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le Boeuf Flo, A.

Publications and source records attributed to le Boeuf Flo, A..

2 recordsLinked to original sources

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↗

Maturation-informed synthetic Magnetic Resonance Images of the Developing Human Fetal Brain

Magnetic resonance imaging is a powerful modality to investigate abnormal developmental patterns in utero. However, since it is not the first-line diagnostic tool in this sensitive population, data remain scarce and heterogeneous between scanners and centers. In addressing the data scarcity issue while generating data representative of real fetal brain MRI, we proposed FaBiAN, a Fetal Brain magnetic resonance Acquisition Numerical phantom. Here, we present a novel synthetic dataset of 594 two-dimensional, low-resolution series of T2-weighted images corresponding to 78 developing human fetal brains between 20.0 and 34.8 weeks of gestational age. Data are generated with substantive improvements from the original FaBiAN to account for local heterogeneities within white matter tissues throughout maturation. These synthetic-yet-highly-realistic images cover both healthy and pathological development trajectories simulated with standard clinical settings and anatomically informed by the Fetal Tissue Annotations (FeTA) dataset. Two independent radiologists qualitatively assessed the realism of the simulated images. We also quantitatively demonstrate the simulated datas increased fidelity to real data compared to the previous FaBiAN version. The reuse potential of the proposed dataset was also evaluated in the context of automated fetal brain tissue segmentation. Besides, our dataset that combines images generated from various clinical scenarios has been made publicly available to support the continuous endeavor of the community to develop advanced post-processing methods aswell as cutting-edge artificial intelligence models.

bioinformatics↗