Reproducible in vivo characterization of multiple sclerosis lesions using multi-modal MRI
(2026)
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- (en) Multiple sclerosis (MS) is the leading cause of non-traumatic neurological disability in young adults, driven by focal lesions in the central nervous system that trigger demyelination, axonal loss, and progressive clinical decline. While conventional magnetic resonance imaging (MRI) remains indispensable for diagnosis, its limited pathological specificity restricts its ability to capture the heterogeneous processes underlying MS evolution, such as chronic inflammation, neurodegeneration, and repair. Advanced quantitative MRI techniques, particularly diffusion-weighted imaging, offer indirect access to tissue microstructure and lesion dynamics in vivo. However, their clinical translation is limited by methodological variability, fragmented biomarker interpretation, and an incomplete understanding of how these metrics relate to underlying pathology. This thesis addresses these challenges through three interconnected contributions, prioritizing reproducibility, biological interpretability, and clinical relevance. First, a user-friendly neuroimaging software platform, BMAT, was developed to facilitate standardized data processing and improve accessibility of advanced MRI analysis pipelines for clinical researchers, thereby promoting reproducibility and open scientific practices. Second, comparative investigations of diffusion MRI models and critical methodological evaluation of chronic active lesion biomarkers were conducted to bridge the gap between engineering implementation and clinical interpretation, clarifying the strengths, limitations, and biological relevance of commonly used imaging markers and methodology. Third, a longitudinal data-driven analysis of MS lesions dynamics was performed to characterize the relationship between chronic inflammatory activity, lesion volume dynamics, and clinical disability, providing new insights into the pathological mechanisms underlying lesion evolution. Collectively, this thesis advances the methodological rigor and interpretability of quantitative MRI in MS research. By integrating standardized processing tools, validated microstructural models, and longitudinal clinical data, it provides a foundation for more precise in vivo characterization of MS pathology. These developments hold promise for refining disease monitoring, improving prognostic accuracy, and ultimately personalizing therapeutic strategies in multiple sclerosis.
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Vanden Bulcke, C. (2026). Reproducible in vivo characterization of multiple sclerosis lesions using multi-modal MRI. https://hdl.handle.net/2078.5/275995