Biology subjects

Jelescu, I.

Publications and source records attributed to Jelescu, I..

6 recordsLinked to original sources

bioRxiv2026

Diffusion MRI of cortical organoids reveals protocol-associated spatial reproducibility and increasing diffusivity with diffusion time

Early human cortical development involves rapid changes in cytoarchitecture that remain difficult to interrogate non-invasively. Biophysical diffusion MRI models provide a potential window onto this microstructure, including water exchange across cell membranes, but their assumptions are difficult to validate directly in developing human tissue. Human cortical organoids provide a tractable biological model in which diffusion measurements can be related to tissue architecture within the same specimen. We scanned six fixed cortical organoids at 9.4~T, three grown under a directed and three under an undirected differentiation protocol, at three diffusion times and b-values up to 7000~s/mm$^2$. Center-to-periphery profiles of DKI-derived diffusion metrics were reproducible across the directed organoids but more variable across the undirected organoids, while nuclear staining revealed greater variability in the internal architecture of the undirected organoids. Unexpectedly, mean diffusivity increased with diffusion time in more than 80% of tissue voxels in both batches, opposite to previous organoid measurements. Across 12,348 simulated two-compartment substrates, this increase was reproduced only with permeable membranes and an extracellular diffusivity substantially exceeding the apparent intracellular diffusivity, a regime that challenges assumptions commonly used in current gray-matter exchange models. These results support cortical organoids as biologically realistic platforms for probing early cortical microstructure and testing diffusion models under controlled conditions, while remaining amenable to post-MRI histological validation.

neuroscience↗

bioRxiv2026

The microstructure-weighted human connectome: network properties and structure-function correlations across spatial scales

Conventional connectome edge weights, such as number of streamlines (NOS) or diffusion tensor imaging (DTI) metrics, lack specificity to microstructural details which may hold relevance for macroscale brain organisation. Since biophysical diffusion modelling offers greater specificity to microstructure, we investigated whether parameters from the Standard Model of white matter diffusion provide informative alternatives for connectome weights - namely the intra-axonal signal fraction (f) and perpendicular extra-axonal diffusivity (DePerp). Using diffusion MRI data from healthy adults, we constructed structural networks at four parcellation scales, weighted by f, DePerp, NOS, fractional anisotropy (FA) and radial diffusivity (RD). While all weights reproduced expected small-world properties and hub structure, only DePerp and normalised NOS captured non-random properties of local organisation at all spatial scales. We then correlated each weighted connectome with resting-state fMRI functional connectivity and intracranial measurements of conduction velocity. At both the whole-brain and regional level, NOS gave strong coupling with fMRI functional connectivity. Connectomes weighted by DePerp, FA and RD gave weak but significant coupling with fMRI functional connectivity and conduction velocity. Notably, DePerp and RD gave highest consistency in regional structure-function coupling across spatial scales. Thus, connectome weights derived from DePerp capture meaningful aspects of brain network organisation with functional relevance.

neuroscience↗

bioRxiv2025

Introducing a translationally relevant mouse model of radiosurgery-induced unilateral hearing loss

BackgroundStereotactic radiosurgery (SRS) is widely used to treat vestibular schwannomas but may cause irreversible hearing loss due to cochlear toxicity. The underlying mechanisms are not fully understood, and no effective otoprotective therapies exist. We aimed to establish a mouse model that replicates the clinical pattern of radiation-induced hearing loss. MethodsC57BL/6J mice (n=31) received 8 Gy (n=3), 16 Gy (n=5), 24 Gy (n=8), or 32 Gy (n=15) using the Leksell Gamma Knife ICON system. Targeting was based on the built-in cone-beam CT, co-registered with MRI and CT-based mouse atlases, to guide unilateral cochlea targeting. A single isocenter was placed lateral to the right cochlea, with the 80% isodose line traversing its medial edge. Auditory brainstem response (ABR) was measured at baseline and at 1 and 4 weeks post-SRS. A 32 Gy subgroup (n=7) was evaluated at 16 weeks. Histological analysis of cochleae was performed at 4 weeks in all groups and at 16 weeks in the long-term 32 Gy group. ResultsSRS was well tolerated, and the contralateral cochlea received a very low radiation dose. No ABR shifts were observed at 8 or 16 Gy, with only minimal histological changes. At 32 Gy, ABR threshold shifts at 22.6 and 32 kHz were evident by week 1 and worsened by week 4. Similar but milder effects occurred at 24 Gy. In the 32 Gy long-term subgroup, hearing loss progressed across all frequencies, most severely at high frequencies, alongside a sustained wave I amplitude decline. At 32 Gy, outer hair cells were reduced by 14% and 44% at 32 and 45.2 kHz, respectively, at 4 weeks, and by 38% and 80% at 16 weeks. Ribbon synapses were mildly reduced at 4 weeks and more markedly at 16 weeks in corresponding high-frequency regions. Spiral ganglion neuron density was mildly reduced at the basal and middle turns. All reported changes were statistically significant when compared to the contralateral ear. ConclusionsThis new model reproduces key features of SRS-induced cochlear toxicity, including unilateral, dose-dependent, and progressive hearing loss. It thus provides a valuable platform for investigating mechanisms and testing otoprotective strategies.

neuroscience↗

bioRxiv2025

Comparative Systematic Analysis of Gray Matter BiophysicalModels on a Public Dataset

Biophysical models of diffusion tailored to characterize gray matter (GM) microstructure are gaining traction in the neuroimaging community. NEXI, SMEX, SANDI, and SANDIX represent recent efforts to incorporate different microstructural features,such as soma contributions and inter-compartment exchange, into the diffusion MRI (dMRI) signal. In this work, we present a comparative evaluation of these four gray matter models on a single, publicly available in vivo human dataset, the Connectome Diffusion Microstructure Dataset (CDMD), acquired with two diffusion times. Using the open-source Gray Matter Swiss Knife toolbox, we estimate cortical microstructure metrics in 26 healthy subjects and evaluate goodness of fit, anatomical patterns and consistency with previous studies. CDMD data yielded GM parameter estimates consistent with values reported in previous studies. This retrospective cross-model analysis establishes the feasibility of estimating exchange models from only two diffusion times and highlights trade-offs in biological specificity, model complexity, and fitting robustness, critical considerations when choosing a model for future clinical and research applications.

neuroscience↗

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↗