Evidence map›Paper›PMID 39120913›Full record

ArticleInvestigative ophthalmology & visual science2024

Topographic Measurement of the Subretinal Pigment Epithelium Space in Normal Aging and Age-Related Macular Degeneration Using High-Resolution OCT.

Jungeun Won, Hiroyuki Takahashi, Stefan B Ploner, Wenke Karbole, Omar Abu-Qamar, Antonio Yaghy, Anna Marmalidou, Stephanie Kaiser, Yunchan Hwang, Junhong Lin and 7 more

Abstract read
In one paragraph

Article in Investigative ophthalmology & visual science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

17 authors.

Jungeun WonDepartment of Electrical Engineering and Computer Science, and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Hiroyuki TakahashiDepartment of Electrical Engineering and Computer Science, and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Stefan B PlonerDepartment of Computer Science, Pattern Recognition Lab, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.
Wenke KarboleDepartment of Computer Science, Pattern Recognition Lab, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.
Omar Abu-QamarNew England Eye Center, School of Medicine, Tufts University, Boston, Massachusetts, United States.
Antonio YaghyNew England Eye Center, School of Medicine, Tufts University, Boston, Massachusetts, United States.
Anna MarmalidouNew England Eye Center, School of Medicine, Tufts University, Boston, Massachusetts, United States.
Stephanie KaiserNew England Eye Center, School of Medicine, Tufts University, Boston, Massachusetts, United States.
Yunchan HwangDepartment of Electrical Engineering and Computer Science, and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Junhong LinDepartment of Electrical Engineering and Computer Science, and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.
Andre WitkinNew England Eye Center, School of Medicine, Tufts University, Boston, Massachusetts, United States.
Shilpa DesaiNew England Eye Center, School of Medicine, Tufts University, Boston, Massachusetts, United States.
Caroline R BaumalNew England Eye Center, School of Medicine, Tufts University, Boston, Massachusetts, United States.
Andreas MaierDepartment of Computer Science, Pattern Recognition Lab, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.
Christine A CurcioDepartment of Ophthalmology and Visual Sciences, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States.
Nadia K WaheedNew England Eye Center, School of Medicine, Tufts University, Boston, Massachusetts, United States.
James G FujimotoDepartment of Electrical Engineering and Computer Science, and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States.

Funding

Novel Optical Diagnostics with Optical Coherence TomographyR01EY011289 · NEI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI JAMES G FUJIMOTO · 1995 to 2026
$9.5M
Functionally Validated Structural Endpoints for Early AMDR01EY029595 · NEI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI CURCIO, CHRISTINE A, OWSLEY, CYNTHIA · 2019 to 2023
$4.1M
The Human Foveal ConnectomeR01EY028282 · NEI · UNIVERSITY OF WASHINGTON · PI DENNIS MICHAEL DACEY · 2020 to 2026
$3.0M
Novel ultrahigh speed swept source OCT angiography methods in diabetic retinopathyR01EY034080 · NEI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI JAMES G FUJIMOTO, Nadia Waheed · 2023 to 2026
$1.9M
NEI NIH HHS R01 EY011289NEI NIH HHS R01 EY028282NEI NIH HHS R01 EY029595NEI NIH HHS R01 EY034080
6 · The paper itself

Abstract

Purpose: A micrometer scale hyporeflective band within the retinal pigment epithelium basal lamina - Bruch's membrane complex (RPE-BL-BrM) was topographically measured in aging and age-related macular degeneration (AMD). Methods: In a prospective cross-sectional study, 90 normal eyes from 76 subjects (range = 23-90 years) and 53 dry AMD eyes from 47 subjects (range = 62-91 years) were enrolled. Isotropic volume raster scans over 6 mm × 6 mm (500 × 500 A-scans) were acquired using a high-resolution (2.7 µm axial resolution) spectral-domain optical coherence tomography (SD-OCT) prototype instrument. Six consecutive optical coherence tomography (OCT) volumes were computationally motion-corrected and fused to improve feature visibility. A boundary regression neural network was developed to measure hyporeflective band thickness. Topographic dependence was evaluated over a 6-mm-diameter Early Treatment Diabetic Retinopathy Study (ETDRS) grid. Results: The hyporeflective band thickness map (median of 4.3 µm and 7.8 µm in normal and AMD eyes, respectively) is thicker below and radially symmetric around the fovea. In normal eyes, age-associated differences occur within 0.7 to 2.3 mm from the foveal center (P < 0.05). In AMD eyes, the hyporeflective band is hypothesized to be basal laminar deposits (BLamDs) and is thicker within the 3-mm ETDRS circle (P < 0.0002) compared with normal eyes. The inner ring is the most sensitive location to detect age versus AMD-associated changes within the RPE-BL-BrM. AMD eyes with subretinal drusenoid deposits (SDDs) have a significantly thicker hyporeflective band (P < 0.001) than those without SDDs. Conclusions: The hyporeflective band is a quantifiable biomarker which differentiates AMD from aging. Longitudinal studies are warranted. The hyporeflective band may be a useful biomarker for risk stratification and disease progression.

Indexed as

AgingRetinal Pigment EpitheliumTomography, Optical CoherenceAdultAgedAged, 80 and overBruch MembraneCross-Sectional StudiesFemaleHumansMacular DegenerationMaleMiddle AgedProspective StudiesYoung Adult

Identifiers

PMID39120913
PMCPMC11318361

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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.