Detecting rs-fMRI Networks in Disorders of Consciousness: Improving Clinical Interpretability

Background: Preserved resting-state functional MRI (rs-fMRI) networks are typically observed in Disorders of Consciousness (DOC). Despite the widespread use of rs-fMRI in DOC, a systematic assessment of networks is needed to improve the interpretability of data in clinical practice. We investigated functional connectivity of the main networks, combining structural MRI to obtain a description of the most observed networks in DOC, their diagnostic ability, and whether they can be related to clinical assessment. Methods: A group of 109 chronic patients [65 vegetative state/unresponsive wakefulness state (VS/UWS), 34 minimally conscious state (MCS), and 10 emerged from MCS (eMCS)], with different etiologies, and 34 control subjects underwent multimodal assessment. Rs-fMRI data were analyzed with a semi-automatic pipeline to assess residual functional activity in terms of number, type, mean intensity, and structural preservation of networks. Results: The more networks observed, the better the patient's clinical condition is likely to be. VS/UWS patients display 0-9, MCS 5-9, and eMCS 8-10 networks. Both the presence and intensity of 5 networks (visual networks, temporal, left fronto-parietal and default mode network) are relevant to distinguish VS/UWS from MCS, with AUCs of 0.64-0.69 (95% confidence interval). Etiology and disease duration have an impact on the number and type of preserved networks. High residual functional connectivity observed in VS/UWS patients, as in MCS, is in agreement with neurophysiological and metabolic evaluations. Conclusions: This systematic assessment of the main rs-fMRI networks in DOC provides basic measures of functional connectivity that can enhance their interpretability in clinical practice.