Modeling time-varying three-dimensional strain fields in the human cerebral ventricular system using finite element methods

Peter Cahoon; Douglas Cochrane; Ellen Grant

doi:10.1117/12.270329

9 April 1997 Modeling time-varying three-dimensional strain fields in the human cerebral ventricular system using finite element methods

Peter Cahoon, Douglas Cochrane, Ellen Grant

Author Affiliations +

Proceedings Volume 3017, Visual Data Exploration and Analysis IV; (1997) https://doi.org/10.1117/12.270329
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

Abstract

Accurate measurement of the strain fields developed in the human ventricular system in the brain would require invasive monitoring at a number of selected spatial locations. Since this is not practically possible the gross behavior of a field must be deduced from time-gated MRI scanned images. The phase-encoded images taken at several coronal locations from posterior to anterior, yield a field averaged over many cardiac cycles. A second sequence of time-gated MRI images are recorded in the same fashion to obtain the range of pulsatile movement of the membrane boundary of the cortical surface. The two data sets provide spatial and temporal information that must be combined in such a way that the flow field complies with the movement of the boundary. Modeling this behavior requires a combination of finite element and hydrostatic models. The finite element model of the ventricles consists of a triangulated surface mesh boundary that has a time varying pressure field applied uniformly to its surface to reflect the continuous change in pressure from systole to diastole and the observed deformation of the brain surface. The interior tetrahedra have displacements applied, posterior to anterior, that reflect the displacements from the phase-encoded sequences.

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Peter Cahoon, Douglas Cochrane, and Ellen Grant "Modeling time-varying three-dimensional strain fields in the human cerebral ventricular system using finite element methods", Proc. SPIE 3017, Visual Data Exploration and Analysis IV, (9 April 1997); https://doi.org/10.1117/12.270329

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