CT Prediction Model for Major Arterial Injury after Blunt Pelvic Ring Disruption.
Radiology. 2018 Mar 20:170997. doi: 10.1148/radiol.2018170997. [Epub ahead of print] Dreizin D1, Bodanapally U1, Boscak A1, Tirada N1, Issa G1, Nascone JW1, Bivona L1, Mascarenhas D1, O'Toole RV1, Nixon E1, Chen R1, Siegel E1.
Purpose: To develop and test a computed tomography (CT)-based predictive model for major arterial injury after blunt pelvic ring disruptions that incorporates semiautomated pelvic hematoma volume quantification.
Materials and Methods: A multivariable logistic regression model was developed in patients with blunt pelvic ring disruptions who underwent arterial phase abdominopelvic CT before angiography from 2008 to 2013. Arterial injury at angiography requiring transarterial embolization (TAE) served as the outcome. Areas under the receiver operating characteristic (ROC) curve (AUCs) for the model and for two trauma radiologists were compared in a validation cohort of 36 patients from 2013 to 2015 by using the Hanley-McNeil method. Hematoma volume cutoffs for predicting the need for TAE and probability cutoffs for the secondary outcome of mortality not resulting from closed head injuries were determined by using ROC analysis. Correlation between hematoma volume and transfusion was assessed by using the Pearson coefficient.
Results: Independent predictor variables included hematoma volume, intravenous contrast material extravasation, atherosclerosis, rotational instability, and obturator ring fracture. In the validation cohort, the model (AUC, 0.78) had similar performance to reviewers (AUC, 0.69-0.72; P = .40-.80). A hematoma volume cutoff of 433 mL had a positive predictive value of 87%-100% for predicting major arterial injury requiring TAE. Hematoma volumes correlated with units of packed red blood cells transfused (r = 0.34-0.57; P = .0002-.0003). Predicted probabilities of 0.64 or less had a negative predictive value of 100% for excluding mortality not resulting from closed head injuries.
Conclusion: A logistic regression model incorporating semiautomated hematoma volume segmentation produced objective probability estimates of major arterial injury. Hematoma volumes correlated with 48-hour transfusion requirement, and low predicted probabilities excluded mortality from causes other than closed head injury. © RSNA, 2018 Online supplemental material is available for this article.