Model-based super-resolution reconstruction of T2 maps

Magn Reson Med. 2020 Mar;83(3):906-919. doi: 10.1002/mrm.27981. Epub 2019 Sep 13.


Purpose: High-resolution isotropic T2 mapping of the human brain with multi-echo spin-echo (MESE) acquisitions is challenging. When using a 2D sequence, the resolution is limited by the slice thickness. If used as a 3D acquisition, specific absorption rate limits are easily exceeded due to the high power deposition of nonselective refocusing pulses. A method to reconstruct 1-mm3 isotropic T2 maps is proposed based on multiple 2D MESE acquisitions. Data were undersampled (10-fold) to compensate for the prolonged scan time stemming from the super-resolution acquisition.

Theory and methods: The proposed method integrates a classical super-resolution with an iterative model-based approach to reconstruct quantitative maps from a set of undersampled low-resolution data. The method was tested on numerical and multipurpose phantoms, and in vivo data. T2 values were assessed with a region-of-interest analysis using a single-slice spin-echo and a fully sampled MESE acquisition in a phantom, and a MESE acquisition in healthy volunteers.

Results: Numerical simulations showed that the best trade-off between acceleration and number of low-resolution datasets is 10-fold acceleration with 4 acquisitions (acquisition time = 18 min). The proposed approach showed improved resolution over low-resolution images for both phantom and brain. Region-of-interest analysis of the phantom compartments revealed that at shorter T2 , the proposed method was comparable with the fully sampled MESE. For the volunteer data, the T2 values found in the brain structures were consistent across subjects (8.5-13.1 ms standard deviation).

Conclusion: The proposed method addresses the inherent limitations associated with high-resolution T2 mapping and enables the reconstruction of 1 mm3 isotropic relaxation maps with a 10 times faster acquisition.

Keywords: T2 mapping; model-based reconstruction; parallel Imaging; super-resolution.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Brain / diagnostic imaging*
  • Healthy Volunteers
  • Humans
  • Image Interpretation, Computer-Assisted / methods
  • Image Processing, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods
  • Magnetic Resonance Imaging*
  • Models, Theoretical
  • Normal Distribution
  • Phantoms, Imaging
  • Signal-To-Noise Ratio
  • Spin Labels


  • Spin Labels