Determination of the self-diffusion coefficient of intracellular water using PGSE NMR with variable gradient pulse length

Åslund, Ingrid; Topgaard, Daniel

doi:10.1016/j.jmr.2009.09.006

Cited by 53 publications

(48 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…for the intracellular component are consistent with restricted diffusion in a spherical cell with a radius between 2.7 and 3.0 μm, an intracellular water diffusivity of 0.56 × 10 −9 m 2 s −1 [44], and the herein used pulse sequence parameters. The cell radius is in reasonable agreement with the literature data for yeast cells [44,66,67].…”

Section: Prl 116 087601 (2016) P H Y S I C a L R E V I E W L E T T Esupporting

confidence: 65%

“…[37]. Two water populations can be distinguished in the cell suspension, an intracellular and an extracellular one, both of them featuring isotropic diffusion but with a few orders of magnitude difference in apparent diffusivity [36,44,63]. The extracellular component resembles extraaxonal water or cerebrospinal fluid, while the intracellular component corresponds to the slow isotropic water that has been inferred from advanced model fitting of conventional diffusion MRI data [61].…”

Section: Prl 116 087601 (2016) P H Y S I C a L R E V I E W L E T T Ementioning

confidence: 99%

“…Even though all the details of restricted diffusion in a porous material cannot be captured within a tensor model, the multitensor approximation is a useful point of departure for the analysis of data from heterogeneous porous materials [6,13,30]. In the case of restricted diffusion, the diffusion tensor should be interpreted as an apparent one, being given by the pore size and shape, the local diffusivity within the pore space, as well as the timing parameters of the used pulse sequence [39][40][41][42][43][44]. A more in-depth analysis of the validity of this approximation is given in the Supplemental Material [45].…”

mentioning

confidence: 99%

See 2 more Smart Citations

Two-Dimensional Correlation of Isotropic and Directional Diffusion Using NMR

Martins

Topgaard

2016

Phys. Rev. Lett.

Self Cite

View full text Add to dashboard Cite

Diffusion nuclear magnetic resonance (NMR) is a powerful technique for studying porous media, but yields ambiguous results when the sample comprises multiple regions with different pore sizes, shapes, and orientations. Inspired by solid-state NMR techniques for correlating isotropic and anisotropic chemical shifts, we propose a diffusion NMR method to resolve said ambiguity. Numerical data inversion relies on sparse representation of the data in a basis of radial and axial diffusivities. Experiments are performed on a composite sample with a cell suspension and a liquid crystal. DOI: 10.1103/PhysRevLett.116.087601 Many porous materials of biological, geological, and synthetic origin contain water in a range of microscopic environments with different local pore geometries. Information about the structure of the pore space can be inferred from nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) measurements of the self-diffusion of the pore water [1,2]. The diffusion MRI approach has been especially powerful for noninvasive studies of the living human brain [3], allowing for quantification of axon diameter [4], mean orientation [5], and orientation distribution [6]. Although useful, classical diffusion MRI protocols relying on the Stejskal-Tanner experiment [7] suffer from the fact that the effects of distributions in pore size, anisotropy, and orientation are intrinsically entangled. A partial solution to this problem is provided by the double diffusion encoding (DDE) family of NMR methods [8], which can give estimates of the pore size and shape even in the presence of orientational disorder [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Current in vivo versions of DDE permit detection of anisotropy in areas of the human brain that are macroscopically isotropic [24] and the assignment of metabolitespecific compartment shapes in animal models [25]. Despite these impressive feats, DDE yields ambiguous results if the investigated volume element comprises several types of water environments, the presence of which has been inferred by fitting multicomponent biophysical models [26][27][28][29] to in vivo data acquired with the StejskalTanner method [30,31]. Selection of a single model from all the ones that are able to reproduce the experimental data remains a challenge [29]. The key to future progress in diffusion NMR and MRI of heterogeneous anisotropic materials lies in designing a method to unambiguously resolve and quantify water compartments with respect to their size and anisotropy, irrespective of the details of their orientations. Once this goal has been achieved, the obtained information could be used as input for existing methods to estimate distributions of axon diameters [4] and orientations [32][33][34].In solid-state NMR spectroscopy [35], the eigenvalues and eigenvectors of the chemical shift tensors can be determined through the dependence of the nuclear spin Hamiltonian on the orientation of the tensors with respect to the static magnetic field. We have recently poin...

show abstract

Section: Prl 116 087601 (2016) P H Y S I C a L R E V I E W L E T T Esupporting

confidence: 65%

Section: Prl 116 087601 (2016) P H Y S I C a L R E V I E W L E T T Ementioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Two-Dimensional Correlation of Isotropic and Directional Diffusion Using NMR

Martins

Topgaard

2016

Phys. Rev. Lett.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The efficiency of the q-MAS sequence is demonstrated using two materials with pronounced water diffusion anisotropy: lyotropic liquid crystals [24,25,27,34,[38][39][40] and pureed asparagus [41][42][43][44]. For contrast, a yeast cells suspension is used, exhibiting two isotropic diffusion components [34,[45][46][47].…”

Section: Introductionmentioning

confidence: 99%

Microanisotropy imaging: quantification of microscopic diffusion anisotropy and orientational order parameter by diffusion MRI with magic-angle spinning of the q-vector

et al. 2014

Self Cite

View full text Add to dashboard Cite

Diffusion tensor imaging (DTI) is the method of choice for non-invasive investigations of the structure of human brain white matter (WM). The results are conventionally reported as maps of the fractional anisotropy (FA), which is a parameter related to microstructural features such as axon density, diameter, and myelination. The interpretation of FA in terms of microstructure becomes ambiguous when there is a distribution of axon orientations within the image voxel. In this paper, we propose a procedure for resolving this ambiguity by determining a new parameter, the microscopic fractional anisotropy (μFA), which corresponds to the FA without the confounding influence of orientation dispersion. In addition, we suggest a method for measuring the orientational order parameter (OP) for the anisotropic objects. The experimental protocol is capitalizing on a recently developed diffusion nuclear magnetic resonance (NMR) pulse sequence based on magic-angle spinning of the q-vector. Proof-of-principle experiments are carried out on microimaging and clinical MRI equipment using lyotropic liquid crystals and plant tissues as model materials with high μFA and low FA on account of orientation dispersion. We expect the presented method to be especially fruitful in combination with DTI and high angular resolution acquisition protocols for neuroimaging studies of gray and white matter.

show abstract

“…This means that water is only slightly impeded by macromolecules such as proteins and DNA, but is efficiently stopped by lipid membrane structures. From experiments on simple eukaryotic cells Åslund et al, 2009), we know that a water molecule samples the entire intracellular space on the time-scale of a few milliseconds, while molecular exchange over the cell membrane is strongly dependent on the physical state of the membrane lipids and the presence of aquaporins; the typical intracellular lifetime could vary from a few milliseconds for red blood cells to over a second for myelinated axons. Still, many basic questions remain about how the nano-and micrometer-scale cell and tissue structure affect the water motion.…”

Section: Biological Limitsmentioning

confidence: 99%