Evidence map›Paper›PMID 30213803›Full record

ArticleAJNR. American journal of neuroradiology2018

Automated Integration of Multimodal MRI for the Probabilistic Detection of the Central Vein Sign in White Matter Lesions.

J D Dworkin, P Sati, A Solomon, D L Pham, R Watts, M L Martin, D Ontaneda, M K Schindler, D S Reich, R T Shinohara

Open access · hybridAbstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 13% of its field
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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Neurodegeneration in multiple sclerosis.WIREs mechanisms of disease · 2023
    Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Detection of central vein should be part of MS diagnostic criteria - Commentary.Multiple sclerosis (Houndmills, Basingstoke, England) · 2020
    Article
  18. Review
  19. The Central Vein Sign in Radiologically Isolated Syndrome.AJNR. American journal of neuroradiology · 2019
    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

10 authors at 6 institutions in 2 countries.

J D DworkinFrom the Department of Biostatistics, Epidemiology, and Informatics (J.D.D., M.L.M., R.T.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania jdwor@pennmedicine.upenn.edu.ORCID 0000-0002-5720-1298
P SatiTranslational Neuroradiology Section (P.S., M.K.S., D.S.R.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-9325-3570
A SolomonDepartments of Neurological Sciences (A.S.).ORCID 0000-0003-1602-1554
D L PhamCenter for Neuroscience and Regenerative Medicine (D.L.P.), Henry M. Jackson Foundation, Bethesda, Maryland.ORCID 0000-0003-0053-2034
R WattsRadiology (R.W.), Larner College of Medicine at the University of Vermont, Burlington, Vermont.ORCID 0000-0003-1026-2293
M L MartinFrom the Department of Biostatistics, Epidemiology, and Informatics (J.D.D., M.L.M., R.T.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.ORCID 0000-0001-8631-5596
D OntanedaMellen Center for Multiple Sclerosis Treatment and Research (D.O.), Cleveland Clinic, Cleveland, Ohio.ORCID 0000-0002-2838-9148
M K SchindlerTranslational Neuroradiology Section (P.S., M.K.S., D.S.R.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0003-3505-5362
D S ReichTranslational Neuroradiology Section (P.S., M.K.S., D.S.R.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-2628-4334
R T ShinoharaFrom the Department of Biostatistics, Epidemiology, and Informatics (J.D.D., M.L.M., R.T.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.ORCID 0000-0001-8627-8203
National Institutes of Health · USUniversity of Pennsylvania · USCleveland Clinic · USHenry M. Jackson Foundation · USInstitute of Neurological Sciences · ITUniversity of Vermont · US

Funding

Multimodal MRI in Multiple SclerosisZIANS003119 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI REICH, DANIEL · 2010 to 2025
$53.4M
Statistical Methods for Multilevel Multivariate Functional StudiesR01NS060910 · NINDS · JOHNS HOPKINS UNIVERSITY · PI Ciprian M Crainiceanu · 2009 to 2026
$8.3M
Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Adaptive Large-Scale Framework for Automatic Biomedical Image SegmentationR01EB017255 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI YUSHKEVICH, PAUL A. · 2014 to 2018
$3.0M
Statistical methods for large and complex databases of ultra-high-dimensionalR01NS085211 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2013 to 2017
$1.8M
Spatiotemporal Modeling of MRI Brain Lesion Trajectories of Biomarker DiscoveryR21NS093349 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI ELOYAN, ANI, SHINOHARA, RUSSELL TAKESHI · 2016 to 2017
$454k
Intramural NIH HHS ZIA NS003119NIBIB NIH HHS R01 EB017255NIMH NIH HHS R01 MH112847NINDS NIH HHS R01 NS060910NINDS NIH HHS R01 NS085211NINDS NIH HHS R21 NS093349
6 · The paper itself

Abstract

background and purposeThe central vein sign is a promising MR imaging diagnostic biomarker for multiple sclerosis. Recent studies have demonstrated that patients with MS have higher proportions of white matter lesions with the central vein sign compared with those with diseases that mimic MS on MR imaging. However, the clinical application of the central vein sign as a biomarker is limited by interrater differences in the adjudication of the central vein sign as well as the time burden required for the determination of the central vein sign for each lesion in a patient's full MR imaging scan. In this study, we present an automated technique for the detection of the central vein sign in white matter lesions. MATERIALS AND

methodsUsing multimodal MR imaging, the proposed method derives a central vein sign probability, π

resultsBy means of the proposed automated technique, participants with MS were found to have significantly higher values of ψ than those without MS (ψ

conclusionsThe current study presents the first fully automated method for detecting the central vein sign in white matter lesions and demonstrates promising performance in a sample of patients with and without MS.

Indexed as

AlgorithmsAdultBrainFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMultiple SclerosisNeuroimagingVeinsWhite Matter

Identifiers

PMID30213803
PMCPMC6177309
OpenAlexW2892251979

What OpenQuestion holds

Textmetadata
LicenceTDM
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.