Microsurgical Resection of Tonsillar Arteriovenous Malformation: Operative Video.

Cerebellar arteriovenous malformation (AVM) comprises 10%-15% of intracranial AVMs.1 Rupture often leads to devastating brainstem compression, with mortality reported as high as 67%.2 AVM can be a challenging disease, especially when large in size.3 AVMs can be treated by 1 or a combination of treatment modalities, namely embolization, radiosurgery, or microsurgical resection.4,5 Arterial adhesions to tonsilobulbar and telovelonsilar segments of posterior inferior cerebellar artery (PICA) can be a challenge, increasing bleeding and ischemic risk.6 We present a 2-dimensional video case of a tonsillar AVM. The patient, a previously healthy female in her 20s, presented with a chronic headache. She had no medical history. Initial magnetic resonance imaging revealed a tonsillar AVM classified as Spetzler-Martin grade II. It received its supply from the tonsilobulbar and telovelotonsilar segments of the PICA and drained directly into the precentral vein, transverse sinus, and sigmoid sinus. An angiogram revealed severe venous engorgement-the source of the patient's headache. The AVM was partially embolized 1 month preoperatively. A medial suboccipital telovelar approach was chosen to reduce the working distance and afford a wider corridor to expose the suboccipital surface of the cerebellum.7,8 Complete resection of the AVM was achieved with no additional morbidity. Microsurgery in experienced hands offers the best chance of cure for AVMs. In Video 1, we demonstrate the relationships among the tonsila, biventral lobule, vallecula cerebelli, PICA, and cerebellomedullary fissure as an important anatomic landmark in a safe total resection of a tonsillar AVM.

Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation.

Background: Visualizing and comprehending 3-dimensional (3D) neuroanatomy is challenging. Cadaver dissection is limited by low availability, high cost, and the need for specialized facilities. New technologies, including 3D rendering of neuroimaging, 3D pictures, and 3D videos, are filling this gap and facilitating learning, but they also have limitations. This proof-of-concept study explored the feasibility of combining the spatial accuracy of 3D reconstructed neuroimaging data with realistic texture and fine anatomical details from 3D photogrammetry to create high-fidelity cadaveric neurosurgical simulations. Methods: Four fixed and injected cadaver heads underwent neuroimaging. To create 3D virtual models, surfaces were rendered using magnetic resonance imaging (MRI) and computed tomography (CT) scans, and segmented anatomical structures were created. A stepwise pterional craniotomy procedure was performed with synchronous neuronavigation and photogrammetry data collection. All points acquired in 3D navigational space were imported and registered in a 3D virtual model space. A novel machine learning-assisted monocular-depth estimation tool was used to create 3D reconstructions of 2-dimensional (2D) photographs. Depth maps were converted into 3D mesh geometry, which was merged with the 3D virtual model's brain surface anatomy to test its accuracy. Quantitative measurements were used to validate the spatial accuracy of 3D reconstructions of different techniques. Results: Successful multilayered 3D virtual models were created using volumetric neuroimaging data. The monocular-depth estimation technique created qualitatively accurate 3D representations of photographs. When 2 models were merged, 63% of surface maps were perfectly matched (mean [SD] deviation 0.7 ± 1.9 mm; range -7 to 7 mm). Maximal distortions were observed at the epicenter and toward the edges of the imaged surfaces. Virtual 3D models provided accurate virtual measurements (margin of error <1.5 mm) as validated by cross-measurements performed in a real-world setting. Conclusion: The novel technique of co-registering neuroimaging and photogrammetry-based 3D models can (1) substantially supplement anatomical knowledge by adding detail and texture to 3D virtual models, (2) meaningfully improve the spatial accuracy of 3D photogrammetry, (3) allow for accurate quantitative measurements without the need for actual dissection, (4) digitalize the complete surface anatomy of a cadaver, and (5) be used in realistic surgical simulations to improve neurosurgical education.

Minimally Invasive Mini-orbitozygomatic Approach for Clipping an Anterior Communicating Artery Aneurysm: Virtual Reality Surgical Planning

Virtual reality (VR) has increasingly been implemented in neurosurgical practice. A patient with an unruptured anterior communicating artery (AcoA) aneurysm was referred to our institution. Imaging data from computed tomography angiography (CTA) was used to create a patient specific 3D model of vascular and skull base anatomy, and then processed to a VR compatible environment. Minimally invasive approaches (mini-pterional, supraorbital and mini-orbitozygomatic) were simulated and assessed for adequate vascular exposure in VR. Using an eyebrow approach, aminiorbitozygomatic approach was performed, with clip exclusion of the aneurysm from the circulation. The step-by-step process of VR planning is outlined, and the advantages and disadvantages for the neurosurgeon of this technology are reviewed.