Abstract
In neurosurgery, brain retraction technique has become popular in the field of image-guided procedures for intracranial operations such as in brain tumor, cerebral aneurysms, cerebral hematoma, etc. Brain retraction is performed for adequate exposure during surgeries as such procedures require consistent retraction. This causes several local brain contusions which limit the accuracy of the image-guided neurosurgical system. Therefore, there is a need for training in this field to enhance the efficiency of the procedure. In this study, we present a 3D finite element brain model, segmented from human head magnetic resonance images, in the visco-hyperelastic framework. The numerical model is used to predict the deformation and stress fields within the brain during brain retraction. The brain was retracted by 5 mm and retained at that position for 30 min. It was observed that during this period, the retraction pressure decreased to 30% of the maximum pressure level generated due to interhemispheric retraction. The results show that brain retraction can be performed continuously up to 30 min without any risk of local brain contusions or postoperative complications. Finally, through a combination of judicious retraction and rigorous preoperative planning, a drop in the morbidity rate due to brain retraction is expected in the future. This technique can be used for preoperative effective planning and training, especially in minimally invasive brain surgeries.
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The authors would like to thank Indian Institute of Technology (IIT) Delhi for supporting this study.
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Awasthi, A., Bhaskar, S., Gautam, U., Roy, S. (2021). Quantification of Brain Retraction Using Visco-hyperelastic Framework for Image-Guided Neurosurgical Applications. In: Saha, S.K., Mukherjee, M. (eds) Recent Advances in Computational Mechanics and Simulations. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-8315-5_11
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DOI: https://doi.org/10.1007/978-981-15-8315-5_11
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