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Neuroimaging biomarkers for the diagnosis and prognosis of patients with disorders of consciousness

神经影像学 持续植物状态 意识障碍 意识的神经相关物 脑电图 大脑活动与冥想 意识 医学 神经功能成像 静息状态功能磁共振成像 心理学 最小意识状态 神经科学 认知
作者
Jiaying Wang,Qiantu Lai,Junrong Han,Pengmin Qin,Hang Wu
出处
期刊:Brain Research [Elsevier BV]
卷期号:1843: 149133-149133 被引量:2
标识
DOI:10.1016/j.brainres.2024.149133
摘要

The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.
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