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Nashira Baena

Publications and source records attributed to Nashira Baena.

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CORTET: Robust generation of simulation-ready tetrahedral meshes of the fetal cerebral cortex

Every human brain folds differently, and such natural variation confounds the search for imaging biomarkers of neurodevelopmental disorders. Physics-based simulation can help determine the causal mechanisms that underpin this variability. Yet every simulation must be initiated from a volumetric mesh of the brain's interior, tetrahedral or hexahedral, and it is the worst element in that mesh, not the average, that decides whether the simulation runs at all. Building that mesh from fetal MRI currently requires labour-intensive manual intervention. We therefore present CORTET (CORtical TETrahedral meshing): a fully automated pipeline that converts a triangulated cortical surface into a solver-ready tetrahedral mesh whose worst-element quality meets a strict quality target with no manual repair. By benchmarking against a general-purpose tetrahedral mesher on the same input surfaces, we isolate the pipeline's contribution from that of the input geometry, and we validate quality across a cohort of nearly 200 fetal subjects spanning the folding period. A mesh taken straight from the pipeline sustains a numerically stable morphoelastic folding simulation of a real fetal subject.

math-ph

NEUBORN: The Neurodevelopmental Evolution framework Using BiOmechanical RemodelliNg

Understanding individual cortical development is essential for identifying deviations linked to neurodevelopmental disorders. However, current normative modelling frameworks struggle to capture fine-scale anatomical details due to their reliance on modelling data within a population-average reference space. Here, we present a novel framework for learning individual growth trajectories from biomechanically constrained, longitudinal, diffeomorphic image registration, implemented via a hierarchical network architecture. Trained on neonatal MRI data from the Developing Human Connectome Project, the method improves the biological plausibility of warps, generating growth trajectories that better follow population-level trends while generating smoother warps, with fewer negative Jacobians, relative to state-of-the-art baselines. The resulting subject-specific deformations provide interpretable, biologically grounded mappings of development. This framework opens new possibilities for predictive modeling of brain maturation and early identification of malformations of cortical development.

q-bio.QM