# Cellular EXchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres

arXiv: https://arxiv.org/abs/2303.16112 · HTML: https://mlsanity.com/paper/2303.16112/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models.
- Builds on 2 of its 66 references that are in the map.
- First posted on arXiv 28 Mar 2023.

## Placed in

- Diffusion models / [Medical imaging and segmentation](https://mlsanity.com/diffusion/medical-imaging-and-segmentation/)

## Builds on (most cited first, 2 of 2)

- [Rotationally-invariant mapping of scalar and orientational metrics of neuronal microstructure with diffusion MRI](https://mlsanity.com/paper/1609.09144/) (2016)
- [Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the substrate complexity and parameter choice on the reproducibility of results](https://mlsanity.com/paper/1908.11203/) (2019)

## Built on by (most cited first, 1 of 1)

- [TRACED: In vivo imaging of extracellular intrinsic diffusivity, tortuosity, cell size distribution and cell density in human glioma patients](https://mlsanity.com/paper/2605.02615/) (2026)

## Abstract (arXiv)

Purpose: Biophysical models of diffusion MRI have been developed to characterize microstructure in various tissues, but existing models are not suitable for tissue composed of permeable spherical cells. In this study we introduce Cellular Exchange Imaging (CEXI), a model tailored for permeable spherical cells, and compares its performance to a related Ball & Sphere (BS) model that neglects permeability. Methods: We generated DW-MRI signals using Monte-Carlo simulations with a PGSE sequence in numerical substrates made of spherical cells and their extracellular space for a range of membrane permeability. From these signals, the properties of the substrates were inferred using both BS and CEXI models. Results: CEXI outperformed the impermeable model by providing more stable estimates cell size and intracellular volume fraction that were diffusion time-independent. Notably, CEXI accurately estimated the exchange time for low to moderate permeability levels previously reported in other studies (kappa<25μ m/s). However, in highly permeable substrates (kappa=50μ m/s), the estimated parameters were less stable, particularly the diffusion coefficients. Conclusion: This study highlights the importance of modeling the exchange time to accurately quantify microstructure properties in permeable cellular substrates. Future studies should evaluate CEXI in clinical applications such as lymph nodes, investigate exchange time as a potential biomarker of tumor severity, and develop more appropriate tissue models that account for anisotropic diffusion and highly permeable membranes.