Evidence map›Paper›PMID 39811265›Full record

ArticleOphthalmology science

Pivotal Trial Toward Effectiveness of Self-administered OCT in Neovascular Age-related Macular Degeneration. Report 2-Artificial Intelligence Analytics.

Eric W Schneider, Jeffrey S Heier, Nancy M Holekamp, Miguel A Busquets, Alan L Wagner, S Krishna Mukkamala, Christopher D Riemann, Seong Y Lee, Brian C Joondeph, Steven S Houston and 3 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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. A Novel Foundation Model-Based Framework for Multimodal Retinal Age Prediction.IEEE journal of translational engineering in health and medicine · 2025
    Article
  11. Article
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

13 authors.

Eric W SchneiderTennessee Retina, PC, Nashville, Tennessee.
Jeffrey S HeierOphthalmic Consultants of Boston, Boston, Massachusetts.
Nancy M HolekampMidwest Vision Research Foundation, Chesterfield, Missouri.
Miguel A BusquetsRetina Associates of Kentucky, Lexington, Kentucky.
Alan L WagnerWagner Kapoor Institute, Norfolk, Virginia.
S Krishna MukkamalaGeorgia Retina, Marietta, Georgia.
Christopher D RiemannCincinnati Eye Institute, Cincinnati, Ohio.
Seong Y LeeStrategic Clinical Research Group, LLC, Willow Park, Texas.
Brian C JoondephColorado Retina Associates, PC, Lakewood, Colorado.
Steven S HoustonFlorida Retina Institute, PA, Orlando, Florida.
Kester NahenNotal Vision Inc., Manassas, Virginia.
Nishant MohanNotal Vision Inc., Manassas, Virginia.
Gidi BenyaminiNotal Vision Inc., Manassas, Virginia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To validate the performance of the Notal OCT Analyzer (NOA) in processing self-administered OCT images from an OCT system designed for home use (home OCT [HOCT]) as part of a pivotal study aimed at achieving de novo United States Food and Drug Admininstration marketing authorization. Design: A prospective quantitative cross-sectional artificial intelligence study. Participants: The study enrolled adults aged ≥55 years diagnosed with neovascular age-related macular degeneration (nAMD) in ≥1 eligible eye with a best-corrected visual acuity of 20/320 or better. Methods: Participants self-imaged 4 times on each of 2 HOCT devices and once with an in-office OCT (IO-OCT) device during a single visit. Scans were segmented by the NOA and human graders at a certified reading center (RC). Main Outcome Measures: Intradevice and interdevice repeatability and reproducibility of total retinal hyporeflective (TRO) volume estimation by the NOA on HOCT-acquired images as compared with that of RC graders on IO-OCT-acquired images. Additionally, to assess the performance of the NOA in segmentation of TRO over multiple B-scans as compared with RC graders. Results: Self-imaging was performed successfully by 387 participants in 2451 of 2616 attempts (93.7%). For repeatability, the coefficient of variance for NOA was 11.1% for eyes with >10 volume units of TRO imaged with HOCT compared with 16.4% for RC graders segmenting IO-OCT images. The median DICE similarity coefficients for segmentation of TRO by NOA vs. Grader 1, Grader 2, and Grader 3; Grader 1 vs. Grader 2 and Grader 3; and Grader 2 vs. Grader 3 were 0.68, 0.68, 0.61, 0.72, 0.63, 0.70, respectively. Conclusions: The performance of NOA supports the intended use of the system as a tool to monitor TRO at home between routine clinical visits in support of the management of nAMD. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Age-related macular degenerationArtificial intelligenceHome OCTNeovascularTelemedicine

Identifiers

PMID39811265
PMCPMC11731483

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.