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Quantifying anomalies in patients with neuropathologies via diffusion Magnetic Resonance Imaging (application to rehabilitation after stroke)

Dujardin, Quentin
(2024)

Files

Dujardin_63292000_2024.pdf
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Details

Supervisors
Macq, Benoît ; Dricot, Laurence
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] : ingénieur civil biomédical, à finalité spécialisée
Abstract
Context: Baby HABIT-ILE therapy for young infants with cerebral palsy (CP) could significantly reduce or even prevent maladaptive neuroplastic changes after brain injury through intensive motor training. However, classical diffusion magnetic resonance imaging (dMRI) analysis software shows difficulties in assessing the extent of corticospinal tract (CST) reorganization after therapy. Objective: In this Master’s thesis, a pipeline consisting exclusively of free and accessible tools for dMRI analysis is proposed, and the possibility of assessing CST reorganization after Baby HABIT-ILE therapy is evaluated. Methods: The main tools used are Elikopy, MRtrix3, and the Unravel framework. A set of microstructural metrics calculated from dMRI data are tested and statistically compared. Results: The proposed pipeline could successfully track the CST for 72 scans and assess the amount of crossing and non-crossing fibers projecting to impaired and non-impaired hemispheres for 60 scans. In addition, Scherrer’s DIAMOND model could significantly suggest axonal reorganization in the CST, which may be more important for fibers projecting to the lesioned hemisphere.