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

Area of Science:

• Neuroimaging
• Clinical Neuroscience
• Brain Network Analysis

Background:

• Resting-state functional MRI (rs-fMRI) networks are consistently found in Disorders of Consciousness (DOC).
• Systematic assessment of these networks is crucial for enhancing clinical interpretability of rs-fMRI data.
• This study investigates the functional connectivity of major brain networks in DOC patients.

Purpose of the Study:

• To systematically assess the main rs-fMRI networks in patients with Disorders of Consciousness (DOC).
• To determine the diagnostic ability of these networks in distinguishing between different DOC states.
• To explore the relationship between network characteristics and clinical assessments.

Main Methods:

• A multimodal assessment was conducted on 109 chronic DOC patients (VS/UWS, MCS, eMCS) and 34 controls.
• Rs-fMRI data were analyzed using a semi-automatic pipeline to evaluate residual functional activity.
• Network analysis focused on number, type, mean intensity, and structural preservation.

Main Results:

• A higher number of observed networks correlated with better clinical condition across VS/UWS, MCS, and eMCS groups.
• The presence and intensity of specific networks (visual, temporal, DMN) differentiated VS/UWS from MCS (AUCs 0.64-0.69).
• Etiology and disease duration influenced network characteristics, with high residual connectivity observed in both VS/UWS and MCS patients.

Conclusions:

• Systematic assessment of rs-fMRI networks provides foundational measures for functional connectivity in DOC.
• These measures enhance the interpretability of rs-fMRI data in clinical practice for Disorders of Consciousness.
• The findings support the utility of rs-fMRI network analysis for understanding and potentially diagnosing DOC states.