Retinal Asymmetry in Multiple Sclerosis
Open accessAbstract
The diagnosis of multiple sclerosis is based on a combination of clinical and paraclinical tests. The potential contribution of retinal optical coherence tomography (OCT) has been recognized. We tested the feasibility of OCT measures of retinal asymmetry as a diagnostic test for multiple sclerosis at the community level. In this community-based study of 72 120 subjects, we examined the diagnostic potential of the inter-eye difference of inner retinal OCT data for multiple sclerosis using the UK Biobank data collected at 22 sites between 2007 and 2010. OCT reporting and quality control guidelines were followed. The inter-eye percentage difference (IEPD) and inter-eye absolute difference (IEAD) were calculated for the macular retinal nerve fibre layer (RNFL), ganglion cell inner plexiform layer (GCIPL) complex and ganglion cell complex. Area under the receiver operating characteristic curve (AUROC) comparisons were followed by univariate and multivariable comparisons accounting for a large range of diseases and co-morbidities. Cut-off levels were optimized by ROC and the Youden index. The prevalence of multiple sclerosis was 0.0023 [95% confidence interval (CI) 0.00229–0.00231]. Overall the discriminatory power of diagnosing multiple sclerosis with the IEPD AUROC curve (0.71, 95% CI 0.67–0.76) and IEAD (0.71, 95% CI 0.67–0.75) for the macular GCIPL complex were significantly higher if compared to the macular ganglion cell complex IEPD AUROC curve (0.64, 95% CI 0.59–0.69, P = 0.0017); IEAD AUROC curve (0.63, 95% CI 0.58–0.68, P < 0.0001) and macular RNFL IEPD AUROC curve (0.59, 95% CI 0.54–0.63, P < 0.0001); IEAD AUROC curve (0.55, 95% CI 0.50–0.59, P < 0.0001). Screening sensitivity levels for the macular GCIPL complex IEPD (4% cut-off) were 51.7% and for the IEAD (4 μm cut-off) 43.5%. Specificity levels were 82.8% and 86.8%, respectively. The number of co-morbidities was important. There was a stepwise decrease of the AUROC curve from 0.72 in control subjects to 0.66 in more than nine co-morbidities or presence of neuromyelitis optica spectrum disease. In the multivariable analyses greater age, diabetes mellitus, other eye disease and a non-white ethnic background were relevant confounders. For most interactions, the effect sizes were large (partial ω2 > 0.14) with narrow confidence intervals. In conclusion, the OCT macular GCIPL complex IEPD and IEAD may be considered as supportive measurements for multiple sclerosis diagnostic criteria in a young patient without relevant co-morbidity. The metric does not allow separation of multiple sclerosis from neuromyelitis optica. Retinal OCT imaging is accurate, rapid, non-invasive, widely available and may therefore help to reduce need for invasive and more costly procedures. To be viable, higher sensitivity and specificity levels are needed.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Co-morbidities such as poorly controlled hypertension and diabetes mellitus can affect OCT measures.
“Co-morbidities such as poorly controlled hypertension and diabetes mellitus, amongst others, can also affect OCT measures.”
From The use of optical coherence tomography and visual evoked potentials in the 2024 McDonald diagnostic criteria for multiple sclerosis (2025) · cites this paper as [89]
The Introduction identifies diabetes mellitus as a public-health condition known to affect OCT data. The cited passages do not identify hypertension as an OCT influence or address whether poor control of either condition matters. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe multiple sclerosis diagnostic accuracy of inter-eye differences in OCT measures diminished according to the number and classes of co-morbidities present.
“Petzold et al found that the MS diagnostic accuracy of IEDs in OCT measures diminished according to the number and classes of co-morbidities present, highlighting the importance of interpreting OCT within the context of co-morbidities. 89”
From The use of optical coherence tomography and visual evoked potentials in the 2024 McDonald diagnostic criteria for multiple sclerosis (2025) · cites this paper as [89]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
No references could be resolved yet.
Research works printed but not linked: 46
- Albers C, Lakens D. When power analyses based on pilot data are biased: inaccurate effect size estimators and follow-up bias. J Exp Soc Psychol 2018; 74: 187– 95.
- Aly L, Havla J, Lepennetier G, Andlauer TFM, Sie C, Strauß E-M, et al Inner retinal layer thinning in radiologically isolated syndrome predicts conversion to multiple sclerosis. Eur J Neurol 2020. doi: 10.1111/ene.14416. 32589804 · DOI
- Balk L, Tewarie P, Killestein J, Polman C, Uitdehaag B, Petzold A. Disease course heterogeneity and OCT in multiple sclerosis. Mult Scler 2014; 20: 1198– 206. 24402036
- Behbehani R, Ali A, Al-Omairah H, Rousseff RT. Optimization of spectral domain optical coherence tomography and visual evoked potentials to identify unilateral optic neuritis. Mult Scler Relat Disord 2020; 41: 101988. 32092503
- Cameron JR, Megaw RD, Tatham AJ, McGrory S, MacGillivray TJ, Doubal FN, et al Lateral thinking - Interocular symmetry and asymmetry in neurovascular patterning, in health and disease. Prog Retin Eye Res 2017; 59: 131– 57. 28457789
- Chua SYL, Thomas D, Allen N, Lotery A, Desai P, Patel P, et al Cohort profile: design and methods in the eye and vision consortium of UK Biobank. BMJ Open 2019; 9: e025077. PMC6398663 30796124
- Coric D, Balk LJ, Uitdehaag BMJ, Petzold A. Diagnostic accuracy of optical coherence tomography Inter-Eye Percentage Difference (IEPD) for optic neuritis in multiple sclerosis. Eur J Neurol 2017; 24: 1479– 84. 28887838
- Costello F, Hodge W, Pan YI, Freedman M, DeMeulemeester C. Differences in retinal nerve fiber layer atrophy between multiple sclerosis subtypes. J Neurol Sci 2009; 281: 74– 9. 19303605
- Cruz-Herranz A, Balk LJ, Oberwahrenbrock T, Saidha S, Martinez-Lapiscina EH, Lagreze WA, et al The APOSTEL recommendations for reporting quantitative optical coherence tomography studies. Neurology 2016; 86: 2303– 9. 27225223 PMC4909557
- Davion J-B, Lopes R, Drumez É, Labreuche J, Hadhoum N, Lannoy J, et al Asymptomatic optic nerve lesions: an underestimated cause of silent retinal atrophy in multiple sclerosis. Neurology 2020. 32434868
- Fauw JD, Ledsam JR, Romera-Paredes B, Nikolov S, Tomasev N, Blackwell S, et al Clinically applicable deep learning for diagnosis and referral in retinal disease. Nat Med 2018; 24: 1342– 50. 30104768
- Filippi M, Preziosa P, Meani A, Ciccarelli O, Mesaros S, Rovira A, et al Prediction of a multiple sclerosis diagnosis in patients with clinically isolated syndrome using the 2016 MAGNIMS and 2010 McDonald criteria: a retrospective study. Lancet Neurol 2018; 17: 133– 42. 29275979
- Filippi M, Rocca MA, Ciccarelli O, De Stefano N, Evangelou N, Kappos L, et al MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines. Lancet Neurol 2016; 15: 292– 303. 26822746 PMC4760851
- Fujimoto N, Adachi-Usami E. Use of blue-on-yellow perimetry to demonstrate quadrantanopia in multiple sclerosis. Arch Ophthalmol 1998; 116: 828– 9. 9639464
- Gabilondo I, Sepulveda M, Ortiz-Perez S, Fraga-Pumar E, Martinez-Lapiscina EH, Llufriu S, et al Retrograde retinal damage after acute optic tract lesion in multiple sclerosis, J Neurol Neurosurg Psychiatry 2013; 84: 824– 6. 23715916
- Green AJ, McQuaid S, Hauser SL, Allen IV, Lyness R. Ocular pathology in multiple sclerosis: retinal atrophy and inflammation irrespective of disease duration. Brain 2010; 133: 1591– 601. 20410146 PMC2877904
- Gündüz K, Cansu K, Bulduklar S, Saatçi I. Homonymous hemianopsia as the initial manifestation of multiple sclerosis. Ophthalmologica 1998; 212: 215– 20. 9562103
- Khawaja AP, Chua S, Hysi PG, Georgoulas S, Currant H, Fitzgerald TW, et al Comparison of associations with different macular inner retinal thickness parameters in a large cohort: the UK Biobank. Ophthalmology 2020; 127: 62– 71. 31585827
- Kleerekooper I, Petzold A, Trip SA. Anterior visual system imaging to investigate energy failure in multiple sclerosis. Brain 2020; 143: 1999– 2008. 32163545
- Ko F, Foster PJ, Strouthidis NG, Shweikh Y, Yang Q, Reisman CA, et al Associations with retinal pigment epithelium thickness measures in a large cohort. Ophthalmology 2017; 124: 105– 17. 27720551
- Lingsma HF, Roozenbeek B, Steyerberg EW, Murray GD, Maas AIR. Early prognosis in traumatic brain injury: from prophecies to predictions. Lancet Neurol 2010; 9: 543– 54. 20398861
- London F, Zéphir H, Drumez E, Labreuche J, Hadhoum N, Lannoy J, et al Optical coherence tomography: a window to the optic nerve in clinically isolated syndrome. Brain 2019; 142: 903– 15. 30847470
- Lycke J, Tollesson PO, Frisén L. Asymptomatic visual loss in multiple sclerosis. J Neurol 2001; 248: 1079– 86. 12013586
- Nielsen JM, Korteweg T, Barkhof F, Uitdehaag BMJ, Polman CH. Overdiagnosis of multiple sclerosis and magnetic resonance imaging criteria. Ann Neurol 2005; 58: 781– 3. 16240352
- Nolan RC, Galetta SL, Frohman TC, Frohman EM, Calabresi PA, Castrillo-Viguera C, et al Optimal intereye difference thresholds in retinal nerve fiber layer thickness for predicting a unilateral optic nerve lesion in multiple sclerosis. J Neuro-Ophthalmol 2018; 1. PMC8845082 29384802
- Nolan-Kenney RC, Liu M, Akhand O, Calabresi PA, Paul F, Petzold A, et al Optimal intereye difference thresholds by optical coherence tomography in multiple sclerosis: an international study. Ann Neurol 2019; 85: 618– 29. 30851125
- Oberwahrenbrock T, Traber GL, Lukas S, Gabilondo I, Nolan R, Songster C, et al Multicenter reliability of semiautomatic retinal layer segmentation using OCT. Neurol Neuroimmunol Neuroinflamm 2018; 5: e449. 29552598 PMC5852947
- Odom JV, Bach M, Brigell M, Holder GE, McCulloch DL, Mizota A, et al ISCEV standard for clinical visual evoked potentials: (2016 update). Doc Ophthalmol 2016; 133: 1– 9. 27443562
- Outteryck O, Lopes R, Drumez É, Labreuche J, Lannoy J, Hadhoum N, et al Optical coherence tomography for detection of asymptomatic optic nerve lesions in clinically isolated syndrome. Neurology 2020; 95: e733– e744. 32723802
- Patel PJ, Foster PJ, Grossi CM, Keane PA, Ko F, Lotery A, et al Spectral-domain optical coherence tomography imaging in 67 321 adults. Ophthalmology 2016; 123: 829– 40. 26746598
- Petzold A. Intrathecal oligoclonal IgG synthesis in multiple sclerosis. J Neuroimmunol 2013; 262: 1– 10. 23890808
- Petzold A, Balcer LJ, Calabresi PA, Costello F, Frohman TC, Frohman EM, et al Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurol 2017; 16: 797– 812. 28920886
- Petzold A, de Boer JF, Schippling S, Vermersch P, Kardon R, Green A, et al Optical coherence tomography in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurol 2010; 9: 921– 32. 20723847
- Petzold A, Wattjes MP, Costello F, Flores-Rivera J, Fraser CL, Fujihara K, et al The investigation of acute optic neuritis: a review and proposed protocol. Nat Rev Neurol 2014; 10: 447– 58. 25002105
- Pulicken M, Gordon-Lipkin E, Balcer LJ, Frohman E, Cutter G, Calabresi PA. Optical coherence tomography and disease subtype in multiple sclerosis. Neurology 2007; 69: 2085– 92. 18040015
- Reich DS, Lucchinetti CF, Calabresi PA. Multiple sclerosis., N Engl J Med 2018; 378: 169– 80. 29320652 PMC6942519
- Riederer I, Mühlau M, Hoshi M-M, Zimmer C, Kleine JF. Detecting optic nerve lesions in clinically isolated syndrome and multiple sclerosis: double-inversion recovery magnetic resonance imaging in comparison with visually evoked potentials. J Neurol 2019; 266: 148– 56. 30446963
- Saidha S, Syc SB, Ibrahim MA, Eckstein C, Warner CV, Farrell SK, et al Primary retinal pathology in multiple sclerosis as detected by optical coherence tomography. Brain 2011; 134: 518– 33. 21252110
- Seshan V, Gönen M, Begg C. Comparing ROC curves derived from regression models. Stat Med 2012; 32: 1483– 93. 23034816 PMC3617074
- Sinnecker T, Clarke MA, Meier D, Enzinger C, Calabrese M, Stefano ND, et al Evaluation of the central vein sign as a diagnostic imaging biomarker in multiple sclerosis. JAMA Neurol 2019. PMC6704746 31424490
- Tewarie P, Balk L, Costello F, Green A, Martin R, Schippling S, et al The OSCAR-IB consensus criteria for retinal OCT quality assessment. PLoS ONE 2012; 7: e34823. 22536333 PMC3334941
- Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, et al Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 2018a; 162– 73. 29275977
- Thompson AJ, Baranzini SE, Geurts J, Hemmer B, Ciccarelli O. Multiple sclerosis. Lancet 2018b; 391: 1622– 36. 29576504
- Villoslada P, Sanchez-Dalmau B, Galetta S. Optical coherence tomography: a useful tool for identifying subclinical optic neuropathy in diagnosing multiple sclerosis. Neurology 2020; 95: 239– 40. 32723803
- de Vries-Knoppert WA, Baaijen JC, Petzold A. Patterns of retrograde axonal degeneration in the visual system. Brain 2019; 142: 2775– 86. 31363733
- Xu SC, Kardon RH, Leavitt JA, Flanagan EP, Pittock SJ, Chen JJ. Optical coherence tomography is highly sensitive in detecting prior optic neuritis. Neurology 2019; 92: e527– e535. 30674600
Cited by
Sorted by citations
Vidal-Jordana, A., Rovira, A., Calderon, W., Arrambide, G., Castilló, J., Moncho, D., Rahnama, K., Collorone, S., Toosy, A. T., Ciccarelli, O., et al. (2024) · Neurology · doi:10.1212/wnl.0000000000207805 · Cited by 88 · see citing works
Saidha, S., Green, A. J., Leocani, L., Vidal-Jordana, A., Kenney, R. C., Bsteh, G., Outteryck, O., Thompson, A., Montalban, X., Coetzee, T., et al. (2025) · The Lancet Neurology · doi:10.1016/s1474-4422(25)00275-3 · Cited by 66 · see citing works
Self-citation
- Authors
- Petzold, A., Chua, S. Y. L., Khawaja, A. P., Keane, P. A., Khaw, P. T., Reisman, C., Dhillon, B., Strouthidis, N. G., Foster, P. J., Patel, P. J., UK Biobank Eye and Vision Consortium, Atan, D., Aslam, T., Barman, S. A., Barrett, J. H., Bishop, P., Bunce, C., Carare, R. O., Chakravarthy, U., Chan, M., Chua, S. Y. L., Crabb, D. P., Day, A., Desai, P., Dhillon, B., Dick, A. D., Egan, C., Ennis, S., Ennis, S., Foster, P. J., Fruttiger, M., Gallacher, J. E. J., Garway-Heath, D. F., Gibson, J., Gore, D., Guggenheim, J. A., Hammond, C. J., Hardcastle, A., Harding, S. P., Hogg, R. E., Hysi, P., Keane, P. A., Khaw, S. P. T., Khawaja, A. P., Lascaratos, G., Lotery, A. J., Macgillivray, T., Mackie, S., McGaughey, M., McGuinness, B., McKay, G. J., McKibbin, M., Moore, T., Morgan, J. E., Muthy, Z. A., O’Sullivan, E., Owen, C. G., Patel, P., Paterson, E., Peto, T., Petzold, A., Rahi, J. S., Rudnikca, A. R., Self, J., Sivaprasad, S., Steel, D., Stratton, I., Strouthidis, N., Sudlow, C., Thomas, D., Trucco, E., Tufail, A., Vitart, V., Vernon, S. A., Viswanathan, A. C., Williams, C., Williams, K., Woodside, J. V., Yates, M. M., & Zheng, Y.
- Affiliations
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
- Topcon Healthcare Solutions Research and Development, Oakland, New Jersey, USA
- NHS Lothian (GB)
- Moorfields Eye Hospital NHS Foundation Trust (GB)
- ORCID
- Reisman, Charles
- Dhillon, Baljean
- Atan, Denize
- Aslam, Tariq
- Barman, Sarah A
- Bunce, Catey
- Carare, Roxana O
- Chakravarthy, Usha
- Chan, Michelle
- Crabb, David P
- Day, Alexander
- Desai, Parul
- Dhillon, Bal
- Dick, Andrew D
- Fruttiger, Marcus
- Gallacher, John E J
- Guggenheim, Jeremy A
- Hardcastle, Alison
- Harding, Simon P
- Hogg, Ruth E
- Hysi, Pirro
- Lascaratos, Gerassimos
- Lotery, Andrew J
- Macgillivray, Tom
- Mackie, Sarah
- McGuinness, Bernadette
- McKay, Gareth J
- McKibbin, Martin
- Moore, Tony
- Paterson, Euan
- Rahi, Jugnoo S
- Self, Jay
- Sivaprasad, Sobha
- Steel, David
- Stratton, Irene
- Sudlow, Cathie
- Thomas, Dhanes
- Trucco, Emanuele
- Tufail, Adnan
- Vernon, Stephen A
- Viswanathan, Ananth C
- Williams, Cathy
- Williams, Katie
- Woodside, Jayne V
- Yates, Max M
- Zheng, Yalin
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-11-30
- Volume
- 144
- Issue
- 1
- Pages
- 224-235
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- PMC
- PMC7880665
- OpenAlex
- W3109970956
- Cited by
- 56
- References
- 0
- Citations by year
- 2026: 10 · 2025: 17 · 2024: 9 · 2023: 8 · 2022: 7 · 2021: 5
- FWCI
- 2.21
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Brain (publishedVersion, cc-by-nc)
- SSRN Electronic Journal (publishedVersion)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- City Research Online (City University London) (acceptedVersion)
- St George's Online Research Archive (St George's University of London) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion, cc-by-nc)
- ePrints Soton (University of Southampton) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion, other-oa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Research Portal (Queen's University Belfast) (submittedVersion, cc-by-nc)
- Bristol Research (University of Bristol) (submittedVersion, cc-by-nc)
- Explore Bristol Research (submittedVersion, cc-by-nc)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Eranda Foundation via the International Glaucoma Association
- UK Department of Health
- National Institute for Health Research
- Moorfields Eye Hospital NHS Foundation Trust
- UCL Institute of Ophthalmology for a Biomedical Research Centre for Ophthalmology
- Helen Hamlyn Trust
- Richard Desmond Charitable Trust
- Clinician Scientist award (CS-2014-14-023)
- NHS
- National Institute for Health Research or the Department of Health
- Moorfields Eye Charity
- The NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust
- Alcon Research Institute
- The NIHR BRC at Moorfields Eye Hospital
- Eranda Foundation
- International Glaucoma Association
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Health Sciences › Medicine › Ophthalmology › Glaucoma and retinal disorders
- Health Sciences › Medicine › Ophthalmology › Drug-Induced Ocular Toxicity
- Keywords
- multiple sclerosis, optical coherence tomography, macular ganglion cell complex, ganglion cell-inner plexiform layer, retinal nerve fiber layer, diagnostic accuracy, UK Biobank, community-based study, prevalence, screening sensitivity and specificity, retinal biomarkers, neurodegeneration biomarkers, retinal ganglion cells
- MeSH terms
- Female, Humans, Male, Middle Aged, Multiple Sclerosis, Retina, Sensitivity and Specificity, Tomography, Optical Coherence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
