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1.
Ann Biomed Eng ; 47(9): 1923-1940, 2019 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-30767132

RESUMEN

We employ an advanced 3D computational model of the head with high anatomical fidelity, together with measured tissue properties, to assess the consequences of dynamic loading to the head in two distinct modes: head rotation and head extension. We use a subject-specific computational head model, using the material point method, built from T1 magnetic resonance images, and considering the anisotropic properties of the white matter which can predict strains in the brain under large rotational accelerations. The material model now includes the shear anisotropy of the white matter. We validate the model under head rotation and head extension motions using live human data, and advance a prior version of the model to include biofidelic falx and tentorium. We then examine the consequences of incorporating the falx and tentorium in terms of the predictions from the computational head model.


Asunto(s)
Encéfalo/fisiología , Cabeza/fisiología , Modelos Biológicos , Anisotropía , Fenómenos Biomecánicos , Encéfalo/anatomía & histología , Cabeza/anatomía & histología , Humanos , Masculino , Persona de Mediana Edad , Rotación
2.
Shock Waves ; 28(1): 127-139, 2018 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-29662272

RESUMEN

Traumatic brain injury such as that developed as a consequence of blast is a complex injury with a broad range of symptoms and disabilities. Computational models of brain biomechanics hold promise for illuminating the mechanics of traumatic brain injury (TBI) and for developing preventive devices. However, reliable material parameters are needed for models to be predictive. Unfortunately, the properties of human brain tissue are difficult to measure, and the bulk modulus of brain tissue in particular is not well-characterized. Thus, a wide range of bulk modulus values are used in computational models of brain biomechanics, spanning up to three orders of magnitude in the differences between values. However, the sensitivity of these variations on computational predictions is not known. In this work, we study the sensitivity of a 3D computational human head model to various bulk modulus values. A subject-specific human head model was constructed from T1-weighted MRI images at 2 mm3 voxel resolution. Diffusion tensor imaging provided data on spatial distribution and orientation of axonal fiber-bundles for modeling white-matter anisotropy. Non-injurious, full-field brain deformations in a human volunteer were used to assess the simulated predictions. The comparison suggests that a bulk modulus value on the order of GPa gives the best agreement with experimentally measured in vivo deformation in the human brain. Further, simulations of injurious loading suggest that bulk modulus values on the order of GPa provide the closest match with the clinical findings in terms of predicated injured regions and extent of injury.

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