Preoperative evaluation for skull base tumors using CISS gadolinium: Total treatment strategy with microsurgery and radiosurgery using Gamma Plan

Motohiro Hayashi1, Shoji Yomo2, Manabu Tamura1

1Tokyo, Japan 2Saitama, Japan

Keywords: skull base, meningioma, vestibular schwannoma, gamma knife, Imaging

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Abstract

     For large skull base tumors, surgical resection should be considered as a first treatment option. In the initial stages, we have performed thin sliced CISS images, and have exported them to the Gamma Plan to make 3D images using delineation of the surrounding vital structures and the tumor. It has been very effective for discussion about total treatment strategy for each patient as a preoperative simulation.
     The purpose of this report was to evaluate the importance of imaging techniques in radiosurgical planning.
     
     0.5mm thickness of CISS axial images are required. Frame fixation is not needed. All obtained images are transported to the Gamma Plan (version 8.3-) in our institute. On display of Gamma Plan, we identify the cranial nerves, arteries, brain stem, and the tumor. We studied 3 types of large skull base tumor; vestibular schwannoma (Koos stage 4), petrous roche meningioma, and paracavernous sinus huge meningioma with oculomotor nerve palsy. We delineate all vital structures and demonstrate them in 3D images. 
     At the moment, we perfectly understand the 4 dimensional anatomical relationship and suspect where the tumor, whose vascularity should be abundant, originates. Finally, we can decide which part should be resected and which part should be residual prior to radiosurgery treatment.
     
     
Preoperative simulation is the most important to treat large skull base tumors to determine individual treatment strategy. Neurosurgeons should know the resected part to prevent new neurological deficit by surgery, and how much volume should be residual intentionally prior to surgery. High collaboration between microsurgery and GK radiosurgery will be effective in the future.
     


Acknowledgements

Project Roles:

M. Hayashi (), S. Yomo (), M. Tamura ()