Biology subjects

Amandola, M.

Publications and source records attributed to Amandola, M..

4 recordsLinked to original sources

bioRxiv2026

Automated Segmentation of Brainstem and Subcortical White Matter: Mapping the Deep Tegmental Core with BundleParc

Diffusion MRI enables noninvasive mapping of human white matter pathways, but automated segmentation methods have largely focused on large association, projection, and commissural bundles. Brainstem and subcortical pathways supporting basal ganglia, cerebellar, limbic/reward, sensory, and homeostatic functions remain underrepresented in large-scale connectomic analyses. To address this gap, we adapted BundleParc, a recently introduced bundle-parcellation architecture, into an automated pipeline for direct segmentation and along-tract parcellation of 97 subcortical and brainstem white matter pathways. The model was trained on a curated reference dataset derived from Human Connectome Project diffusion MRI using anatomy-guided tractography, explicit inclusion and exclusion criteria, automated outlier filtering, and manual quality assurance. Operating directly on native-space fiber orientation distributions, the algorithm successfully recovers these intricate anatomical trajectories and ordered parcellations. We show the model generalizes to diverse external datasets spanning development, aging, and neurodegenerative disease cohorts, maintaining robust performance across variations in spatial resolution and angular sampling. The released container, trained model, population atlas, reference streamlines, and quality assurance outputs provide a resource for studying deep brainstem and subcortical pathways in development, aging, disease, and neuromodulation-relevant anatomy.

neuroscience↗

bioRxiv2026

Charting Cervical Spinal Cord Morphometry Across the Lifespan

Spinal cord morphometry provides essential biomarkers of neurological health, but clinical interpretations are confounded by inter-subject variability and a lack of normative references across the full human lifespan. We address this gap by generating the first comprehensive lifespan charts for cervical spinal cord morphometry. We leveraged 30 population-based brain MRI datasets, aggregating 78,269 scans from 41,042 individuals (ages 0-100) whose imaging protocols included cervical cord coverage. To overcome contrast variability, we employed a state-of-the-art contrast-agnostic deep learning segmentation method, extracting cross-sectional area (CSA), anteroposterior (AP) and right-left (RL/transverse), and shape indices (compression ratio, eccentricity, and solidity) from C1 to C7. Normative trajectories were modeled using Generalized Additive Models for Location, Scale, and Shape (GAMLSS). The resulting charts reveal distinct non-linear lifespan changes: rapid growth through childhood and adolescence, peak maturation occurring in early-to-mid adulthood (e.g., mid-30s for CSA), followed by gradual decreases. Significant regional variations along the cervical cord and consistent sex differences (males > females for size metrics) were quantified. Spinal cord trajectories showed strong temporal coupling with brain white matter and brainstem volumes, suggesting integrated CNS development and aging. These lifespan charts provide a robust normative framework, enabling age- and sex-specific centile scoring of individual spinal cord morphometry. This resource offers a critical tool for differentiating typical variation from pathological changes, enhancing the clinical utility of spinal cord MRI in studies of development and neurodegeneration.

neuroscience↗

bioRxiv2025

Advancing High-Resolution 7T Diffusion MRI: Evaluating Phase-Encoding Correction Strategies for Distortion Correction from Basic to Four-Way Acquisitions

PurposeHigh-resolution 7T diffusion MRI (dMRI) is limited by image artifacts that compromise anatomical accuracy. The purpose of this study was to systematically evaluate phase-encoding (PE) acquisition and correction strategies to determine which methods best mitigate geometric distortions and improve data reproducibility. MethodsFive healthy adults were each scanned twice on a 7T MRI scanner (0.9 mm isotropic resolution), using a highly oversampled dMRI protocol with four PE directions (AP, PA, RL, LR). From this dataset, we created and processed eleven time-equivalent, 10-minute acquisitions, ranging from uncorrected single-PE data to comprehensive 4-way PE schemes. These strategies were quantitatively compared on their geometric alignment with T1-weighted images and on the scan-rescan reproducibility of DTI-derived metrics. Results(1) All distortion-corrected schemes significantly improved geometric accuracy over uncorrected data; (2) Strategies correcting with a full set of reversed-PE (2-way) diffusion weighted images (DWIs) outperformed the common approach of using only a single reversed b=0 image; and (3) a 4-way PE acquisition consistently provided the highest image fidelity and reproducibility. The optimized acquisition enabled high-quality reconstruction of both long-range and fine-scale superficial white matter pathways. ConclusionFor high-resolution 7T dMRI, multi-PE acquisition is essential to achieve accurate geometry and stable microstructural estimates (i.e., less residual EPI distortion and better scan-rescan agreement). A 4-way PE scheme provides the most accurate and reproducible results for microstructural and connectivity modeling. Data statementData will be made available in BIDS format upon acceptance of the manuscript. To be updated with DOI.

neuroscience↗

bioRxiv2025

Bridging Histology and Tractography: First Visualization of the Short-Range Prefrontal Connections in the Human Brain

Decades of histological research in non-human primates have revealed a dense web of short-range connections underpinning prefrontal cortex (PFC) function. However, translating this anatomical ground-truth to the living human brain has been a major challenge, leaving our understanding of the PFCs intrinsic wiring incomplete. These short-range fibers are difficult to resolve with non-invasive methods like diffusion tractography, which are often hampered by false positives. Here, we provide the first systematic in-vivo visualization of these pathways in the human brain. By informing high-resolution probabilistic tractography with established tract-tracing findings, we mapped 91 histologically-defined short-range connections within and between five major PFC subdivisions in 1,003 individuals (547 F, 456 M). Our anatomically-informed approach successfully reconstructed these intricate connections with high precision (>80%) and accuracy (>70%) relative to histological findings. The resulting tracts not only captured broad organizational principles but also replicated fine-grained patterns previously only seen in invasive studies. Furthermore, these connections showed high test-retest reliability within individuals alongside significant variability between them, highlighting a stable yet unique anatomical fingerprint. Ultimately, this study shows how linking histology to tractography provides a powerful framework to advance our understanding of the human connectome and opens avenues to investigate local circuitry that underpins cognition and disease.

neuroscience↗