European Conference on Mathematical and Theoretical Biology (ECMTB 2026)

Computational Approaches to Multiple Sclerosis: Immune Dynamics and Data-Driven Lesion Modeling

MS11-01

13 Jul 2026, 15:00

20m

15.12 - HS (University of Graz)

Minisymposium Talk Neuroscience and Neural Systems Immune attack on the nervous system: mathematical models of multiple sclerosis

Speakers

Barbara Quintela (Universidade Federal de Juiz de Fora) Gustavo G Silva (Federal University of Juiz de Fora (UFJF)) Luan C Silva (Federal University of Juiz de Fora (UFJF)) Marcelo Lobosco (Federal University of Juiz de Fora (UFJF)) Philippe Neumann (Federal University of Juiz de Fora (UFJF))

Description

Multiple Sclerosis (MS) is a chronic autoimmune disease affecting approximately 1.8 million people worldwide and demands improved tools for diagnosis and disease understanding. This talk presents two complementary computational models addressing distinct challenges in MS research and care. The first focuses on medical imaging and builds upon an MS lesion segmentation dataset [1]. To address data scarcity, we investigate generative deep learning for artificial data augmentation. A two-stage pipeline is employed: a Variational Autoencoder (VAE) generates synthetic lesion masks, followed by a Conditional Generative Adversarial Network (cGAN) that synthesizes realistic brain textures conditioned on these masks. We evaluate the impact of augmented data on MRI lesion segmentation performance. The second model targets disease mechanisms through an in silico representation of Experimental Autoimmune Encephalomyelitis (EAE) [2]. The model captures key immunological dynamics of EAE progression, enabling simulation of disease evolution and therapeutic strategies while reducing costs and ethical constraints of animal experimentation. Together, these approaches demonstrate how computational modeling advances both clinical applications and mechanistic understanding of MS.

Bibliography

@article{guarnera_mslesseg_2025,
title = {{MSLesSeg}: baseline and benchmarking of a new {Multiple} {Sclerosis} {Lesion} {Segmentation} dataset},
volume = {12},
issn = {2052-4463},
shorttitle = {{MSLesSeg}},
doi = {10.1038/s41597-025-05250-y},
language = {en},
number = {1},
journal = {Scientific Data},
author = {Guarnera, Francesco and Rondinella, Alessia and Crispino, Elena and Russo, Giulia and Di Lorenzo, Clara and Maimone, Davide and Pappalardo, Francesco and Battiato, Sebastiano},
month = may,
year = {2025},
pages = {920},
}

@article{dasilva2020,
author={da Silva, Luan Cristian and de Assis Lima, Isabel Vieira and da Silva, Maria Carolina Machado and Corr{\^e}a, Ta{\'\i}s Arthur and de Souza, Viviane Passos and de Almeida, Mauro Vieira and de Oliveira, Ant{\^o}nio Carlos Pinheiro and Ferreira, Ana Paula},
title={A new lipophilic amino alcohol, chemically similar to compound FTY720, attenuates the pathogenesis of experimental autoimmune encephalomyelitis by PI3K/Akt pathway inhibition},
journal={International Immunopharmacology},
volume={84},
pages={106553},
year={2020}
}