0597

Diffusivity and kurtosis time-dependence changes in the rat brain during somatosensory evoked response

Andreea Hertanu¹, Tommaso Pavan¹, and Ileana O. Jelescu¹
¹Dept. of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland

Synopsis

Keywords: Microstructure, Gray Matter, Microstructure, Permeability, fMRI (task based), Multimodal, Small Animals, Preclinical

Motivation: The microstructure-function relationship is essential for our understanding of the healthy and pathological human brain.

Goal(s): In this context, the goal of our study was to investigate microstructural changes arising in the brain during neuronal activity.

Approach: Differences in mean diffusivity MD and mean kurtosis MK time-dependence between rest and active states were assessed in the somatosensory cortex following rat forepaw stimulation.

Results: While no changes were found in control cortical regions, the BOLD-fMRI positive cluster presented a significant decrease in MD and MK during activation. Interestingly, subcortical somatosensory relays displayed the opposite trend which could result from changes in inhibitory/excitatory balance.

Impact: Neuronal activity is accompanied by a myriad of microstructural changes. The diffusion-weighted signal sensitivity to underlying brain microstructure brings new perspectives into the structure-function relationship along with the promise of a functional contrast unbound from the current limitations of BOLD-fMRI.

Introduction

In diffusion MRI (dMRI), universal classes of tissue disorder¹ allow the exploration of the time-dependent nature of diffusion in tissues and offer valuable insights into microstructural properties and dynamic phenomena^2–6. Neuronal activity is accompanied by several physiological and biochemical processes, which lead to cellular swelling^7–10 and increased transmembrane permeability¹¹. In this study we propose to investigate differences in mean diffusivity MD(∆) and mean kurtosis MK(∆) that arise during neuronal activation on account of morphological and metabolic changes. Forepaw electrical stimulation is used in adult rats to generate a somatosensory response. BOLD-fMRI is acquired as a control for the activation and the BOLD activation cluster is employed to define the region-of-interest (ROI) in which main diffusion changes between the rest and active states are assessed. Other ROIs in the brain devoid of BOLD response are also examined.

Methods

Animal preparation: Experiments were performed in vivo on six female rats (241±16g) on a 14.1T system, using a home-built surface transceiver RF-coil. Electrodes were implanted in the rat forepaws¹² under isoflurane anesthesia. Anesthesia was gradually switched to medetomidine and the dMRI/BOLD-fMRI protocol started at fixed time-delay after medetomidine bolus (Fig.1A).

Paradigm design: Stimulation consisted in 0.3ms pulses at 2mA and 9Hz frequency, triggered by the scanner. Each run consisted in blocks of 28s stimulation and 28s rest (Fig.1A). Left and right paw stimulation were alternated.

Structural: RARE-T₂w sequences (TEeff/TR=6/2500ms, matrix size 160×160x45; in-plane resolution 125x125μm2; slice thickness 0.5mm) were used for anatomical reference.

dMRI: PGSE-EPI sequences (TE/TR=48/2000ms; matrix size 80x80x21; slice thickness 0.75µm; in-plane resolution 0.25x0.25µm2; δ=4ms) were used. For each run there were five dMRI acquisitions (Δ=9.5;15;20;25;30ms). Each acquisition included 21 measurements¹³ (3 b₀, two b-values bval^i,j, where i=1;2ms/µm² and j=9 directions) repeated 4 times while alternating between rest and stimulation (Fig.1A). Data underwent denoising¹⁴, topup¹⁵ and eddy¹⁶ corrections (Fig.1B) before the estimation of axially-symmetric diffusion and kurtosis tensors¹⁷. MD(∆)&MK(∆) were evaluated using functional forms of disorder and exchange.

BOLD-fMRI: A gradient-echo EPI sequence was used (TE/TR=11.1/1000ms) with the same geometry as the dMRI acquisitions. Data underwent topup¹⁵, slice timing correction and spatial smoothing prior to analyzing the BOLD response in SPM12.

Template generation: ANTs¹⁸ was employed to generate multivariate b₀/BOLD-fMRI/T₂w templates (Fig.1B), which served as a common space for the propagation of ROIs from the Waxholm Space Atlas¹⁹, as well as the propagation of the BOLD cluster segmentations to the diffusion images.

Statistical analysis: A mixed effects model was used to determine the significance of differences in MD&MK across diffusion times and across state (rest vs. active). Subjects and run numbers were modeled as nested random effects.

Results and Discussion

Only results for the right hemisphere are presented, where contralateral designates the left forepaw stimulation (BOLD response in the right somatosensory cortex - SC), and ipsilateral designates right forepaw stimulation (BOLD response in the left SC).

Fig.2 shows an example of BOLD activation cluster and other atlas-defined ROIs investigated, along with examples of MD&MK maps.

Fig.3 displays MD(∆)&MK(∆) in the BOLD-defined cluster and the other ROIs.

Rest/Stimulus differences: Statistically significant decrease in MD&MK in the active state was obtained in the contralateral BOLD cluster (green asterisks), while no differences were found ipsilaterally or in any cortical control region (cingulate, retrosplenial, motor). The decrease in MD during activation is in line with previous studies^20,21 and attributed to cellular swelling^7–10. MK is expected to result from competing mechanisms of increased restriction (MK increase) and permeability (MK decrease). The net decrease suggests permeability dominates.

Remarkably, a statistically significant increase in MD&MK was obtained in the thalamus, hippocampus, and striatum for contralateral and ipsilateral activations of SC, while these regions did not display significant BOLD response. The thalamus is responsible for relaying somatosensory signals^22,23, with known temporal coherence between thalamus and SC during activation²⁴, while the striatum²⁵ and hippocampus²⁶ are also part of the somatosensory relays. The increase in MD&MK during activation might reflect complex inhibitory and excitatory responses occurring in these brain regions during somatosensory input processing.

Measurable MD(∆)&MK(∆) was found in all ROIs and both conditions (Fig.3, purple asterisks). Lower AICc from the 1D-disorder model (Fig.4A) points towards a superior contribution from intracellular disorder to the MD temporal decay. For MK(∆), similar AICc for 1D-structural disorder (Fig.4B) and the Kärger (Fig.5) models outline the contribution of both effects, thus hampering a robust estimation of the exchange time from the Kärger model.

Conclusion

A significant decrease in MD(∆)&MK(∆) accompanies the activation of the somatosensory cortex and can be attributed to changes in both morphology and permeability. Remarkably, subcortical relays displayed opposite trends which could result from changes in inhibitory/excitatory balance.

Acknowledgements

The authors thank Lucas Soustelle for sharing the diffusion sequence with the reversed phase encoding and for help with the implementation of the trigger in the diffusion sequence, Stefan Mitrea and Analina Hausin for their assistance with animal setup and monitoring, Bernard Lanz and Claudia Zanella for providing the RF coil. This work took place at the CIBM Center for Biomedical Imaging, a Swiss research center founded and supported by Lausanne University Hospital (CHUV), the University of Lausanne (UNIL), the Swiss Federal Institute of Technology (EPFL), the University of Geneva (UNIGE) and Geneva University Hospital (HUG) and was supported by the Swiss National Science Foundation under Eccellenza grant PCEFP2_194260.

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Figures

Figure 1. Data acquisition (A) and processing pipeline (B). (A): Up to 5 dMRI (x5 diffusion times) and BOLD-fMRI runs were acquired per rat. Within each dMRI acquisition, data were sampled for 2 b-values, 9 directions and 4 repetitions to yield one MD(∆) and MK(∆) map in each state (rest/active). (B): After generating a b₀ and an fMRI template for each rat from the pre-processed images inside each run, the multivariate template construction routine from ANTs was used to generate b₀/BOLD-fMRI/T₂w templates.

Figure 2. Rostro-caudal slices of the rat brain depict an example of BOLD activation cluster during left forepaw stimulation (contralateral activation) and the atlas-defined ROIs investigated in this study: Cpu (striatum), ACC (cingulate cortex), M (motor cortex), RSC (retrosplenial cortex), Tha (thalamus) and Hip (hippocampus). (B): Mean diffusivity (MD) and mean kurtosis (MK) average maps over all runs for one rat illustrate the quality of the estimated axially-symmetric diffusion and kurtosis tensors.

Figure 3. (A) MD(∆) and (B) MK(∆) for active and rest states in the BOLD cluster and other ROIs represented as the mean over all rats and runs ± standard error. Green: significant state difference (rest/active); Purple: significant time-dependence. *p<0.05, **p<0.01, ***p<0.001 (no FDR correction). A significant drop in MD and MK during activation is seen contralaterally, without any change ipsilaterally, while significant increase is noted in Tha, Hip, Cpu, and no significant changes in RSC, ACC, M.

Figure 4. Results of the functional form fits for structural disorder for (A): MD(∆) and (B): MK(∆) in the BOLD cluster. Structural 1D disorder model fit the data best in both active and rest state contralaterally and ipsilaterally for MD and MK according to the corrected Akaike Information Criterion (AICc), suggesting a superior contribution from intracellular disorder.

Figure 5. Fits of the Kärger model of exchange to MK(∆) in the BOLD cluster. Similar AICc as compared to the 1D structural disorder (Fig.4B) and the Kärger outlines the contribution of both effects, thus hampering the estimation of the exchange time (t_ex). Despite the slight decrease/increase in t_ex between rest and active conditions obtained contralaterally/ipsilaterally, which also supports the net decrease in MK between rest and active conditions, the difference remains inside the estimation error.

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

0597

DOI: https://doi.org/10.58530/2024/0597