TY - JOUR

T1 - Development and evaluation of a manual segmentation protocol for deep grey matter in multiple sclerosis

T2 - Towards accelerated semi-automated references

AU - de Sitter, Alexandra

AU - Burggraaff, Jessica

AU - Bartel, Fabian

AU - Palotai, Miklos

AU - Liu, Yaou

AU - Simoes, Jorge

AU - Ruggieri, Serena

AU - Schregel, Katharina

AU - Ropele, Stefan

AU - Rocca, Maria A.

AU - Gasperini, Claudio

AU - Gallo, Antonio

AU - Schoonheim, Menno M.

AU - Amann, Michael

AU - Yiannakas, Marios

AU - Pareto, Deborah

AU - Wattjes, Mike P.

AU - Sastre-Garriga, Jaume

AU - Kappos, Ludwig

AU - Filippi, Massimo

AU - Enzinger, Christian

AU - Frederiksen, Jette

AU - Uitdehaag, Bernard

AU - Guttmann, Charles R.G.

AU - Barkhof, Frederik

AU - Vrenken, Hugo

N1 - Publisher Copyright: © 2021 The Authors

PY - 2021

Y1 - 2021

N2 - Background: 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. Objectives: 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). Methods: 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. Results: 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. Conclusions: 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.

AB - Background: 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. Objectives: 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). Methods: 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. Results: 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. Conclusions: 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.

KW - Atrophy

KW - Deep grey matter

KW - MRI

KW - Multiple Sclerosis

KW - Reference set

KW - Segmentation

U2 - 10.1016/j.nicl.2021.102659

DO - 10.1016/j.nicl.2021.102659

M3 - Journal article

C2 - 33882422

AN - SCOPUS:85104345552

VL - 30

JO - NeuroImage: Clinical

JF - NeuroImage: Clinical

SN - 2213-1582

M1 - 102659

ER -