Three‐dimensional simultaneous brain mapping of T1, T2, and magnetic susceptibility with MR Multitasking Academic Article uri icon

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  • Purpose

    To develop a new technique that enables simultaneous quantification of whole-brain T1 , T2 , T2∗ , as well as susceptibility and synthesis of six contrast-weighted images in a single 9.1-minute scan.


    The technique uses hybrid T2 -prepared inversion-recovery pulse modules and multi-echo gradient-echo readouts to collect k-space data with various T1, T2, and T2∗ weightings. The underlying image is represented as a six-dimensional low-rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi-echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast-weighted images was also examined.


    High quality, co-registered T1 , T2 , and T2∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and T2∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast-weighted images.


    The MR Multitasking-based 3D brain mapping of T1 , T2 , T2∗ , and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.


  • Cao, Tianle
  • Ma, Sen
  • Wang, Nan
  • Gharabaghi, Sara
  • Xie, Yibin
  • Fan, Zhaoyang
  • Hogg, Elliot
  • Wu, Chaowei
  • Han, Fei
  • Tagliati, Michele
  • Haacke, Mark
  • Christodoulou, Anthony G
  • Li, Debiao

publication date

  • March 2022