Intraoperative Resting-State Functional Connectivity Based on RGB Imaging.

RGB imaging functional connectivity intraoperative imaging optical imaging resting-state

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
09 Nov 2021
Historique:
received: 16 09 2021
revised: 27 10 2021
accepted: 04 11 2021
entrez: 27 11 2021
pubmed: 28 11 2021
medline: 28 11 2021
Statut: epublish

Résumé

RGB optical imaging is a marker-free, contactless, and non-invasive technique that is able to monitor hemodynamic brain response following neuronal activation using task-based and resting-state procedures. Magnetic resonance imaging (fMRI) and functional near infra-red spectroscopy (fNIRS) resting-state procedures cannot be used intraoperatively but RGB imaging provides an ideal solution to identify resting-state networks during a neurosurgical operation. We applied resting-state methodologies to intraoperative RGB imaging and evaluated their ability to identify resting-state networks. We adapted two resting-state methodologies from fMRI for the identification of resting-state networks using intraoperative RGB imaging. Measurements were performed in 3 patients who underwent resection of lesions adjacent to motor sites. The resting-state networks were compared to the identifications provided by RGB task-based imaging and electrical brain stimulation. Intraoperative RGB resting-state networks corresponded to RGB task-based imaging (DICE:0.55±0.29). Resting state procedures showed a strong correspondence between them (DICE:0.66±0.11) and with electrical brain stimulation. RGB imaging is a relevant technique for intraoperative resting-state networks identification. Intraoperative resting-state imaging has several advantages compared to functional task-based analyses: data acquisition is shorter, less complex, and less demanding for the patients, especially for those unable to perform the tasks.

Identifiants

pubmed: 34829414
pii: diagnostics11112067
doi: 10.3390/diagnostics11112067
pmc: PMC8625493
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : LABEX PRIMES
ID : ANR-11-LABX-0063
Organisme : French National Research Agency
ID : ANR-11-IDEX-0007
Organisme : Infrastructures d'Avenir en Biologie Santé
ID : ANR-11-INBS-000
Organisme : France Life Imaging
ID : ANR-11-INBS-0006

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Auteurs

Charly Caredda (C)

INSA-Lyon, Univ Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F69100 Lyon, France.

Laurent Mahieu-Williame (L)

INSA-Lyon, Univ Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F69100 Lyon, France.

Raphaël Sablong (R)

INSA-Lyon, Univ Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F69100 Lyon, France.

Michaël Sdika (M)

INSA-Lyon, Univ Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F69100 Lyon, France.

Fabien C Schneider (FC)

Service de Radiologie, Centre Hospitalier Universitaire de Saint Etienne, TAPE EA7423, Université de Lyon, UJM, F42023 Saint Etienne, France.

Jacques Guyotat (J)

Service de Neurochirurgie D, Hospices Civils de Lyon, F69500 Bron, France.

Bruno Montcel (B)

INSA-Lyon, Univ Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F69100 Lyon, France.

Classifications MeSH