Simulation of decompressive craniectomy for ischaemic stroke treatment: A conceptual modeling study

Decompressive craniectomy is a treatment in which part of the skull is removed so as to reduce the intracranial pressure in the skull, especially during brain tissue swelling. Computational modeling studies may be used to understand the efficiency of this treatment in ischaemic stroke for advance clinical decision making. Thus, we performed a simulation using a mathematical model based on poroelastic theory and capillary filtration to see the effects of craniectomy in treating brain tissue swelling using 3D brain geometry. The results show that performing craniectomy can reduce intracranial pressure and reduce the effect of herniation. However, part of the brain is bulging out from the surgical hole and exerts a small amount of stress on the tissue by the surgical edge. This mathematical modeling framework can be used for further investigation of finding the suitable parameters for a decompressive craniectom

Simulation of decompressive craniectomy for ischaemic stroke treatment: A computational study

To evaluate the effectiveness of DC in treating brain tissue swelling using computational study based on capillary filtration and poroelastic theory

Finite element poroelastic modelling of brain oedema formation after ischaemic stroke reperfusion

One of the risks of ischaemic stroke reperfusion treatment is the formation of brain oedema. This is usually observed clinically by the formation of herniation, which if not treated, it may disrupt brain functionality. In this paper, a mathematical model of brain oedema formation after stroke has been developed and simulated on an ideal 3D brain geometry with different infarct sizes and locations, to see their effects on brain herniation. The brain tissue displacement and pressure are then analyzed. It is found that those infarcts with large sizes and located nearer to the brain ventricle cause severe brain herniation

Simulation of Craniectomy Size in Decompressive Craniectomy for Ischaemic Stroke

Decompressive Craniectomy (DC) surgery is recommended to treat patients who suffered from large ischaemic cerebral infarction. Although DC surgery has been proven to reduce intracranial pressure (ICP) within the skull, too large of DC opening may contribute to risk of tissue injury. Computational studies nowadays are very useful in predicting and decision making, especially in clinical studies. Therefore, a simulation was performed using mathematical modeling on an idealized 3D brain model to evaluate the outcome of different skull opening sizes in DC towards treating the brain tissue swelling in ischaemic stroke. The model is simulated based on poroelastic theory and capillary filtration. Our results show that larger craniectomy size may reduce the midline shift of the ventricle due to swelling tissue. Nevertheless, the bulging of swollen tissue out from the skull opening causes a little amount of stress applied at the edges of the opening. This modelling work may be used for further research in further research in evaluating the suitable craniectomy size for DC

Simulation of decompressive craniectomy for ischaemic stroke: a conceptual modelling study

Decompressive craniectomy is a treatment in which part of the skull is removed so as to reduce the intracranial pressure in the skull, especially during brain tissue swelling. Computational modelling studies may be used to understand the efficiency of this treatment in ishaemic stroke for advance clinical decision making. Thus, we performed a simulation using a mathematical model based on poroelastic theory and capillary filtration to see the effects of craniectomy in treating brain tissue swelling using 3D brain geometry. The results show that performing craniectomy can reduce intracranial pressure and reduce the effect of herniation. However, part of the brain is bulging out from the surgical hole and exert a small amount of stress on the tissue by the surgical edge. This mathematical modelling framework can be used for further investigation of finding the suitable parameters for a decompressive craniectom