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Lea Scherschinski, Ian T. McNeill, Leslie Schlachter, William H. Shuman, Holly Oemke, Kurt A. Yaeger, and Joshua B. Bederson


Arteriovenous malformations (AVMs) of the brain are vessel conglomerates of feeding arteries and draining veins that carry a risk of spontaneous and intraoperative rupture. Augmented reality (AR)-assisted neuronavigation permits continuous, real-time, updated visualization of navigation information through a heads-up display, thereby potentially improving the safety of surgical resection of AVMs.


The authors report a case of a 37-year-old female presenting with a 2-year history of recurrent falls due to intermittent right-sided weakness and increasing clumsiness in the right upper extremity. Magnetic resonance imaging, magnetic resonance angiography, and cerebral angiography of the brain revealed a left parietal Spetzler-Martin grade III AVM. After endovascular embolization of the AVM, microsurgical resection using an AR-assisted neuronavigation system was performed. Postoperative angiography confirmed complete obliteration of arteriovenous shunting. The postsurgical course was unremarkable, and the patient remains in excellent health.


Our case describes the operative setup and intraoperative employment of AR-assisted neuronavigation for AVM resection. Application of this technology may improve workflow and enhance patient safety.

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Visish M. Srinivasan, Katherine Karahalios, Kavelin Rumalla, Nathan A. Shlobin, Redi Rahmani, Lea Scherschinski, Dimitri Benner, Joshua S. Catapano, Mohamed A. Labib, Christopher S. Graffeo, and Michael T. Lawton


Giant cerebral cavernous malformations (GCCMs) are rare vascular malformations. Unlike for tumors and aneurysms, there is no clear definition of a "giant" cavernous malformation (CM). As a result of variable definitions, working descriptions and outcome data of patients with GCCM are unclear. A new definition of GCCM related to surgical outcomes is needed.


An institutional database was searched for all patients who underwent resection of CMs > 1 cm in diameter. Patient information, surgical technique, and clinical and radiographic outcomes were assessed. A systematic review was performed to augment an earlier published review.


In the authors’ institutional cohort of 183 patients with a large CM, 179 with preoperative and postoperative modified Rankin Scale (mRS) scores were analyzed. A maximum CM diameter of ≥ 3 cm was associated with greater risk of severe postoperative decline (≥ 2-point increase in mRS score). After adjustment for age and deep versus superficial location, size ≥ 3 cm was strongly predictive of severe postoperative decline (OR 4.5, 95% CI 1.2–16.9). A model with CM size and deep versus superficial location was developed to predict severe postoperative decline (area under the receiver operating characteristic curve 0.79). Thirteen more patients with GCCMs have been reported in the literature since the most recent systematic review, including some patients who were treated earlier and not discussed in the previous review.


The authors propose that cerebral CMs with a diameter ≥ 3 cm be defined as GCCMs on the basis of the inflection point for functional and neurological outcomes. This definition is in line with the definitions for other giant lesions. It is less exclusive than earlier definitions but captures the rarity of these lesions (approximately 1% incidence) and variation in outcomes. GCCMs remain operable with potentially favorable outcomes. The term "giant" is not meant to deter or contraindicate surgery.

Free access

Lea Scherschinski, Joshua S. Catapano, Katherine Karahalios, Stefan W. Koester, Dimitri Benner, Ethan A. Winkler, Christopher S. Graffeo, Visish M. Srinivasan, Ruchira M. Jha, Ashutosh P. Jadhav, Andrew F. Ducruet, Felipe C. Albuquerque, and Michael T. Lawton


Good functional outcomes after aneurysmal subarachnoid hemorrhage (aSAH) are often dependent on early detection and treatment of cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI). There is growing evidence that continuous monitoring with cranial electroencephalography (cEEG) can predict CVS and DCI. Therefore, the authors sought to assess the value of continuous cEEG monitoring for the detection of CVS and DCI in aSAH.


The cerebrovascular database of a quaternary center was reviewed for patients with aSAH and cEEG monitoring between January 1, 2017, and July 31, 2019. Demographic data, cardiovascular risk factors, Glasgow Coma Scale score at admission, aneurysm characteristics, and outcomes were abstracted from the medical record. Patient data were retrospectively analyzed for DCI and angiographically assessed CVS. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and odds ratio for cEEG, transcranial Doppler ultrasonography (TCDS), CTA, and DSA in detecting DCI and angiographic CVS were calculated. A systematic literature review was conducted in accordance with PRISMA guidelines querying the PubMed, Cochrane Controlled Trials Register, Web of Science, and Embase databases.


A total of 77 patients (mean age 60 years [SD 15 years]; female sex, n = 54) were included in the study. Continuous cEEG monitoring detected DCI and angiographically assessed CVS with specificities of 82.9% (95% CI 66.4%–93.4%) and 94.4% (95% CI 72.7%–99.9%), respectively. The sensitivities were 11.1% (95% CI 3.1%–26.1%) for DCI (n = 71) and 18.8% (95% CI 7.2%–36.4%) for angiographically assessed CVS (n = 50). Furthermore, TCDS detected angiographically determined CVS with a sensitivity of 87.5% (95% CI 71.0%–96.5%) and specificity of 25.0% (95% CI 7.3%–52.4%). In patients with DCI, TCDS detected vasospasm with a sensitivity of 85.7% (95% CI 69.7%–95.2%) and a specificity of 18.8% (95% CI 7.2%–36.4%). DSA detected vasospasm with a sensitivity of 73.9% (95% CI 51.6%–89.8%) and a specificity of 47.8% (95% CI 26.8%–69.4%).


The study results suggest that continuous cEEG monitoring is highly specific in detecting DCI as well as angiographically assessed CVS. More prospective studies with predetermined thresholds and endpoints are needed to assess the predictive role of cEEG in aSAH.