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[FG] Granziera Cristina

Publications

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Burguet Villena, Federico et al. (2025) ‘Retinal neuronal loss and progression independent of relapse activity in multiple sclerosis’, Journal of Neurology, 272. Available at: https://doi.org/10.1007/s00415-025-13185-y.

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Damiano, Marastoni et al. (2025) ‘Intrathecal Inflammatory Profile and Gray Matter Damage Predict Progression Independent of Relapse Activity in Early Multiple Sclerosis’, Neurol Neuroimmunol Neuroinflamm . , 12(4), p. e200399. Available at: https://doi.org/10.1212/NXI.0000000000200399.

Cagol, A. and Rovira, À. (2025) ‘Reinforcing the evidence framework for paramagnetic rim lesions in MS: Advancing toward broad clinical integration’, Multiple Sclerosis Journal [Preprint]. Available at: https://doi.org/10.1177/13524585251349971.

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Cagol, A. and Granziera, C. (2025) ‘Rethinking Multiple Sclerosis Diagnosis’, Neurology Open Access, 1(2). Available at: https://doi.org/10.1212/wn9.0000000000000021.

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Iaquinto, Stefania et al. (2025) ‘Confirmed Worsening of Health-Related Quality of Life to Monitor Long-Term MS Disease Progression: A Longitudinal Analysis From the Swiss Multiple Sclerosis Registry’, European Journal of Neurology, 32. Available at: https://doi.org/10.1111/ene.70230.

Martina, Greselin et al. (2025) ‘AI-assisted identification of disability patterns within identical EDSS grades’, Mult Scler ., 31(6), pp. 677–688. Available at: https://doi.org/10.1177/13524585251327300.

Géraldine, Androdias et al. (2025) ‘De-escalating and discontinuing disease-modifying therapies in multiple sclerosis’, Brain ., 148(5), pp. 1459–1478. Available at: https://doi.org/10.1093/brain/awae409.

Greselin, Martina et al. (2025) ‘AI-assisted identification of disability patterns within identical EDSS grades’, Multiple Sclerosis Journal, 31, pp. 677–688. Available at: https://doi.org/10.1177/13524585251327300.

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David R, van Nederpelt et al. (2025) ‘User requirements for quantitative radiological reports in multiple sclerosis’, Eur Radiol ., Online ahead of print. Available at: https://doi.org/10.1007/s00330-025-11544-x.

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Ocampo-Pineda, M. et al. (2025) ‘White Matter Tract Degeneration in Multiple Sclerosis Patients With Progression Independent of Relapse Activity’, Neurology: Neuroimmunology and NeuroInflammation, 12(3). Available at: https://doi.org/10.1212/NXI.0000000000200388.

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Riccardo Galbusera et al. (2025) ‘Quantitative T1 is sensitive to cortical remyelination in multiple sclerosis: A postmortem MRI study’, Brain Pathol . , p. e70010. Available at: https://doi.org/10.1111/bpa.70010 .

Kaminska, Karolina et al. (2025) ‘Bi-allelic variants in three genes encoding distinct subunits of the vesicular AP-5 complex cause hereditary macular dystrophy’, American Journal of Human Genetics, 112(4), pp. 808–828. Available at: https://doi.org/10.1016/j.ajhg.2025.02.015.

Bédard, S. et al. (2025) ‘Towards contrast-agnostic soft segmentation of the spinal cord’, Medical Image Analysis, 101, p. 103473. Available at: https://doi.org/10.1016/j.media.2025.103473.

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Lukasz Kolakowski, Katarina Alexandra Ebner and Athina Papadopoulou (2025) ‘Headache and Facial Pain in Multiple Sclerosis: A Narrative Review’, Clinical and translational neuroscience [Preprint]. Available at: https://doi.org/10.3390/ctn9010016.

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Elisabeth A, Kappos et al. (2025) ‘The LYMPH trial: comparing microsurgical with conservative treatment for chronic breast cancer-associated lymphoedema - study protocol of a pragmatic randomised international multicentre superiority trial’, BMJ Open . , 15(2), p. e090662. Available at: https://doi.org/10.1136/bmjopen-2024-090662.

Benno Gesierich et al. (2025) ‘Extended Technical and Clinical Validation of Deep Learning-Based Brainstem Segmentation for Application in Neurodegenerative Diseases’, Hum Brain Mapp ., 46(3), p. e70141. Available at: https://doi.org/10.1002/hbm.70141.

Gordaliza, P.M. et al. (2025) ‘Fluid and White Matter Suppression Contrasts MRI Improves Deep Learning Detection of Multiple Sclerosis Cortical Lesions’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2025.01.19.25320792.

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Benkert, Pascal et al. (2025) ‘Serum Glial Fibrillary Acidic Protein and Neurofilament Light Chain Levels Reflect Different Mechanisms of Disease Progression under B-Cell Depleting Treatment in Multiple Sclerosis’, Annals of Neurology, 97(1), pp. 104–115. Available at: https://doi.org/10.1002/ana.27096.

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Disanto, Giulio et al. (2025) ‘Treatment persistence and clinical outcomes in patients starting B cell depleting therapies within the Swiss MS Cohort’, Multiple Sclerosis Journal - Experimental, Translational and Clinical, 11(1). Available at: https://doi.org/10.1177/20552173251315457.

Durrer, Alicia et al. (2025) ‘Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Marrakesh, Morocco: Springer Science and Business Media Deutschland GmbH (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ), pp. 87–97. Available at: https://doi.org/10.1007/978-3-031-72744-3_9.

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Molchanova, Nataliia et al. (2025) ‘Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation’, Computers in Biology and Medicine, 184. Available at: https://doi.org/10.1016/j.compbiomed.2024.109336.

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Müller, Jannis et al. (2025) ‘Standardized Definition of Progression Independent of Relapse Activity (PIRA) in Relapsing-Remitting Multiple Sclerosis’, JAMA Neurology [Preprint]. Available at: https://doi.org/10.1001/jamaneurol.2025.0495.

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Sanabria-Diaz, Gretel et al. (2025) ‘Advanced MRI Measures of Myelin and Axon Volume Identify Repair in Multiple Sclerosis’, Annals of Neurology, 97(1), pp. 134–148. Available at: https://doi.org/10.1002/ana.27102.

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Spagnolo, F. et al. (2025) ‘Exploiting XAI Maps to Improve MS Lesion Segmentation and Detection in MRI’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Cham: Springer Science and Business Media Deutschland GmbH (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ), pp. 121–131. Available at: https://doi.org/10.1007/978-3-031-77610-6_12.

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Yaldizli, Özgür et al. (2025) ‘Personalized treatment decision algorithms for the clinical application of serum neurofilament light chain in multiple sclerosis: A modified Delphi Study’, Multiple Sclerosis Journal [Preprint]. Available at: https://doi.org/10.1177/13524585251335466.

Barakovic, Muhamed et al. (2024) ‘A novel imaging marker of cortical “cellularity” in multiple sclerosis patients’, Scientific Reports, 14(1). Available at: https://doi.org/10.1038/s41598-024-60497-6.

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Janiaud, Perrine et al. (2024) ‘MultiSCRIPT-Cycle 1—a pragmatic trial embedded within the Swiss Multiple Sclerosis Cohort (SMSC) on neurofilament light chain monitoring to inform personalized treatment decisions in multiple sclerosis: a study protocol for a randomized clinical trial’, Trials, 25(1). Available at: https://doi.org/10.1186/s13063-024-08454-6.

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Weigel, M. et al. (2024) ‘Feasibility of interleaved multislice averaged magnetization inversion-recovery acquisitions of the spinal cord’, Magnetic Resonance in Medicine, 92(6), pp. 2588–2595. Available at: https://doi.org/10.1002/mrm.30223.

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Pontillo, Giuseppe et al. (2024) ‘Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap’, Neurology, 103(10). Available at: https://doi.org/10.1212/WNL.0000000000209976.

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Scalfari, Antonio et al. (2024) ‘Smouldering-Associated Worsening in Multiple Sclerosis: An International Consensus Statement on Definition, Biology, Clinical Implications, and Future Directions’, Annals of Neurology, 96(5), pp. 826–845. Available at: https://doi.org/10.1002/ana.27034.

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Gordaliza, P.M. et al. (2024) ‘Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2024.09.17.613272.

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Cagol, Alessandro et al. (2024) ‘Advanced Quantitative MRI Unveils Microstructural Thalamic Changes Reflecting Disease Progression in Multiple Sclerosis’, Neurology: Neuroimmunology and NeuroInflammation, 11(6). Available at: https://doi.org/10.1212/NXI.0000000000200299.

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Rocca, Maria A. et al. (2024) ‘Current and future role of MRI in the diagnosis and prognosis of multiple sclerosis’, The Lancet Regional Health - Europe, 44. Available at: https://doi.org/10.1016/j.lanepe.2024.100978.

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Wendebourg, Maria Janina et al. (2024) ‘The Lateral Corticospinal Tract Sign: An MRI Marker for Amyotrophic Lateral Sclerosis’, Radiology, 312(3). Available at: https://doi.org/10.1148/radiol.231630.

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Müller, Jannis et al. (2024) ‘Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions’, Neurology, 103(6). Available at: https://doi.org/10.1212/WNL.0000000000209604.

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Spagnolo, F. et al. (2024) ‘Exploiting XAI maps to improve MS lesion segmentation and detection in MRI’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2024.08.29.610090.

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Schoenholzer, Kean et al. (2024) ‘Hemimacular Thinning Due to Lesions in the Lateral Geniculate Nucleus in 2 Patients with Neuroinflammatory Diseases’, Neurology: Neuroimmunology and NeuroInflammation, 11(6). Available at: https://doi.org/10.1212/NXI.0000000000200297.

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Sastre-Garriga, J. et al. (2024) ‘Value of Optic Nerve MRI in Multiple Sclerosis Clinical Management’, Neurology, 103(3). Available at: https://doi.org/10.1212/wnl.0000000000209677.

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Cagol, Alessandro, Tsagkas, Charidimos and Granziera, Cristina (2024) ‘Advanced Brain Imaging in Central Nervous System Demyelinating Diseases’, Neuroimaging Clinics of North America, 34(3), pp. 335–357. Available at: https://doi.org/10.1016/j.nic.2024.03.003.

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Graber, M. et al. (2024) ‘Recommendations for the Treatment of Multiple Sclerosis in Family Planning, Pregnancy and Lactation in Switzerland: Immunotherapy’, Clinical and Translational Neuroscience, 8(3), p. 26. Available at: https://doi.org/10.3390/ctn8030026.

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Moura, João et al. (2024) ‘Emerging imaging markers in radiologically isolated syndrome: implications for earlier treatment initiation’, Neurological Sciences, 45(7), pp. 3061–3068. Available at: https://doi.org/10.1007/s10072-024-07402-1.

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Schuchardt, F.F. et al. (2024) ‘Clinical value of neuroimaging indicators of intracranial hypertension in patients with cerebral venous thrombosis’, Neuroradiology, 66(7), pp. 1161–1176. Available at: https://doi.org/10.1007/s00234-024-03363-6.

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Ciccarelli, O. et al. (2024) ‘Using the Progression Independent of Relapse Activity Framework to Unveil the Pathobiological Foundations of Multiple Sclerosis’, Neurology, 103(1). Available at: https://doi.org/10.1212/WNL.0000000000209444.

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Hirt, Julian et al. (2024) ‘Clinical trial evidence of quality-of-life effects of disease-modifying therapies for multiple sclerosis: a systematic analysis’, Journal of Neurology, 271(6), pp. 3131–3141. Available at: https://doi.org/10.1007/s00415-024-12366-5.

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Wendebourg, Maria Janina et al. (2024) ‘Cervical and thoracic spinal cord gray matter atrophy is associated with disability in patients with amyotrophic lateral sclerosis’, European Journal of Neurology, 31(6). Available at: https://doi.org/10.1111/ene.16268.

Wendebourg, Maria Janina et al. (2024) ‘Cervical and thoracic spinal cord gray matter atrophy is associated with disability in patients with amyotrophic lateral sclerosis’, European Journal of Neurology, 31(6). Available at: https://doi.org/10.1111/ene.16268.

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Müller, Jannis et al. (2024) ‘Escalating to medium- versus high-efficacy disease modifying therapy after low-efficacy treatment in relapsing remitting multiple sclerosis’, Brain and Behavior, 14(5). Available at: https://doi.org/10.1002/brb3.3498.

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Papadopoulou, Athina et al. (2024) ‘Visual evoked potentials in multiple sclerosis: P100 latency and visual pathway damage including the lateral geniculate nucleus’, Clinical Neurophysiology. 20.02.2024, 161, pp. 122–132. Available at: https://doi.org/10.1016/j.clinph.2024.02.020.

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Weigel, M. et al. (2024) ‘Cerebellar Ex Vivo Magnetic Resonance Imaging at its Feasibility Limit: Up to 77-Microns Isotropic Resolution using Low-Bandwidth Balanced Steady State Free Precession (LoBa-bSSFP) Sequences and 3T Standard Equipment’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2024.04.18.589707.

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Christensen, R.H. et al. (2024) ‘Differences in Cortical Morphology in People With and Without Migraine A Registry for Migraine (REFORM) MRI Study’, Neurology, 102(9). Available at: https://doi.org/10.1212/WNL.0000000000209305.

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Hirt, Julian et al. (2024) ‘Use of pragmatic randomized trials in multiple sclerosis: A systematic overview’, Multiple Sclerosis Journal, 30(4-5), pp. 463–478. Available at: https://doi.org/10.1177/13524585231221938.

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Wenger, Antonia, Calabrese, Pasquale and Granziera, Cristina (2024) ‘Unraveling the cerebellum’s role in multiple sclerosis’, Current Opinion in Behavioral Sciences, 56. Available at: https://doi.org/10.1016/j.cobeha.2024.101357.

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Janiaud, Perrine et al. (2024) ‘MultiSCRIPT-Cycle 1- A Pragmatic trial embedded within the Swiss Multiple Sclerosis Cohort (SMSC) on neurofilament light chain monitoring to inform personalized treatment decisions in Multiple Sclerosis: a study protocol for a randomized clinical trial’, medRxiv [Preprint]. Cold Spring Harbor Laboratory (medRxiv). Available at: https://doi.org/10.1101/2024.03.22.24304720.

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Callegari, Ilaria et al. (2024) ‘Cell-binding IgM in CSF is distinctive of multiple sclerosis and targets the iron transporter SCARA5’, Brain, 147(3), pp. 839–848. Available at: https://doi.org/10.1093/brain/awad424.

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Federau, Christian et al. (2024) ‘Evaluation of the quality and the productivity of neuroradiological reading of multiple sclerosis follow-up MRI scans using an intelligent automation software’, Neuroradiology, 66(3), pp. 361–369. Available at: https://doi.org/10.1007/s00234-024-03293-3.

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Vermersch, P. et al. (2024) ‘Inhibition of CD40L with Frexalimab in Multiple Sclerosis’, New England Journal of Medicine, 390(7), pp. 589–600. Available at: https://doi.org/10.1056/NEJMoa2309439.

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Oechtering, Johanna et al. (2024) ‘Complement Activation Is Associated With Disease Severity in Multiple Sclerosis’, Neurology: Neuroimmunology and NeuroInflammation, 11(2). Available at: https://doi.org/10.1212/NXI.0000000000200212.

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Cagol, Alessandro et al. (2024) ‘Association of Spinal Cord Atrophy and Brain Paramagnetic Rim Lesions With Progression Independent of Relapse Activity in People With MS’, Neurology, 102(1). Available at: https://doi.org/10.1212/wnl.0000000000207768.

Chen, Xinjie (2024) Advanced magnetic resonance imaging in multiple sclerosis: disentangling aging and pathology effects. Doctoral Thesis. Universität Basel .

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Durrer, Alicia et al. (2024) ‘Denoising diffusion models for 3D healthy brain tissue inpainting’, in Medical Image Computing and Computer Assisted Interventions. Marrakesh (Medical Image Computing and Computer Assisted Interventions).

Granziera C (2024) ‘Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling’, bioRxiv [Preprint]. Available at: https://www.biorxiv.org/content/10.1101/2024.09.17.613272v1.

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Harrison, Daniel M. et al. (2024) ‘The use of 7T MRI in multiple sclerosis: review and consensus statement from the North American Imaging in Multiple Sclerosis Cooperative’, Brain Communications, 6(5). Available at: https://doi.org/10.1093/braincomms/fcae359.

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Iaquinto, Stefania et al. (2024) ‘Rising Prevalence of Multiple Sclerosis in Switzerland: Results from the Swiss Multiple Sclerosis Registry’, Neuroepidemiology [Preprint]. Available at: https://doi.org/10.1159/000542632.

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Mueller, Simon M. et al. (2024) ‘Serum Neurofilament Light Chain Levels Correlate With Skin Inflammation and Scratch Lesions in Patients With Pruritus’, Dermatologic Therapy, 2024. Available at: https://doi.org/10.1155/2024/3542876.

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Spagnolo, Federico et al. (2024) ‘Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study’, Frontiers in Neuroimaging, 3. Available at: https://doi.org/10.3389/fnimg.2024.1359589.

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Galbusera, Riccardo et al. (2023) ‘Characteristics, Prevalence, and Clinical Relevance of Juxtacortical Paramagnetic Rims in Patients With Multiple Sclerosis’, Neurology, 102(3), p. e207966. Available at: https://doi.org/10.1212/WNL.0000000000207966.

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Galbusera, Riccardo et al. (2023) ‘Characteristics, Prevalence, and Clinical Relevance of Juxtacortical Paramagnetic Rims in Patients With Multiple Sclerosis’, Neurology, 102(3). Available at: https://doi.org/10.1212/wnl.0000000000207966.

Abdelhak, Ahmed et al. (2023) ‘Neurofilament Light Chain Elevation and Disability Progression in Multiple Sclerosis’, JAMA Neurology, 80(12), pp. 1317–1325. Available at: https://doi.org/10.1001/jamaneurol.2023.3997.

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Müller, Jannis et al. (2023) ‘Comparative analysis of dimethyl fumarate and teriflunomide in relapsing–remitting multiple sclerosis’, European Journal of Neurology, 30(12), pp. 3809–3818. Available at: https://doi.org/10.1111/ene.16044.

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Woelfle, Tim et al. (2023) ‘Smartwatch-derived sleep and heart rate measures complement step counts in explaining established metrics of MS severity’, Multiple Sclerosis and Related Disorders, 80. Available at: https://doi.org/10.1016/j.msard.2023.105104.

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Müller, Jannis et al. (2023) ‘Harmonizing Definitions for Progression Independent of Relapse Activity inMultiple Sclerosis A Systematic Review’, JAMA Neurology, 80(11), pp. 1232–1245. Available at: https://doi.org/10.1001/jamaneurol.2023.3331.

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Cerdá-Fuertes, Nuria et al. (2023) ‘Optical coherence tomography versus other biomarkers: Associations with physical and cognitive disability in multiple sclerosis’, Multiple Sclerosis Journal, 29(13), pp. 1540–1550. Available at: https://doi.org/10.1177/13524585231198760.

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Galbusera, Riccardo et al. (2023) ‘Postmortem quantitative MRI disentangles histological lesion types in multiple sclerosis’, Brain Pathology, 33(6). Available at: https://doi.org/10.1111/bpa.13136.

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Abdelhak, Ahmed et al. (2023) ‘Serum neurofilament light chain reference database for individual application in paediatric care: a retrospective modelling and validation study’, The Lancet Neurology, 22(9), pp. 826–833. Available at: https://doi.org/10.1016/S1474-4422(23)00210-7.

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Damas J et al. (2023) ‘One for all, all for one: neuro-HIV multidisciplinary platform for the assessment and management of neurocognitive complaints in people living with HIV’, HIV Medicine, 24(6), pp. 738–748. Available at: https://doi.org/10.1111/hiv.13472.

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Tsagkas, Charidimos et al. (2023) ‘Anterior horn atrophy in the cervical spinal cord: A new biomarker in progressive multiple sclerosis’, Multiple Sclerosis Journal, 29(6), pp. 702–718. Available at: https://doi.org/10.1177/13524585221139152.

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Tsagkas, Charidimos et al. (2023) ‘Anterior horn atrophy in the cervical spinal cord: A new biomarker in progressive multiple sclerosis’, Multiple Sclerosis Journal, 29(6), pp. 702–718. Available at: https://doi.org/10.1177/13524585221139152.

Cagol A et al. (2023) ‘Optical coherence tomography reflects clinically relevant gray matter damage in patients with multiple sclerosis’, Journal of Neurology, 270(4), pp. 2139–2148. Available at: https://doi.org/10.1007/s00415-022-11535-8.

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Tsagkas, Charidimos et al. (2023) ‘Longitudinal assessment of cervical spinal cord compartments in multiple sclerosis’, Multiple Sclerosis and Related Disorders, 71, p. 104545. Available at: https://doi.org/10.1016/j.msard.2023.104545.

Tsagkas C et al. (2023) ‘Longitudinal assessment of cervical spinal cord compartments in multiple sclerosis’, Multiple Sclerosis and Related Disorders, 71, p. 104545. Available at: https://doi.org/10.1016/j.msard.2023.104545.

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Müller J et al. (2023) ‘Understanding the Role of the Choroid Plexus in Multiple Sclerosis as an MRI Biomarker of Disease Activity’, Neurology. Lippincott Williams and Wilkins, 100(9). Available at: https://doi.org/10.1212/WNL.0000000000206806.

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Granziera, Cristina, Derfuss, Tobias and Kappos, Ludwig (2023) ‘Time to Change the Current Clinical Classification of Multiple Sclerosis?’, JAMA Neurology, 80(2), pp. 128–130. Available at: https://doi.org/10.1001/jamaneurol.2022.4156.

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Wenger, A.L. et al. (2023) ‘An investigation of the association between focal damage and global network properties in cognitively impaired and cognitively preserved patients with multiple sclerosis’, Frontiers in Neuroscience, 17. Available at: https://doi.org/10.3389/fnins.2023.1007580.

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Saemann, Attill et al. (2023) ‘Hemiparkinsonism caused by a lateral sphenoid wing meningioma, with tractography analysis: illustrative case’, Journal of Neurosurgery: Case Lessons, 5(6). Available at: https://doi.org/10.3171/CASE22398.

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Saemann, Attill et al. (2023) ‘Hemiparkinsonism caused by a lateral sphenoid wing meningioma, with tractography analysis: illustrative case’, Journal of Neurosurgery: Case Lessons, 5(6). Available at: https://doi.org/10.3171/case22398.

Tsagkas C et al. (2023) ‘Fully Automatic Method for Reliable Spinal Cord Compartment Segmentation in Multiple Sclerosis’, American Journal of Neuroradiology, 44(2), pp. 218–227. Available at: https://doi.org/10.3174/ajnr.A7756.

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Tsagkas, C. et al. (2023) ‘Fully Automatic Method for Reliable Spinal Cord Compartment Segmentation in Multiple Sclerosis’, American Journal of Neuroradiology, 44(2), pp. 218–227. Available at: https://doi.org/10.3174/ajnr.a7756.

Barakovic, Muhamed et al. (2023) ‘Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology’, Frontiers in Neuroscience, 17. Available at: https://doi.org/10.3389/fnins.2023.1209521.

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Bosticardo, Sara et al. (2023) ‘Evaluation of tractography-based myelin-weighted connectivity across the lifespan’, Frontiers in Neuroscience, 17. Available at: https://doi.org/10.3389/fnins.2023.1228952.

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Chen, Xinjie et al. (2023) ‘Personalized maps of T1 relaxometry abnormalities provide correlates of disability in multiple sclerosis patients’, NeuroImage: Clinical, 37. Available at: https://doi.org/10.1016/j.nicl.2023.103349.

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Durrer, Alicia et al. (2023) ‘Diffusion Models for Contrast Harmonization of Magnetic Resonance Images’, in Proceedings of Machine Learning Research. ML Research Press (Proceedings of Machine Learning Research), pp. 526–551.

Molchanova, Nataliia et al. (2023) ‘Novel Structural-Scale Uncertainty Measures and Error Retention Curves: Application to Multiple Sclerosis’, in Proceedings - International Symposium on Biomedical Imaging. IEEE Computer Society (Proceedings - International Symposium on Biomedical Imaging). Available at: https://doi.org/10.1109/ISBI53787.2023.10230563.

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Spagnolo, F. et al. (2023) ‘How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review’, NeuroImage: Clinical, 39. Available at: https://doi.org/10.1016/j.nicl.2023.103491.

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Etter, Manina M. et al. (2022) ‘Severe Neuro-COVID is associated with peripheral immune signatures, autoimmunity and neurodegeneration: a prospective cross-sectional study’, Nature Communications, 13(1). Available at: https://doi.org/10.1038/s41467-022-34068-0.

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Meaton I et al. (2022) ‘Paramagnetic rims are a promising diagnostic imaging biomarker in multiple sclerosis’, Multiple Sclerosis Journal, 28(14), pp. 2212–2220. Available at: https://doi.org/10.1177/13524585221118677.

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Müller, Jannis et al. (2022) ‘Fluid and White Matter Suppression: New Sensitive 3 T Magnetic Resonance Imaging Contrasts for Cortical Lesion Detection in Multiple Sclerosis’, Investigative Radiology, 57(9), pp. 592–600. Available at: https://doi.org/10.1097/RLI.0000000000000877.

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Granziera C, Woelfle T and Kappos L (2022) ‘Development and implementation of new diagnostic technologies in neurology’, Nature Reviews Neurology, 18(8), pp. 445–446. Available at: https://doi.org/10.1038/s41582-022-00692-z.

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La Rosa F et al. (2022) ‘Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI’, NMR in Biomedicine, 35(8), p. e4730. Available at: https://doi.org/10.1002/nbm.4730.

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Parmar K et al. (2022) ‘Regional Cerebellar Volume Loss Predicts Future Disability in Multiple Sclerosis Patients’, Cerebellum, 21(4), pp. 632–646. Available at: https://doi.org/10.1007/s12311-021-01312-0.

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Wendebourg MJ et al. (2022) ‘Spinal cord gray matter atrophy is associated with functional decline in post-polio syndrome’, European Journal of Neurology, 29(5), pp. 1435–1445. Available at: https://doi.org/10.1111/ene.15261.

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