4.5 Article

Resting-State fMRI in Chronic Patients with Disorders of Consciousness: The Role of Lower-Order Networks for Clinical Assessment

Journal

BRAIN SCIENCES
Volume 12, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/brainsci12030355

Keywords

disorders of consciousness; resting-state fMRI; visual; auditory and sensorimotor networks

Categories

Funding

  1. Ministero della Salute [GR-2016-02361225]

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Resting-state fMRI was used to investigate the association between lower-order networks and clinical assessment in patients with Disorders of Consciousness (DoC). The results showed that patients in vegetative state had fewer networks and decreased activity in each network compared to minimally conscious state patients. Visual networks were correlated with clinical status, and the combination of rs-fMRI and structural MRI data improved classification results. The findings suggest that lower-order rs-fMRI networks can be used to support visual function assessments in DoC.
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.

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