Affiliation:
1. Kafkas University
2. Ege Üniversitesi Tıp Fakültesi Hastanesi
Abstract
Abstract
Surgical treatment of gliomas requires an intervention that does not leave residual tumor tissue in the brain and preserves functional centers. Although orientation parameters are not present in the traditional-MRI navigation information calculated from MRI, poor mans are observed for the neuro-oncological surgery in most parts of the world. The aim of this study is to obtain instant personalized neuro-navigational information through a 3D-patient-specific model to perform functional resection of the brain. 20 patients diagnosed with gliomas were included in this study. Neuro-oncological navigation calculations of 10 patients were carried out with traditional-MRI support and the remaining 10 with the 3D-model. In this way, the actual size of the tumor, its distance from cortical structures, and perioperative surgical planning were made by the 20 neurosurgeons based on the patient-specific model. They were required to compare their perception level of the cases with traditional-MR and 3D-models in terms of identifying the invasion of the mass, making the proximity to functional centers and anatomical structures as part of perioperative planning. All neurosurgeons have given higher scores for 3D-model supported neuro-navigations. 80–90% of them preferred the model in preoperative planning as they are beneficial in anticipating determining and envisaging the entire process of the functional resection covering the location and extent of craniotomy, the extent of tumor resection on functional areas. For this, orientation parameters of the neuro-navigation information such as tumor size, margin size of surgical resection, presence of functional areas in the gyrus/sulcus where the tumor is located, proximity of the tumor, anatomical structures as (ventricles, arteries, veins, myelinated pathways, capsula interna, basal ganglia) should be included. It also target the perioperative advantages of 3D supported neuro-navigational information over the traditional method.
Publisher
Research Square Platform LLC