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September 17, 2025Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition0 citations

Modeling lactate diffusion in gray matter in the context of the astrocyte-neuron lactate-shuttle

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EMEloïse MougelJVJulien Valette

Key Points

  • Estimated neuronal lactate fraction is about 4%, while the astrocytic fraction is around 66%, highlighting the distribution in gray matter.
  • The three-compartment model indicates approximately 40% of the lactate is found in extracellular space, compatible with astrocyte-neuron lactate shuttle dynamics.
  • Using time-dependent diffusion-weighted magnetic resonance spectroscopy (DW-MRS), this approach provides new insights into lactate transport in the brain.
  • Three-compartment modeling may enhance understanding of lactate roles in gray matter, but accuracy is challenged by high noise levels.

Abstract

Motivation: Astrocyte-neuron lactate shuttle hypothesis (ANLS) remains fiercely debated due to the difficulty to assess lactate compartmentation non-invasively. Goal(s): Using time-dependent DW-MRS and a new, three-compartment model, we propose to assess the neuronal, astrocytic and extracellular fraction of lactate. Approach: A three-compartment model is built with parameters describing intra-neuronal and intra-astrocytic lactate diffusion derived from NAA and myo-inositol diffusion, respectively, and an extracellular compartment considered Gaussian. Results: Using this model, neuronal lactate fraction is estimated at ~4%, astrocytic fraction at ~66% and extracellular fraction at ~40%, suggesting a concentration gradient from astrocytes to neurons compatible with ANLS. Impact: Three-compartment modeling of lactate diffusion is a promising tool for assessing lactate compartmentation in gray matter. It yields lactate fraction in astrocyte, neurons and extracellular space compatible with ANLS, but its use remains difficult when noise is large.

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Cite This Study

Mougel et al. (2025) studied this question.

synapsesocial.com/papers/68d4597b31b076d99fa5cb25https://doi.org/10.58530/2025/0151
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