Imaging correlates of visual function in multiple sclerosis
No single neuroimaging technique or sequence is capable of reflecting the functional deficits manifest in MS. Given the interest in imaging biomarkers for short- to medium-term studies, we aimed to assess which imaging metrics might best represent functional impairment for monitoring in clinical tri...
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| Abstract | No single neuroimaging technique or sequence is capable of reflecting the functional deficits manifest in MS. Given the interest in imaging biomarkers for short- to medium-term studies, we aimed to assess which imaging metrics might best represent functional impairment for monitoring in clinical trials. Given the complexity of functional impairment in MS, however, it is useful to isolate a particular functionally relevant pathway to understand the relationship between imaging and neurological function. We therefore analyzed existing data, combining multiparametric MRI and OCT to describe MS associated visual impairment. We assessed baseline data from fifty MS patients enrolled in ReBUILD, a prospective trial assessing the effect of a remyelinating drug (clemastine). Subjects underwent 3T MRI imaging, including Neurite Orientation Dispersion and Density Imaging (NODDI), myelin content quantification, and retinal imaging, using OCT. Visual function was assessed, using low-contrast letter acuity. MRI and OCT data were studied to model visual function in MS, using a partial, least-squares, regression analysis. Measures of neurodegeneration along the entire visual pathway, described most of the observed variance in visual disability, measured by low contrast letter acuity. In those patients with an identified history of ON, however, putative myelin measures also showed correlation with visual performance. In the absence of clinically identifiable inflammatory episodes, residual disability correlates with neurodegeneration, whereas after an identifiable exacerbation, putative measures of myelin content are additionally informative. |
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| AbstractList | No single neuroimaging technique or sequence is capable of reflecting the functional deficits manifest in MS. Given the interest in imaging biomarkers for short- to medium-term studies, we aimed to assess which imaging metrics might best represent functional impairment for monitoring in clinical trials. Given the complexity of functional impairment in MS, however, it is useful to isolate a particular functionally relevant pathway to understand the relationship between imaging and neurological function. We therefore analyzed existing data, combining multiparametric MRI and OCT to describe MS associated visual impairment. We assessed baseline data from fifty MS patients enrolled in ReBUILD, a prospective trial assessing the effect of a remyelinating drug (clemastine). Subjects underwent 3T MRI imaging, including Neurite Orientation Dispersion and Density Imaging (NODDI), myelin content quantification, and retinal imaging, using OCT. Visual function was assessed, using low-contrast letter acuity. MRI and OCT data were studied to model visual function in MS, using a partial, least-squares, regression analysis. Measures of neurodegeneration along the entire visual pathway, described most of the observed variance in visual disability, measured by low contrast letter acuity. In those patients with an identified history of ON, however, putative myelin measures also showed correlation with visual performance. In the absence of clinically identifiable inflammatory episodes, residual disability correlates with neurodegeneration, whereas after an identifiable exacerbation, putative measures of myelin content are additionally informative. No single neuroimaging technique or sequence is capable of reflecting the functional deficits manifest in MS. Given the interest in imaging biomarkers for short- to medium-term studies, we aimed to assess which imaging metrics might best represent functional impairment for monitoring in clinical trials. Given the complexity of functional impairment in MS, however, it is useful to isolate a particular functionally relevant pathway to understand the relationship between imaging and neurological function. We therefore analyzed existing data, combining multiparametric MRI and OCT to describe MS associated visual impairment. We assessed baseline data from fifty MS patients enrolled in ReBUILD, a prospective trial assessing the effect of a remyelinating drug (clemastine). Subjects underwent 3T MRI imaging, including Neurite Orientation Dispersion and Density Imaging (NODDI), myelin content quantification, and retinal imaging, using OCT. Visual function was assessed, using low-contrast letter acuity. MRI and OCT data were studied to model visual function in MS, using a partial, least-squares, regression analysis. Measures of neurodegeneration along the entire visual pathway, described most of the observed variance in visual disability, measured by low contrast letter acuity. In those patients with an identified history of ON, however, putative myelin measures also showed correlation with visual performance. In the absence of clinically identifiable inflammatory episodes, residual disability correlates with neurodegeneration, whereas after an identifiable exacerbation, putative measures of myelin content are additionally informative.No single neuroimaging technique or sequence is capable of reflecting the functional deficits manifest in MS. Given the interest in imaging biomarkers for short- to medium-term studies, we aimed to assess which imaging metrics might best represent functional impairment for monitoring in clinical trials. Given the complexity of functional impairment in MS, however, it is useful to isolate a particular functionally relevant pathway to understand the relationship between imaging and neurological function. We therefore analyzed existing data, combining multiparametric MRI and OCT to describe MS associated visual impairment. We assessed baseline data from fifty MS patients enrolled in ReBUILD, a prospective trial assessing the effect of a remyelinating drug (clemastine). Subjects underwent 3T MRI imaging, including Neurite Orientation Dispersion and Density Imaging (NODDI), myelin content quantification, and retinal imaging, using OCT. Visual function was assessed, using low-contrast letter acuity. MRI and OCT data were studied to model visual function in MS, using a partial, least-squares, regression analysis. Measures of neurodegeneration along the entire visual pathway, described most of the observed variance in visual disability, measured by low contrast letter acuity. In those patients with an identified history of ON, however, putative myelin measures also showed correlation with visual performance. In the absence of clinically identifiable inflammatory episodes, residual disability correlates with neurodegeneration, whereas after an identifiable exacerbation, putative measures of myelin content are additionally informative. |
| Audience | Academic |
| Author | Hauser, Stephen L. Papinutto, Nico Yiu, Hao H. Bennett, Daniel J. Devereux, Michael Zhu, Alyssa H. Green, Ari J. Inman, Justin Caverzasi, Eduardo Henry, Roland G. Kirkish, Gina Cree, Bruce A. C. Gelfand, Jeffrey M. Cordano, Christian Baker, Nicholas Zhao, Chao Bischof, Antje |
| AuthorAffiliation | 2 Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, United States of America 4 Department of Ophthalmology, University of California, San Francisco, San Francisco, CA, United States of America 3 Neurology and Immunology Clinic, University Hospital Basel, Switzerland 1 Division of Neuroimmunology and Glial Biology UCSF, Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, United States of America University at Buffalo, UNITED STATES |
| AuthorAffiliation_xml | – name: University at Buffalo, UNITED STATES – name: 4 Department of Ophthalmology, University of California, San Francisco, San Francisco, CA, United States of America – name: 2 Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, United States of America – name: 1 Division of Neuroimmunology and Glial Biology UCSF, Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, United States of America – name: 3 Neurology and Immunology Clinic, University Hospital Basel, Switzerland |
| Author_xml | – sequence: 1 givenname: Eduardo orcidid: 0000-0002-0350-0460 surname: Caverzasi fullname: Caverzasi, Eduardo – sequence: 2 givenname: Christian surname: Cordano fullname: Cordano, Christian – sequence: 3 givenname: Alyssa H. surname: Zhu fullname: Zhu, Alyssa H. – sequence: 4 givenname: Chao surname: Zhao fullname: Zhao, Chao – sequence: 5 givenname: Antje surname: Bischof fullname: Bischof, Antje – sequence: 6 givenname: Gina surname: Kirkish fullname: Kirkish, Gina – sequence: 7 givenname: Daniel J. surname: Bennett fullname: Bennett, Daniel J. – sequence: 8 givenname: Michael surname: Devereux fullname: Devereux, Michael – sequence: 9 givenname: Nicholas surname: Baker fullname: Baker, Nicholas – sequence: 10 givenname: Justin surname: Inman fullname: Inman, Justin – sequence: 11 givenname: Hao H. surname: Yiu fullname: Yiu, Hao H. – sequence: 12 givenname: Nico surname: Papinutto fullname: Papinutto, Nico – sequence: 13 givenname: Jeffrey M. surname: Gelfand fullname: Gelfand, Jeffrey M. – sequence: 14 givenname: Bruce A. C. surname: Cree fullname: Cree, Bruce A. C. – sequence: 15 givenname: Stephen L. surname: Hauser fullname: Hauser, Stephen L. – sequence: 16 givenname: Roland G. surname: Henry fullname: Henry, Roland G. – sequence: 17 givenname: Ari J. surname: Green fullname: Green, Ari J. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32745132$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1093_brain_awaf144 crossref_primary_10_3390_bioengineering12060650 crossref_primary_10_1136_jnnp_2022_329221 crossref_primary_10_1016_j_msard_2025_106644 crossref_primary_10_1016_j_cct_2023_107333 crossref_primary_10_1080_13543784_2025_2472240 crossref_primary_10_1186_s12967_025_06105_1 crossref_primary_10_3390_jcm12062382 |
| Cites_doi | 10.1186/1756-0500-7-910 10.1016/S1361-8415(01)00036-6 10.1097/WCO.0b013e32832d954b 10.1016/S0140-6736(17)32346-2 10.1016/j.nicl.2012.09.013 10.1006/nimg.1998.0395 10.3389/fninf.2014.00008 10.1136/jnnp-2017-317509 10.1002/ana.25463 10.1177/1352458516637679 10.1056/NEJMoa1803583 10.1016/j.aca.2013.01.004 10.1056/NEJMoa1104318 10.1212/NXI.0000000000000492 10.1212/WNL.0000000000002774 10.1016/j.neuroimage.2007.10.033 10.1001/archneur.64.10.1416 10.1016/S0896-6273(02)00569-X 10.1016/S1474-4422(16)00068-5 10.1097/00019052-200206000-00003 10.1016/j.neuroimage.2012.03.072 10.1007/s00415-014-7340-9 10.1016/j.neuroimage.2011.09.015 |
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| Copyright | COPYRIGHT 2020 Public Library of Science 2020 Caverzasi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2020 Caverzasi et al 2020 Caverzasi et al |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have read the journal’s policy and have the following potential competing interests: SLH serves on the Board of Directors for Neurona, on the Scientific Advisory Board for Alector, Annexon, Bionure, and Molecular Stethoscope, and he has also received non-financial support from F. Hoffmann-La Roche Ltd and Novartis AG. AB has received travel fees from Actelion and speaker fees from Biogen. JMG reports research support to UCSF from Genentech for a clinical trial and consulting for Biogen and Alexion. BACC has received personal compensation for consulting from Akili, Alexion, Atara, Biogen, EMD Serono, Novartis, Sanofi and TG Therapeutics. AJG has served on the Scientific Advisory Board for Bionure, Inception Sciences and Pipeline Therapeutics. He serves as an Associate Editor at JAMA Neurology. He has served on an Adjudication Committee for MedImmune/Viela Bio. He has provided expert support for Mylan, Synthon and Pharmasciences and personal fees from and other financial relationships with Pipeline Therapeutics. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products to declare. All other authors have declared that no competing interests exist. |
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| SubjectTerms | Acuity Adult Biology Biology and Life Sciences Biomarkers Brain - diagnostic imaging Clinical trials Correlation analysis Diagnosis Female Health aspects Humans Impairment Inflammation Magnetic Resonance Imaging Male Medical imaging Medicine and Health Sciences Middle Aged Multiple sclerosis Multiple Sclerosis - diagnostic imaging Multiple Sclerosis - pathology Multiple Sclerosis - physiopathology Myelin Myelin Sheath - pathology Neurodegeneration Neuroimaging Neurology Neurosciences Orientation Orientation behavior Physiological aspects Regression analysis Research and Analysis Methods Retina - diagnostic imaging Retinal images Social Sciences Supervision Tomography, Optical Coherence Vision, Ocular Visual impairment Visual observation Visual pathway Visual perception |
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| Title | Imaging correlates of visual function in multiple sclerosis |
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