Background

Hypoxic-ischemic encephalopathy (HIE) is a leading cause of morbidity and mortality in neonates, but quantitative methods to predict outcomes early in their course of illness remain elusive. Real-time physiologic biomarkers of neurologic injury are needed in order to predict which neonates will benefit from therapies. Neurovascular coupling (NVC) describes the correlation of neural activity with cerebral blood flow, and the degree of impairment could predict those at risk for poor outcomes.

Objective

To determine if neurovascular coupling (NVC) calculated in the first 24-hours of life based on wavelet transform coherence analysis (WTC) of near-infrared spectroscopy (NIRS) and amplitude-integrated electroencephalography (aEEG) can predict abnormal brain MRI in neonatal HIE.

Methods

WTC analysis was performed between dynamic oscillations of simultaneously recorded aEEG and cerebral tissue oxygen saturation (SctO2) signals for the first 24 h after birth. The squared cross-wavelet coherence, R², of the time–frequency domain described by the WTC, is a localized correlation coefficient (ranging between 0 and 1) between these two signals in the time–frequency domain. Statistical analysis was based on Monte Carlo simulation with a 95% confidence interval to identify the time–frequency areas from the WTC scalograms. Brain MRI was performed on all neonates and classified as normal or abnormal based on an accepted classification system for HIE. Wavelet metrics of % significant SctO2-aEEG coherence was compared between the normal and abnormal MRI groups.

Result

This prospective study recruited a total of 36 neonates with HIE. A total of 10 had an abnormal brain MRI while 26 had normal MRI. The analysis showed that the SctO2-aEEG coherence between the group with normal and abnormal MRI were significantly different (p = 0.0007) in a very low-frequency (VLF) range of 0.06–0.2 mHz. Using receiver operating characteristic (ROC) curves, the use of WTC-analysis of NVC had an area under the curve (AUC) of 0.808, and with a cutoff of 10% NVC. Sensitivity was 69%, specificity was 90%, positive predictive value (PPV) was 94%, and negative predictive value (NPV) was 52% for predicting brain injury on MRI. This was superior to the clinical Total Sarnat score (TSS) where AUC was 0.442 with sensitivity 61.5%, specificity 30%, PPV 75%, and NPV 31%.

Conclusion

NVC is a promising neurophysiological biomarker in neonates with HIE, and in our prospective cohort was superior to the clinical Total Sarnat score for prediction of abnormal brain MRI.

中文翻译：

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基于小波的神经血管耦合可以预测新生儿脑病的大脑异常

 背景

缺氧缺血性脑病（HIE）是新生儿发病和死亡的主要原因，但在病程早期预测结果的定量方法仍然难以捉摸。为了预测哪些新生儿将从治疗中受益，需要神经损伤的实时生理生物标志物。神经血管耦合（NVC）描述了神经活动与脑血流量的相关性，损伤程度可以预测那些有不良结果风险的人。

 客观的

确定基于近红外光谱 (NIRS) 和振幅积分脑电图 (aEEG) 的小波变换相干分析 (WTC) 计算的生命前 24 小时内的神经血管耦合 (NVC) 是否可以预测新生儿 HIE 中的异常脑部 MRI 。

 方法

在出生后第一个 24 小时内同时记录的 aEEG 和脑组织氧饱和度 (SctO2) 信号的动态振荡之间进行 WTC 分析。 WTC 描述的时频域的平方交叉小波相干性R ²是时频域中这两个信号之间的局部相关系数（范围在 0 和 1 之间）。统计分析基于蒙特卡罗模拟，具有 95% 的置信区间，可从 WTC 尺度图中识别时频区域。对所有新生儿进行脑部 MRI 检查，并根据公认的 HIE 分类系统将其分为正常或异常。比较正常和异常 MRI 组之间的显着 SctO2-aEEG 一致性百分比的小波指标。

 结果

这项前瞻性研究总共招募了 36 名患有 HIE 的新生儿。共有 10 人脑部 MRI 异常，26 人 MRI 正常。分析表明，正常和异常 MRI 组之间的 SctO2-aEEG 一致性在 0.06-0.2 mHz 的极低频 (VLF) 范围内存在显着差异 (p = 0.0007)。使用受试者工作特征 (ROC) 曲线，使用 WTC 分析 NVC 的曲线下面积 (AUC) 为 0.808，且 NVC 的截止值为 10%。 MRI 预测脑损伤的敏感性为 69%，特异性为 90%，阳性预测值 (PPV) 为 94%，阴性预测值 (NPV) 为 52%。这优于临床总 Sarnat 评分 (TSS)，其中 AUC 为 0.442，敏感性为 61.5%，特异性为 30%，PPV 为 75%，NPV 为 31%。

 结论

NVC 是 HIE 新生儿中一种很有前途的神经生理学生物标志物，在我们的前瞻性队列中，在预测异常脑部 MRI 方面优于临床总 Sarnat 评分。