Dataset Information

Monocular retinopathy of prematurity-like retinal vasculopathy in a dog.

ABSTRACT:

Purpose

To describe a case of monocular retinopathy of prematurity (ROP)-like vasculopathy without oxygen supplementation in the dog.

Methods

Fundus photographs (RetCam), spectral-domain optical coherence tomography (sdOCT), confocal scanning laser ophthalmoscopy (cSLO), and fluorescein angiography (FA), as well as postmortem histology and immunohistochemistry (Collagen IV and anti-vWF antibodies), were carried out to characterize the vascular abnormalities.

Results

Ophthalmic examination showed peripheral and mid-temporal avascular areas in the tapetal region, neovascularization and abnormally dilated and tortuous retinal vessels in the left eye. sdOCT demonstrated not only cross-sectional views of preretinal fibrovascular proliferation but also extensive proliferation extraretinally into the vitreous. FA emphasized demarcation of vascular and avascular zones with neovascular tufts "popcorns." Histology and immunohistochemistry confirmed presence of abnormally dilated vessels and the intravitreal blood vessels.

Conclusions

ROP is a disease of abnormally developed retinal vascularization associated with oxygen supplementation therapy, potentially causing blindness in premature infants. Although the mechanism of ROP-like vasculopathy in our case is unclear, it is important to appreciate that the abnormal vascular pattern seen in ROP in premature infants can occur in canines without oxygen administration.

SUBMITTER: Sato Y

PROVIDER: S-EPMC9548383 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Publications

Monocular retinopathy of prematurity-like retinal vasculopathy in a dog.

Sato Yu Y Gray Alexa A Takahashi Kei K Dufour Valerie V Lutty Gerard G Miyadera Keiko K Aguirre Gustavo G

Veterinary ophthalmology 20211203 1

<h4>Purpose</h4>To describe a case of monocular retinopathy of prematurity (ROP)-like vasculopathy without oxygen supplementation in the dog.<h4>Methods</h4>Fundus photographs (RetCam), spectral-domain optical coherence tomography (sdOCT), confocal scanning laser ophthalmoscopy (cSLO), and fluorescein angiography (FA), as well as postmortem histology and immunohistochemistry (Collagen IV and anti-vWF antibodies), were carried out to characterize the vascular abnormalities.<h4>Results</h4>Ophthal ...[more]

PMID: 34861080

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Project description:TopicRetinopathy of prematurity (ROP) is a proliferative retinal vascular disease in premature infants, and is a major cause of childhood blindness worldwide. In addition to known clinical risk factors such as low birth weight and gestational age, there is a growing body of evidence supporting a genetic basis for ROP.Clinical relevanceWhile comorbidities and environmental factors have been identified as contributing to ROP outcomes in premature infants, most notably gestational age and oxygen, some infants progress to severe disease despite absence of these clinical risk factors. The contribution of genetic factors may explain these differences and allow better detection and treatment of infants at risk for severe ROP.MethodsTo comprehensively review genetic factors that potentially contribute to the development and severity of ROP, we conducted a literature search focusing on the genetic basis for ROP. Terms related to other heritable retinal vascular diseases like "familial exudative vitreoretinopathy", as well as to genes implicated in animal models of ROP, were also used to capture research in diseases with similar pathogenesis to ROP in humans with known genetic components.ResultsContributions across several genetic domains are described including vascular endothelial growth factor, the Wnt signaling pathway, insulin-like growth factor 1, inflammatory mediators, and brain-derived neurotrophic factor.ConclusionsMost candidate gene studies of ROP have limitations such as inability to replicate results, conflicting results from various studies, small sample size, and differences in clinical characterization. Additional difficulty arises in separating the contribution of genetic factors like Wnt signaling to ROP and prematurity. Although studies have implicated involvement of multiple signaling pathways in ROP, the genetics of ROP have not been clearly elucidated. Next-generation sequencing and genome-wide association studies have potential to expand future understanding of underlying genetic risk factors and pathophysiology of ROP.

Project description:ImportanceA retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of ROP to improve visual outcomes.ObjectiveTo develop a retinal image-based, multidimensional, automated, deep learning platform for ROP screening and validate its performance accuracy.Design, setting, and participantsA total of 14 108 eyes of 8652 preterm infants who received ROP screening from 4 centers from November 4, 2010, to November 14, 2019, were included, and a total of 52 249 retinal images were randomly split into training, validation, and test sets. Four main dimensional independent classifiers were developed, including image quality, any stage of ROP, intraocular hemorrhage, and preplus/plus disease. Referral-warranted ROP was automatically generated by integrating the results of 4 classifiers at the image, eye, and patient levels. DeepSHAP, a method based on DeepLIFT and Shapley values (solution concepts in cooperative game theory), was adopted as the heat map technology to explain the predictions. The performance of the platform was further validated as compared with that of the experienced ROP experts. Data were analyzed from February 12, 2020, to June 24, 2020.ExposureA deep learning algorithm.Main outcomes and measuresThe performance of each classifier included true negative, false positive, false negative, true positive, F1 score, sensitivity, specificity, receiver operating characteristic, area under curve (AUC), and Cohen unweighted κ.ResultsA total of 14 108 eyes of 8652 preterm infants (mean [SD] gestational age, 32.9 [3.1] weeks; 4818 boys [60.4%] of 7973 with known sex) received ROP screening. The performance of all classifiers achieved an F1 score of 0.718 to 0.981, a sensitivity of 0.918 to 0.982, a specificity of 0.949 to 0.992, and an AUC of 0.983 to 0.998, whereas that of the referral system achieved an F1 score of 0.898 to 0.956, a sensitivity of 0.981 to 0.986, a specificity of 0.939 to 0.974, and an AUC of 0.9901 to 0.9956. Fine-grained and class-discriminative heat maps were generated by DeepSHAP in real time. The platform achieved a Cohen unweighted κ of 0.86 to 0.98 compared with a Cohen κ of 0.93 to 0.98 by the ROP experts.Conclusions and relevanceIn this diagnostic study, an automated ROP screening platform was able to identify and classify multidimensional pathologic lesions in the retinal images. This platform may be able to assist routine ROP screening in general and children hospitals.

Dataset Information

Monocular retinopathy of prematurity-like retinal vasculopathy in a dog.

Purpose

Methods

Results

Conclusions

Publications

Monocular retinopathy of prematurity-like retinal vasculopathy in a dog.

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