Structural and functional connectivity of the ascending arousal network for prediction of outcome in patients with acute disorders of consciousness

Abstract

To determine the role of early acquisition of blood oxygen level-dependent (BOLD) signals and diffusion tensor imaging (DTI) for analysis of the connectivity of the ascending arousal network (AAN) in predicting neurological outcomes after acute traumatic brain injury (TBI), cardiopulmonary arrest (CPA), or stroke. A prospective analysis of 50 comatose patients was performed during their ICU stay. Image processing was conducted to assess structural and functional connectivity of the AAN. Outcomes were evaluated after 3 and 6 months. Nineteen patients (38%) had stroke, 18 (36%) CPA, and 13 (26%) TBI. Twenty-three patients were comatose (44%), 11 were in a minimally conscious state (20%), and 16 had unresponsive wakefulness syndrome (32%). Univariate analysis demonstrated that measurements of diffusivity, functional connectivity, and numbers of fibers in the gray matter, white matter, whole brain, midbrain reticular formation, and pontis oralis nucleus may serve as predictive biomarkers of outcome depending on the diagnosis. Multivariate analysis demonstrated a correlation of the predicted value and the real outcome for each separate diagnosis and for all the etiologies together. Findings suggest that the above imaging biomarkers may have a predictive role for the outcome of comatose patients after acute TBI, CPA, or stroke.

Figure 1

Description of the enrollment of patients in the study.

Figure 2

Receiver operating characteristic (ROC) curves of single measurements for different cortical and subcortical areas. ROC curves demonstrate the possible predictive value of data comparing true positive and false positive rates for fractional anisotropy, mean diffusivity, and radial diffusivity among patients with TBI (yellow), cardiac arrest (purple), and stroke (green).

Figure 3

Reconstruction of the tractography of ascending arousal network. (A) A complete reconstruction of the AAN of a normal subject is demonstrated. Major components including the medial forebrain bundle (MFB) projecting to the dorsal frontal cortex, the dorsal raphe (DR), the thalamic-hypothalamic complex (asterisk), and superior and inferior tegmental tracts (TT) projecting to the basal frontal cortex are shown. (B) A reconstruction of the AAN of a comatose patient after a severe traumatic brain injury is observed, denoting a destruction of the tegmental tracts. (C) A reconstruction of the AAN of a patient after a stroke demonstrates a disruption of the tracts in the length of the MFB, the fibers of the DR, and the tegmental tracts. (D) A reconstruction of the AAN is shown in a comatose patient after a cardiac arrest, demonstrating a decrease in the number of fibers of all components of the AAN.

Figure 4

Multivariate analysis for prediction of outcomes of consciousness by etiology. In the three scenarios (traumatic brain injury, cardiac arrest, and stroke), the outcome for each patient is demonstrated by a linear model. The curves show a direct correlation between imaging and prediction of consciousness outcome, with corresponding R² values of 0.463, 0.92 and 0,84, respectively.

Figure 5

Multivariate prediction at the group level. The relationship between outcome and prediction of the general linear model is demonstrated using (A) both the structural and functional descriptors together, (B) the functional descriptors alone, and (C) the structural descriptors alone. The corresponding R² values are 0.82, 0.46 and 0.5, respectively.