Partial volume-aware assessment of multiple sclerosis lesions.

Détails

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Etat: Public
Version: Final published version
Licence: CC BY-NC-ND 4.0
ID Serval
serval:BIB_C921F4A494E4
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Partial volume-aware assessment of multiple sclerosis lesions.
Périodique
NeuroImage. Clinical
Auteur(s)
Fartaria M.J., Todea A., Kober T., O'brien K., Krueger G., Meuli R., Granziera C., Roche A., Bach Cuadra M.
ISSN
2213-1582 (Electronic)
ISSN-L
2213-1582
Statut éditorial
Publié
Date de publication
2018
Peer-reviewed
Oui
Volume
18
Pages
245-253
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
White-matter lesion count and volume estimation are key to the diagnosis and monitoring of multiple sclerosis (MS). Automated MS lesion segmentation methods that have been proposed in the past 20 years reach their limits when applied to patients in early disease stages characterized by low lesion load and small lesions. We propose an algorithm to automatically assess MS lesion load (number and volume) while taking into account the mixing of healthy and lesional tissue in the image voxels due to partial volume effects. The proposed method works on 3D MPRAGE and 3D FLAIR images as obtained from current routine MS clinical protocols. The method was evaluated and compared with manual segmentation on a cohort of 39 early-stage MS patients with low disability, and showed higher Dice similarity coefficients (median DSC = 0.55) and higher detection rate (median DR = 61%) than two widely used methods (median DSC = 0.50, median DR < 45%) for automated MS lesion segmentation. We argue that this is due to the higher performance in segmentation of small lesions, which are inherently prone to partial volume effects.
Mots-clé
Adult, Brain/diagnostic imaging, Brain/pathology, Female, Humans, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis/diagnostic imaging, Multiple Sclerosis/pathology, White Matter/diagnostic imaging, White Matter/pathology, Young Adult, Lesion segmentation, MRI, Multiple sclerosis, Partial volume
Pubmed
Web of science
Open Access
Oui
Création de la notice
15/06/2018 16:37
Dernière modification de la notice
20/08/2019 15:44
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