Evidence map›Paper›PMID 39866345›Full record

ArticleOphthalmology science

Automated Quantification of Retinopathy of Prematurity Stage via Ultrawidefield OCT.

Spencer S Burt, Aaron S Coyner, Elizabeth V Roti, Yakub Bayhaqi, John Jackson, Mani K Woodward, Shuibin Ni, Susan R Ostmo, Guangru Liang, Yali Jia and 5 more

Abstract read
In one paragraph

Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Spencer S BurtCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Aaron S CoynerCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Elizabeth V RotiCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Yakub BayhaqiCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
John JacksonCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Mani K WoodwardCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Shuibin NiCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Susan R OstmoCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Guangru LiangCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Yali JiaCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
David HuangCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Michael F ChiangNational Eye Institute, National Institutes of Health, Bethesda, Maryland.
Benjamin K YoungCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
Yifan JianCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.
John Peter CampbellCasey Eye Institute, Oregon Health and Science University, Portland, Oregon.

Funding

Proteomics CoreP30EY010572 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI Kate E Keller · 1995 to 2026
$19.4M
Clinical and Genetic Analysis of Retinopathy of PrematurityR01EY019474 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI CAMPBELL, JOHN PETER · 2010 to 2020
$7.0M
OCTA Precursors of Vision-Threatening Complications of Diabetic RetinopathyR01EY035410 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI Thomas Hwang, Yali Jia · 2023 to 2026
$2.5M
Artificial Intelligence Assisted Panoramic Optical Coherence Tomography Angiography for Retinopathy of PrematurityR01HD107494 · NICHD · OREGON HEALTH & SCIENCE UNIVERSITY · PI John Peter Campbell, Yifan Jian · 2021 to 2026
$2.4M
NEI NIH HHS P30 EY010572NEI NIH HHS R01 EY019474NEI NIH HHS R01 EY035410NICHD NIH HHS R01 HD107494
6 · The paper itself

Abstract

Purpose: Retinopathy of prematurity (ROP) stage is defined by the visual appearance of the vascular-avascular border, which reflects a spectrum of pathologic neurovascular tissue (NVT). Previous work demonstrated that the thickness of the ridge lesion, measured using OCT, corresponds to higher clinical diagnosis of stage. This study evaluates whether the volume of anomalous NVT (ANVTV), defined as abnormal tissue protruding from the regular contour of the retina, can be measured automatically using deep learning to develop quantitative OCT-based biomarkers in ROP. Design: Single-center retrospective case series. Participants: Thirty-three infants with ROP in the Oregon Health & Science University neonatal intensive care unit. Methods: OCT B-scans were collected using an investigational ultrawidefield OCT. The ANVTV was manually segmented. A set of 3347 B-scans and corresponding manual segmentations from 12 volumes from 6 patients were used to train an automated segmentation tool using a U-Net. An additional held-out test data set of 60 B-scans from 6 infants was used to evaluate model performance. The Dice-Sorensen coefficient (DSC) comparing manual and automated segmentation of ANVTV was calculated. Scans from 21 additional infants were used for clinical evaluation of ANVTV using the visit in which they had developed their peak stage of ROP. Each infant had every B-scan in a volume automatically segmented for ANVTV (total number of segmented voxels within the 60° temporal to the optic disc). The ANVTV was compared between infants with stage 1 to 3 ROP using a Kruskal-Wallis test and tracked over time in all infants with stage 3 ROP. Main Outcome Measurements: Cross sectional and longitudinal association between ANVTV and stages 1 to 3 ROP. Results: Comparing automated and manual segmentation of ANVTV achieved a DSC of 0.61 ± 0.13. Using the U-Net, ANVTV was associated with higher disease stage both cross sectionally and longitudinally. Median ANVTV significantly increased as ROP stage worsened from 1 (0, [interquartile range: 0-0] kilovoxels) to 2 (170.1 [interquartile range: 104.2-183.6] kilovoxels) to 3 (421.4 [interquartile range: 312.3-1110.8] kilovoxels; Conclusions: Automated OCT-based measurement of ANVTV was associated with clinical disease stage in ROP, both cross sectionally and longitudinally. Ultrawidefield-OCT may facilitate more objective screening, diagnosis, and monitoring in the future. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Anomalous neurovascular tissueIsolated retinal neovascularizationOptical coherence tomographyRetinopathy of prematurityRidge

Identifiers

PMID39866345
PMCPMC11760822

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.