Retinal Structural and Microvascular Alterations in Different Acute Ischemic Stroke Subtypes

Zhang, Ying; Shi, Chaoji; Chen, Yihong; Wang, Weicheng; Huang, Shenghai; Han, Zhao; Lin, Xianda; Liu, Fan; Shen, Meixiao

doi:10.1155/2020/8850309

Cited by 20 publications

(18 citation statements)

References 38 publications

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“…It is suggested that the retina can act as a novel and non-invasive imaging marker with potential diagnostic and clinical significance in neurological diseases ( Cabrera DeBuc et al, 2017 ; Mutlu et al, 2017 ; Kwapong et al, 2018 ). Thinning of the retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL)-inner plexiform layer (GCIPL) has been consistently documented in previous reports ( Park et al, 2013 ; Zhang et al, 2020 ; Kashani et al, 2021 ; Snyder et al, 2021 ; Ye et al, 2022 ) in most cerebrovascular disorders. These reports suggest retinal neurodegeneration reflects cerebral neurodegeneration, and this mechanism may occur simultaneously.…”

Section: Introductionmentioning

confidence: 56%

“…The last few decades have seen a substantial increase in research identifying alterations in retinal structure and microvasculature after stroke ( Park et al, 2013 ; Wang et al, 2014 ; Zhang et al, 2020 ; Kwapong et al, 2021 ). It is suggested that the retina can act as a novel and non-invasive imaging marker with potential diagnostic and clinical significance in neurological diseases ( Cabrera DeBuc et al, 2017 ; Mutlu et al, 2017 ; Kwapong et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

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Alterations of optic tract and retinal structure in patients after thalamic stroke

Kwapong

Tao

et al. 2022

Front. Aging Neurosci.

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ObjectivesTo investigate the association between degeneration of retinal structure and shrinkage of the optic tract in patients after thalamic stroke.Materials and methodsPatients with unilateral thalamic stroke were included. Structural magnetic resonance imaging (MRI) and optical coherence tomography (OCT) were performed to obtain parameters of optic tract shrinkage (lateral index) and retina structural thickness (retinal nerve fiber layer, RNFL; peripapillary retinal nerve fiber layer, pRNFL; ganglion cell-inner plexiform layer, GCIP), respectively. Visual acuity (VA) examination under illumination was conducted using Snellen charts and then converted to the logarithm of the minimum angle of resolution (LogMAR). We investigated the association between LI and OCT parameters and their relationships with VA.ResultsA total of 33 patients and 23 age-sex matched stroke-free healthy controls were enrolled. Patients with thalamic stroke showed altered LI compared with control participants (P = 0.011) and a significantly increased value of LI in the subgroup of disease duration more than 6 months (P = 0.004). In these patients, LI were significantly associated with pRNFL thickness (β = 0.349, 95% confidence interval [CI]: 0.134–0.564, P = 0.002) after adjusting for confounders (age, sex, hypertension, diabetes, dyslipidemia, and lesion volume). LI and pRNFL were both significantly associated with VA in all patients (LI: β = −0.275, 95% CI: −0.539 to −0.011, P = 0.041; pRNFL: β = −0.023, 95% CI: −0.046 to −0.001, P = 0.040) and in subgroup of disease duration more than 6 months (LI: β = −0.290, 95% CI: −0.469 to −0.111, P = 0.002; pRNFL: β = −0.041, 95% CI: −0.065 to −0.017, P = 0.003).ConclusionShrinkage of the optic tract can be detected in patients with thalamic stroke, especially after 6 months of stroke onset. In these patients, the extent of optic tract atrophy is associated with pRNFL thickness, and they are both related to visual acuity changes.

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Section: Introductionmentioning

confidence: 56%

Section: Introductionmentioning

confidence: 99%

Alterations of optic tract and retinal structure in patients after thalamic stroke

Kwapong

Tao

et al. 2022

Front. Aging Neurosci.

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“…They have the same embryo origin and histological structure as cerebral vessels ( 10 – 13 ). Retinal microvascular damages can reflect damage to cerebral microvasculature and neurons ( 14 ). It provides us with a convenient way to assess cardiovascular conditions.…”

Section: Introductionmentioning

confidence: 99%

Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis

Zhuo

Lee

et al. 2022

Front. Neurol.

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BackgroundStroke is the second leading cause of death worldwide, causing a considerable disease burden. Ischemic stroke is more frequent, but haemorrhagic stroke is responsible for more deaths. The clinical management and treatment are different, and it is advantageous to classify their risk as early as possible for disease prevention. Furthermore, retinal characteristics have been associated with stroke and can be used for stroke risk estimation. This study investigated machine learning approaches to retinal images for risk estimation and classification of ischemic and haemorrhagic stroke.Study designA case-control study was conducted in the Shenzhen Traditional Chinese Medicine Hospital. According to the computerized tomography scan (CT) or magnetic resonance imaging (MRI) results, stroke patients were classified as either ischemic or hemorrhage stroke. In addition, a control group was formed using non-stroke patients from the hospital and healthy individuals from the community. Baseline demographic and medical information was collected from participants' hospital medical records. Retinal images of both eyes of each participant were taken within 2 weeks of admission. Classification models using a machine-learning approach were developed. A 10-fold cross-validation method was used to validate the results.Results711 patients were included, with 145 ischemic stroke patients, 86 haemorrhagic stroke patients, and 480 controls. Based on 10-fold cross-validation, the ischemic stroke risk estimation has a sensitivity and a specificity of 91.0% and 94.8%, respectively. The area under the ROC curve for ischemic stroke is 0.929 (95% CI 0.900 to 0.958). The haemorrhagic stroke risk estimation has a sensitivity and a specificity of 93.0% and 97.1%, respectively. The area under the ROC curve is 0.951 (95% CI 0.918 to 0.983).ConclusionA fast and fully automatic method can be used for stroke subtype risk assessment and classification based on fundus photographs alone.

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“…The difference in vessel density in the deep retinal plexus was not significant. A study on retinal structural and microvascular alterations in individuals with acute ischaemic stroke of various subtypes noted reduced vessel density, and the deep microvascular network was more sensitive to ischaemic stroke than was the superficial microvascular network [ 31 ]. However, another study displayed that decreased vessel density of the superficial retinal plexus could be a biomarker of SVD [ 32 ].…”

Section: Discussionmentioning

confidence: 99%

Reduced macular vessel density and inner retinal thickness correlate with the severity of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL)

et al. 2022

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Background Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), caused by mutations in NOTCH3, is the most common cause of hereditary cerebral small vessel disease. Whether it will involve systemic vasculopathy such as retinal vessel remains unknown. Optical coherence tomography angiography (OCT-A) is a noninvasive technique for visualising retinal blood flow. We analysed vessel density and retinal thickness in patients with CADASIL and investigated their correlations with disease severity. Methods This prospective study enrolled 35 patients with CADASIL (59 eyes) and 35 healthy controls (54 eyes). OCT-A was used to measure the vessel density of the macular region and the thickness of retinal layers. Patients with CADASIL were divided into stroke (n = 20) and nonstroke (n = 15) subgroups and underwent cognition and gait speed evaluation. Neuroimaging markers of cortical thickness, white matter hyperintensity, lacunae, and cerebral microbleeds were examined through brain magnetic resonance imaging. Results The OCT-A parameters, including vessel density, were comparable between the patients with CADASIL and the controls. In patients with CADASIL, vessel density in the superficial retinal plexus in the macula as was inner retinal thickness was significantly lower in the stroke than the nonstroke subgroup. Macular vessel density and inner retinal thickness were positively correlated with gait speed, while negatively correlated with number of lacunae. Conclusions OCT-A is potentially a useful tool for evaluating disease severity, ischaemic burden, and neurodegeneration in patients with advanced CADASIL.

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Retinal Structural and Microvascular Alterations in Different Acute Ischemic Stroke Subtypes

Cited by 20 publications

References 38 publications

Alterations of optic tract and retinal structure in patients after thalamic stroke

Alterations of optic tract and retinal structure in patients after thalamic stroke

Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis

Reduced macular vessel density and inner retinal thickness correlate with the severity of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL)

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