Retinal vessel multifractals predict pial collateral status in patients with acute ischemic stroke

Khan, Adnan; Boever, Patrick De; Gerrits, Nele; Akhtar, Naveed; Saqqur, Maher; Ponirakis, Georgios; Gad, Hoda; Petropoulos, Ioannis N.; Shuaib, Ashfaq; Faber, James E.; Kamran, Saadat; Malik, Rayaz A.

doi:10.1371/journal.pone.0267837

Cited by 9 publications

(5 citation statements)

References 48 publications

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“…These findings need to be confirmed on larger studies, and the usefulness of these metrics in patients with intra-or extracranial vascular stenosis or occlusion prior to ischemic stroke remains to be explored. 55…”

Section: Other Methods To Assess the Collateral Circulationmentioning

confidence: 99%

Collateral Circulation in Ischemic Stroke: An Updated Review

Maguida

Shuaib

2023

J Stroke

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The collateral circulation plays a crucial role in maintaining perfusion to brain tissue in ischemic stroke, which prolongs the time window for effective therapies to be provided and ultimately avoids irreversible damage that may lead to worse clinical outcomes. The understanding of this complex vascular bypass system has advanced greatly in the past few years, yet effective treatments for its potentiation as a therapeutic target remain a challenge. The assessment of the collateral circulation is now part of the routine neuroimaging protocols for acute ischemic stroke, which provides a more complete pathophysiological picture in each patient that allows for a better selection for acute reperfusion therapies and a more accurate prognostication of outcomes, among other potential uses. In this review, we aim to provide a structured and updated approach to the collateral circulation while highlighting ongoing research areas with promising future clinical applications.

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Section: Other Methods To Assess the Collateral Circulationmentioning

confidence: 99%

Collateral Circulation in Ischemic Stroke: An Updated Review

Maguida

Shuaib

2023

J Stroke

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“…Other investigations using retinal image information for clinical application are starting to appear. For example, a recent study shows that multifractals of the retinal vessel can be used to predict pial collateral status for patients with ischemic stroke ( 47 ).…”

Section: Discussionmentioning

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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“…Retinal images were arranged, organized, and prepared for analysis. A trained operator, without any previous knowledge about the details of the study, used the semi-automated MONA REVA software (VITO, Mol, Belgium; [ 27 ]) to analyze the retinal images. The software automatically processed the retinal images and analyzed the diameters of retinal microvessels in areas 0.5 to 1 of the optic disc radius from the optic disc margin.…”

Section: Methodsmentioning

confidence: 99%

Vascular Responses following Light Therapy: A Pilot Study with Healthy Volunteers

Salon

Brix

Neshev

et al. 2023

JCM

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(1) Background: Studies have reported the effectiveness of light therapy in various medical conditions. Our pilot study aimed to assess the effect of Maharishi light therapy (MLT) on physiological parameters, such as the heart rate (HR), HR variability (HRV), blood pressure (BP), BP variability (BPV), and the retinal microvasculature of healthy participants; (2) Methodology: Thirty (14 males and 16 females) healthy, non-smoking participants between 23 and 71 years old (46 ± 18 years) were included in this randomized crossover study. Each participant was tested with a placebo (using LED light) and gem lights, 24 h apart. Hemodynamic parameters were recorded during the session, and 24 h heart rate and BP levels were assessed via mobile devices. Retinal vascular responses were captured with fundus images and the subsequent analysis of retinal vessel widths. A linear model, using repeated measures ANOVA, was used to compare the responses across the sexes and to assess the effect of the MLT; (3) Results: Changes in the central retinal artery equivalent (CRAE) (p < 0.001) and central retinal vein equivalent (CRVE) (p = 0.002) parameters were observed. CRAE and CRVE decreased under MLT and increased under the placebo condition from before to after. However, the baseline values of the participants already differed significantly before the application of any therapy, and the variation in the retinal vessel diameters was already large in the baseline measurements. This suggests that the observed effect results may only reflect naturally occurring fluctuations in the microcirculation and not the effect of MLT. Furthermore, no significant effects were observed in any other investigated parameters; (4) Conclusion: Our study with healthy participants finds significant changes in retinal parameters, but the biological variation in the baseline measurements was large to begin with. This suggests that the observed effect results only reflect naturally occurring fluctuations in the microcirculation and not the effect of MLT. However, in the future, larger studies in which MLT is applied for longer periods and/or in patients with different diseases could discover the physiological impacts of this type of therapy.

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Retinal vessel multifractals predict pial collateral status in patients with acute ischemic stroke

Cited by 9 publications

References 48 publications

Collateral Circulation in Ischemic Stroke: An Updated Review

Collateral Circulation in Ischemic Stroke: An Updated Review

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

Vascular Responses following Light Therapy: A Pilot Study with Healthy Volunteers

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