Jelescu, I. | Search bioRxiv

bioRxiv2024

Human gray matter microstructure mapped using Neurite Exchange Imaging (NEXI) on a clinical scanner

Biophysical models of diffusion in gray matter (GM) can provide unique information about microstructure of the human brain, in health and disease. Therefore, their compatibility with clinical settings is key. Neurite Exchange Imaging (NEXI) is a two-compartment model of GM microstructure that accounts for inter-compartment exchange, whose parameter estimation requires multi-shell multi-diffusion time data. In this work, we report the first estimates of NEXI in human cortex obtained on a clinical MRI scanner. To do that, we establish an acquisition protocol and fitting routine compatible with clinical scanners. The model signal equation can be expressed either in the narrow-pulse approximation, NEXINPA, or accounting for the actual width of the diffusion gradient pulses, NEXIWP. While NEXINPA enables a faster analytical fit and is a valid approximation for data acquired on high-performance gradient systems (preclinical and Connectom scanners), on which NEXI was first implemented, NEXIWP has significant relevance for data acquired on clinical scanners with longer gradient pulses. We establish that, in the context of broad pulses, NEXIWP estimates were more comparable to previous literature values. Furthermore, we evaluate the repeatability of NEXI estimates in the human cortex on a clinical MRI scanner and show intra-subject variability to be lower than inter-subject variability, which is promising for characterizing healthy and patient cohorts. Finally, we analyze the relationship of NEXI parameters on the cortical surface to the Myelin Water Fraction (MWF), estimated using an established multicomponent T2 relaxation technique. Indeed, although it is present in small quantities in the cortex, myelin can be expected to decrease permeability. We confirm a strong correlation between the exchange time (tex) estimates and the MWF, although the spatial correspondence between the two is brain-region specific and other drivers of tex than myelin density are likely at play.

neuroscience↗

bioRxiv2024

Mapping activity and functional organisation of the motor and visual pathways using ADC-fMRI in the human brain

In contrast to blood-oxygenation-level-dependent (BOLD) functional MRI (fMRI), which relies on changes in blood flow and oxygenation levels to infer brain activity, diffusion fMRI (DfMRI) investigates brain dynamics by monitoring alterations in the Apparent Diffusion Coefficient (ADC) of water. These ADC changes may arise from fluctuations in neuronal morphology, providing a distinctive perspective on neural activity. The potential of ADC as an fMRI contrast (ADC-fMRI) lies in its capacity to reveal neural activity independently of neurovascular coupling, thus yielding complementary insights into brain function. To demonstrate the specificity and value of ADC-fMRI, both ADC-and BOLD-fMRI data were collected at 3T in human subjects during visual stimulation and motor tasks. The first aim of this study was to identify an acquisition design for ADC that minimises BOLD contributions. By examining the timings in responses, we report that ADC 0/1 timeseries (acquired with b-values of 0 and 1 ms/{micro}m2) exhibit residual vascular contamination while ADC 0.2/1 timeseries (with b-values of 0.2 and 1 ms/{micro}m2) show minimal BOLD influence and higher sensitivity to neuromorphological coupling. Second, a General Linear Model was employed to identify activation clusters for ADC 0.2/1 and BOLD, from which average ADC and BOLD responses were calculated. The negative ADC response exhibited a significantly reduced delay relative to the task onset and offset as compared to BOLD. This early onset further supports the notion that ADC is sensitive to neuromorphological rather than neurovascular coupling. Remarkably, in the group-level analysis, positive BOLD activation clusters were detected in the visual and motor cortices, while the negative ADC clusters mainly highlighted pathways in white matter connected to the motor cortex. In the averaged individual level analysis, negative ADC activation clusters were also present in the visual cortex. This finding confirmed the reliability of negative ADC as an indicator of brain function, even in regions with lower vascularisation such as white matter. Finally, we established that ADC-fMRI timecourses yield the expected functional organisation of the visual system, including both gray and white matter regions of interest. Functional connectivity matrices were used to perform hierarchical clustering of brain regions, where ADC-fMRI successfully reproduced the expected structure of the dorsal and ventral visual pathways. This organisation was not replicated with the b=0.2 ms/{micro}m2 diffusion-weighted time courses, which can be seen as a proxy for BOLD (via T2-weighting). These findings underscore the robustness of ADC time courses in functional MRI studies, offering complementary insights to BOLD-fMRI regarding brain function and connectivity patterns. KeypointsO_LIThe functional time course of the Apparent Diffusion Coefficient (ADC), specifically measured with alternating b-values of 0.2 and 1 ms/{micro}m2 at 3T, appears to be minimally affected by BOLD contamination. C_LIO_LIIn the activity maps, the location of negative ADC clusters suggests neural activity in WM tracts that are connected to the motor cortex, which is not detected with positive BOLD. C_LIO_LIFunctional Connectivity analysis utilising ADC is better able to detect the organisation of the dorsal and ventral visual streams than diffusion- and T2-weighted time courses. C_LI

neuroscience↗