Intraoperative Resting-State Functional Connectivity Based on RGB Imaging - Physics, Radiobiology, Medical Imaging, and Simulation (PRIMES)
Article Dans Une Revue Diagnostics Année : 2021

Intraoperative Resting-State Functional Connectivity Based on RGB Imaging

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.

Domaines

Imagerie
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Dates et versions

hal-03423345 , version 1 (13-11-2024)

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Charly Caredda, Laurent Mahieu-Williame, Raphaël Sablong, Michaël Sdika, Fabien Schneider, et al.. Intraoperative Resting-State Functional Connectivity Based on RGB Imaging. Diagnostics, 2021, 11 (11), pp.2067. ⟨10.3390/diagnostics11112067⟩. ⟨hal-03423345⟩
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