L Arko1, M Lambrych1, A Montaser1, D Zurakowski2, D B Orbach3,4. 1. From the Departments of Neurosurgery (L.A., M.L., A.M., D.B.O.). 2. Anesthesiology and Surgery (D.Z.). 3. From the Departments of Neurosurgery (L.A., M.L., A.M., D.B.O.) darren.orbach@childrens.harvard.edu. 4. Neurointerventional Radiology (D.B.O.), Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
Abstract
BACKGROUND AND PURPOSE: Neonates with vein of Galen malformations are split into 2 cohorts: one needing urgent neonatal embolization, with relatively high mortality and morbidity even with expert care, and a cohort in which embolization can be deferred until infancy, with far better prognosis. We aimed to identify brain MR imaging characteristics obtained from fetal and early neonatal scans that can predict the clinical presentation. MATERIALS AND METHODS: Patients with vein of Galen malformations were stratified into a neonatal at-risk cohort if the patient needed urgent neonatal intervention or if neonatal death occurred; or an infantile treatment cohort if they were stable enough not to require treatment until >1 month of age. Twelve vascular MR imaging parameters, measured by 2 independent observers, were systematically correlated with the need for early neonatal intervention and/or neonatal mortality. RESULTS: A total of 32 neonatal patients (21 patients in the neonatal at-risk cohort, 11 in the infantile treatment cohort) were identified. Maximal mediolateral diameter (area under the curve = 0.866, P < .001) and cross-sectional area (area under the curve = 0.836, P = .002) at the narrowest point of the straight or falcine sinus were most predictive of clinical evolution into the neonatal at-risk cohort. There were 15 patients who had fetal MRIs (10 in the neonatal at-risk cohort and 5 in the infantile treatment cohort). Here too, maximal mediolateral diameter (area under the curve = 0.980, P = .003) and cross-sectional area (area under the curve = 0.941, P = .007) at the narrowest point of the straight or falcine sinus were highly predictive of the neonatal at-risk cohort. CONCLUSIONS: Early neonatal and fetal MR imaging can be readily used for accurate early risk stratification, assisting in directing resources, timing treatment decisions, and identifying appropriate cohorts for novel interventions.
BACKGROUND AND PURPOSE: Neonates with vein of Galen malformations are split into 2 cohorts: one needing urgent neonatal embolization, with relatively high mortality and morbidity even with expert care, and a cohort in which embolization can be deferred until infancy, with far better prognosis. We aimed to identify brain MR imaging characteristics obtained from fetal and early neonatal scans that can predict the clinical presentation. MATERIALS AND METHODS:Patients with vein of Galen malformations were stratified into a neonatal at-risk cohort if the patient needed urgent neonatal intervention or if neonatal death occurred; or an infantile treatment cohort if they were stable enough not to require treatment until >1 month of age. Twelve vascular MR imaging parameters, measured by 2 independent observers, were systematically correlated with the need for early neonatal intervention and/or neonatal mortality. RESULTS: A total of 32 neonatal patients (21 patients in the neonatal at-risk cohort, 11 in the infantile treatment cohort) were identified. Maximal mediolateral diameter (area under the curve = 0.866, P < .001) and cross-sectional area (area under the curve = 0.836, P = .002) at the narrowest point of the straight or falcine sinus were most predictive of clinical evolution into the neonatal at-risk cohort. There were 15 patients who had fetal MRIs (10 in the neonatal at-risk cohort and 5 in the infantile treatment cohort). Here too, maximal mediolateral diameter (area under the curve = 0.980, P = .003) and cross-sectional area (area under the curve = 0.941, P = .007) at the narrowest point of the straight or falcine sinus were highly predictive of the neonatal at-risk cohort. CONCLUSIONS: Early neonatal and fetal MR imaging can be readily used for accurate early risk stratification, assisting in directing resources, timing treatment decisions, and identifying appropriate cohorts for novel interventions.
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