title: A genetic algorithm-based model for longitudinal changes detection in white matter fiber-bundles of patient with multiple sclerosis.
abstract: Analysis of white matter (WM) tissue is essential to understand the mechanisms of neurodegenerative pathologies like multiple sclerosis (MS). Recently longitudinal studies started to show how the temporal component is important to investigate temporal diffuse effects of neurodegenerative pathologies. Diffusion tensor imaging (DTI) constitutes one of the most sensitive techniques for the detection and characterization of brain related pathological processes and allows also the reconstruction of WM fibers. The analysis of spatial and temporal pathological changes along the fibers are thus possible by merging quantitative maps with structural information provided by DTI. In this work, we present a new genetic algorithm (GA) based method to analyze longitudinal changes occurring along WM fiber-bundles. In the first part of this paper, we describe the data processing pipeline, including data registration and fiber tract post-processing. In the second part, we focus our attention to the description of our GA model. In the last part, we show the tests we performed on simulated and real MS longitudinal data. Our method reached a high level of precision, recall and F-Measure in the detection of longitudinal pathological alterations occurring along different WM fiber-bundles.
authors.affiliation: CREATIS CNRS UMR5220 & INSERM U1044, Université de Lyon, Université Claude Bernard-Lyon 1, INSA-Lyon, Villeurbanne, France; Service de Neurologie A, Hôpital Neurologique, Hospices Civils de Lyon, Bron, France.
authors.forename: Claudio
authors.initials: C
authors.lastname: Stamile
authors.affiliation: CREATIS CNRS UMR5220 & INSERM U1044, Université de Lyon, Université Claude Bernard-Lyon 1, INSA-Lyon, Villeurbanne, France; Service de Neurologie A, Hôpital Neurologique, Hospices Civils de Lyon, Bron, France.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Kocevar
authors.affiliation: CREATIS CNRS UMR5220 & INSERM U1044, Université de Lyon, Université Claude Bernard-Lyon 1, INSA-Lyon, Villeurbanne, France; Service de Radiologie, Centre Hospitalier Lyon-Sud, Hospices Civils de Lyon, Pierre-Bénite, France.
authors.forename: François
authors.initials: F
authors.lastname: Cotton
authors.affiliation: CREATIS CNRS UMR5220 & INSERM U1044, Université de Lyon, Université Claude Bernard-Lyon 1, INSA-Lyon, Villeurbanne, France; CERMEP - Imagerie du Vivant, Université de Lyon, Bron, France. Electronic address: dominique.sappey-marinier@univ-lyon1.fr.
authors.forename: Dominique
authors.initials: D
authors.lastname: Sappey-Marinier
mesh_terms: D000328:Adult; D000465:Algorithms; D056324:Diffusion Tensor Imaging / Q000379:methods*; D018450:Disease Progression; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D009103:Multiple Sclerosis / Q000000981:diagnostic imaging* / Q000473:pathology; D009413:Nerve Fibers, Myelinated / Q000473:pathology; D066127:White Matter / Q000000981:diagnostic imaging* / Q000473:pathology
keywords: Diffusion tensor imaging; Genetic algorithm; Longitudinal study; MRI; Multiple sclerosis; White matter fiber-bundles