Jessica Burggraaff1, Yao Liu2, Juan C Prieto3, Jorge Simoes4, Alexandra de Sitter5, Serena Ruggieri6, Iman Brouwer7, Birgit I Lissenberg-Witte8, Mara A Rocca9, Paola Valsasina10, Stefan Ropele11, Claudio Gasperini12, Antonio Gallo13, Deborah Pareto14, Jaume Sastre-Garriga15, Christian Enzinger16, Massimo Filippi17, Nicola De Stefano18, Olga Ciccarelli19, Hanneke E Hulst20, Mike P Wattjes21, Frederik Barkhof22, Bernard M J Uitdehaag23, Hugo Vrenken24, Charles R G Guttmann25. 1. Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. Electronic address: j.burggraaff@amsterdamumc.nl. 2. Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. Electronic address: yaouliu80@163.com. 3. Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 1249 Boylston Street, Boston, MA 02215, USA. Electronic address: juanprietob@gmail.com. 4. Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. Electronic address: jp.simoes@live.com. 5. Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. Electronic address: a.desitter@amsterdamumc.nl. 6. Department 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, Italy. Electronic address: serena.ruggieri@gmail.com. 7. Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. Electronic address: i.brouwer2@amsterdamumc.nl. 8. Department of Epidemiology and Biostatistics, Amsterdam UMC, Location VUmc, De Boelelaan 1089a, 1081 HV Amsterdam, the Netherlands. Electronic address: b.lissenberg@amsterdamumc.nl. 9. Neuroimaging 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. Electronic address: rocca.mara@hsr.it. 10. Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, San Raffaele Scientific Institute, Via Olgettina, 58, 20132 Milano MI, Italy. Electronic address: valsasina.paola@hsr.it. 11. Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria. Electronic address: stefan.ropele@medunigraz.at. 12. Department of Neurosciences, San Camillo Forlanini Hospital, Circonvallazione Gianicolense, 87, 00152 Roma RM, Italy. Electronic address: c.gasperini@libero.it. 13. 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. Electronic address: antonio.gallo@unicampania.it. 14. Section 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, Spain. Electronic address: deborah.pareto.idi@gencat.cat. 15. Department of Neurology, University Hospital iValld'Hebron, Autonomous University of Barcelona, Passeig de la Vall d'Hebron 119-129, 08035 Barcelona, Spain. Electronic address: jsastre-garriga@cem-cat.org. 16. Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria. Electronic address: chris.enzinger@medunigraz.at. 17. Neuroimaging 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 (14)Vita-Salute San Raffaele University, Via Olgettina, 58, 20132 Milano, MI, Italy; Department of Neurological and Behavioural Sciences, University of Siena, 53100 Siena SI, Italy. Electronic address: filippi.massimo@hsr.it. 18. Department of Neurological and Behavioural Sciences, University of Siena, 53100 Siena SI, Italy. Electronic address: destefano@unisi.it. 19. Department of Neuroinflammation UCL, Queen Square Institute of Neurology UCL, Queen Square, London WC1N 3BG, United Kingdom. Electronic address: o.ciccarelli@ucl.ac.uk. 20. Department 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 Netherlands. Electronic address: he1.hulst@vumc.nl. 21. Department 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, Germany. Electronic address: Wattjes.Mike@mh-hannover.de. 22. Department 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 Kingdom. Electronic address: f.barkhof@amsterdamumc.nl. 23. Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. Electronic address: bmj.uitdehaag@amsterdamumc.nl. 24. Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. Electronic address: h.vrenken@amsterdamumc.nl. 25. Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 1249 Boylston Street, Boston, MA 02215, USA. Electronic address: guttmann@bwh.harvard.edu.
Abstract
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.
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.
Authors: Thomas Williams; Carmen Tur; Arman Eshaghi; Anisha Doshi; Dennis Chan; Sophie Binks; Henny Wellington; Amanda Heslegrave; Henrik Zetterberg; Jeremy Chataway Journal: Mult Scler Date: 2022-08-09 Impact factor: 5.855