Age-related rarefaction in retinal vasculature is not linear

Azemin, Mohd Zulfaezal Che; Hamid, Fadilah Ab; Aminuddin, Amilia; Wang, J. J.; Kawasaki, Ryo; Kumar, Deepak

doi:10.1016/j.exer.2013.10.010

Cited by 15 publications

(20 citation statements)

References 21 publications

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“…The initial retinal image samples consisted of 852 right eye retinal images collected from those who attended IIUM Optometry Clinic at various time points from January 2009 till June 2012 as reported in the previous study [ 3 ]. Informed consent was obtained from the subjects and approval from the local ethics committee was granted in accordance with the principles laid down by the Declaration of Helsinki.…”

Section: Methodsmentioning

confidence: 99%

“…The use of this special camera enables the use of retinal image as a means for diagnosing vascular-related conditions. It is therefore not surprising that the retina has been extensively explored by researchers in various areas [ 1 – 3 ]. The retinal image has been widely used and has great significance in detecting various eye diseases which include the diabetic retinopathy [ 4 ], hypertensive retinopathy [ 5 ], and glaucoma [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

“…An important methodological consideration in quantitative measurement of retinal vasculature complexity is the effect of refractive error, lens opacity, and aging [ 3 , 12 ]. It is important to understand the influence of these parameters on the measurement of retinal fractal dimension.…”

Section: Introductionmentioning

confidence: 99%

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Influence of Refractive Condition on Retinal Vasculature Complexity in Younger Subjects

Azemin

Daud

Hamid

et al. 2014

The Scientific World Journal

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Objective. The aim of this study was to compare the retinal vasculature complexity between emmetropia, and myopia in younger subjects. Methods. A total of 82 patients (24.12 ± 1.25 years) with two types of refractive conditions, myopia and emmetropia were enrolled in this study. Refraction data were converted to spherical equivalent refraction. These retinal images (right eyes) were obtained from NAVIS Lite Image Filing System and the vasculature complexity was measured by fractal dimension (D f), quantified using a computer software following a standardized protocol. Results. There was a significant difference (P < 0.05) in the value of D f between emmetropic (1.5666 ± 0.0160) and myopic (1.5588 ± 0.0142) groups. A positive correlation (rho = 0.260, P < 0.05) between the D f and the spherical equivalent refraction was detected in this study. Using a linear model, it was estimated that 6.7% of the variation in D f could be explained by spherical equivalent refraction. Conclusions. This study provides valuable findings about the effect of moderate to high myopia on the fractal dimension of the retinal vasculature network. These results show that myopic refraction in younger subjects was associated with a decrease in D f, suggesting a loss of retinal vessel density with moderate to high myopia.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influence of Refractive Condition on Retinal Vasculature Complexity in Younger Subjects

Azemin

Daud

Hamid

et al. 2014

The Scientific World Journal

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“…The retinal microvasculature can be considered to be more dimensional than a line (1-dimensional), but less than a square (2-dimensional), hence a dimension between 1 and 2 can be attributed to this pattern with a higher number reflecting a more complex branching pattern. The retinal FD is associated with age (Azemin et al, 2012;Che Azemin et al, 2013;Wei et al, 2017), refractive error (Li et al, 2010Azemin et al, 2014;Yang et al, 2016;Al-Sheikh et al, 2017;Tai et al, 2017) and comorbidities (Avakian et al, 2002;Liew et al, 2008;Cheung et al, 2009Cheung et al, , 2011.…”

Section: Introduction Rationalementioning

confidence: 99%

Systematic Review on Fractal Dimension of the Retinal Vasculature in Neurodegeneration and Stroke: Assessment of a Potential Biomarker

et al. 2020

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Introduction: Ocular manifestations in several neurological pathologies accentuate the strong relationship between the eye and the brain. Retinal alterations in particular can serve as surrogates for cerebral changes. Offering a "window to the brain," the transparent eye enables non-invasive imaging of these changes in retinal structure and vasculature. Fractal dimension (FD) reflects the overall complexity of the retinal vasculature. Changes in FD could reflect subtle changes in the cerebral vasculature that correspond to preclinical stages of neurodegenerative diseases. In this review, the potential of this retinal vessel metric to serve as a biomarker in neurodegeneration and stroke will be explored.Methods: A literature search was conducted, following the PRISMA Statement 2009 criteria, in four large bibliographic databases (Pubmed, Embase, Web Of Science and Cochrane Library) up to 12 October 2019. Articles have been included based upon their relevance. Wherever possible, level of evidence (LOE) has been assessed by means of the Oxford Centre for Evidence-based Medicine Level of Evidence classification.Results: Twenty-one studies were included for qualitative synthesis. We performed a narrative synthesis and produced summary tables of findings of included papers because methodological heterogeneity precluded a meta-analysis. A significant association was found between decreased FD and neurodegenerative disease, mainly addressing cognitive impairment (CI) and dementia. In acute, subacute as well as chronic settings, decreased FD seems to be associated with stroke. Differences in FD between subtypes of ischemic stroke remain unclear. Conclusions:This review provides a summary of the scientific literature regarding the association between retinal FD and neurodegenerative disease and stroke. Central pathology is associated with a decreased FD, as a measure of microvascular network complexity. As retinal FD reflects the global integrity of the cerebral microvasculature, it is an attractive parameter to explore. Despite obvious concerns, mainly due to a lack of methodological standardization, retinal FD Lemmens et al.Retinal Fractals: Neurodegeneration and Stroke remains a promising non-invasive and low-cost diagnostic biomarker for neurodegenerative and cerebrovascular disease. Before FD can be implemented in clinic as a diagnostic biomarker, the research community should strive for uniformization and standardization.

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“…The proposed framework is able to reduce features from 16 to 4 dimensions and the performance is only decreased by 1% in average. This framework can be used when the number of retina images in the training set is dramatically increased [8][9][10] to reduce the computational time to model the ANN architecture.…”

Section: Discussionmentioning

confidence: 99%

Supervised vessel segmentation with minimal features

Azemin

Tamrin

2014

2014 IEEE 19th International Functional Electrical Stimulation Society Annual Conference (IFESS)

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Current state-of-the art supervised vessel segmentation methods require large number of feature vectors to construct a good model. In this paper, we propose a framework to optimally search for optimal features as inputs to Artificial Neural Network (ANN) trained by Scaled Conjugate Gradient (SCG). SCG is known to speed-up the learning stage in a supervised learning especially when error reduction is critical. The proposed framework is able to reduce features from 16 to 4 dimensions and the overall performance is only decreased by 1% in average.Index Terms-vessel segmentation, feature selection, artificial neural network, scaled conjugate gradient backpropation.

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Age-related rarefaction in retinal vasculature is not linear

Cited by 15 publications

References 21 publications

Influence of Refractive Condition on Retinal Vasculature Complexity in Younger Subjects

Influence of Refractive Condition on Retinal Vasculature Complexity in Younger Subjects

Systematic Review on Fractal Dimension of the Retinal Vasculature in Neurodegeneration and Stroke: Assessment of a Potential Biomarker

Supervised vessel segmentation with minimal features

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