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

Carlo Cavaliere; Sivayini Kandeepan; Marco Aiello; Demetrius Ribeiro de Paula; Rocco Marchitelli; Salvatore Fiorenza; Mario Orsini; Luigi Trojano; Orsola Masotta; Keith St Lawrence; Vincenzo Loreto; Blaine Alexander Chronik; Emanuele Nicolai; Andrea Soddu; Anna Estraneo

doi:10.3389/fneur.2018.00861

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

Front Neurol. 2018 Oct 18:9:861. doi: 10.3389/fneur.2018.00861. eCollection 2018.

Authors

Carlo Cavaliere^{1

2}, Sivayini Kandeepan³, Marco Aiello¹, Demetrius Ribeiro de Paula³, Rocco Marchitelli¹, Salvatore Fiorenza⁴, Mario Orsini¹, Luigi Trojano⁵, Orsola Masotta⁴, Keith St Lawrence⁶, Vincenzo Loreto⁴, Blaine Alexander Chronik³, Emanuele Nicolai¹, Andrea Soddu³, Anna Estraneo⁴

Affiliations

¹ IRCCS SDN, Istituto di Ricerca Diagnostica e Nucleare, Naples, Italy.
² Coma Science Group, GIGA-Research, University and University Hospital of Liege, Liege, Belgium.
³ Department of Physics and Astronomy, Brain and Mind Institute, Western University, London, ON, Canada.
⁴ Neurorehabilitation Unit and Research Laboratory for Disorder of Consciousness, Maugeri ICS, IRCCS, Telese Terme, Italy.
⁵ Department of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy.
⁶ Lawson Health Research Institute London, Medical Biophysics, University of Western Ontario, London, ON, Canada.

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.