The Virtual Family computational whole-body anatomical human models were originally developed for electromagnetic (EM) exposure evaluations, in particular to study how absorption of radiofrequency radiation from external sources depends on anatomy. However, the models immediately garnered much broader interest and are now applied by over 300 research groups, many from medical applications research fields. In a first step, the Virtual Family was expanded to the Virtual Population to provide considerably broader population coverage with the inclusion of models of both sexes ranging in age from 5 to 84 years old. Although these models have proven to be invaluable for EM dosimetry, it became evident that significantly enhanced models are needed for reliable effectiveness and safety evaluations of diagnostic and therapeutic applications, including medical implants safety. This paper describes the research and development performed to obtain anatomical models that meet the requirements necessary for medical implant safety assessment applications. These include implementation of quality control procedures, re-segmentation at higher resolution, more-consistent tissue assignments, enhanced surface processing and numerous anatomical refinements. Several tools were developed to enhance the functionality of the models, including discretization tools, posing tools to expand the posture space covered, and multiple morphing tools, e.g., to develop pathological models or variations of existing ones. A comprehensive tissue properties database was compiled to complement the library of models. The results are a set of anatomically independent, accurate, and detailed models with smooth, yet feature-rich and topologically conforming surfaces. The models are therefore suited for the creation of unstructured meshes, and the possible applications of the models are extended to a wider range of solvers and physics. The impact of these improvements is shown for the MRI exposure of an adult woman with an orthopedic spinal implant. Future developments include the functionalization of the models for specific physical and physiological modeling tasks.
Traumatic spinal cord injury (SCI) has been shown to trigger structural atrophic changes within the spinal cord and brain. However, the relationship between structural changes and magnitude of neuropathic pain (NP) remains incompletely understood. Voxel-wise analysis of anatomical magnetic resonance imaging data provided information on cross-sectional cervical cord area and volumetric brain changes in 30 individuals with chronic traumatic SCI and 31 healthy controls. Participants were clinically assessed including neurological examination and pain questionnaire. Compared to controls, individuals with SCI exhibited decreased cord area, reduced grey matter (GM) volumes in anterior cingulate cortex (ACC), left insula, left secondary somatosensory cortex, bilateral thalamus, and decreased white matter volumes in pyramids and left internal capsule. The presence of NP was related with smaller cord area, increased GM in left ACC and right M1, and decreased GM in right primary somatosensory cortex and thalamus. Greater GM volume in M1 was associated with amount of NP. Below-level NP-associated structural changes in the spinal cord and brain can be discerned from trauma-induced consequences of SCI. The directionality of these relationships reveals specific changes across the neuroaxis (i.e., atrophic changes versus increases in volume) and may provide substrates of underlying neural mechanisms in the development of NP.
T -weighted scans provided data on the extent and dynamics of neuronal tissue damage and midsagittal tissue bridges at the epicenter of traumatic cervical spinal cord lesions in 24 subacute tetraplegic patients. At 1 month postinjury, smaller lesion area and midsagittal tissue bridges identified those patients with lower extremity evoked potentials and better clinical recovery. Wider midsagittal tissue bridges and smaller lesions at 1 month post-injury were associated with neurological and functional recovery at 1-year follow-up. Neuroimaging biomarkers of lesion size and midsagittal tissue bridges are potential outcome predictors and patient stratifiers in both subacute and chronic clinical trials. Ann Neurol 2017;81:740-748.
ObjectiveTo investigate whether gray matter pathology above the level of injury, alongside white matter changes, also contributes to sensorimotor impairments after spinal cord injury.MethodsA 3T MRI protocol was acquired in 17 tetraplegic patients and 21 controls. A sagittal T2-weighted sequence was used to characterize lesion severity. At the C2-3 level, a high-resolution T2*-weighted sequence was used to assess cross-sectional areas of gray and white matter, including their subcompartments; a diffusion-weighted sequence was used to compute voxel-based diffusion indices. Regression models determined associations between lesion severity and tissue-specific neurodegeneration and associations between the latter with neurophysiologic and clinical outcome.ResultsNeurodegeneration was evident within the dorsal and ventral horns and white matter above the level of injury. Tract-specific neurodegeneration was associated with prolonged conduction of appropriate electrophysiologic recordings. Dorsal horn atrophy was associated with sensory outcome, while ventral horn atrophy was associated with motor outcome. White matter integrity of dorsal columns and corticospinal tracts was associated with daily-life independence.ConclusionOur results suggest that, next to anterograde and retrograde degeneration of white matter tracts, neuronal circuits within the spinal cord far above the level of injury undergo transsynaptic neurodegeneration, resulting in specific gray matter changes. Such improved understanding of tissue-specific cord pathology offers potential biomarkers with more efficient targeting and monitoring of neuroregenerative (i.e., white matter) and neuroprotective (i.e., gray matter) agents.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.