The identification of children with traumatic brain injury (TBI) who are at risk of death or poor global neurological functional outcome remains a challenge. Magnetic resonance imaging (MRI) can detect several brain pathologies that are a result of TBI; however, the types and locations of pathology that are the most predictive remain to be determined. Forty-two critically ill children with TBI were recruited prospectively from pediatric intensive care units at five Canadian children's hospitals. Pathologies detected on subacute phase MRIs included cerebral hematoma, herniation, cerebral laceration, cerebral edema, midline shift, and the presence and location of cerebral contusion or diffuse axonal injury (DAI) in 28 regions of interest were assessed. Global functional outcome or death more than 12 months post-injury was assessed using the Pediatric Cerebral Performance Category score. Linear modeling was employed to evaluate the utility of an MRI composite score for predicting long-term global neurological function or death after injury, and nonlinear Random Forest modeling was used to identify which MRI features have the most predictive utility. A linear predictive model of favorable versus unfavorable long-term outcomes was significantly improved when an MRI composite score was added to clinical variables. Nonlinear Random Forest modeling identified five MRI variables as stable predictors of poor outcomes: presence of herniation, DAI in the parietal lobe, DAI in the subcortical white matter, DAI in the posterior corpus callosum, and cerebral contusion in the anterior temporal lobe. Clinical MRI has prognostic value to identify children with TBI at risk of long-term unfavorable outcomes.

中文翻译：

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磁共振成像结果与危重儿童脑外伤后的长期整体神经功能或死亡相关


识别有死亡风险或整体神经功能结果不佳的创伤性脑损伤 (TBI) 儿童仍然是一个挑战。磁共振成像 (MRI) 可以检测由 TBI 引起的多种脑部病变；然而，最具预测性的病理类型和位置仍有待确定。从加拿大五家儿童医院的儿科重症监护病房前瞻性招募了 42 名患有 TBI 的危重儿童。亚急性期 MRI 检测到的病理包括脑血肿、脑疝、脑裂伤、脑水肿、中线移位，并对 28 个感兴趣区域中脑挫裂伤或弥漫性轴索损伤 (DAI) 的存在和位置进行了评估。使用儿科脑功能类别评分评估损伤后 12 个月以上的整体功能结果或死亡。采用线性模型来评估 MRI 综合评分在预测长期整体神经功能或损伤后死亡方面的效用，并使用非线性随机森林模型来确定哪些 MRI 特征最具预测效用。当将 MRI 综合评分添加到临床变量中时，有利与不利的长期结果的线性预测模型得到显着改善。非线性随机森林模型确定了五个 MRI 变量作为不良结果的稳定预测因素：存在疝气、顶叶 DAI、皮质下白质 DAI、后胼胝体 DAI 和前颞叶脑挫伤。临床 MRI 对于识别有长期不良结果风险的 TBI 儿童具有预后价值。