Grant: Project Grant
Polytechnique Montréal
$826,200.00
Translating AI-based methods to quantify pathology in MS: Development, validation and implementation of a sustainable MRI analysis framework within a pan-Canadian network
EF 2022-23
Résumé
This grant proposal aims to establish a comprehensive and sustainable AI framework for the segmentation of multiple sclerosis (MS) lesions in brain and spinal cord MRI scans, and to translate these developments across multiple clinical sites in Canada. The current methods of MRI analysis in radiology are not precise enough for accurate diagnosis and monitoring of MS. This proposal leverages a unique pan-Canadian MRI study to train artificial intelligence algorithms, and implement the MRI acquisition and AI models into clinical sites for sustainability. The goal is to provide a complete picture of MS pathology along the brain-spine axis using an optimised MRI protocol and AI-driven analysis tools. This project will contribute to the advancement of MS diagnosis and monitoring methods. We will dedicate efforts to make these tools available to major MS clinics in Canada and to train local personnel for integration into the clinical workflow. The expected outcome is to provide a clinically relevant understanding of MS pathology and advance diagnosis and monitoring methods.
Programme
Project Grant
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
CIHR Funding Decisions Database
Tel que publié
Id
480232
Name
Cohen-Adad Julien
Region
Québec
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Neurosciences, Mental Health and Addiction
Theme2
Biomedical
Prcname2
Behavioural Sciences - B-2
Projecttitle
Translating AI-based methods to quantify pathology in MS: Development, validation and implementation of a sustainable MRI analysis framework within a pan-Canadian network
Programtype2
Operating Grants
Orgnameinp2
Polytechnique Montréal
Cihramount2
$826,200
Cihrequipment2
$0
Programname2
Project Grant
Keyworddelim
Brain; Deep Learning; Generalization; Knowledge Transfer; Lesions; Mri; Multiple Sclerosis; Segmentation; Spinal Cord
Abstract
This grant proposal aims to establish a comprehensive and sustainable AI framework for the segmentation of multiple sclerosis (MS) lesions in brain and spinal cord MRI scans, and to translate these developments across multiple clinical sites in Canada. The current methods of MRI analysis in radiology are not precise enough for accurate diagnosis and monitoring of MS. This proposal leverages a unique pan-Canadian MRI study to train artificial intelligence algorithms, and implement the MRI acquisition and AI models into clinical sites for sustainability. The goal is to provide a complete picture of MS pathology along the brain-spine axis using an optimised MRI protocol and AI-driven analysis tools. This project will contribute to the advancement of MS diagnosis and monitoring methods. We will dedicate efforts to make these tools available to major MS clinics in Canada and to train local personnel for integration into the clinical workflow. The expected outcome is to provide a clinically relevant understanding of MS pathology and advance diagnosis and monitoring methods.
Competitiondate
202303
Approvedterm2
5 yrs 0 mth
Pinamesdelim
Cohen-Adad, Julien
Approvedterm
5 ans 0 mois
Cihrcontribution2
~ $826,200~ $0~