Development and evaluation of a manual segmentation protocol for deep grey matter in multiple sclerosis : Towards accelerated semi-automated references
de Sitter, Alexandra (MS Center Amsterdam)
Burggraaff, Jessica (MS Center Amsterdam)
Bartel, Fabian (MS Center Amsterdam)
Palotai, Miklos (Harvard Medical School)
Liu, Yaou (MS Center Amsterdam)
Simoes, Jorge (MS Center Amsterdam)
Ruggieri, Serena (San Camillo Forlanini Hospital)
Schregel, Katharina (University Medical Center Goettingen)
Ropele, Stefan (Medical University of Graz)
Rocca, Maria A. (San Raffaele Scientific Institute)
Gasperini, Claudio (San Camillo Forlanini Hospital)
Gallo, Antonio (University of Campania "Luigi Vanvitelli", Naples)
Schoonheim, Menno M. (Amsterdam UMC)
Amann, Michael (University Hospital Basel (Basilea, Suïssa))
Yiannakas, Marios (UCL Institute of Neurology (Regne Unit))
Pareto, Deborah (Hospital Universitari Vall d'Hebron)
Wattjes, Mike P. (Hannover Medical School)
Sastre-Garriga, Jaume (Hospital Universitari Vall d'Hebron)
Kappos, Ludwig (University Hospital Basel (Basilea, Suïssa))
Filippi, Massimo (Vita-Salute San Raffaele University)
Enzinger, Christian (Medical University of Graz)
Frederiksen, Jette (Glostrup University Hospital Copenhagen)
Uitdehaag, Bernard (MS Center Amsterdam)
Guttmann, Charles R. G. (Harvard Medical School)
Barkhof, Frederik (Institutes of Neurology & Healthcare Engineering, London)
Vrenken, Hugo (Amsterdam UMC)
Universitat Autònoma de Barcelona

Date:	2021
Abstract:	Deep grey matter (dGM) structures, particularly the thalamus, are clinically relevant in multiple sclerosis (MS). However, segmentation of dGM in MS is challenging; labeled MS-specific reference sets are needed for objective evaluation and training of new methods. This study aimed to (i) create a standardized protocol for manual delineations of dGM; (ii) evaluate the reliability of the protocol with multiple raters; and (iii) evaluate the accuracy of a fast-semi-automated segmentation approach (FASTSURF). A standardized manual segmentation protocol for caudate nucleus, putamen, and thalamus was created, and applied by three raters on multi-center 3D T1-weighted MRI scans of 23 MS patients and 12 controls. Intra- and inter-rater agreement was assessed through intra-class correlation coefficient (ICC); spatial overlap through Jaccard Index (JI) and generalized conformity index (CIgen). From sparse delineations, FASTSURF reconstructed full segmentations; accuracy was assessed both volumetrically and spatially. All structures showed excellent agreement on expert manual outlines: intra-rater JI > 0. 83; inter-rater ICC ≥ 0. 76 and CIgen ≥ 0. 74. FASTSURF reproduced manual references excellently, with ICC ≥ 0. 97 and JI ≥ 0. 92. The manual dGM segmentation protocol showed excellent reproducibility within and between raters. Moreover, combined with FASTSURF a reliable reference set of dGM segmentations can be produced with lower workload.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Multiple Sclerosis ; MRI ; Deep grey matter ; Atrophy ; Segmentation ; Reference set
Published in:	NeuroImage, Vol. 30 (april 2021) , ISSN 2213-1582

DOI: 10.1016/j.nicl.2021.102659
PMID: 33882422

8 p, 2.0 MB

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