Disorder of consciousness: Structural integrity of brain networks for the clinical assessment

AimWhen studying brain networks in patients with Disorders of Consciousness (DoC), it is important to evaluate the structural integrity of networks in addition to their functional activity. Here, we investigated whether structural MRI, together with clinical variables, can be useful for diagnostic purposes and whether a quantitative analysis is feasible in a group of chronic DoC patients. MethodsWe studied 109 chronic patients with DoC and emerged from DoC with structural MRI: 65 in vegetative state/unresponsive wakefulness state (VS/UWS), 34 in minimally conscious state (MCS), and 10 with severe disability. MRI data were analyzed through qualitative and quantitative approaches. ResultsThe qualitative MRI analysis outperformed the quantitative one, which resulted to be hardly feasible in chronic DoC patients. The results of the qualitative approach showed that the structural integrity of HighOrder networks, altogether, had better diagnostic accuracy than LowOrder networks, particularly when the model included clinical variables (AUC = 0.83). Diagnostic differences between VS/UWS and MCS were stronger in anoxic etiology than vascular and traumatic etiology. MRI data of all LowOrder and HighOrder networks correlated with the clinical score. The integrity of the left hemisphere was associated with a better clinical status. ConclusionsStructural integrity of brain networks is sensitive to clinical severity. When patients are chronic, the qualitative analysis of MRI data is indicated.

Automated summary

When studying brain networks in patients with Disorders of Consciousness (DoC), it is important to evaluate both the structural integrity and functional activity of the networks. This study investigated the usefulness of structural MRI and clinical variables for diagnosis in chronic DoC patients and found that qualitative analysis of MRI data is more effective than quantitative analysis. The results showed that the structural integrity of HighOrder networks had better diagnostic accuracy than LowOrder networks, especially when clinical variables were included in the analysis. The integrity of the left hemisphere was associated with a better clinical status.