Medina Jean Paul, Nigri Anna, Stanziano Mario, D'Incerti Ludovico, Sattin Davide, Ferraro Stefania, Rossi Sebastiano Davide, Pinardi Chiara, Marotta Giorgio, Leonardi Matilde, Bruzzone Maria Grazia, Rosazza Cristina
Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy.
Neurosciences Department "Rita Levi Montalcini", University of Turin, 10126 Turin, Italy.
Brain Sci. 2022 Mar 7;12(3):355. doi: 10.3390/brainsci12030355.
Resting-state fMRI (rs-fMRI) is a widely used technique to investigate the residual brain functions of patients with Disorders of Consciousness (DoC). Nonetheless, it is unclear how the networks that are more associated with primary functions, such as the sensory-motor, medial/lateral visual and auditory networks, contribute to clinical assessment. In this study, we examined the rs-fMRI lower-order networks alongside their structural MRI data to clarify the corresponding association with clinical assessment. We studied 109 chronic patients with DoC and emerged from DoC with structural MRI and rs-fMRI: 65 in vegetative state/unresponsive wakefulness state (VS/UWS), 34 in minimally conscious state (MCS) and 10 with severe disability. rs-fMRI data were analyzed with independent component analyses and seed-based analyses, in relation to structural MRI and clinical data. The results showed that VS/UWS had fewer networks than MCS patients and the rs-fMRI activity in each network was decreased. Visual networks were correlated to the clinical status, and in cases where no clinical response occurred, rs-fMRI indicated distinctive networks conveying information in a similar way to other techniques. The information provided by single networks was limited, whereas the four networks together yielded better classification results, particularly when the model included rs-fMRI and structural MRI data (AUC = 0.80). Both quantitative and qualitative rs-fMRI analyses yielded converging results; vascular etiology might confound the results, and disease duration generally reduced the number of networks observed. The lower-order rs-fMRI networks could be used clinically to support and corroborate visual function assessments in DoC.
静息态功能磁共振成像(rs-fMRI)是一种广泛应用于研究意识障碍(DoC)患者残余脑功能的技术。然而,目前尚不清楚与初级功能(如感觉运动、内侧/外侧视觉和听觉网络)更相关的网络如何有助于临床评估。在本研究中,我们检查了rs-fMRI低阶网络及其结构MRI数据,以阐明与临床评估的相应关联。我们研究了109例慢性DoC患者,这些患者通过结构MRI和rs-fMRI从DoC中苏醒过来:65例处于植物状态/无反应觉醒状态(VS/UWS),34例处于最低意识状态(MCS),10例有严重残疾。将rs-fMRI数据与结构MRI和临床数据相关联,采用独立成分分析和基于种子点的分析方法进行分析。结果表明,VS/UWS患者的网络比MCS患者少,且每个网络中的rs-fMRI活动均降低。视觉网络与临床状态相关,在无临床反应的情况下,rs-fMRI显示出与其他技术以相似方式传递信息的独特网络。单个网络提供的信息有限,而四个网络一起产生了更好的分类结果,特别是当模型包括rs-fMRI和结构MRI数据时(AUC = 0.80)。rs-fMRI的定量和定性分析均得出了一致的结果;血管病因可能会混淆结果,且病程通常会减少观察到的网络数量。rs-fMRI低阶网络可在临床上用于支持和佐证DoC患者的视觉功能评估。