, 10, 15, 20, 30, 40, 50°); 3) One bSSFPv scans over a range of RF pulse width (T_RF) at T_RF/TR=0.27/2.5ms, 0.3/2.5ms, 0.4/2.6ms, 0.6/2.8ms, 0.8/3.0ms, 1.2/3.4ms, 1.6/3.8ms, 2/4.2ms and α=35°. 4) Inversion recovery SPGR scan with TR/TE=4.1/1.5ms, TI=450ms, and α=5°. All scans were performed in the sagittal plane with a 25.6cm field of view, 128×128 matrix, 2mm thickness, one excitation.mcRISE was able to simultaneously generate MWF map and additional quantitative MT f map of the entire brain at 3.0T (Figure 2). The spatial variations of the MWF and f maps within the brain tissue are consistent with the previous reported values from multiple multicomponent T2 and quantitative MT studies (1,8). A significant reduced MWF values is observed in the mcRISE method compared to mcDESPOT. A recent study comparing the MWF between mcDESPOT and a multi-echo T2 decay method demonstrated an overestimation of mcDESPOT MWF values in brain tissue, which was largely attributed to MT effects (3). The MT-corrected MWF values from mcRISE shows a better correspondence to reported multiecho T2 MWF and our previous simulation results (7). In addition, a strong correlation (p<0.0001 in Pearson test) between MWF and macromolecular proton fraction f for both mcRISE and mcDESPOT is observed (Figure 3) which corresponds well to one previous study comparing mcDESPOT MWF and f obtained from traditional off-resonance MT method (9), indicating the strong correlation between myelin content and macromolecular proton from qMT. Our previous in-vivo qMT studies also show the primary source of qMT f comes from the myelin sheath (10). However, this correlation is decreased for mcRISE (r²=0.41) as compared to mcDESPOT (r²=0.78), indicate that the MT corrected MWF might preserve complimentary information from that of MT measurements, although detailed studies comparing MWF and qMT parameters in terms of sensitivity and specificity to myelin content and structure are still required. In conclusion, mcRISE is capable of simultaneously estimating MT corrected MWF and qMT parameters in whole brain, combination of which might provide a new set of biomarkers for rapid and comprehensive assessing myelin content and structure in multiple brain studies.