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

© 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association..

AIM: When 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.

METHODS: We 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.

RESULTS: The 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.

CONCLUSIONS: Structural integrity of brain networks is sensitive to clinical severity. When patients are chronic, the qualitative analysis of MRI data is indicated.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Annals of clinical and translational neurology - 10(2023), 3 vom: 01. März, Seite 384-396

Sprache:

Englisch

Beteiligte Personen:

Medina Carrion, Jean Paul [VerfasserIn]
Stanziano, Mario [VerfasserIn]
D'Incerti, Ludovico [VerfasserIn]
Sattin, Davide [VerfasserIn]
Palermo, Sara [VerfasserIn]
Ferraro, Stefania [VerfasserIn]
Sebastiano, Davide Rossi [VerfasserIn]
Leonardi, Matilde [VerfasserIn]
Bruzzone, Maria Grazia [VerfasserIn]
Rosazza, Cristina [VerfasserIn]
Nigri, Anna [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 16.03.2023

Date Revised 17.03.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1002/acn3.51729

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM351491635