Evidence map›Paper›PMID 35513028›Full record

ArticleAmerican journal of ophthalmology2022

Diagnostic Accuracy of Macular Thickness Map and Texture En Face Images for Detecting Glaucoma in Eyes With Axial High Myopia.

Christopher Bowd, Akram Belghith, Jasmin Rezapour, Mark Christopher, Leslie Hyman, Jost B Jonas, Robert N Weinreb, Linda M Zangwill

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PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 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

8 authors.

Christopher BowdFrom the Hamilton Glaucoma Center (C.B., A.B., J.R., M.C., R.N.W., L.M.Z.), Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California San Diego, La Jolla, California.
Akram BelghithFrom the Hamilton Glaucoma Center (C.B., A.B., J.R., M.C., R.N.W., L.M.Z.), Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California San Diego, La Jolla, California.
Jasmin RezapourFrom the Hamilton Glaucoma Center (C.B., A.B., J.R., M.C., R.N.W., L.M.Z.), Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California San Diego, La Jolla, California; Department of Ophthalmology (J.R.), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Mark ChristopherFrom the Hamilton Glaucoma Center (C.B., A.B., J.R., M.C., R.N.W., L.M.Z.), Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California San Diego, La Jolla, California.
Leslie HymanThe Vickie and Jack Farber Vision Research Center at Wills Eye, Wills Eye Hospital, Philadelphia PA (L.H.); Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia PA (L.H.).
Jost B JonasDepartment of Ophthalmology (J.B.J.), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Privatpraxis Prof Jonas und Dr Panda-Jonas (J.B.J.), Heidelberg, Germany; Institute of Molecular and Clinical Ophthalmology Basel (J.B.J.), Basel, Switzerland.
Robert N WeinrebFrom the Hamilton Glaucoma Center (C.B., A.B., J.R., M.C., R.N.W., L.M.Z.), Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California San Diego, La Jolla, California.
Linda M ZangwillFrom the Hamilton Glaucoma Center (C.B., A.B., J.R., M.C., R.N.W., L.M.Z.), Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California San Diego, La Jolla, California. Electronic address: lzangwill@health.ucsd.edu.

Funding

Vision BiostatisticsP30EY022589 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Radha Ayyagari · 2012 to 2026
$10.3M
Diagnostic Innovations in Glaucoma Study (DIGS): High Myopia and Advanced DiseaseR01EY027510 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LINDA M ZANGWILL · 2017 to 2026
$5.3M
Diagnosis and Monitoring of Glaucoma with Optical Coherence Tomography AngiographyR01EY029058 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WEINREB, ROBERT N · 2018 to 2024
$4.2M
Multimodal Artificial Intelligence to Predict Glaucomatous Progression and Surgical InterventionR01EY034146 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAXTER, SALLY LIU, CHRISTOPHER, MARK · 2022 to 2025
$1.8M
Deep Learning Approaches to Detect Glaucoma and Predict Progression from Spectral Domain Optical Coherence TomographyR00EY030942 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHRISTOPHER, MARK · 2023 to 2025
$747k
Machine Learning Methods for Detecting Disease-related Functional and Structural Change in GlaucomaR21EY027945 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BOWD, CHRISTOPHER · 2017 to 2018
$426k
AI-Based Identification of Rapid Glaucoma Progression to Guide Clinical Management and Accelerate Clinical TrialsR41EY034424 · NEI · AISIGHT HEALTH, INC. · PI TAFRESHI, ALI, ZANGWILL, LINDA M · 2022 to 2022
$240k
Deep Learning Approaches to Detect Glaucoma and Predict Progression from Spectral Domain Optical Coherence TomographyK99EY030942 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHRISTOPHER, MARK · 2020 to 2021
$235k
NEI NIH HHS K99 EY030942NEI NIH HHS P30 EY022589NEI NIH HHS R00 EY030942NEI NIH HHS R01 EY027510NEI NIH HHS R01 EY029058NEI NIH HHS R01 EY034146NEI NIH HHS R21 EY027945NEI NIH HHS R41 EY034424
6 · The paper itself

Abstract

purposeTo evaluate the diagnostic accuracy of a novel optical coherence tomography texture-based en face image analysis (SALSA-Texture) that requires segmentation of only 1 retinal layer for glaucoma detection in eyes with axial high myopia, and to compare SALSA-Texture with standard macular ganglion cell-inner plexiform layer (GCIPL) thickness, macular retinal nerve fiber layer (mRNFL) thickness, and ganglion cell complex (GCC) thickness maps.

designComparison of diagnostic approaches.

methodsCross-sectional data were collected from 92 eyes with primary open-angle glaucoma (POAG) and 44 healthy control eyes with axial high myopia (axial length >26 mm). Optical coherence tomography texture en face images, developed using SALSA-Texture to model the spatial arrangement patterns of the pixel intensities in a region, were generated from 70-μm slabs just below the vitreal border of the inner limiting membrane. Areas under the receiver operating characteristic curves (AUROCs) and areas under the precision recall curves (AUPRCs) adjusted for both eyes, axial length, age, disc area, and image quality were used to compare different approaches.

resultsThe best parameter-adjusted AUROCs (95% confidence intervals) for differentiating between healthy and glaucoma high myopic eyes were 0.92 (0.88-0.94) for texture en face images, 0.88 (0.86-0.91) for macular RNFL thickness, 0.87 (0.83-0.89) for macula GCIPL thickness, and 0.87 (0.84-0.89) for GCC thickness. A subset analysis of highly advanced myopic eyes (axial length ≥27 mm; 38 glaucomatous eyes and 22 healthy eyes) showed the best AUROC was 0.92 (0.89-0.94) for texture en face images compared with 0.86 (0.84-0.88) for macular GCIPL, 0.86 (0.84-0.88) for GCC, and 0.84 (0.81-0.87) for RNFL thickness (P ≤ .02 compared with texture for all comparisons).

conclusionThe current results suggest that our novel en face texture-based analysis method can improve on most investigated macular tissue thickness measurements for discriminating between highly myopic glaucomatous and highly myopic healthy eyes. While further investigation is needed, texture en face images show promise for improving the detection of glaucoma in eyes with high myopia where traditional retinal layer segmentation often is challenging.

Indexed as

GlaucomaGlaucoma, Open-AngleMyopiaCross-Sectional StudiesHumansIntraocular PressureRetinal Ganglion CellsROC CurveTomography, Optical Coherence

Identifiers

PMID35513028
PMCPMC10970712

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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.