Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis : A multicenter study
Burggraaff, Jessica (Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands)
Liu, Yao (Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands)
Prieto, Juan C. (Harvard Medical School)
Simoes, Jorge (Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands)
de Sitter, Alexandra (Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands)
Ruggieri, Serena (San Camillo Forlanini Hospital)
Brouwer, Iman (Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands)
Lissenberg-Witte, Birgit I. (Department of Epidemiology and Biostatistics, Amsterdam UMC, Location VUmc, De Boelelaan 1089a, 1081 HV Amsterdam, the Netherlands)
Rocca, Mara A. (Neurology Unit, San Raffaele Scientific Institute, Via Olgettina, 58, 20132 Milano MI, Italy)
Valsasina, Paola (Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, San Raffaele Scientific Institute, Via Olgettina, 58, 20132 Milano MI, Italy)
Ropele, Stefan (Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria)
Gasperini, Claudio (San Camillo Forlanini Hospital)
Gallo, Antonio (Division of Neurology and 3T MRI Research Center, Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Viale Abramo Lincoln, 5, 81100 Caserta, CE, Napoli, Italy)
Pareto, Deborah (Hospital Universitari Vall d'Hebron)
Sastre-Garriga, Jaume (Hospital Universitari Vall d'Hebron)
Enzinger, Christian (Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria)
Filippi, Massimo (Department of Neurological and Behavioural Sciences, University of Siena, 53100 Siena SI, Italy)
De Stefano, Nicola (Department of Neurological and Behavioural Sciences, University of Siena, 53100 Siena SI, Italy)
Ciccarelli, Olga (UCL Institute of Neurology (Regne Unit))
Hulst, Hanneke E. (Amsterdam UMC. University Medical Center)
Wattjes, Mike P. (Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Carl-Neuberg-Straße, 30625 Hannover, Germany)
Barkhof, Frederik (Institutes of Neurology & Healthcare Engineering, UCL, 235 Euston Rd, Bloomsbury, London NW1 2BU, United Kingdom)
Uitdehaag, Bernard M. J. (Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands)
Vrenken, Hugo (Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands)
Guttmann, Charles R. G. (Harvard Medical School)
Universitat Autònoma de Barcelona

Date:	2020
Abstract:	Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ ρ =(-0. 42)-(-0. 76); p- values < 0. 001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0. 23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings.
Grants:	Instituto de Salud Carlos III PI18/00823
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 ; Cognition ; Thalamus ; Deep grey matter ; Atrophy ; Segmentation ; BRB-N, Brief Repeatable Battery of Neuropsychological Tests ; CAT12, Computational Anatomy Toolbox for Statistical Parametric Mapping 12 ; CI, cognitively impaired and preserved (CP) ; CII, cognitive impairment index ; CNR, contrast-to-noise ratio ; CP, cognitively preserved ; EDSS, Expanded Disability Status Scale ; Etiv, estimated total intracranial volume ; FSL-FIRST, FMRIB Integrated Registration and Segmentation Tool ; GIF, Geodesic Information Flows ; GM, grey matter ; GMV, grey matter volume ; ICC, intraclass correlation coefficient ; MS, Multiple Sclerosis ; NBV, Normalized brain volume ; NGMV, Normalized grey matter volume ; NWMV, Normalized white matter volume ; IPS, information processing speed ; HC, healthy control ; PASAT, Paced Auditory Serial Addition Test ; RRMS, Relapsing-Remitting Multiple Sclerosis ; SD, standard deviations ; SDMT, Symbol Digit Modalities Test ; SPM12, Statistical Parametric Mapping 12 ; SRT, Selective Reminding Test ; 10/36 SRT, 10/36 Spatial Recall Test ; WCST, Wisconsin Card Sorting Test ; WLG, Word List Generation ; WM, white matter ; WMV, white matter volume ; VolBrain, MRI Brain Volumetry System
Published in:	NeuroImage, Vol. 29 (december 2020) , ISSN 2213-1582

DOI: 10.1016/j.nicl.2020.102549
PMID: 33401136

12 p, 3.1 MB

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