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

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.

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T.

Artificial neural networks (ANNs) were used for voxel-wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least-squares regression (LSR) and state-of-the-art multi-step fitting (LSR-MS) in Monte-Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR-MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo-diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR-MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR-MS, 19%; LSR, 8%), D* (ANN, 21%; LSR-MS, 25%; LSR, 23%) and K (ANN, 0%; LSR-MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR-MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state-of-the-art method LSR-MS with several advantages in the estimation of IVIM-kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times.

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

Diffusion pore imaging (DPI) has recently been proposed as a means to acquire images of the average pore shape in an image voxel or region of interest. The highly asymmetric gradient scheme of its sequence makes it substantially demanding in terms of the hardware of the NMR system. The aim of this work is to show the feasibility of DPI on a preclinical 9.4T animal scanner. Using water-filled capillaries with an inner radius of 10µm, four different variants of the DPI sequence were compared in 1D and 2D measurements. The pulse sequences applied cover the basic implementation using one long and one temporally narrow gradient pulse, a CPMG-like variant with multiple refocusing RF pulses as well as two variants splitting up the long gradient and distributing it on either side of the refocusing pulse. Substantial differences between the methods were found in terms of signal-to-noise ratio, contrast, blurring, deviations from the expected results and sensitivity to gradient imperfections. Each of the tested sequences was found to produce characteristic gradient mismatches dependent on the absolute value, direction and sign of the applied q-value. Read gradients were applied to compensate these mismatches translating them into time shifts, which enabled 1D DPI yielding capillary radius estimations within the tolerances specified by the manufacturer. For a successful DPI application in 2D, a novel gradient amplitude adaption scheme was implemented to correct for the occurring time shifts. Using this adaption, higher conformity to the expected pore shape, reduced blurring and enhanced contrast were achieved. Images of the phantom's pore shape could be acquired with a nominal resolution of 2.2µm.