Measuring diffusion exchange across the cell membrane with DEXSY (Diffusion Exchange Spectroscopy)

Breen-Norris, James O.; Siow, Bernard; Walsh, Claire; Hipwell, Ben; Hill, Ioana; Roberts, Thomas A.; Hall, Matt G.; Lythgoe, Mark F.; Ianuş, Andrada; Alexander, Daniel C.; Walker‐Samuel, Simon

doi:10.1002/mrm.28207

Cited by 10 publications

(9 citation statements)

References 26 publications

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“…Diffusion MRI has the great potential of investigating this parameter noninvasively. 25,26,35,36,41,43,[52][53][54] Several publications have already demonstrated the potential for in vivo application. The relation to microstructural parameters such as the actual exchange rate and geometrical properties of the diffusion restrictions has been investigated in Tian et al 43 Our study extends this work by investigating the relation of AXR to permeability, geometry, free diffusion coefficients, axon dispersion, gradient directions, T 1 relaxation, permeability distributions, and real exchange rate.…”

Section: Discussionmentioning

confidence: 99%

“…Cell membrane permeability is a very important parameter in characterizing cell status and has the potential of being related to various pathologies. Diffusion MRI has the great potential of investigating this parameter noninvasively 25,26,35,36,41,43,52‐54 . Several publications have already demonstrated the potential for in vivo application.…”

Section: Discussionmentioning

confidence: 99%

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Apparent exchange rate imaging: On its applicability and the connection to the real exchange rate

Ludwig

Laun

Ladd

et al. 2021

Magnetic Resonance in Med

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Apparent exchange rate imaging: On its applicability and the connection to the real exchange rate

Ludwig

Laun

Ladd

et al. 2021

Magnetic Resonance in Med

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“…For example, the framework is immediately applicable to spectrumbased analysis of multi-echo T2 relaxometry for myelin water imaging [1]. The method can also be applied to other multidimensional experiments beyond the diffusion-relaxometry example in this paper, such as diffusion exchange spectroscopy [5,6]. To conclude, our approach opens up spectral techniques to a wide range of situations where they are currently impossible.…”

Section: Discussionmentioning

confidence: 95%

Data-Driven Multi-contrast Spectral Microstructure Imaging with InSpect

Slator

Hutter

Marinescu

et al. 2020

Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

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We introduce and demonstrate an unsupervised machine learning method for spectroscopic analysis of quantitative MRI (qMRI) experiments. qMRI data can support estimation of multidimensional correlation (or single-dimensional) spectra, which allow model-free investigation of tissue properties, but this requires an ill-posed calculation. Moreover, in the vast majority of applications ground truth knowledge is unobtainable, preventing the application of supervised machine learning. Here we present a new method that addresses these limitations in a data-driven way. The algorithm simultaneously estimates a canonical basis of spectral components and voxelwise maps of their weightings, thereby pooling information across whole images to regularise the ill-posed problem. We show that our algorithm substantially outperforms current voxelwise spectral approaches. We demonstrate the method on combined diffusionrelaxometry placental MRI scans, revealing anatomically-relevant substructures, and identifying dysfunctional placentas. Our algorithm vastly reduces the data required to reliably estimate multidimensional correlation (or single-dimensional) spectra, opening up the possibility of spectroscopic imaging in a wide range of new applications.

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“…The presented phantoms provide a potential tool for quantifying the effect of a specific microstructural parameter for a specific disease on ADC. Moreover, the phantoms may be applied to other diffusion MRI methodologies that are sensitive to membrane permeability, such as DEXSY, 36,37 FEXSY, 38 and the Karger model. 39 PVP solution is suitable for filling diffusion MRI phantom.…”

Section: Future Directions and Limitationsmentioning

confidence: 99%

Assessment of the effects of mimicking tissue microstructural properties on apparent diffusion coefficient and apparent exchange rate in diffusion MRI via a series of specially designed phantoms

Bai

Liao

et al. 2021

Magnetic Resonance in Med

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Purpose Diffusion MRI provides a valuable tool for imaging tissue microstructure. However, due to the lack of related experimental methods and specially designed phantoms, no experimental study has been conducted yet to quantitatively assess the effects of membrane permeability, intracellular volume fraction (IVF), and intracellular diffusivity on the apparent diffusion coefficient (ADC) obtained from diffusion weighted imaging (DWI), and the effects of membrane permeability on the apparent exchange rate (AXR) obtained from filter exchange imaging (FEXI). Methods A series of phantoms with three adjustable parameters was designed to mimic tissue microstructural properties including membrane permeability, IVF, and intracellular diffusivity. Quantitative experiments were conducted to assess the effects of these properties on ADC and AXR. DWI scans were performed to obtain axial and radial ADC values. FEXI scans were performed to obtain AXR values. Results Axial ADC values range from 1.148 μm2/ms to 2.157 μm2/ms, and radial ADC values range from 0.904 μm2/ms to 2.067 μm2/ms. Radial ADC decreased with a decrease in fiber permeability. Decreased axial and radial ADC values with increased intra‐fiber volume fraction, and increased polyvinylpyrrolidone (PVP) concentration of the intra‐fiber space were observed. AXR values range from 2.1 s−1 to 4.9 s−1. AXR increases with fiber permeability. Conclusion The proposed phantoms can quantitatively evaluate the effects of mimicking tissue microstructural properties on ADC and AXR. This new phantom design provides a potential method for further understanding the biophysical mechanisms underlying the change in ADC and diffusion exchange.

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Measuring diffusion exchange across the cell membrane with DEXSY (Diffusion Exchange Spectroscopy)

Cited by 10 publications

References 26 publications

Apparent exchange rate imaging: On its applicability and the connection to the real exchange rate

Apparent exchange rate imaging: On its applicability and the connection to the real exchange rate

Data-Driven Multi-contrast Spectral Microstructure Imaging with InSpect

Assessment of the effects of mimicking tissue microstructural properties on apparent diffusion coefficient and apparent exchange rate in diffusion MRI via a series of specially designed phantoms

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