3469

Selective probe of intra- and extra-cellular diffusion with non-invasive MRI using non-uniform oscillating gradients

Ignacio Lembo Ferrari^1,2, Manuel Avellaneda^1,2, Ezequiel L. Saidman^1,2, Francisco Divi¹, and Gonzalo A. Alvarez^1,2,3
¹Instituto Balseiro, CNEA, Universidad Nacional de Cuyo, S. C. de Bariloche, Argentina, ²Centro Atómico Bariloche, CONICET, CNEA, S. C. de Bariloche, Argentina, ³Instituto de Nanociencia y Nanotecnologia, CNEA, CONICET, S. C. de Bariloche, Argentina

Synopsis

Keywords: Microstructure, Diffusion/other diffusion imaging techniques

Motivation: Overcoming MRI resolution limitations is crucial for early-diagnosis of cellular-level pathologies. Achieving non-invasive MRI-images with cellular-resolution promises deeper insights into tissue-microstructure for advancing medical diagnosis.

Goal(s): We aim to obtain cellular-resolution by characterizing molecular diffusion within intra- and extra-cellular compartments. We use Non-uniform Oscillating-Gradient Spin-Echo (NOGSE) signal-filtering potential, to address this intricate molecular diffusion problem.

Approach: We employ diffusion-theory and the NOGSE-sequence, to quantitatively characterize yeast-cell phantoms mimicking tissue-microstructure.

Results: We successfully characterize distinct diffusion-regimes within and outside cells. We introduce an innovative method to discriminate intra- and extra-cellular signals without complex models and analyses, allowing selective measurements of specific tissue-microstructure compartments.

Impact: We introduce a transformative approach to non-invasive imaging, allowing cellular-level resolution discriminating different tissue-microstructure features without model assumptions. It offers a tool to investigate intricate cellular structures. Harnessing this technology might benefit patient early-diagnosis of diseases, based on quantitative images.

Introduction

Our study is motivated by the dual goals of advancing our understanding of cellular microstructure probed by molecular diffusion^1-7 while harnessing the potential of using Non-uniform Oscillating-Gradient Spin-Echo (NOGSE) sequence^8-10 for this purpose. These insights carry far-reaching implications, as understanding cellular microstructure and molecular diffusion in complex systems is vital for medical sciences, offering opportunities for enhanced diagnostics and therapeutic strategies^11-14.

In this context, our work represents a step forward to unlock the potential of NOGSE as a powerful tool for non-invasive cellular microstructure characterization, enabling the precise separation of signals originating from within and outside cells. The key advantage is that it facilitates precise investigations without the need for complex mathematical models and analyses. These results hold substantial promise as a diagnosis paradigm for the understanding of tissue microstructure to address critical questions connected with diseases^11-14.

Methods

Tissue phantom
We imitate cellular tissue properties, using fresh saccharomyces cerevisiae commercial yeast cells dissolved in water (Fig. 1). We wait until cells are deposited at the bottom of a plastic tube. Previous work¹⁰ on similar samples have shown that the mean diameter of cells is around 5.8 $$$\mu$$$m. We assume the cells have a spherical geometry.

Diffusion weighted imaging
Diffusion weighted MRI experiments were performed in a 9.4T preclinical-scanner (Bruker Avance III HD WB-NMR). We exploit the signal decay due to dephasing induced by the molecular diffusion that contains information of the sample microstructure. Utilizing time-modulated magnetic field gradients enables the probing of the spins' Brownian motion, which is governed by the microstructural morphology of the sample, thereby facilitating its characterization^8-10,15-17.

Pulsed-Gradient Spin-Echo probing
We conducted Pulsed-Gradient Spin-Echo (PGSE) experiments on the yeast cells^18-19, with diffusion times systematically varied (Fig. 1b). We quantified the apparent diffusion coefficients for each diffusion time. We performed bi-exponential fittings to discern and extract the diffusion coefficients specific to the extra- and intra-cellular spaces (Fig. 2).

Selective diffusion probing by Non-uniform Oscillating Gradient Spin-echo
We employed the Non-uniform Oscillating Gradient Spin-Echo (NOGSE) technique^8-10 to selectively measure diffusion processes in our sample (Fig. 3a). NOGSE allowed us to filter signals from spins diffusing within specific restriction-sizes²⁰ (Fig. 3b). By adjusting control parameters, we scan and measure these restriction-sizes based on the signal evolution over different diffusion times (Fig. 4).

Results and Discussions

Intra- and extra-cellular apparent diffusion coefficients
We identified two diffusion regimes within the yeast cells phantom (Fig. 2). We extracted the apparent diffusion coefficients by fitting a bi-exponential model to the experimental data with varying b-values. The extra-cellular diffusion, characterized by a constant diffusion coefficient smaller than free water diffusion, suggests tortuous diffusion. The intracellular component exhibits a diffusion coefficient inversely proportional to the diffusion-time, indicating restricted diffusion.

NOGSE size-filters of intra- and extra-cellular compartments
Using NOGSE, we achieved selective separation of signals from within and outside the yeast cells, eliminating the need for complex diffusion models (Fig. 4). This means that we observed a bimodal distribution based on the NOGSE signal filter, where one mode is static (intracellular) and the other exhibits a time-dependent increase (extracellular) as a function of the diffusion-time (Fig. 4b). This dynamic behavior in the extracellular component is consistent with previous observations of extra-axonal (extra-cellular) phantom-models²¹.

Selective estimation of intra- and extra-cellular restriction-sizes
NOGSE's selective signal filtration showcases its ability to determine cellular sizes while filtering out extra-cellular signals (Fig. 5). The mean cell diameter estimation is in agreement with measurements obtained through optical microscopy¹⁰, underscoring NOGSE's reliability and its capacity to provide comprehensive data on cellular microstructure. Moreover, it can also determine selectively, extra-cellular microstructure sizes determined by a microtortuosity phenomenon evidencing an effective restriction size that grows as a function of the diffusion time, consistently with previous observations with extra-cellular (extra-axonal) phantom models²¹.

Conclusions

Our study highlights the capability of NOGSE to selectively filter two distinct water diffusion regimes, enabling precise investigations of specific microstructure regions without the need for complex mathematical models and analysis. Specifically, it offers an approach to selectively target and investigate distinct tissue microstructure regions, allowing a focused analysis of intra- and extra-cellular compartments. This feature offers versatility across a wide-range of parameters, making NOGSE advantageous over standard PGSE. Additionally, NOGSE requires lower diffusion-times and gradient strengths for cell diameter determination. Our experiments provided insights into the short-time diffusion processes within the extracellular compartments evidencing effective restriction-sizes that grow as a function of time, which remains an area for future investigation. Overall, NOGSE shows promise as a non-invasive tool for cellular microstructure studies, contributing to our understanding of cellular processes that might be connected to diseases.

Acknowledgements

This work was supported by CNEA; CONICET; ANPCyT-FONCyT PICT-2017-3156, PICT-2017-3699, PICT-2018-4333, PICT-2021-GRF-TI-00134, PICT-2021-I-A-00070; PIP-CONICET (11220170100486CO); UNCUYO SIIP Tipo I 2019-C028, 2022-C002, 2022-C030; Instituto Balseiro; Collaboration programs between the MINCyT (Argentina) and, MAECI (Italy) and MOST (Israel); and Erasmus+ Higher Education program from the European Commission between the CIMEC (University of Trento) and the Instituto Balseiro (Universidad Nacional de Cuyo).

References

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Figures

Fig. 1: (a,b) Yeast cells scheme-models for intra- and extra-cellular diffusion. (c) Expected behaviors for the apparent diffusion coefficients as a function of the diffusion time for free diffusion, intra- and extra-cellular diffusion.

Fig. 2: PGSE experimental data determined from the yeast cells. (a) Typical PGSE decay as a function of the $$$b$$$-value evidencing a bi-modal exponential decay. The black circles are the measured data. After fitting only the tail of the decay –the intra-cellular signal–, one can subtract this exponential component to the total signal to obtain the extra-cellular component shown in orange circles. (b) The determined apparent diffusion coefficients for free water, and the intra- and extra-cellular components. PGSE based on spin-echo (SE) and stimulated-echo (STE) were performed.

Fig. 3: (a) NOGSE sequence scheme used for selectively probe diffusion of specific microstructure regions. The NOGSE modulation weights diffusion on the signal amplitude and after an inversion pulse the signal is encoded with an EPI acquisition. (b) NOGSE contrast as a function of the restriction length $$$l_c$$$. It is given by the signal difference between the modulation extremes $$$x=y$$$ (CPMG modulation), and the $$$x=0$$$ limit (Hahn modulation). The difference has a maximum for a specific restriction-size $$$l_{c,f}$$$ that can be tuned²⁰ with $$$G$$$ and $$$t_d$$$.

Fig. 4: NOGSE contrast as a function of the filter center $$$l_{c,f}$$$ defined in Fig. 3. (a) Experimental data determined from the yeast cell samples for different diffusion times. A bimodal distribution is observed highlighting the intra- and extra-cellular contributions. (b) Restriction-size distributions derived from fittings of the intra- and extra-cellular components. Notice that the intra-cell has a constant average restriction-size, associated with the cell-size, while the extra-cellular restriction grows as a function of time.

Fig. 5: Typical NOGSE signals as a function of the modulation time $$$x$$$ (a). Restricted diffusion is evidence for the green circles, where the NOGSE contrast saturates after a finite time $$$x$$$, evidencing the intra-cell diameter constraining the diffusion (b). However, the extra-celullar component does not manifest a closed compartment, and the effective diameter size grows as a function of time (b). In (a), at a diffusion time $$$t_d= 30.0$$$ ms, the intra-cellular signal is filtered at $$$G = 500.0$$$ mT/m, and the extra-cellular signal at $$$G = 100.0$$$ mT/m.

Proc. Intl. Soc. Mag. Reson. Med. 32 (2024)

3469

DOI: https://doi.org/10.58530/2024/3469