Original research••

Association between optic disc pallor and lacunar stroke

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Abstract

Objective To test for associations between optic disc pallor and two clinical variables: ischaemic stroke subtype (cortical and lacunar) and cerebral small vessel disease (SVD) scores in a cohort of hospital patients admitted with mild stroke (Mild Stroke Study 1).

Methods We used previously validated software, PallorMetrics, to quantify optic disc pallor in colour fundus photographs of patients diagnosed as having either cortical (n=92) or lacunar (n=92) stroke. We used logistic regression to assess the relationship between stroke type and disc pallor in several zones and ordinal logistic regression to assess the relationship between disc pallor and total SVD score. The left and right eyes were analysed separately.

Results In the right eye, independent of age, sex, disc area, hypertension and diabetes, increased optic disc pallor was significantly associated with lacunar stroke in all zones (for global pallor: OR per SD increase=1.55, 95% CI 1.11 to 2.17, p=0.011) and total SVD score in the temporal superior (standardised β=0.36, SE=0.15, p=0.020) and nasal-inferior zones (standardised β=0.44, SE=0.15, p=0.004) in the right eye. Weaker trends were observed in the left eye; however, these did not reach statistical significance.

Conclusion Optic disc pallor may be associated with SVD severity and lacunar stroke, which may reflect vascular damage to the optic nerve or its pathways. Our findings underscore the utility of colour fundus photography to learn more about SVD pathology.

What is already known on this topic

Cerebral small vessel disease (SVD) causes lacunar stroke, which accounts for around 25% of all ischaemic strokes and differs from other ischaemic strokes in terms of prognosis, therapy and prevention strategies. The retina, particularly the optic disc, due to its vascular similarity to the brain, has been identified as a potential site for biomarkers that could help in understanding and diagnosing SVD and stroke.

What this study adds

This study found that optic disc pallor is significantly associated with the lacunar stroke subtype (compared with atheromatous large artery cortical strokes) and higher SVD scores. This finding suggests that optic disc pallor could be a marker of chronic small vessel vascular impairment affecting the optic nerve and may serve as a non-invasive indicator of SVD severity.

How this study might affect research, practice or policy

The association between optic disc pallor and SVD highlights another feature of retinal fundus imaging that can act as a convenient and non-invasive method for assessing brain health and SVD severity. This could potentially lead to improved diagnostic tools and more targeted therapeutic strategies to prevent SVD-related stroke and cognitive decline, influencing clinical practice and policy in stroke management and prevention.

Introduction

Cerebral small vessel disease (SVD) is an age-associated condition impacting the perforating small blood vessels of the central nervous system and constitutes a significant factor in the development of stroke, dementia and cognitive decline.1–3 In particular, SVD is a major cause of lacunar stroke,4 5 which accounts for around 25% of all ischaemic strokes6 7 and differs from other ischaemic strokes with regard to prognosis, therapy and prevention strategies.6 8–10 SVD can be detected in the brain with MRI. Key visible indicators of SVD include lacunes, microbleeds, white matter hyperintensities (WMHs) and enlarged perivascular spaces.1–4 However, MRI is expensive, with limited availability. Instead, the retina, owing to its homology with the brain,11 particularly with regard to the microvasculature, has become a target for biomarker discovery and mechanistic insight into SVD and stroke.12

Previous work using colour fundus photographs investigating the eye–brain connection in SVD and lacunar stroke has shown increased microvasculature signs in lacunar compared with cortical stroke, including wider retinal venules,13 14 decreased fractal dimension,15 narrower arterioles and greater arteriovenous nipping,14 highlighting the importance of vascular changes in lacunar stroke. Most other work looking at retinal features and stroke has also focused on the retinal vasculature.13–18 However, an under-researched feature of the retina that could provide further insight into SVD is the optic disc.

A pale disc, for instance, indicates optic atrophy and represents loss or damage to retinal ganglion cell (RGC) axons along the anterior visual pathway, and to some extent, a loss of vasculature.19 The quantity of RGC axons is captured by the retinal nerve fibre layer (RNFL), which can be measured with three-dimensional scanning technology, optical coherence tomography (OCT). Thinning of the peripapillary RNFL (pRNFL; circular OCT scan around the optic disc) has been associated with SVD,12 Alzheimer’s disease, mild cognitive impairment,20 increased risk of dementia,21 future cognitive decline22 and increased cardiovascular risk.23 One study looked directly at pRNFL defects and stroke,24 finding increased defects (and hence thinner pRNFL) in acute stroke compared with controls. However, research investigating optic disc pallor/atrophy and stroke is scant; we found just one study,25 with the authors reporting a high prevalence of optic atrophy in patients who had ischaemic stroke; stroke subtypes were not assessed.

One potential reason for the scarcity of research in this area could be the need for specialist ophthalmological assessment to diagnose optic atrophy/pallor, which can vary among observers.26 Recently, we developed an automatic method of obtaining continuous measurements of optic disc pallor from colour fundus photographs,27 which may act as a proxy for pRNFL thickness and the detection of defects. In the current study, we explore associations between optic disc pallor and two clinical features: ischaemic stroke subtype (cortical and lacunar) and total SVD scores in a prospective study of minor stroke and SVD.

Methods

Participants and image capture

The Mild Stroke Study 1 population has been described in detail elsewhere.13 15 28 Briefly, 220 patients who had experienced a clinical ischaemic or minor cortical stroke were recruited from a hospital stroke service in Edinburgh, UK. Due to legacy problems with data linkage, retinal fundus photographs were available for 186 patients. All patients underwent MRI (1.5 T; Signa LX; General Electric) at presentation and had retinal fundus images (Canon CR-DGi; Canon USA) taken within 4 weeks of stroke onset. The MRI sequence included axial diffusion-weighted, T2-weighted, fluid-attenuated inversion recovery (FLAIR) and gradient echo, while the retinal photography was six-field (including optic disc centred) of both eyes. Retinal imaging was carried out according to the Early Treatment Diabetic Retinopathy Study protocol,29 which always captured the right eye first, and administered 1% tropicamide as necessary (two drops per eye) to dilate the pupil. Prior to dilation, patients were screened for glaucoma and a history of glaucoma.

Stroke classification

Clinical

A stroke physician (author FD) examined all patients and assessed stroke severity using the NIH Stroke Scale.30 The stroke clinical syndrome was classified as either lacunar or cortical based on the Oxfordshire Community Stroke Project classification.31 Briefly, cortical stroke was defined as a partial anterior circulation stroke syndrome or, if in the posterior circulation, visual field loss. Lacunar stroke was defined by pure motor weakness and/or sensory loss in the face and arm, arm and leg, or all three, as well as ataxic hemiparesis or clumsy hand dysarthria syndrome.13 32

Radiological

A consultant neuroradiologist (author JW) identified and located acute ischaemic stroke lesions (low signal on apparent diffusion coefficient (ADC) map, high signal on diffusion imaging), old ischaemic stroke lesions (high/low FLAIR signal, high T2 signal, no signal on diffusion imaging/ADC map) and old haemorrhages (low gradient-echo signal). Lacunar infarcts were defined as acute ischaemic lesions, round and under 2 cm in the centrum semiovale, internal capsule, brainstem or basal ganglia. Cortical lesions were defined as acute ischaemic lesions affecting cortical and adjacent subcortical tissue in a known cortical arterial branch territory, including striatocapsular infarcts (>2 cm diameter in the basal ganglia).32 Clinical ratings were combined with MRI-based measures (whether the recent infarct was cortical or lacunar) to produce a final stroke subtype classification. Where the two differed, the radiological classification was preferred.

Total SVD score

Total SVD score (ordinal score of 0–4) was calculated according to Staal’s (2014) method,33 whereby one point was allocated for each of four MRI features of SVD: presence of lacunes, presence of microbleeds, moderate to severe enlarged perivascular spaces (grades 2–4) and WMHs (Fazekas score 2 or 3 for deep WMH and Fazekas score 3 for WMH extending into deep white matter).

Optic disc pallor quantification

We generated continuous measures of optic disc pallor from colour fundus photographs using previously validated software, PallorMetrics.27 Briefly, a set of deep learning-based convolutional neural networks segmented the optic disc to the inner edge of the border tissue and calculated pallor based on the reflectance of red and green light in the neuroretinal rim relative to a control region. Visible retinal vasculature was segmented and subtracted from measurement and control regions. Measurements of pallor were then obtained for seven zones, in concordance with zones used for peripapillary OCT scans and aligned with the fovea, which was automatically detected by the software. Key stages in PallorMetrics for a single image are presented in figure 1.

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Figure 1

Analysing optic disc pallor in a fundus image. (A) Full image rotated along the optic disc-fovea line (fovea location is predicted to lie within the red circle). (B) Image cropped to the optic disc. (C) Segmented whole disc with measured pallor value. (D) Segmented measurement and control region. (E) Measurement region with global pallor value. (F) Diagram of zones. Note: Retinal vessels are excluded in (C, D and E). PMB, papillomacular bundle.

When PallorMetrics failed at segmentation, we manually annotated features by fitting a deformable ellipse to the inner edge of the optic disc border tissue and marking the fovea with a single mouse click; if the fovea was not visible, we estimated its location based on its position relative to the optic disc and the vessel arc of the central arcades (procedure detailed in Gibbon et al27). Annotations were performed by the author, SG, who was masked to stroke type.

Sample derivation

Of the 186 patients recruited, 354 fundus photographs were available. Of the 354 images presented to the software, 73 had segmentation errors and were subsequently annotated manually. Via visual inspection of all processed images, eight were rejected for one or more rotation errors (two images), overexposure (two images) and high myope (five images). The final sample contained 346 images from 184 patients. For comparison, the final sample in our previous work using the same dataset was 166.15

Statistical analysis

We used logistic regression to assess the relationship between disc pallor and stroke type and ordinal logistic regression to assess the relationship between pallor and total SVD score. In accordance with previous work,13 15 we controlled for age, sex, hypertension and diabetes; however, we included information on hyperlipidaemia, history of transient ischaemic attack, history of stroke and smoking status to table 1 for completeness. We also controlled for disc area. Correcting for multiple comparisons was not applied in this study because the primary aim was exploratory, intended to identify potential associations that could guide future research. The right eye was consistently paler than the left (table 1); therefore, the left and right eyes were assessed separately. Pallor, age and disc area were standardised before analysis. Differences in demographics and risk factors between the groups were assessed using t-tests (where one variable was continuous) or χ² (where both variables were dichotomous). Missing data points were removed at the time of analysis. All statistical analysis was carried out in R (V.4.2.1; www. R-project.org). We used the ‘polyr’ package for ordinal logistic regression.

Table 1

Demographics and study variables by stroke subtype and eye

Results

Optic disc pallor was measured in 184 patients (346 images). The mean age was 68.6 years (SD=11.5) and the majority sex was male (66.8%). There were 92 patients with cortical stroke and 92 with lacunar stroke. Individuals who experienced lacunar stroke were younger than those with cortical stroke (mean age 66.1 compared with 70, p=0.017). There was no evidence of significant differences in male/female split, hypertension, cholesterol, diabetes, history of stroke, history of transient ischaemic attack or smoking status between stroke types. Demographic and study variables are summarised in table 1.

Associations between disc pallor and stroke type

In the right eye, independent of covariates, increased optic disc pallor was significantly associated with lacunar stroke globally (OR per SD increase=1.54, CI: 1.12 to 2.19, p=0.011) and across all zones (figure 2). The left eye did not reach statistical significance; however, the direction was mostly the same, potentially indicating a small effect.

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Figure 2

Forest plot showing the associations between disc pallor and stroke type. Each eye is modelled separately. All models are adjusted for age, sex, disc area, hypertension diagnosis and diabetes. Continuous variables were standardised prior to analysis. PMB, papillomacular bundle; NT, nasal-temporal.

Associations between disc pallor and total SVD score

Ordinal logistic models of the entire sample (lacunar and cortical) revealed significant associations between pallor and total SVD score in the temporal superior (standardised β=0.36, SE=0.15, p=0.020) and nasal-inferior zones (standardised β=0.44, SE=0.15, p=0.004) in the right eye. The direction of β was the same in both eyes (except for the NT ratio in the right eye and nasal superior zone in the left eye), indicating that a statistical effect may have emerged given more data. Results are summarised in table 2.

Table 2

Ordinal logistic regression results for SVD score and optic disc pallor, by zone and eye

Discussion

We show here that the optic disc is slightly paler in patients with lacunar stroke compared with cortical stroke. This effect was independent of covariates and held despite the patients with lacunar stroke being around 4 years younger than patients with cortical stroke. Furthermore, we show that increasing paleness of the disc may be weakly associated with total SVD score. Both findings were stronger for the right eye; however, this may be due to the imaging protocol and known differences between the eyes. Taken together, our findings suggest that SVD may be associated with damage to the optic nerve.

A pale optic disc is symptomatic of optic atrophy, which refers to the permanent loss or damage to retinal ganglion cell axons along the anterior visual pathway, with pallor usually beginning to show around 4–6 weeks after axonal damage.19 The retinal imaging in the current study was carried out within 4 weeks of stroke occurrence; therefore, it is unlikely that the stroke itself caused the observed increase in paleness. More likely is that the observed increase in pallor is a long-term result of SVD, which has been associated with pRNFL thinning,12 and by association—disc pallor. This hypothesis is consistent with the current demonstration of associations between disc pallor and both lacunar stroke and SVD severity.

One possible mechanism by which SVD and resulting lacunar stroke could cause optic disc pallor/atrophy is through effects on the blood supply to the optic nerve or its pathways. For example, if a lacunar infarct occurred in any part of an optic pathway, it could lead to retrograde demyelination along the optic nerve, manifesting as pallor in the optic disc. However, this scenario is rare, as lacunar strokes do not usually affect the visual system directly.34 Optic disc pallor can reflect not only the loss of nerve fibres but also gliosis,35 axonal degeneration and other changes within the optic nerve head. It indicates chronic, longstanding optic nerve damage, which may be more aligned with the cumulative effects of chronic SVD.

Strengths of this study include the accuracy of stroke subtyping, which used both clinical and radiological features, the relatively large sample and the use of novel, validated software to quantify optic disc pallor in several zones.

This study has several limitations. First, associations were only statistically significant in the right eye and not the left. However, it is worth noting that the right eye was always captured first, using six flashes of light. This procedure may have had a subtle impact on image quality in the fellow eye, potentially due to patient fatigue or challenges in visualising the left optic disc. This claim remains to be tested and is beyond the scope of this study; empirically assessing image quality in fundus photographs is an area of much research and controversy.36 Notwithstanding, associations in the left eye showed a trend, which may have borne out in a larger sample. Furthermore, there are known differences in RNFL thickness between the eyes,37 which may have subtly affected the pallor measurement. Ocular dominance may also play a role; if patients are right-eye dominant, this could potentially lead to a thicker RNFL,38 which may result in greater variation in pallor measurements. This increased variation could potentially enhance the ability to detect differences or trends through statistical testing. Unfortunately, neither ocular dominance nor handedness (a proxy) was available for the current cohort.

Second, although patients were screened for glaucoma, they were not screened for other optic neuropathies, such as non-arteritic anterior ischaemic optic neuropathy (NAAION), which could affect disc pallor. However, NAAION is rare, affecting between 2.3 and 10.3 people per 100 000,39 making it unlikely that any patients in the study were affected. Even if one or two patients were affected, it is improbable that this would have significantly impacted the model estimates. Additionally, markers of optic disc dysfunction, such as colour vision deficiency and reduced visual acuity, which likely correlate with optic disc pallor, could have been useful covariates. Unfortunately, these variables were not collected.

Third, the study was cross-sectional in design, which precluded us from inferring a temporal association. In addition, most patients in the current study were white in ethnicity; therefore, further research is needed to determine if the results apply to other ethnicities. Finally, although we used MRI in deciding each stroke type and all patients had a definite stroke diagnosed by an expert panel, there may be some misclassification in stroke type. The classification used was a pragmatic system based on the most likely mechanism to explain the different stroke subtypes. We acknowledge that there will be a small group of people whose lacunar stroke may not have been caused by intrinsic SVD and also that there will be patients with coexistent small and large artery disease given the high prevalence of shared risk factors.

Conclusion

We show here that the optic disc is slightly paler in lacunar compared with cortical stroke and that increasing disc pallor is weakly associated with increasing SVD severity. This may reflect RNFL loss or degeneration caused by vascular damage to the optic pathway. Our results strengthen the case for retinal fundus imaging as a convenient and promising method for exploring alterations in brain health linked to SVD.

Contributors: SG led the project by contributing to the conceptualisation and methodology, developed the software used in the study, performed the formal analysis and investigation, was responsible for data curation and drafting the original manuscript and also created visualisations of the data. FD secured funding for the project, was involved in data curation and resource provision, supervised the study, participated in the investigation and contributed to the manuscript by reviewing and editing it. FC handled data curation and formal analysis, managed the project administration and contributed to the manuscript by reviewing and editing it. JMW was instrumental in acquiring funding and providing resources for the project and contributed to the manuscript through review and editing. BD contributed to the manuscript by reviewing and editing it. TMG supervised the project, provided the necessary resources and contributed to the manuscript by reviewing and editing it. SG is designated as the guarantor for this study, taking responsibility for the overall content and integrity of the manuscript.
Funding: The authors declare that there is no conflict of interest. Funding includes the Chief Scientist Office CZB/4/281; Row Fogo Charitable Trust; Wellcome Trust RTF 075611; SG was supported by EASTBIO, a consortium of Scottish Universities, which is funded by the BBSRC (Biotechnology and Biological Sciences Research Council). JMW is supported by the UK Dementia Research Institute (award no. UKDRI-Edin002, DRIEdi17/18 and MRC MC_PC_17113), which receives its funding from DRI, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. FC was supported by the UK Dementia Research Institute, which receives its funding from DRI; the Fondation Leducq Network for the Study of Perivascular Spaces in Small Vessel Disease (16 CVD 05) and the Row Fogo Charitable Trust Centre for Research into Ageing and the Brain.
Competing interests: None declared.
Provenance and peer review: Not commissioned; internally peer reviewed.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication:

Ethics approval:

This study involves human participants and was approved by Lothian Research Ethics Committee (reference number LREC/2002/8/64). Participants gave informed consent to participate in the study before taking part.

Cannistraro RJ, Badi M, Eidelman BH, et al. CNS small vessel disease: A clinical review. Neurology (ECronicon) 2019; 92:1146–56.
doi:10.1212/WNL.0000000000007654•Google Scholar
Wardlaw JM, Smith C, Dichgans M, et al. Small vessel disease: mechanisms and clinical implications. Lancet Neurol 2019; 18:684–96.
doi:10.1016/S1474-4422(19)30079-1•Google Scholar
Li Q, Yang Y, Reis C, et al. Cerebral Small Vessel Disease. Cell Transplant 2018; 27:1711–22.
doi:10.1177/0963689718795148•Google Scholar
Wardlaw JM, Smith EE, Biessels GJ, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol 2013; 12:822–38.
doi:10.1016/S1474-4422(13)70124-8•Google Scholar
Wardlaw JM. What causes lacunar stroke? J Neurol Neurosurg Psychiatry 2005; 76:617–9.
doi:10.1136/jnnp.2004.039982•Google Scholar
Norrving B. Long-term prognosis after lacunar infarction. Lancet Neurol 2003; 2:238–45.
doi:10.1016/s1474-4422(03)00352-1•Google Scholar
Regenhardt RW, Das AS, Lo EH, et al. Advances in Understanding the Pathophysiology of Lacunar Stroke: A Review. JAMA Neurol 2018; 75:1273–81.
doi:10.1001/jamaneurol.2018.1073•Google Scholar
Das AS, Regenhardt RW, Feske SK, et al. Treatment Approaches to Lacunar Stroke. J Stroke Cerebrovasc Dis 2019; 28:2055–78.
doi:10.1016/j.jstrokecerebrovasdis.2019.05.004•Google Scholar
Grysiewicz RA, Ruland SD. Lacunar infarcts, Encyclopedia of the Neurological Sciences (Second Edition). Academic Press 2014;
Google Scholar
Ganesh A, Gutnikov SA, Rothwell PM, et al. Late functional improvement after lacunar stroke: a population-based study. J Neurol Neurosurg Psychiatry 2018; 89:1301–7.
doi:10.1136/jnnp-2018-318434•Google Scholar
Patton N, Aslam T, Macgillivray T, et al. Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: a rationale based on homology between cerebral and retinal microvasculatures. J Anat 2005; 206:319–48.
doi:10.1111/j.1469-7580.2005.00395.x•Google Scholar
Biffi E, Turple Z, Chung J, et al. Retinal biomarkers of Cerebral Small Vessel Disease: A systematic review. PLoS One 2022; 17.
doi:10.1371/journal.pone.0266974•Google Scholar
Doubal FN, MacGillivray TJ, Hokke PE, et al. Differences in retinal vessels support a distinct vasculopathy causing lacunar stroke. Neurology (ECronicon) 2009; 72:1773–8.
doi:10.1212/WNL.0b013e3181a60a71•Google Scholar
Lindley RI, Wang JJ, Wong M-C, et al. Retinal microvasculature in acute lacunar stroke: a cross-sectional study. Lancet Neurol 2009; 8:628–34.
doi:10.1016/S1474-4422(09)70131-0•Google Scholar
Doubal FN, MacGillivray TJ, Patton N, et al. Fractal analysis of retinal vessels suggests that a distinct vasculopathy causes lacunar stroke. Neurology (ECronicon) 2010; 74:1102–7.
doi:10.1212/WNL.0b013e3181d7d8b4•Google Scholar
Cheung N, Liew G, Lindley RI, et al. Retinal fractals and acute lacunar stroke. Ann Neurol 2010; 68:107–11.
doi:10.1002/ana.22011•Google Scholar
Cheung CYL, Ikram MK, Chen C, et al. Imaging retina to study dementia and stroke. Prog Retin Eye Res 2017; 57:89–107.
doi:10.1016/j.preteyeres.2017.01.001•Google Scholar
Doubal FN, Hokke PE, Wardlaw JM, et al. Retinal microvascular abnormalities and stroke: a systematic review. J Neurol Neurosurg Psychiatry 2009; 80:158–65.
doi:10.1136/jnnp.2008.153460•Google Scholar
Ahmad SS, Kanukollu VM. Optic atrophy, StatPearls. StatPearls Publishing 2022;
Available: here
Google Scholar
Thomson KL, Yeo JM, Waddell B, et al. A systematic review and meta-analysis of retinal nerve fiber layer change in dementia, using optical coherence tomography. Alzheimers Dement Diagn Assess Dis Monit 2015; 1:136–43.
doi:10.1016/j.dadm.2015.03.001•Google Scholar
Mutlu U, Colijn JM, Ikram MA, et al. Association of Retinal Neurodegeneration on Optical Coherence Tomography With Dementia: A Population-Based Study. JAMA Neurol 2018; 75:1256–63.
doi:10.1001/jamaneurol.2018.1563•Google Scholar
Ko F, Muthy ZA, Gallacher J, et al. Association of Retinal Nerve Fiber Layer Thinning With Current and Future Cognitive Decline: A Study Using Optical Coherence Tomography. JAMA Neurol 2018; 75:1198–205.
doi:10.1001/jamaneurol.2018.1578•Google Scholar
Chen Y, Yuan Y, Zhang S, et al. Retinal nerve fiber layer thinning as a novel fingerprint for cardiovascular events: results from the prospective cohorts in UK and China. BMC Med 2023; 21.
doi:10.1186/s12916-023-02728-7•Google Scholar
Wang D, Li Y, Wang C, et al. Localized retinal nerve fiber layer defects and stroke. Stroke 2014; 45:1651–6.
doi:10.1161/STROKEAHA.113.004629•Google Scholar
Wolz J, Audebert H, Laumeier I, et al. Telemedical assessment of optic nerve head and retina in patients after recent minor stroke or TIA. Int Ophthalmol 2017; 37:39–46.
doi:10.1007/s10792-016-0222-7•Google Scholar
O’Neill EC, Danesh-Meyer HV, Kong GXY, et al. Optic disc evaluation in optic neuropathies: the optic disc assessment project. Ophthalmology 2011; 118:964–70.
doi:10.1016/j.ophtha.2010.09.002•Google Scholar
Gibbon S, Muniz-Terrera G, Yii FSL, et al. PallorMetrics: Software for Automatically Quantifying Optic Disc Pallor in Fundus Photographs, and Associations With Peripapillary RNFL Thickness. Transl Vis Sci Technol 2024; 13.
doi:10.1167/tvst.13.5.20•Google Scholar
Doubal FN, Dhillon B, Dennis MS, et al. Retinopathy in Ischaemic Stroke Subtypes. Stroke J Cereb Circ 2009; 40:389–93.
doi:10.1161/STROKEAHA.108.529388•Google Scholar
Early Treatment Diabetic Retinopathy Study Design and Baseline Patient Characteristics: ETDRS Report Number 7. Ophthalmology 1991; 98:741–56.
doi:10.1016/S0161-6420(13)38009-9•Google Scholar
Brott T, Adams HP, Olinger CP, et al. Measurements of acute cerebral infarction: a clinical examination scale. Stroke 1989; 20:864–70.
doi:10.1161/01.str.20.7.864•Google Scholar
Bamford J, Sandercock P, Dennis M, et al. Classification and natural history of clinically identifiable subtypes of cerebral infarction. Lancet Lond Engl 1991; 337:1521–6.
doi:10.1016/0140-6736(91)93206-o•Google Scholar
Wardlaw JM, Doubal F, Armitage P, et al. Lacunar stroke is associated with diffuse blood-brain barrier dysfunction. Ann Neurol 2009; 65:194–202.
doi:10.1002/ana.21549•Google Scholar
Staals J, Makin SDJ, Doubal FN, et al. Stroke subtype, vascular risk factors, and total MRI brain small-vessel disease burden. Neurology (ECronicon) 2014; 83:1228–34.
doi:10.1212/WNL.0000000000000837•Google Scholar
Gore M, Bansal K, Khan Suheb MZ, et al. Lacunar stroke, StatPearls. StatPearls Publishing 2024;
Available: here
Google Scholar
Osaguona VB. Differential diagnoses of the pale/white/atrophic disc. Community Eye Health 2016; 29:71–4.
Google Scholar
Gonçalves MB, Nakayama LF, Ferraz D, et al. Image quality assessment of retinal fundus photographs for diabetic retinopathy in the machine learning era: a review. Eye (Lond) 2024; 38:426–33.
doi:10.1038/s41433-023-02717-3•Google Scholar
Dalgliesh JD, Tariq YM, Burlutsky G, et al. Symmetry of retinal parameters measured by spectral-domain OCT in normal young adults. J Glaucoma 2015; 24:20–4.
doi:10.1097/IJG.0b013e318287ac2f•Google Scholar
Choi JA, Kim JS, Park HYL, et al. Retinal nerve fiber layer thickness profiles associated with ocular laterality and dominance. Neurosci Lett 2014; 558:197–202.
doi:10.1016/j.neulet.2013.10.054•Google Scholar
Hattenhauer MG, Leavitt JA, Hodge DO, et al. Incidence of nonarteritic anterior ischemic optic neuropathy. Am J Ophthalmol 1997; 123:103–7.
doi:10.1016/s0002-9394(14)70999-7•Google Scholar

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