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Three-dimensional assessment of vascular and perivascular characteristics in subjects with retinopathy of prematurity.

ABSTRACT: To study vascular features detected with spectral domain optical coherence tomography (SD-OCT) in subjects undergoing retinopathy of prematurity (ROP) screening.Cross-sectional study.Fifty-seven premature neonates, 10 with plus disease in at least 1 eye and 47 without plus disease.Bedside noncontact SD-OCT imaging was performed after obtaining parental consent on 97 consecutive infants between January 2009 and September 2012. Fifty-seven subjects (31-49 weeks' post-menstrual age) who had an SD-OCT scan in at least 1 eye showing the edge of the optic nerve and at least 1 major retinal vascular arcade were included. One eye per subject was randomly selected for analysis. Two masked graders evaluated scans for (1) retinal vessel elevation, (2) scalloped retinal layers, (3) hyporeflective vessels, and (4) retinal spaces. To coalesce the weight of these features, a Vascular Abnormality Score by OCT (VASO) was created. For quantitative assessment of vessel elevation, retinal surface maps were created.Prevalence of SD-OCT vascular abnormalities, the VASO, intergrader agreement, and presence of elevation on surface maps.From among 67 SD-OCT characteristics that were recorded, the most common characteristics found were vessel elevation (44%), hyporeflective vessels (40%), scalloped layers (22%), and retinal spaces (11%). Features significantly associated with plus disease were vessel elevation (P = 0.01), hyporeflective vessels (P = 0.04), and scalloped retinal layers (P = 0.006). Intragrader agreement was between 74% and 90% for all features. The VASO was significantly higher in subjects with plus disease (P = 0.0013). On 3-dimensional SD-OCT volumes, eyes with plus disease had greater retinal surface elevation that more often matched en face retinal vascular patterns.We present a novel 3-dimensional analysis of vascular and perivascular abnormalities identified in SD-OCT images of eyes with ROP. The SD-OCT characteristics that are more common in eyes with plus disease provide the first in vivo demonstration of the effects of vascular dilation and tortuosity on perivascular tissue. The VASO and surface maps also delineate the severity of vascular pathology in plus disease. Further studies evaluating these findings in eyes with pre-plus versus normal posterior pole vessels may determine the usefulness of SD-OCT in the early detection of vascular abnormalities in ROP.

SUBMITTER: Maldonado RS

PROVIDER: S-EPMC4070381 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Three-dimensional assessment of vascular and perivascular characteristics in subjects with retinopathy of prematurity.

Maldonado Ramiro S RS Yuan Eric E Tran-Viet Du D Rothman Adam L AL Tong Amy Y AY Wallace David K DK Freedman Sharon F SF Toth Cynthia A CA

Ophthalmology 20140121 6

<h4>Purpose</h4>To study vascular features detected with spectral domain optical coherence tomography (SD-OCT) in subjects undergoing retinopathy of prematurity (ROP) screening.<h4>Design</h4>Cross-sectional study.<h4>Participants and controls</h4>Fifty-seven premature neonates, 10 with plus disease in at least 1 eye and 47 without plus disease.<h4>Methods</h4>Bedside noncontact SD-OCT imaging was performed after obtaining parental consent on 97 consecutive infants between January 2009 and Septe ...[more]

PMID: 24461542

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Project description:BACKGROUND:The application of three-dimensional (3D) visualization techniques to evaluate the earliest visible onset of abnormal retinal vascular development in preterm infants with retinopathy of prematurity (ROP), using bedside non-contact optical coherence tomography (OCT) imaging to characterize morphology and sequential structural changes of abnormal extraretinal neovascularization. METHODS:Thirty-one preterm infants undergoing routine ROP screening with written informed consent for research imaging were enrolled in this prospective observational study. We imaged the macula and temporal periphery of preterm infants using a handheld OCT system (Envisu 2300 or handheld swept-source research system). The scans obtained were segmented and, using enhanced ray casting, were converted to 3D volumes to which color filter was applied. RESULTS:Using colorized 3D visualization, we defined extraretinal neovascular structures as buds, bridging networks, and placoid lesions. We could longitudinally follow progression and regression of extraretinal neovascularization in stage 3 ROP after treatment in one infant over 12 weeks and document the appearance of early buds, and formation of florid neovascularization. From stages 2 to 3 ROP, we observed progression from sessile buds to a complex plaque that corresponded to stage 3 ROP on clinical examination. We demonstrated regression of neovascular complexes to small pre-retinal tufts after treatment with anti-VEGF. CONCLUSIONS:The extension of OCT processing to include surface flattening and colorization that further improved structural analysis rendered better understanding of extraretinal tissue. Our ability to image similar areas in the same infant over multiple visits enabled us to study the evolution of these structural components and follow pathological vascular events longitudinally in development and regression after treatment. These methods can be applied to further study which are likely contribute to our understanding of the pathophysiology of neovascularization in ROP.

Project description:Importance:To prevent blindness, repeated infant eye examinations are performed to detect severe retinopathy of prematurity (ROP), yet only a small fraction of those screened need treatment. Early individual risk stratification would improve screening timing and efficiency and potentially reduce the risk of blindness. Objectives:To create and validate an easy-to-use prediction model using only birth characteristics and to describe a continuous hazard function for ROP treatment. Design, Setting, and Participants:In this retrospective cohort study, Swedish National Patient Registry data from infants screened for ROP (born between January 1, 2007, and August 7, 2018) were analyzed with Poisson regression for time-varying data (postnatal age, gestational age [GA], sex, birth weight, and important interactions) to develop an individualized predictive model for ROP treatment (called DIGIROP-Birth [Digital ROP]). The model was validated internally and externally (in US and European cohorts) and compared with 4 published prediction models. Main Outcomes and Measures:The study outcome was ROP treatment. The measures were estimated momentary and cumulative risks, hazard ratios with 95% CIs, area under the receiver operating characteristic curve (hereinafter referred to as AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results:Among 7609 infants (54.6% boys; mean [SD] GA, 28.1 [2.1] weeks; mean [SD] birth weight, 1119 [353] g), 442 (5.8%) were treated for ROP, including 142 (40.1%) treated of 354 born at less than 24 gestational weeks. Irrespective of GA, the risk for receiving ROP treatment increased during postnatal weeks 8 through 12 and decreased thereafter. Validations of DIGIROP-Birth for 24 to 30 weeks' GA showed high predictive ability for the model overall (AUC, 0.90 [95% CI, 0.89-0.92] for internal validation, 0.94 [95% CI, 0.90-0.98] for temporal validation, 0.87 [95% CI, 0.84-0.89] for US external validation, and 0.90 [95% CI, 0.85-0.95] for European external validation) by calendar periods and by race/ethnicity. The sensitivity, specificity, PPV, and NPV were numerically at least as high as those obtained from CHOP-ROP (Children's Hospital of Philadelphia-ROP), OMA-ROP (Omaha-ROP), WINROP (weight, insulinlike growth factor 1, neonatal, ROP), and CO-ROP (Colorado-ROP), models requiring more complex postnatal data. Conclusions and Relevance:This study validated an individualized prediction model for infants born at 24 to 30 weeks' GA, enabling early risk prediction of ROP treatment based on birth characteristics data. Postnatal age rather than postmenstrual age was a better predictive variable for the temporal risk of ROP treatment. The model is an accessible online application that appears to be generalizable and to have at least as good test statistics as other models requiring longitudinal neonatal data not always readily available to ophthalmologists.

Project description:The condition known as Plus disease is distinguished by atypical alterations in the retinal vasculature of neonates born prematurely. It has been demonstrated that the diagnosis of Plus disease is subjective and qualitative in nature. The utilization of quantitative methods and computer-based image analysis to enhance the objectivity of Plus disease diagnosis has been extensively established in the literature. This study presents the development of a computer-based image analysis method aimed at automatically distinguishing Plus images from non-Plus images. The proposed methodology conducts a quantitative analysis of the vascular characteristics linked to Plus disease, thereby aiding physicians in making informed judgments. A collection of 76 posterior retinal images from a diverse group of infants who underwent screening for Retinopathy of Prematurity (ROP) was obtained. A reference standard diagnosis was established as the majority of the labeling performed by three experts in ROP during two separate sessions. The process of segmenting retinal vessels was carried out using a semi-automatic methodology. Computer algorithms were developed to compute the tortuosity, dilation, and density of vessels in various retinal regions as potential discriminative characteristics. A classifier was provided with a set of selected features in order to distinguish between Plus images and non-Plus images. This study included 76 infants (49 [64.5%] boys) with mean birth weight of 1305 ± 427 g and mean gestational age of 29.3 ± 3 weeks. The average level of agreement among experts for the diagnosis of plus disease was found to be 79% with a standard deviation of 5.3%. In terms of intra-expert agreement, the average was 85% with a standard deviation of 3%. Furthermore, the average tortuosity of the five most tortuous vessels was significantly higher in Plus images compared to non-Plus images (p ≤ 0.0001). The curvature values based on points were found to be significantly higher in Plus images compared to non-Plus images (p ≤ 0.0001). The maximum diameter of vessels within a region extending 5-disc diameters away from the border of the optic disc (referred to as 5DD) exhibited a statistically significant increase in Plus images compared to non-Plus images (p ≤ 0.0001). The density of vessels in Plus images was found to be significantly higher compared to non-Plus images (p ≤ 0.0001). The classifier's accuracy in distinguishing between Plus and non-Plus images, as determined through tenfold cross-validation, was found to be 0.86 ± 0.01. This accuracy was observed to be higher than the diagnostic accuracy of one out of three experts when compared to the reference standard. The implemented algorithm in the current study demonstrated a commendable level of accuracy in detecting Plus disease in cases of retinopathy of prematurity, exhibiting comparable performance to that of expert diagnoses. By engaging in an objective analysis of the characteristics of vessels, there exists the possibility of conducting a quantitative assessment of the disease progression's features. The utilization of this automated system has the potential to enhance physicians' ability to diagnose Plus disease, thereby offering valuable contributions to the management of ROP through the integration of traditional ophthalmoscopy and image-based telemedicine methodologies.

Dataset Information

Three-dimensional assessment of vascular and perivascular characteristics in subjects with retinopathy of prematurity.

Publications

Three-dimensional assessment of vascular and perivascular characteristics in subjects with retinopathy of prematurity.

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