Evidence map›Paper›PMID 36715449›Full record

ArticleJournal of neuroimaging : official journal of the American Society of Neuroimaging

T

Abigail R Manning, Erin S Beck, Matthew K Schindler, Govind Nair, Kelly A Clark, Prasanna Parvathaneni, Daniel S Reich, Russell T Shinohara, Andrew J Solomon

Open access · bronzeAbstract read
In one paragraph

Article in Journal of neuroimaging : official journal of the American Society of Neuroimaging. 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
2.0field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Decoding Gray Matter Involvement in Multiple Sclerosis via Imaging.Neuroimaging clinics of North America · 2024
    Review
  6. Observational
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

9 authors at 3 institutions in 1 country.

Abigail R ManningPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID 0000-0001-9221-5612
Erin S BeckDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Matthew K SchindlerDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID 0000-0003-0157-5669
Govind NairTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA.
Kelly A ClarkPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Prasanna ParvathaneniTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA.
Daniel S ReichTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA.
Russell T ShinoharaPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Andrew J SolomonDepartment of Neurological Sciences, Larner College of Medicine at The University of Vermont, Burlington, Vermont, USA.
National Institutes of Health · USUniversity of Pennsylvania · USUniversity 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
Advanced Statistical Analytics of MRI in MSR01NS112274 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2020 to 2024
$2.8M
NINDS NIH HHS R01 NS112274
6 · The paper itself

Abstract

background and purposeCortical demyelinated lesions are prevalent in multiple sclerosis (MS), associated with disability, and have recently been incorporated into MS diagnostic criteria. Presently, advanced and ultrahigh-field MRIs-not routinely available in clinical practice-are the most sensitive methods for detection of cortical lesions. Approaches utilizing MRI sequences obtainable in routine clinical practice remain an unmet need. We plan to assess the sensitivity of the ratio of T

methods3-Tesla and 7-Tesla MRI collected from 10 adults with MS were included in the study. T

resultsT

conclusionT

Indexed as

Multiple SclerosisAdultHumansMagnetic Resonance Imagingcortical lesionsMRImultiple sclerosis

Identifiers

PMID36715449
PMCPMC10175128
OpenAlexW4318542597

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.