Kalpatthi, H. | bioRxiv Science

bioRxiv2025

Mapping the Fascicular Morphology and Organization of the Human Sciatic Nerve via High-Resolution MicroCT Imaging

ObjectiveImplanted neuroprostheses can restore standing and walking after spinal cord injury and somatosensation after limb loss. Yet current approaches often fail to reliably activate hamstring muscles crucial for upright stability and mobility or to target afferent fibers for sensory restoration. We developed a novel methodology using high-resolution micro-computed tomography (microCT) to visualize and track fascicle groups innervating distinct hamstring muscles along the human sciatic nerve. This approach provides a framework for mapping fascicular topography in complex neural pathways to optimize standing neuroprostheses. MethodsBilateral sciatic nerves were dissected and excised from an embalmed human cadaver, annotated with branch names, and stained with phosphotungstic acid before undergoing microCT scanning at 11.4 m isotropic resolution. Images were segmented with a 3D U-Net convolutional neural network. Segmentation results were used to quantify morphological metrics and track fascicular organization along [~]25 cm of the nerve. MicroCT reconstructions were validated against histological cross sections. ResultsGross dissection revealed matched proximal-to-distal branching between left and right sciatic nerves: branch to long head of the biceps femoris (lhBF), branch to hamstring part of the adductor magnus and semimembranosus (HAM/SM), and branch to semitendinosus (ST). All branches originated medially and followed an inferomedial trajectory. Branch-free lengths of the sciatic exhibited asymmetry, especially between the lumbosacral roots to the first branch (5.5 cm left vs. 1.5 cm right) and lhBF to the HAM/SM branch (9.0 cm left vs. 16.5 cm right). MicroCT analysis revealed bilateral symmetry in fascicle diameters ([~]0.4 mm) and total fascicle counts ([~]84) but asymmetry in hamstring-innervating fascicle counts (left [~]7, right: [~]9). The 3D fascicular maps revealed that hamstring fascicles were located in the anteromedial portion of the sciatic nerve cross section and remained separate for distances up to 15.9 cm proximal to their branching points. SignificanceOur microCT-based approach enables efficient, high-resolution 3D mapping of fascicular organization within large, complex peripheral nerves like the sciatic nerve, overcoming previous technical limitations. This methodology informs development of neuroprostheses with improved hamstring muscle activation for enhanced standing function.

bioengineering↗

bioRxiv2025

Automated 3D Segmentation of Human Vagus Nerve Fascicles and Epineurium from Micro-Computed Tomography Images Using Anatomy-Aware Neural Networks

ObjectivePrecise segmentation and quantification of nerve morphology from imaging data are critical for designing effective and selective peripheral nerve stimulation (PNS) therapies. However, prior studies on nerve morphology segmentation suffer from important limitations in both accuracy and efficiency. This study introduces a deep learning approach for robust and automated 3D segmentation of human vagus nerve fascicles and epineurium from high-resolution micro-computed tomography (microCT) images. MethodsWe developed a multi-class 3D U-Net to segment fascicles and epineurium that incorporates a novel anatomy-aware loss function to ensure that predictions respect nerve topology. We trained and tested the network using subject-level five-fold cross-validation with 100 microCT sub-volumes (11.4 m isotropic resolution) from cervical and thoracic vagus nerves stained with phosphotungstic acid from five subjects. We benchmarked the 3D U-Nets performance against a 2D U-Net using both standard and anatomy-specific segmentation metrics. ResultsOur 3D U-Net generated high-quality segmentations (average Dice similarity coefficient: 0.93). Compared to the 2D U-Net, our 3D U-Net yielded significantly better volumetric overlap, boundary delineation, and fascicle-level accuracy. The 3D approach reduced anatomical errors by 2.5-fold, provided more consistent inter-slice boundaries, and improved detection of fascicle splits/merges by nearly 6-fold. SignificanceOur automated 3D segmentation pipeline provides anatomically accurate 3D maps of peripheral neural morphology from microCT data. The automation allows for high throughput, and the substantial improvement in segmentation quality and anatomical fidelity enhances the reliability of morphological analysis, vagal pathway mapping, and the implementation of realistic computational models. These advancements provide a foundation for understanding the functional organization of the vagus and other peripheral nerves and optimizing PNS therapies.

neuroscience↗