Project description
Automated analysis tool for traumatic spinal cord injury management
Traumatic spinal cord injury (tSCI) impacts patients’ quality of life. Current neurological examinations and MRI scans often fail to assess tSCI severity due to the complex nature of the analysis and variability across hospitals. With the support of the Marie Skłodowska-Curie Actions programme, the SCIseg project will develop an automated analysis tool to improve tSCI management. This tool will employ deep learning models for the automatic segmentation of the spinal cord and lesions from MRI images, addressing the limitations of manual segmentation. The models will be trained on a multi-institutional MRI dataset to ensure reliability across hospitals. Additionally, the project will generate quantitative measures of tSCI severity from the segmented data.
Objective
Traumatic spinal cord injury (tSCI) markedly reduces patients quality of life and economically burdens health systems. Neurological examinations and clinical magnetic resonance imaging (MRI) scans are currently insufficient for the proper classification of the tSCI baseline level (i.e. severity). Although MRI scans are routinely employed in tSCI patients, the MRI potential is not fully utilised due to the complexity of the analysis and diversity of MRI data across hospitals. The aim of this project is to propose a fully automatic and reproducible analysis tool that could be run by clinicians to improve the clinical management of tSCI patients. First, deep learning models for automatic spinal cord and lesion segmentation from MRI images will be developed to go beyond the currently used error-prone and time-consuming manual segmentations. The models will be trained on a multi institutional MRI dataset to be robust to MRI data heterogeneity across hospitals. Then, quantitative measures of the tSCI severity will be automatically computed from the segmented structures (i.e. spinal cord and lesions) and employed within the statistical model to predict tSCI severity. Finally, the developed methodology will be translated to the real-world healthcare system and tested on a prospectively acquired dataset of tSCI patients. Importantly, deep learning models, analysis pipeline, and statistical model will be seamlessly integrated into the current state-of-the-art ecosystem for spinal cord MRI data analysis and made publicly available to facilitate open science and reproducibility across hospitals. The project will create the first step in the improvement of care and clinical management in millions of patients with tSCI worldwide. In the longer term, after demonstrating the clinical relevance of the proposed tools, we assume that advanced MRI-based methods will be adopted by the larger clinical community for more personalised care.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2022-PF-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
771 47 Olomouc
Czechia
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.