Integrating Surgery and Radiosurgery: Our First Experiences with Adaptive Hybrid Surgery Analysis Software in Benign Skull Base Tumors

Background: Benign skull base tumors are often located in close relationship to critical structures and can be quite large when finally diagnosed. Thus a radical tumor resection can be virtually impossible and multimodal treatment concepts with partial tumor resection followed by radiosurgery are often the optimal strategy. Adaptive Hybrid Surgery Analysis (AHSA) is a software developed by Brainlab that provides an automatic virtual real-time treatment plan during surgery for the feasibility of stereotactic radiosurgery.

Methods: The AHSA software was applied in four patients who underwent partial resection of a benign skull base tumor. Tumor volumetry was obtained on preoperative and postoperative MR scans. Organs at risk were automatically delineated with the Atlas Mapping feature of the Elements software by Brainlab and adapted if needed.

Results: Three patients underwent a suboccipital craniotomy for a partial resection of a tumor within the posterior fossa (vestibular schwannoma, ependymoma, petroclival meningioma) and in one patient a temporal approach for resection of a medial sphenoid wing meningioma was performed. The preoperative tumor volumes ranged between 8.52 and 25.2 cm³. The intraoperative volume of the residual tumor measured with the AHSA software was between 2.13–12.17 cm³ (25–47% of the preoperative tumor volume) differing between 8–20% from the real residual tumor volume measured on the postoperative MR scan. The preoperative estimated residual tumor volume differed only between 3–5% from the real residual volume measured on the postoperative MR. The intraoperative automatic AHSA plans of the remaining tumor volume suggested in all four patients that a safe radiosurgery would be feasible.

Conclusion: The AHSA software is a smart tool that enables the neurosurgeon to preoperatively plan and estimate a multi-modal approach for complex skull base tumors and thus minimizing the morbidity risks for surgery as well as radiosurgery. Further the software provides a continuous intraoperative feedback of residual tumor volume and the resulting radiosurgery plan, which appraises if the remaining tumor could be feasibly and safely treated with radiosurgery. The accuracy of the intraoperative surface scanning of the residual tumor depends on the angle, location and depth of the remaining tumor together with the relation of the pointer and camera visibility respectively and therefore can differ quite a bit from the real residual tumor volume.