Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study
Background and rationale: 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 f...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-01-01
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| Series: | NeuroImage: Clinical |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158220303867 |
| _version_ | 1818611848430223360 |
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| author | Jessica Burggraaff Yao Liu Juan C. Prieto Jorge Simoes Alexandra de Sitter Serena Ruggieri Iman Brouwer Birgit I. Lissenberg-Witte Mara A. Rocca Paola Valsasina Stefan Ropele Claudio Gasperini Antonio Gallo Deborah Pareto Jaume Sastre-Garriga Christian Enzinger Massimo Filippi Nicola De Stefano Olga Ciccarelli Hanneke E. Hulst Mike P. Wattjes Frederik Barkhof Bernard M.J. Uitdehaag Hugo Vrenken Charles R.G. Guttmann |
| author_facet | Jessica Burggraaff Yao Liu Juan C. Prieto Jorge Simoes Alexandra de Sitter Serena Ruggieri Iman Brouwer Birgit I. Lissenberg-Witte Mara A. Rocca Paola Valsasina Stefan Ropele Claudio Gasperini Antonio Gallo Deborah Pareto Jaume Sastre-Garriga Christian Enzinger Massimo Filippi Nicola De Stefano Olga Ciccarelli Hanneke E. Hulst Mike P. Wattjes Frederik Barkhof Bernard M.J. Uitdehaag Hugo Vrenken Charles R.G. Guttmann |
| author_sort | Jessica Burggraaff |
| collection | DOAJ |
| description | Background and rationale: 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. Methods: 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. Results: 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. Conclusion: 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. |
| first_indexed | 2024-12-16T15:36:51Z |
| format | Article |
| id | doaj.art-f2ede02938334165a2f7c4caea4c0296 |
| institution | Directory Open Access Journal |
| issn | 2213-1582 |
| language | English |
| last_indexed | 2024-12-16T15:36:51Z |
| publishDate | 2021-01-01 |
| publisher | Elsevier |
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| series | NeuroImage: Clinical |
| spelling | doaj.art-f2ede02938334165a2f7c4caea4c02962022-12-21T22:26:09ZengElsevierNeuroImage: Clinical2213-15822021-01-0129102549Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter studyJessica Burggraaff0Yao Liu1Juan C. Prieto2Jorge Simoes3Alexandra de Sitter4Serena Ruggieri5Iman Brouwer6Birgit I. Lissenberg-Witte7Mara A. Rocca8Paola Valsasina9Stefan Ropele10Claudio Gasperini11Antonio Gallo12Deborah Pareto13Jaume Sastre-Garriga14Christian Enzinger15Massimo Filippi16Nicola De Stefano17Olga Ciccarelli18Hanneke E. Hulst19Mike P. Wattjes20Frederik Barkhof21Bernard M.J. Uitdehaag22Hugo Vrenken23Charles R.G. Guttmann24Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands; Corresponding author.Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The NetherlandsCenter for Neurological Imaging, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, 1249 Boylston Street, Boston, MA 02215, USADepartment of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The NetherlandsDepartment of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The NetherlandsDepartment of Human Neurosciences, “Sapienza” University of Rome, Piazzale Aldo Moro, 5, 00185 Roma RM, Italy; Department of Neurosciences, San Camillo Forlanini Hospital, Circonvallazione Gianicolense, 87, 00152 Roma RM, ItalyDepartment of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The NetherlandsDepartment of Epidemiology and Biostatistics, Amsterdam UMC, Location VUmc, De Boelelaan 1089a, 1081 HV Amsterdam, the NetherlandsNeuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, San Raffaele Scientific Institute, Via Olgettina, 58, 20132 Milano MI, Italy; Neurology Unit, San Raffaele Scientific Institute, Via Olgettina, 58, 20132 Milano MI, ItalyNeuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, San Raffaele Scientific Institute, Via Olgettina, 58, 20132 Milano MI, ItalyDepartment of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, AustriaDepartment of Neurosciences, San Camillo Forlanini Hospital, Circonvallazione Gianicolense, 87, 00152 Roma RM, ItalyDivision 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, ItalySection of Neuroradiology and MRI Unit, Department of Radiology, University Hospital iValld’Hebron, Autonomous University of Barcelona, Passeig de la Vall d'Hebron 119-129, 08035 Barcelona, SpainDepartment of Neurology, University Hospital iValld’Hebron, Autonomous University of Barcelona, Passeig de la Vall d'Hebron 119-129, 08035 Barcelona, SpainDivision of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, AustriaNeuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, San Raffaele Scientific Institute, Via Olgettina, 58, 20132 Milano MI, Italy; Neurology Unit, San Raffaele Scientific Institute, Via Olgettina, 58, 20132 Milano MI, Italy; Neurophysiology Unit, San Raffaele Scientific Institute, and 14Vita-Salute San Raffaele University, Via Olgettina, 58, 20132 Milano, MI, Italy; Department of Neurological and Behavioural Sciences, University of Siena, 53100 Siena SI, ItalyDepartment of Neurological and Behavioural Sciences, University of Siena, 53100 Siena SI, ItalyDepartment of Neuroinflammation UCL, Queen Square Institute of Neurology UCL, Queen Square, London WC1N 3BG, United KingdomDepartment of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1108, P.O. Box 7057, 1007 MB, Amsterdam, The NetherlandsDepartment of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands; Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Carl-Neuberg-Straße, 30625 Hannover, GermanyDepartment of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands; Institutes of Neurology & Healthcare Engineering, UCL, 235 Euston Rd, Bloomsbury, London NW1 2BU, United KingdomDepartment of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The NetherlandsDepartment of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The NetherlandsCenter for Neurological Imaging, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, 1249 Boylston Street, Boston, MA 02215, USABackground and rationale: 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. Methods: 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. Results: 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. Conclusion: 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.http://www.sciencedirect.com/science/article/pii/S2213158220303867Multiple SclerosisMRICognitionThalamusDeep grey matterAtrophy |
| spellingShingle | Jessica Burggraaff Yao Liu Juan C. Prieto Jorge Simoes Alexandra de Sitter Serena Ruggieri Iman Brouwer Birgit I. Lissenberg-Witte Mara A. Rocca Paola Valsasina Stefan Ropele Claudio Gasperini Antonio Gallo Deborah Pareto Jaume Sastre-Garriga Christian Enzinger Massimo Filippi Nicola De Stefano Olga Ciccarelli Hanneke E. Hulst Mike P. Wattjes Frederik Barkhof Bernard M.J. Uitdehaag Hugo Vrenken Charles R.G. Guttmann Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study NeuroImage: Clinical Multiple Sclerosis MRI Cognition Thalamus Deep grey matter Atrophy |
| title | Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study |
| title_full | Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study |
| title_fullStr | Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study |
| title_full_unstemmed | Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study |
| title_short | Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study |
| title_sort | manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis a multicenter study |
| topic | Multiple Sclerosis MRI Cognition Thalamus Deep grey matter Atrophy |
| url | http://www.sciencedirect.com/science/article/pii/S2213158220303867 |
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