A Framework for Calculating Time-Efficient Diffusion MRI Protocols for Anisotropic IVIM and An Application in the Placenta

  • Paddy J. SlatorEmail author
  • Jana Hutter
  • Andrada Ianus
  • Eleftheria Panagiotaki
  • Mary A. Rutherford
  • Joseph V. Hajnal
  • Daniel C. Alexander
Conference paper
Part of the Mathematics and Visualization book series (MATHVISUAL)


We develop a framework for calculating clinically-viable diffusion MRI (dMRI) protocols for anisotropic IVIM modelling. The proposed multi-stage framework combines previous approaches to dMRI protocol optimisation: first optimising b-values by minimizing Cramer-Rao lower bounds on parameter variances, and subsequently optimising gradient directions jointly to provide maximum angular coverage across all shells. This removes unnecessary measurements of closely spaced b-values with the same gradient directions, which encode very similar information, and hence reduces the total number of dMRI measurements. We applied the framework to establish an organ-specific, data-driven, set of optimised b-values and gradient directions for dMRI of the placenta. The optimised protocol leads to higher contrast-to-noise ratios in parameter maps compared to a naive protocol of comparable scan time. Applying this framework in other organs has the potential to reduce scanning times required for anisotropic IVIM modelling.


Diffusion MRI IVIM Anisotropic IVIM Placenta Microstructural modelling Experimental design Cramer-Rao lower bound 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Paddy J. Slator
    • 1
    Email author
  • Jana Hutter
    • 2
    • 3
  • Andrada Ianus
    • 1
  • Eleftheria Panagiotaki
    • 1
  • Mary A. Rutherford
    • 2
  • Joseph V. Hajnal
    • 2
    • 3
  • Daniel C. Alexander
    • 1
  1. 1.Centre for Medical Image Computing and Department of Computer ScienceUniversity College LondonLondonUK
  2. 2.Centre for the Developing Brain, King’s College LondonLondonUK
  3. 3.Biomedical Engineering DepartmentKing’s College LondonLondonUK

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