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Separating blood and water: Perfusion and free water elimination from diffusion MRI in the human brain

Anna S Rydhög1, Filip Szczepankiewicz1, Ronnie Wirestam1

  • 1Department of Medical Radiation Physics, Lund University, Barngatan 2B, SE-221 85 Lund, Sweden.

Neuroimage
|April 17, 2017
PubMed

Insights

This study shows that blood flow (perfusion) in the brain can skew free water fraction estimates from diffusion MRI. A new three-compartment model accurately separates blood effects from free water, improving brain tissue analysis.

Area of Science:

  • Neuroimaging
  • Biophysics
  • Medical Physics

Background:

  • Free water fraction in brain diffusion MRI is vital for assessing extracellular processes like atrophy and neuroinflammation.
  • Current methods may overestimate free water due to uncorrected intravoxel incoherent motion (IVIM) from blood perfusion.

Purpose of the Study:

  • To develop and validate a method for separating the signal contribution of perfusing blood from free water and other brain diffusivities in diffusion MRI.
  • To investigate the influence of the vascular compartment on free water fraction and diffusivity estimations.

Main Methods:

  • Simulated perfusion in diffusion MRI data to quantify the effect of blood flow on diffusivity estimates.
  • Explored two approaches: increasing minimal b-value and implementing a three-compartment model accounting for capillary blood.
  • Validated the three-compartment model using diffusion MRI data from a healthy volunteer and a clinically feasible protocol.

Main Results:

  • Perfusion significantly impacts free water fraction estimation, particularly when low b-value data are included.
  • The three-compartment model demonstrated stability and accurately estimated the capillary blood volume fraction, disentangling perfusion from free water diffusion.
  • Diffusion MRI data revealed a non-zero blood fraction, suggesting previous studies may have overestimated free water due to uncorrected perfusion.

Conclusions:

  • The three-compartment diffusion MRI model effectively separates free water diffusion from blood perfusion effects.
  • This improved accuracy is crucial for distinguishing between extracellular pathologies (neuroinflammation, atrophy) and vascular changes (vasodilation, capillary density).
  • The method is applicable to clinically feasible diffusion MRI protocols, enhancing diagnostic potential.

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