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Automated brain morphometric biomarkers from MRI at term predict motor development in very preterm infants
NeuroImage: Clinical ( IF 3.4 ) Pub Date : 2020-10-28 , DOI: 10.1016/j.nicl.2020.102475
Julia E Kline 1 , Venkata Sita Priyanka Illapani 1 , Lili He 2 , Nehal A Parikh 3
Affiliation  

Very preterm infants are at high risk for motor impairments. Early interventions can improve outcomes in this cohort, but they would be most effective if clinicians could accurately identify the highest-risk infants early. A number of biomarkers for motor development exist, but currently none are sufficiently accurate for early risk-stratification. We prospectively enrolled very preterm (gestational age 31 weeks) infants from four level-III NICUs. Structural brain MRI was performed at term-equivalent age. We used a well-established pipeline to automatically derive brain volumetrics and cortical morphometrics – cortical surface area, sulcal depth, gyrification index, and inner cortical curvature – from structural MRI. We related these objective measures to Bayley-III motor scores (overall, gross, and fine) at two-years corrected age. Lasso regression identified the three best predictive biomarkers for each motor scale from our initial feature set. In multivariable regression, we assessed the independent value of these brain biomarkers, over-and-above known predictors of motor development, to predict motor scores. 75 very preterm infants had high-quality T2-weighted MRI and completed Bayley-III motor testing. All three motor scores were positively associated with regional cortical surface area and subcortical volumes and negatively associated with cortical curvature throughout the majority of brain regions. In multivariable regression modeling, thalamic volume, curvature of the temporal lobe, and curvature of the insula were significant predictors of overall motor development on the Bayley-III, independent of known predictors. Objective brain morphometric biomarkers at term show promise in predicting motor development in very preterm infants.



中文翻译:

足月MRI的自动脑形态计量生物标志物可预测早产儿的运动发育

早产儿极易发生运动障碍。早期干预可以改善这一队列的结果,但是如果临床医生可以尽早准确识别出高危婴儿,它们将是最有效的。存在许多用于运动发育的生物标记物,但目前尚无足够准确的方法可用于早期风险分层。我们前瞻性地注册了早产儿(胎龄31周)来自四个III级重症监护病房的婴儿。在等效年龄进行结构性脑MRI。我们使用了完善的管道,从结构MRI自动得出大脑的容积和皮质形态计量学-皮质表面积,沟深,回旋指数和内皮质曲率。我们将这些客观指标与两年校正年龄下的Bayley-III运动成绩(总体,总体和罚款)相关联。Lasso回归从我们的初始特征集中为每种运动量表确定了三个最佳的预测生物标记。在多变量回归中,我们评估了这些大脑生物标志物的独立价值,这些运动标志物是运动发育的重要预测指标,可以预测运动评分。75名极早产儿接受了高质量的T2加权MRI检查,并完成了Bayley-III运动测试。在整个大脑大部分区域中,所有三个运动评分均与区域皮质表面积和皮质下体积呈正相关,与皮质曲率呈负相关。在多变量回归模型中,与已知的预测因素无关,丘脑体积,颞叶曲率和岛状弯曲是Bayley-III上总体运动发育的重要预测因素。足月的客观脑形态计量生物标志物显示了预测非常早产儿运动发育的希望。绝缘体的弯曲度和弯曲度是Bayley-III上整体运动发育的重要预测因素,与已知的预测因素无关。足月的客观脑形态计量生物标志物显示了预测非常早产儿运动发育的希望。绝缘体的弯曲度和弯曲度是Bayley-III上整体运动发育的重要预测因素,与已知的预测因素无关。足月的客观脑形态计量生物标志物显示了预测非常早产儿运动发育的希望。

更新日期:2020-10-29
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