Neuroimaging Radiological Interpretation System for Acute Traumatic Brain Injury.
The purpose of the study was to develop an outcome-based NeuroImaging Radiological Interpretation System (NIRIS) for patients with acute traumatic brain injury (TBI) that would standardize the interpretation of noncontrast head computer tomography (CT) scans and consolidate imaging findings into ordinal severity categories that would inform specific patient management actions and that could be used as a clinical decision support tool. We retrospectively identified all patients transported to our emergency department by ambulance or helicopter for whom a trauma alert was triggered per established criteria and who underwent a noncontrast head CT because of suspicion of TBI, between November 2015 and April 2016. Two neuroradiologists reviewed the noncontrast head CTs and assessed the TBI imaging common data elements (CDEs), as defined by the National Institutes of Health (NIH). Using descriptive statistics and receiver operating characteristic curve analyses to identify imaging characteristics and associated thresholds that best distinguished among outcomes, we classified patients into five mutually exclusive categories: 0-discharge from the emergency department; 1-follow-up brain imaging and/or admission; 2-admission to an advanced care unit; 3-neurosurgical procedure; 4-death up to 6 months after TBI. Sensitivity of NIRIS with respect to each patient's true outcome was then evaluated and compared with that of the Marshall and Rotterdam scoring systems for TBI. In our cohort of 542 patients with TBI, NIRIS was developed to predict discharge (182 patients), follow-up brain imaging/admission (187 patients), need for advanced care unit (151 patients), neurosurgical procedures (10 patients), and death (12 patients). NIRIS performed similarly to the Marshall and Rotterdam scoring systems in terms of predicting death. We developed an interpretation system for neuroimaging using the CDEs that informs specific patient management actions and could be used as a clinical decision support tool for patients with TBI. Our NIRIS classification, with evidence-based grouping of the CDEs into actionable categories, will need to be validated in different TBI populations.
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School of Medicine