Journal
JOURNAL OF NEUROTRAUMA
Volume 37, Issue 11, Pages 1269-1282Publisher
MARY ANN LIEBERT, INC
DOI: 10.1089/neu.2019.6710
Keywords
Common Data Elements; computed tomography; structured reporting; traumatic brain injury
Funding
- Hannelore Kohl Foundation (Germany)
- One Mind
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The aim of this study is to investigate the prognostic value of using the National Institute of Neurological Disorders and Stroke (NINDS) standardized imaging-based pathoanatomic descriptors for the evaluation and reporting of acute traumatic brain injury (TBI) lesions. For a total of 3392 patients (2244 males and 1148 females, median age = 51 years) enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we extracted 96 Common Data Elements (CDEs) from the structured reports, spanning all three levels of pathoanatomic information (i.e., 20 basic, 60 descriptive, and 16 advanced CDE variables per patient). Six-month clinical outcome scores were dichotomized into favorable (Glasgow Outcome Scale Extended [GOS-E] = 5-8) versus unfavorable (GOS-E = 1-4). Regularized logistic regression models were constructed and compared using the optimism-corrected area under the curve (AUC). An abnormality was reported for the majority of patients (64.51%). In 79.11% of those patients, there was at least one coexisting pathoanatomic lesion or associated finding. An increase in lesion severity, laterality, and volume was associated with more unfavorable outcomes. Compared with the full set of pathoanatomic descriptors (i.e., all three categories of information), reporting basic CDE information provides at least equal discrimination between patients with favorable versus unfavorable outcome (AUC = 0.8121 vs. 0.8155, respectively). Addition of a selected subset of descriptive detail to the basic CDEs could improve outcome prediction (AUC = 0.8248). Addition of advanced or emerging/exploratory information had minimal prognostic value. Our results show that the NINDS standardized-imaging based pathoanatomic descriptors can be used in large-scale studies and provide important insights into acute TBI lesion patterns. When used in clinical predictive models, they can provide excellent discrimination between patients with favorable and unfavorable 6-month outcomes. If further validated, our findings could support the development of structured and itemized templates in routine clinical radiology.
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