Spinal cord computational model

We define and explain the quasistatic approximation (QSA) as applied to field modeling for electrical and magnetic stimulation. Neuromodulation analysis pipelines include discrete stages, and QSA is applied specifically when calculating the electric and magnetic fields generated in tissues by a given stimulation dose. QSA simplifies the modeling equations to support tractable analysis, enhanced understanding, and computational efficiency. The application of QSA in neuromodulation is based on four underlying assumptions: (A1) no wave propagation or self-induction in tissue, (A2) linear tissue properties, (A3) purely resistive tissue, and (A4) non-dispersive tissue...

OBJECTIVE: This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients. METHODS: 4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model...

Individuals who have suffered a spinal cord injury often require assistance to complete daily activities, and for individuals with tetraplegia, recovery of upper-limb function is among their top priorities. Hybrid functional electrical stimulation (FES) and exoskeleton systems have emerged as a potential solution to provide upper limb movement assistance. These systems leverage the user's own muscles via FES and provide additional movement support via an assistive exoskeleton. To date, these systems have focused on single joint movements, limiting their utility for the complex movements necessary for independence...

Hemorrhagic progression of contusion (HPC) often occurs early in cerebral contusions (CC) patients, significantly impacting their prognosis. It is vital to promptly assess HPC and predict outcomes for effective tailored interventions, thereby enhancing prognosis in CC patients. We utilized the Attention-3DUNet neural network to semi-automatically segment hematomas from computed tomography (CT) images of 452 CC patients, incorporating 695 hematomas. Subsequently, 1,502 radiomic features were extracted from 358 hematomas in 261 patients...

Mild traumatic brain injury (mTBI) is a common condition seen in emergency departments worldwide. Blood-based biomarkers glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) are recently U.S. Food and Drug Administration-approved for the prediction of intracranial lesions on head computed tomography (CT) scans in mTBI. We evaluated the diagnostic performance of GFAP and UCH-L1 in a Dutch cohort using the i-STAT TBI assay. In a multi-center observational study, we enrolled 253 mTBI patients...

BACKGROUND: Cerebrospinal fluid leakage through the spinal meninges is difficult to diagnose and treat. Moreover, its underlying mechanism remains unknown. Considering that the dura mater is structurally the strongest and outermost membrane among the three-layered meninges, we hypothesized that a dural mechanical tear would trigger spontaneous cerebrospinal fluid leakage, especially when a traumatic loading event is involved. Thus, accurate biomechanical properties of the dura mater are indispensable for improving computational models, which aid in predicting blunt impact injuries and creating artificial substitutes for transplantation and surgical training...

INTRODUCTION: The disconnected-interacting protein 2 homolog A (DIP2A), a member of disconnected-interacting 2 protein family, has been shown to be involved in human nervous system-related mental illness. This protein is highly expressed in the nervous system of mouse. Mutation of mouse DIP2A causes defects in spine morphology and synaptic transmission, autism-like behaviors, and defective social novelty [5], [27], indicating that DIP2A is critical to the maintenance of neural development...

Computed tomography (CT) is an important imaging modality for guiding prognostication in patients with traumatic brain injury (TBI). However, because of the specialized expertise necessary, timely and dependable TBI prognostication based on CT imaging remains challenging. This study aimed to enhance the efficiency and reliability of TBI prognostication by employing machine learning (ML) techniques on CT images. A retrospective analysis was conducted on the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) data set ( n  = 1016)...

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a promising technique for assessing spinal cord injury that has historically been challenged by the presence of metallic stabilization hardware. This study leverages recent advances in metal-artifact resistant multi-spectral DW-MRI to enable diffusion quantification throughout the spinal cord even after fusion stabilization. Twelve cervical spinal cord injury subjects treated with fusion stabilization and 49 asymptomatic controls underwent multi-spectral DW-MRI evaluation...

Neural circuits embed limb dynamics for motor control and sensorimotor integration. The somatotopic organization of motoneuron pools in the spinal cord may support these computations. Here, we tested if the spatial organization of motoneurons is related to the musculoskeletal anatomy. We created a 3D model of motoneuron locations within macaque spinal cord and compared the spatial distribution of motoneurons to the anatomical organization of the muscles they innervate. We demonstrated that the spatial distribution of motoneuron pools innervating the upper limb and the anatomical relationships between the muscles they innervate were similar between macaque and human species...

The pathophysiology of syringomyelia remains poorly understood. Two prevailing challenges stand out: the need for a comprehensive understanding of its diverse types and the yet-to-be-explained mechanism of cerebrospinal fluid (CSF) retention in the syrinx despite its higher pressure than that in the adjacent subarachnoid space. Expanding on our previous proposal that direction-selective resistance to subarachnoid CSF flow drives syringomyelia genesis, this study uses a computer model to explore this mechanism further...

BACKGROUND: Preclinical models of spinal cord stimulation (SCS) are lacking objective measurements to inform translationally applicable SCS parameters. The evoked compound action potential (ECAP) represents a measure of dorsal column fiber activation. This measure approximates the onset of SCS-induced sensations in humans and provides effective analgesia when used with ECAP-controlled closed-loop (CL)-SCS systems. Therefore, ECAPs may provide an objective surrogate for SCS dose in preclinical models that may support better understanding of SCS mechanisms and further translations to the clinics...

BACKGROUND: Tension in the spinal cord is a trademark of tethered cord syndrome. Unfortunately, existing tests cannot quantify tension across the bulk of the cord, making the diagnostic evaluation of stretch ambiguous. A potential non-destructive metric for spinal cord tension is ultrasound-derived shear wave velocity (SWV). The velocity is sensitive to tissue elasticity and boundary conditions including strain. We use the term Ultrasound Tensography to describe the acoustic evaluation of tension with SWV...

Complex interactions between brain regions and the spinal cord (SC) govern body motion, which is ultimately driven by muscle activation. Motor planning or learning are mainly conducted at higher brain regions, whilst the SC acts as a brain-muscle gateway and as a motor control centre providing fast reflexes and muscle activity regulation. Thus, higher brain areas need to cope with the SC as an inherent and evolutionary older part of the body dynamics. Here, we address the question of how SC dynamics affects motor learning within the cerebellum; in particular, does the SC facilitate cerebellar motor learning or constitute a biological constraint? We provide an exploratory framework by integrating biologically plausible cerebellar and SC computational models in a musculoskeletal upper limb control loop...

Recent studies have emphasized the importance of dynamic activity in the development of myelopathy. However, current knowledge of how degenerative factors affect the spinal cord during motion is still limited. This study aimed to investigate the effect of various types of preexisting herniated cervical disc and the ligamentum flavum ossification on the spinal cord during cervical flexion and extension. A detailed dynamic fluid-structure interaction finite element model of the cervical spine with the spinal cord was developed and validated...

[This retracts the article DOI: 10.1155/2022/4955982.].

[This retracts the article DOI: 10.1155/2022/4121910.].

STUDY DESIGN: Retrospective diagnostic study. OBJECTIVE: To automatically detect osteolytic bone metastasis lesions in the thoracolumbar region using conventional computed tomography (CT) scans, we developed a new deep learning (DL)-based computer aided detection (CAD) model. SUMMARY OF BACKGROUND DATA: Radiographic detection of bone metastasis is often difficult even for orthopedic surgeons and diagnostic radiologists, with a consequent risk for pathologic fracture or spinal cord injury...

The purpose of this study was to use machine learning (ML) algorithms to identify tissue damage based on the mechanical outputs of computational models of spinal cord injury (SCI). Three datasets corresponding to gray matter, white matter, and the combination of gray and white matter tissues were used to train the models. These datasets were built from the comparison of histological images taken from SCI experiments in non-human primates and corresponding subject-specific finite element (FE) models. Four ML algorithms were evaluated and compared using cross-validation and the area under the receiver operating characteristic curve (AUC)...

An accurate classification of upper limb movements using electroencephalogram (EEG) signals is gaining significant importance in recent years due to the prevalence of brain-computer interfaces. The upper limbs in the human body are crucial since different skeletal segments combine to make a range of motions that helps us in our trivial daily tasks. Decoding EEG-based upper limb movements can be of great help to people with spinal cord injury (SCI) or other neuro-muscular diseases such as amyotrophic lateral sclerosis (ALS), primary lateral sclerosis, and periodic paralysis...