Patient-specific modeling for guided rehabilitation of stroke patients: the BrainX3 use-case.

BrainX3 automatic lesion identification stroke transcranial ultrasound stimulation whole-brain models

Journal

Frontiers in neurology
ISSN: 1664-2295
Titre abrégé: Front Neurol
Pays: Switzerland
ID NLM: 101546899

Informations de publication

Date de publication:
2023
Historique:
received: 22 08 2023
accepted: 06 11 2023
medline: 15 12 2023
pubmed: 15 12 2023
entrez: 15 12 2023
Statut: epublish

Résumé

BrainX3 is an interactive neuroinformatics platform that has been thoughtfully designed to support neuroscientists and clinicians with the visualization, analysis, and simulation of human neuroimaging, electrophysiological data, and brain models. The platform is intended to facilitate research and clinical use cases, with a focus on personalized medicine diagnostics, prognostics, and intervention decisions. BrainX3 is designed to provide an intuitive user experience and is equipped to handle different data types and 3D visualizations. To enhance patient-based analysis, and in keeping with the principles of personalized medicine, we propose a framework that can assist clinicians in identifying lesions and making patient-specific intervention decisions. To this end, we are developing an AI-based model for lesion identification, along with a mapping of tract information. By leveraging the patient's lesion information, we can gain valuable insights into the structural damage caused by the lesion. Furthermore, constraining whole-brain models with patient-specific disconnection masks can allow for the detection of mesoscale excitatory-inhibitory imbalances that cause disruptions in macroscale network properties. Finally, such information has the potential to guide neuromodulation approaches, assisting in the choice of candidate targets for stimulation techniques such as Transcranial Ultrasound Stimulation (TUS), which modulate E-I balance, potentiating cortical reorganization and the restoration of the dynamics and functionality disrupted due to the lesion.

Identifiants

pubmed: 38099071
doi: 10.3389/fneur.2023.1279875
pmc: PMC10719856
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1279875

Informations de copyright

Copyright © 2023 Sharma, Páscoa dos Santos and Verschure.

Déclaration de conflit d'intérêts

FP is employed by the company Eodyne Systems S.L. PV is founder and shareholder of Eodyne Systems S.L., which aims at bringing scientifically validated neurorehabilitation and education technology to society. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Vivek Sharma (V)

Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, Netherlands.

Francisco Páscoa Dos Santos (F)

Eodyne Systems S.L., Barcelona, Spain.
Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona, Spain.

Paul F M J Verschure (PFMJ)

Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, Netherlands.

Classifications MeSH