Related Experiment Video
Updated: Jan 3, 2026

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
Published on: December 9, 2010
Revisiting double diffusion encoding MRS in the mouse brain at 11.7T: Which microstructural features are we sensitive
Mélissa Vincent1, Marco Palombo2, Julien Valette1
1Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), MIRCen, F-92260, Fontenay-aux-Roses, France; Neurodegenerative Diseases Laboratory, UMR9199, CEA, CNRS, Université Paris Sud, Université Paris-Saclay, F-92260, Fontenay-aux-Roses, France.
Abstract:
Brain metabolites, such as N-acetylaspartate or myo-inositol, are constantly probing their local cellular environment under the effect of diffusion. Diffusion-weighted NMR spectroscopy therefore presents unparalleled potential to yield cell-type specific microstructural information. Double diffusion encoding (DDE) consists in applying two diffusion blocks, where gradient's direction in the second block is varied during the course of the experiment. Unlike single diffusion encoding, DDE measurements at long mixing time display some angular modulation of the signal amplitude which reflects microscopic anisotropy (microA), while requiring relatively low gradient strength. This angular dependence has been formerly used to quantify cell fiber diameter using a model of isotropically oriented infinite cylinders. However, how additional features of the cell microstructure (such as cell body diameter, fiber length and branching) may also influence the DDE signal has been little explored. Here, we used a cryoprobe as well as state-of-the-art post-processing to perform DDE acquisitions with high accuracy and precision in the mouse brain at 11.7 T. We then compared our results to simulated DDE datasets obtained in various 3D cell models in order to pinpoint which features of cell morphology may influence the most the angular dependence of the DDE signal. While the infinite cylinder model poorly fits our experimental data, we show that incorporating branched fiber structure in our model allows more realistic interpretation of the DDE signal. Lastly, data acquired in the short mixing time regime suggest that some sensitivity to cell body diameter might be retrieved, although additional experiments would be required to further support this statement.
Insights
Double diffusion encoding (DDE) in NMR spectroscopy reveals brain microstructure. Incorporating branched fiber structures improves DDE signal interpretation, offering insights beyond simple fiber diameter measurements.
Area of Science:
- Neuroimaging
- Biophysical techniques
- Magnetic Resonance Imaging
Background:
- Diffusion-weighted NMR spectroscopy offers potential for cell-type specific microstructural information.
- Brain metabolites probe their cellular environment via diffusion.
- Double diffusion encoding (DDE) measures microscopic anisotropy (microA) using angular modulation.
Purpose of the Study:
- To investigate the influence of cell morphology features on DDE signal.
- To compare experimental DDE data with simulated datasets from 3D cell models.
- To refine models for interpreting DDE signals in brain microstructure.
Main Methods:
- High-accuracy DDE acquisitions in mouse brain at 11.7 T using a cryoprobe.
- State-of-the-art post-processing techniques for DDE data.
- Comparison of experimental data with simulated DDE datasets from various 3D cell models.
Main Results:
- The infinite cylinder model showed poor fit to experimental DDE data.
- Incorporating branched fiber structures into the model improved DDE signal interpretation.
- Short mixing time DDE data suggest potential sensitivity to cell body diameter.
Conclusions:
- Branched fiber structure is a critical feature for realistic DDE signal interpretation in brain microstructure.
- Current models based on infinite cylinders are insufficient for capturing DDE signal complexity.
- Further experiments are needed to confirm the sensitivity of DDE to cell body diameter.

