UNLABELLED: OBJECTIVE :To develop a novel method for use of diagnostic imaging, finite element analysis (FEA), and simulated biomechanical response behavior of brain tissue in noninvasive assessment and estimation of intracranial pressure (ICP) of dogs. SAMPLE: MRI data for 5 dogs. PROCEDURES: MRI data for 5 dogs (1 with a geometrically normal brain that had no detectable signs of injury or disease and 4 with various degrees of geometric abnormalities) were obtained from a digital imaging archiving and communication system database. Patient-specific 3-D models composed of exact brain geometries were constructed from MRI images. Finite element analysis was used to simulate and observe patterns of nonlinear biphasic biomechanical response behavior of geometrically normal and abnormal canine brains at various levels of decreasing cerebral perfusion pressure and increasing ICP. RESULTS: Changes in biomechanical response behavior were detected with FEA for decreasing cerebral perfusion pressure and increasing ICP. Abnormalities in brain geometry led to observable changes in deformation and biomechanical response behavior for increased ICP, compared with results for geometrically normal brains. CONCLUSIONS AND CLINICAL RELEVANCE: In this study, patient-specific critical ICP was identified, which could be useful as a method to predict the onset of brain herniation. Results indicated that it was feasible to apply FEA to brain geometry obtained from MRI data of clinical patients and to use biomechanical response behavior resulting from increased ICP as a diagnostic and prognostic method to noninvasively assess or classify levels of brain injury in clinical veterinary settings.
UNLABELLED: OBJECTIVE :To develop a novel method for use of diagnostic imaging, finite element analysis (FEA), and simulated biomechanical response behavior of brain tissue in noninvasive assessment and estimation of intracranial pressure (ICP) of dogs. SAMPLE: MRI data for 5 dogs. PROCEDURES: MRI data for 5 dogs (1 with a geometrically normal brain that had no detectable signs of injury or disease and 4 with various degrees of geometric abnormalities) were obtained from a digital imaging archiving and communication system database. Patient-specific 3-D models composed of exact brain geometries were constructed from MRI images. Finite element analysis was used to simulate and observe patterns of nonlinear biphasic biomechanical response behavior of geometrically normal and abnormal canine brains at various levels of decreasing cerebral perfusion pressure and increasing ICP. RESULTS: Changes in biomechanical response behavior were detected with FEA for decreasing cerebral perfusion pressure and increasing ICP. Abnormalities in brain geometry led to observable changes in deformation and biomechanical response behavior for increased ICP, compared with results for geometrically normal brains. CONCLUSIONS AND CLINICAL RELEVANCE: In this study, patient-specific critical ICP was identified, which could be useful as a method to predict the onset of brain herniation. Results indicated that it was feasible to apply FEA to brain geometry obtained from MRI data of clinical patients and to use biomechanical response behavior resulting from increased ICP as a diagnostic and prognostic method to noninvasively assess or classify levels of brain injury in clinical veterinary settings.
Authors: K Sasaoka; K Nakamura; T Osuga; T Morita; N Yokoyama; K Morishita; N Sasaki; H Ohta; M Takiguchi Journal: J Vet Intern Med Date: 2017-12-19 Impact factor: 3.333