BACKGROUND: Once considered inoperable lesions in inviolable territory, brainstem cavernous malformations (BSCM) are now surgically curable with acceptable operative morbidity. Recommending surgery is a difficult decision that would be facilitated by a grading system designed specifically for BSCMs that predicted surgical outcomes. OBJECTIVE: Informed by our efforts to develop a supplementary grading system for arteriovenous malformations, we hypothesized that a similar system might predict long-term outcomes and guide clinical decision-making. METHODS: A consecutive, single-surgeon series of 104 patients was used to assess preoperative clinical and imaging predictors of microsurgical outcomes. Univariable logistic regression identified predictors and a multivariable logistic regression model tested the association of the combined predictors with final modified Rankin Scale scores. A grading system assigned points for lesion size, location crossing the brainstem's midpoint, presence of developmental venous anomaly, age, and time from last hemorrhage to surgery. RESULTS: Average maximal diameter of BSCMs was 19.5 mm; 50% crossed the axial midpoint; 54.8% had developmental venous anomalies; mean age was 42.1 years; and median time from last hemorrhage to surgery was 60 days. One patient died (0.96%), and 15 patients (14.4%) experienced worsened cranial nerve or motor dysfunction, of which 10 increased their modified Rankin Scale scores (9.6%). BSCM grades ranged from 0 to 7 points and predicted outcomes with high accuracy (receiver operating characteristic = 0.86, 95% confidence interval: 0.78-0.94). CONCLUSION: Rather than developing a grading system for all cerebral cavernous malformations that is weak with BSCMs, we propose a system for the patients who need it most. The BSCM grading system differentiates patients who might expect favorable surgical outcomes and offers guidance to neurosurgeons forced to select these patients.
- Brainstem cavernous malformation
- Grading system
- Surgical resection
ASJC Scopus subject areas
- Clinical Neurology