Title | Simulation of brain mass effect with an arbitrary Lagrangian and Eulerian FEM. |
Publication Type | Journal Article |
Year of Publication | 2010 |
Authors | Chen, Yasheng, Songbai Ji, Xunlei Wu, Hongyu An, Hongtu Zhu, Dinggang Shen, and Weili Lin |
Journal | Med Image Comput Comput Assist Interv |
Volume | 13 |
Issue | Pt 2 |
Pagination | 274-81 |
Date Published | 2010 |
Keywords | Algorithms, Brain, Computer Simulation, Finite Element Analysis, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Models, Neurological, Reproducibility of Results, Sensitivity and Specificity |
Abstract | Estimation of intracranial stress distribution caused by mass effect is critical to the management of hemorrhagic stroke or brain tumor patients, who may suffer severe secondary brain injury from brain tissue compression. Coupling with physiological parameters that are readily available using MRI, eg, tissue perfusion, a non-invasive, quantitative and regional estimation of intracranial stress distribution could offer a better understanding of brain tissue's reaction under mass effect. A quantitative and sound measurement serving this particular purpose remains elusive due to multiple challenges associated with biomechanical modeling of the brain. One such challenge for the conventional Lagrangian frame based finite element method (LFEM) is that the mesh distortion resulted from the expansion of the mass effects can terminate the simulation prematurely before the desired pressure loading is achieved. In this work, we adopted an arbitrary Lagrangian and Eulerian FEM method (ALEF) with explicit dynamic solutions to simulate the expansion of brain mass effects caused by a pressure loading. This approach consists of three phases: 1) a Lagrangian phase to deform mesh like LFEM, 2) a mesh smoothing phase to reduce mesh distortion, and 3) an Eulerian phase to map the state variables from the old mesh to the smoothed one. In 2D simulations with simulated geometries, this approach is able to model substantially larger deformations compared to LFEM. We further applied this approach to a simulation with 3D real brain geometry to quantify the distribution of von Mises stress within the brain. |
DOI | 10.1007/978-3-642-15745-5_34 |
Alternate Journal | Med Image Comput Comput Assist Interv |
Original Publication | Simulation of brain mass effect with an arbitrary Lagrangian and Eulerian FEM. |
PubMed ID | 20879325 |
PubMed Central ID | PMC2963568 |
Grant List | R21 AG033387-02 / AG / NIA NIH HHS / United States AG033387 / AG / NIA NIH HHS / United States R01 NS055754-05 / NS / NINDS NIH HHS / United States R21 AG033387-01A1 / AG / NIA NIH HHS / United States P01CA142538-01 / CA / NCI NIH HHS / United States R01 MH086633 / MH / NIMH NIH HHS / United States R01 NS055754 / NS / NINDS NIH HHS / United States R01 NS055754-04 / NS / NINDS NIH HHS / United States P01 CA142538 / CA / NCI NIH HHS / United States R01 NS055754-02 / NS / NINDS NIH HHS / United States R01 NS055754-01A1 / NS / NINDS NIH HHS / United States UL1 RR025747-01S1 / RR / NCRR NIH HHS / United States P01 CA142538-01 / CA / NCI NIH HHS / United States UL1 RR025747-02S1 / RR / NCRR NIH HHS / United States R01 MH086633-02 / MH / NIMH NIH HHS / United States P01 CA142538-02 / CA / NCI NIH HHS / United States UL1 RR025747-02 / RR / NCRR NIH HHS / United States R01 MH086633-01A1 / MH / NIMH NIH HHS / United States MH086633 / MH / NIMH NIH HHS / United States UL1 RR025747 / RR / NCRR NIH HHS / United States R01 NS055754-03 / NS / NINDS NIH HHS / United States UL1-RR025747-01 / RR / NCRR NIH HHS / United States R21 AG033387 / AG / NIA NIH HHS / United States |
Simulation of brain mass effect with an arbitrary Lagrangian and Eulerian FEM.
Project: