Brainstem volume, diffusion, and metabolism are associated with chronic consciousness disorders after traumatic brain injury

Sawamura, Shogo; Ikegame, Yuka; Kawasaki, Terukazu; Nakayama, Noriyuki; Yano, Hirohito; Shinoda, Jun

doi:10.1111/jon.13071

Cited by 1 publication

(1 citation statement)

References 21 publications

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“…Four papers focused on improving DoC diagnosis and prognosis by integrating different neuroimaging and neurometabolic techniques (Annen et al, 2018; Qin et al, 2015; Sawamura et al, 2023; Soddu et al, 2016). Although F‐FDG‐PET has traditionally been considered the most reliable technique to assess DoC patients, these studies tested the possibility of integrating F‐FDG‐PET with MRI‐derived measures to improve the diagnostic process, or to replace metabolic data in case of necessity.…”

Section: Resultsmentioning

confidence: 99%

Multimodal approaches supporting the diagnosis, prognosis and investigation of neural correlates of disorders of consciousness: A systematic review

Gallucci,

Varoli,

Del Mauro

et al. 2023

Eur J of Neuroscience

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The limits of the standard, behaviour‐based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain‐based covert markers of awareness. However, uni‐modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer‐review original articles in which a multi‐modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety‐two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi‐modal approaches that involve electroencephalography‐based (EEG‐based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori‐designed multi‐modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs.

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