Dataset Information

Written in Blood: Applying Shape Grammars to Retinal Vasculatures.

ABSTRACT: Purpose:Blood vessel networks within the retina are crucial for maintaining tissue perfusion and therefore good vision. Their complexity and unique patterns often require a steep learning curve for humans to identify trends and changes in the shape and topology of the networks, even though there exists much information important to identifying disease within them. Methods:Through image processing, the vasculature is isolated from other features of the fundus images, forcing the viewer to focus on the complex vascular feature. This article explores an approach using a grammar based on shape to describe retinal vasculature and to generate realistic and increasingly unrealistic artificial vascular networks that are then reviewed by ophthalmologists via digital survey. The ophthalmologists are asked whether these artificial vascular networks appeared realistic or unrealistic. Results:With only three rules (initiate, branch, and curve), the grammar accomplishes these goals. Networks are generated by adding noise to rule parameters present in existing networks. Via the survey of synthetic networks generated with different noise parameters, a correlation between noise in the branch rule and realistic association is revealed. Conclusions:By creating a language to describe retinal vasculature, this article allows for the potential of new insight into such an important but less understood feature of the retina, which in the future may play a role in diagnosing or helping to predict types of ocular disease. Translational Relevance:Applying shape grammar to describe retinal vasculature permits new understanding, which in turn provides the potential for new diagnostic tools.

SUBMITTER: Yeh RY

PROVIDER: S-EPMC7453052 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Written in Blood: Applying Shape Grammars to Retinal Vasculatures.

Yeh Ryan Y RY Nischal Ken K KK LeDuc Philip P Cagan Jonathan J

Translational vision science & technology 20200824 9

<h4>Purpose</h4>Blood vessel networks within the retina are crucial for maintaining tissue perfusion and therefore good vision. Their complexity and unique patterns often require a steep learning curve for humans to identify trends and changes in the shape and topology of the networks, even though there exists much information important to identifying disease within them.<h4>Methods</h4>Through image processing, the vasculature is isolated from other features of the fundus images, forcing the vi ...[more]

PMID: 32908799

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Project description:IntroductionRetinal detachment is a sight-threatening emergency, with more than half of those affected suffering permanent visual impairment. A diagnostic test to identify eyes at risk before vision is threatened would enable exploration of prophylactic treatment. This report presents the use of irregularities in retinal shape, quantified from optical coherence tomography (OCT) images, as a biomarker for retinal detachment.MethodsOCT images were taken from posterior and mid-peripheral retina of 264 individuals [97 after a posterior vitreous detachment (PVD), 99 after vitrectomy for retinal detachment and 68 after laser for a retinal tear]. Diagnoses were taken from history, examination and OCT. Retinal irregularity was quantified in the frequency domain, and the distribution of irregularity across the regions of the eye was explored to identify features exhibiting the greatest difference between retinal detachment and PVD eyes. Two of these features plus axial length were used to train a quadratic discriminant analysis classifier. Classifier performance was assessed by its sensitivity and specificity in identifying retinal detachment eyes and visualised with a receiver operating characteristic (ROC) curve.ResultsValidation set specificity was 84% (44/52 PVD eyes correctly labelled) and sensitivity 35% (23/64 retinal detachment eyes identified, p = 0.02). Area under the ROC curve was 0.75 (95% confidence intervals 0.58-0.85). Retinal detachment eyes were significantly more irregular than PVD eyes in the superior retina (0.70 mm versus 0.49 mm, p < 0.05) and supero-temporal retina (1.12 mm versus 0.80 mm, p < 0.05). Lower sensitivity (16/68, 24%) was seen for eyes with a retinal tear without detachment, that were intermediate in size between retinal detachment and PVD eyes. Axial length on its own was a poor classifier. Neither irregularity nor classification were affected by surgery for retinal detachment or the development of PVD.ConclusionsThe classifier identified 1/3 of retinal detachment eyes in this sample. In future work, these features can be evaluated as a test for retinal detachment prior to PVD.

Dataset Information

Written in Blood: Applying Shape Grammars to Retinal Vasculatures.

Publications

Written in Blood: Applying Shape Grammars to Retinal Vasculatures.

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