1D and 2D diffusion pore imaging on a preclinical MR system using adaptive rephasing: Feasibility and pulse sequence comparison

Bertleff, Marco; Domsch, Sebastian; Laun, Frederik Bernd; Kuder, Tristan Anselm; Schad, Lothar R.

doi:10.1016/j.jmr.2017.03.008

Cited by 4 publications

(1 citation statement)

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“…The phase problem was overcome by modifying the temporal gradient profile: Laun et al replaced one of the narrow gradient pulses with a very long pulse of equal area and could thus preserve the phase information [25,26]. With the greater information content of the thus determinable 𝜌 �(𝒒), the direct reconstruction of arbitrary pore space functions was enabled so that the average pore shape in an imaging volume element could be measured [27][28][29][30][31]. This technique, known as diffusion pore imaging, potentially enables in-vivo estimations of histology-like parameters such as cell-size distributions.…”

Section: Introductionmentioning

confidence: 99%

Experimental determination of pore shapes using phase retrieval from q -space NMR diffraction

et al. 2018

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This paper presents an approach to solving the phase problem in nuclear magnetic resonance (NMR) diffusion pore imaging, a method that allows imaging the shape of arbitrary closed pores filled with an NMR-detectable medium for investigation of the microstructure of biological tissue and porous materials. Classical q-space imaging composed of two short diffusion-encoding gradient pulses yields, analogously to diffraction experiments, the modulus squared of the Fourier transform of the pore image which entails an inversion problem: An unambiguous reconstruction of the pore image requires both magnitude and phase. Here the phase information is recovered from the Fourier modulus by applying a phase retrieval algorithm. This allows omitting experimentally challenging phase measurements using specialized temporal gradient profiles. A combination of the hybrid input-output algorithm and the error reduction algorithm was used with dynamically adapting support (shrinkwrap extension). No a priori knowledge on the pore shape was fed to the algorithm except for a finite pore extent. The phase retrieval approach proved successful for simulated data with and without noise and was validated in phantom experiments with well-defined pores using hyperpolarized xenon gas.

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