Multimodal Neuroimaging Approach to Variability of Functional Connectivity in Disorders of Consciousness: A PET/MRI Pilot Study

Abstract

Behavioral assessments could not suffice to provide accurate diagnostic information in individuals with disorders of consciousness (DoC). Multimodal neuroimaging markers have been developed to support clinical assessments of these patients. Here we present findings obtained by hybrid fludeoxyglucose (FDG-)PET/MR imaging in three severely brain-injured patients, one in an unresponsive wakefulness syndrome (UWS), one in a minimally conscious state (MCS), and one patient emerged from MCS (EMCS). Repeated behavioral assessment by means of Coma Recovery Scale-Revised and neurophysiological evaluation were performed in the two weeks before and after neuroimaging acquisition, to ascertain that clinical diagnosis was stable. The three patients underwent one imaging session, during which two resting-state fMRI (rs-fMRI) blocks were run with a temporal gap of about 30 min. rs-fMRI data were analyzed with a graph theory approach applied to nine independent networks. We also analyzed the benefits of concatenating the two acquisitions for each patient or to select for each network the graph strength map with a higher ratio of fitness. Finally, as for clinical assessment, we considered the best functional connectivity pattern for each network and correlated graph strength maps to FDG uptake. Functional connectivity analysis showed several differences between the two rs-fMRI acquisitions, affecting in a different way each network and with a different variability for the three patients, as assessed by ratio of fitness. Moreover, combined PET/fMRI analysis demonstrated a higher functional/metabolic correlation for patients in EMCS and MCS compared to UWS. In conclusion, we observed for the first time, through a test-retest approach, a variability in the appearance and temporal/spatial patterns of resting-state networks in severely brain-injured patients, proposing a new method to select the most informative connectivity pattern.

Keywords: PET/MRI; brain connectivity; diagnosis; glucose metabolism; graph theory; minimally conscious state; resting-state fMRI; unresponsive wakefulness syndrome.

Figures

Figure 1

Flow chart of patient selection in each step of the study.

Figure 2

Coma Recovery Scale-Revised total score and neurophysiological (EEG and evoked related potential) evaluations recorded in the 3rd and 5th day before PET/fMRI exam and in the 7th and 9th day after the PET/fMRI exam. The green arrow marks the day of neuroimaging acquisition. The blue diamond and line denote the patient in unresponsive wakefulness syndrome (UWS). The orange square and line denote the patient in minimally conscious state (MCS). The gray triangle and line denote the patient emerged from MCS (EMCS). CRS-R, Coma Recovery Scale-Revised; P, presence of P300 on evoked related potential; A, absence of P300 on evoked related potential; +, presence of EEG reactivity to eye opening and closing; –, absence of EEG reactivity to eye opening and closing; MiA, mildly abnormal EEG background activity; MoA, moderately abnormal EEG background activity; DS, Diffuse slowing EEG background activity; LV, Low voltage EEG background activity.

Figure 3

A visual representation of the regions highlighted by the thresholded GS (values greater than half of the maximum GS value for the network), separated by the regions within and outside the network for patients in EMCS, MCS and UWS for nine RSNs. Regions belonging to the network and having GS values greater than the thresholded GS are represented by green, regions which should be in the network but do not have GS values greater than the thresholded GS are represented by blue, regions outside the network but have GS values greater than the thresholded GS are represented by red color. NN represents non-neuronal networks. Here the size of the circle doesn't represent the value of the GS, all the regions with a GS value are plotted evenly.