From the Department of Diagnostic Radiology and Nuclear Medicine, Trauma and Emergency Radiology (D.D., U.B., A.B., N.T., G.I., E.N., R.C., E.S.) and Department of Orthopedics, Division of Orthopedic Traumatology (J.W.N., L.B., D.M., R.V.O.), University of Maryland Medical Center, R Adams Cowley Shock Trauma Center, 22 S Greene St, Baltimore, MD 21201.
Radiology. 2018 Jun;287(3):1061-1069. doi: 10.1148/radiol.2018170997. Epub 2018 Mar 20.
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.
开发并验证一种基于体层摄影术(CT)的预测模型,该模型可用于评估骨盆环骨折患者的主要动脉损伤风险,模型中包含半自动骨盆血肿体积量化方法。
回顾性分析 2008 年至 2013 年期间接受动脉期腹盆 CT 检查且随后接受血管造影的钝性骨盆环骨折患者,建立多变量逻辑回归模型。将血管造影时需要进行经动脉栓塞术(TAE)的动脉损伤作为结局。使用 Hanley-McNeil 方法比较 2013 年至 2015 年期间的验证队列中 36 例患者的模型、两位放射科医师的诊断效能(通过计算受试者工作特征曲线下面积 AUC)。通过 ROC 分析确定用于预测 TAE 需求的血肿体积截断值和用于预测非闭合性颅脑损伤相关死亡率的次要结局概率截断值。采用 Pearson 系数评估血肿体积与输血之间的相关性。
独立预测变量包括血肿体积、静脉造影剂外渗、动脉粥样硬化、旋转不稳定和闭孔环骨折。在验证队列中,模型(AUC:0.78)的表现与阅片者相似(AUC:0.69-0.72;P 值分别为.40-.80)。血肿体积 433 mL 时,预测 TAE 所需的主要动脉损伤的阳性预测值为 87%-100%。血肿体积与输入的浓缩红细胞单位数呈正相关(r 值为 0.34-0.57;P 值均<.0003)。预测概率为 0.64 或更低时,排除非闭合性颅脑损伤相关死亡率的阴性预测值为 100%。
纳入半自动血肿体积分割的逻辑回归模型可生成主要动脉损伤的客观概率预测值。血肿体积与 48 小时内的输血需求相关,而低预测概率可排除非闭合性颅脑损伤以外的原因导致的死亡率。
放射学学会,2018 年
在线补充材料附于本文后。