Amplitude and frequency modulation of EEG predicts Intraventricular hemorrhage in preterm infants

IF 5.3 2区 医学 Q1 ENGINEERING, BIOMEDICAL Biocybernetics and Biomedical Engineering Pub Date : 2024-07-01 DOI:10.1016/j.bbe.2024.08.012
Emad Arasteh , Maria Luisa Tataranno , Maarten De Vos , Xiaowan Wang , Manon J.N.L. Benders , Jeroen Dudink , Thomas Alderliesten
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Abstract

Background

Intraventricular hemorrhage (IVH) is a common and significant complication in premature infants. While cranial ultrasound is the golden standard for IVH detection, it may not identify lesions until hours or days after occurring, which limits early intervention. Predicting IVH in premature infants would be highly advantageous. Recent studies have shown that EEG data’s amplitude and frequency modulation features could offer predictive insights for neurological diseases in adults.

Methods

To investigate the association between IVH and EEG monitoring, a retrospective case-control study was conducted in preterm infants. All infants underwent amplitude integrated EEG monitoring for at least 3 days after birth. The study included 20 cases who had an IVH diagnosed on cranial ultrasound and had a negative ultrasound 24 h earlier, and 20 matched controls without IVH. Amplitude and frequency modulation features were extracted from single-channel EEG data, and various machine learning algorithms were evaluated to create a predictive model.

Results

Cases had an average gestational age and birth weight of 26.4 weeks and 965 g, respectively. The best-performing algorithm was adaptive boosting. EEG data from 24 h before IVH detection proved predictive with an area under the receiver operating characteristic curve of 93 %, an accuracy of 91 %, and a Kappa value of 0.85. The most informative features were the slow varying instantaneous frequency and amplitude in the Delta frequency band.

Conclusion

Amplitude and frequency modulation features obtained from single-channel EEG signals in extremely preterm infants show promise for predicting IVH occurrence within 24 h before detection on cranial ultrasound.

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脑电图的振幅和频率调制可预测早产儿脑室内出血
背景脑室内出血(IVH)是早产儿常见的严重并发症。虽然头颅超声波是检测 IVH 的黄金标准,但它可能要在 IVH 发生数小时或数天后才能发现病变,这就限制了早期干预。对早产儿进行 IVH 预测是非常有利的。最近的研究表明,脑电图数据的振幅和频率调制特征可为成人神经系统疾病提供预测性洞察力。方法为了研究 IVH 与脑电图监测之间的关联,我们对早产儿进行了一项回顾性病例对照研究。所有婴儿均在出生后至少 3 天接受了振幅综合脑电图监测。研究包括 20 例经头颅超声诊断为 IVH 且 24 小时前超声检查结果为阴性的病例,以及 20 例无 IVH 的匹配对照组。研究人员从单通道脑电图数据中提取了振幅和频率调制特征,并对各种机器学习算法进行了评估,以建立预测模型。表现最好的算法是自适应提升算法。IVH检测前24小时的脑电图数据具有预测性,接收者工作特征曲线下面积为93%,准确率为91%,Kappa值为0.85。结论从极早产儿单通道脑电信号中获得的幅值和频率调制特征有望预测颅脑超声检测前 24 小时内 IVH 的发生。
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来源期刊
CiteScore
16.50
自引率
6.20%
发文量
77
审稿时长
38 days
期刊介绍: Biocybernetics and Biomedical Engineering is a quarterly journal, founded in 1981, devoted to publishing the results of original, innovative and creative research investigations in the field of Biocybernetics and biomedical engineering, which bridges mathematical, physical, chemical and engineering methods and technology to analyse physiological processes in living organisms as well as to develop methods, devices and systems used in biology and medicine, mainly in medical diagnosis, monitoring systems and therapy. The Journal''s mission is to advance scientific discovery into new or improved standards of care, and promotion a wide-ranging exchange between science and its application to humans.
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