Evidence map›Paper›PMID 26090228›Full record

ArticleMultiple sclerosis international2015

Applying an Open-Source Segmentation Algorithm to Different OCT Devices in Multiple Sclerosis Patients and Healthy Controls: Implications for Clinical Trials.

Pavan Bhargava, Andrew Lang, Omar Al-Louzi, Aaron Carass, Jerry Prince, Peter A Calabresi, Shiv Saidha

Abstract read
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In one paragraph

Article in Multiple sclerosis international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Recurrent Self Fusion: Iterative Denoising for Consistent Retinal OCT Segmentation.Ophthalmic medical image analysis : 10th International Workshop, OMIA 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. OMIA (Workshop) (10th : 2023 : Vancouver, B.C. ; Online) · 2023
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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

7 authors.

Pavan BhargavaDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.ORCID 0000-0002-7947-9418
Andrew LangDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21287, USA.
Omar Al-LouziDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Aaron CarassDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21287, USA.
Jerry PrinceDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21287, USA.
Peter A CalabresiDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Shiv SaidhaDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.

Funding

Imaging Neurodegeneration in Multiple SclerosisR01NS082347 · NINDS · JOHNS HOPKINS UNIVERSITY · PI PETER A CALABRESI, Shiv Saidha · 2013 to 2026
$7.0M
3D segmentation and registration of macular SD-OCT for application in MSR01EY024655 · NEI · JOHNS HOPKINS UNIVERSITY · PI PRINCE, JERRY L · 2014 to 2017
$1.6M
NEI NIH HHS R01 EY024655NINDS NIH HHS R01 NS082347
6 · The paper itself

Abstract

Background. The lack of segmentation algorithms operative across optical coherence tomography (OCT) platforms hinders utility of retinal layer measures in MS trials. Objective. To determine cross-sectional and longitudinal agreement of retinal layer thicknesses derived from an open-source, fully-automated, segmentation algorithm, applied to two spectral-domain OCT devices. Methods. Cirrus HD-OCT and Spectralis OCT macular scans from 68 MS patients and 22 healthy controls were segmented. A longitudinal cohort comprising 51 subjects (mean follow-up: 1.4 ± 0.9 years) was also examined. Bland-Altman analyses and interscanner agreement indices were utilized to assess agreement between scanners. Results. Low mean differences (-2.16 to 0.26 μm) and narrow limits of agreement (LOA) were noted for ganglion cell and inner and outer nuclear layer thicknesses cross-sectionally. Longitudinally we found low mean differences (-0.195 to 0.21 μm) for changes in all layers, with wider LOA. Comparisons of rate of change in layer thicknesses over time revealed consistent results between the platforms. Conclusions. Retinal thickness measures for the majority of the retinal layers agree well cross-sectionally and longitudinally between the two scanners at the cohort level, with greater variability at the individual level. This open-source segmentation algorithm enables combining data from different OCT platforms, broadening utilization of OCT as an outcome measure in MS trials.

Identifiers

PMID26090228
PMCPMC4452193

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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.