Evidence map›Paper›PMID 28210541›Full record

ArticleNeuroImage. Clinical2017

A T1 and DTI fused 3D corpus callosum analysis in MCI subjects with high and low cardiovascular risk profile.

Yi Lao, Binh Nguyen, Sinchai Tsao, Niharika Gajawelli, Meng Law, Helena Chui, Michael Weiner, Yalin Wang, Natasha Leporé

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage. Clinical, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

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  8. Multivariate surface-based analysis of corpus callosum in patients with sickle cell disease.Proceedings of SPIE--the International Society for Optical Engineering · 2016
    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

9 authors at 4 institutions in 1 country.

Yi LaoCIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA; Department of Biomedical Engineering, University of Southern California, USA.
Binh NguyenCIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA.
Sinchai TsaoCIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA.
Niharika GajawelliCIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA; Department of Biomedical Engineering, University of Southern California, USA.
Meng LawDepartment of Biomedical Engineering, University of Southern California, USA; Department of Radiology, Keck School of Medicine, University of Southern California, USA.
Helena ChuiDepartment of Biomedical Engineering, University of Southern California, USA; Department of Radiology, Keck School of Medicine, University of Southern California, USA.
Michael WeinerDepartment of Radiology, University of California, San Francisco, USA.
Yalin WangSchool of Computing, Informatics, and Decision Systems Engineering, Arizona State University, USA.
Natasha LeporéCIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA; Department of Biomedical Engineering, University of Southern California, USA.
Children's Hospital of Los Angeles · USUniversity of Southern California · USDecision Systems (United States) · USUniversity of California, San Francisco · US

Funding

VASCULAR RISK AND COGNITIVE STATUS IN A LATINO POPULATIONP50AG005142 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ARANDA, MARIA P. · 1985 to 2019
$41.0M
The Aging Brain: Vasculature, Ischemia, and BehaviorP01AG012435 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI REED, BRUCE · 1994 to 2012
$26.4M
Multi-Source Sparse Learning to Identify MCI and Predict DeclineRF1AG051710 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI THOMPSON, PAUL M, WANG, YALIN · 2016 to 2016
$2.8M
Empowering Diffusion MRI Measures by Integrating White and Grey Matter MorphologyR21AG049216 · NIA · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI WANG, YALIN · 2015 to 2016
$381k
NIA NIH HHS P01 AG012435NIA NIH HHS P50 AG005142
6 · The paper itself

Abstract

Understanding the extent to which vascular disease and its risk factors are associated with prodromal dementia, notably Alzheimer's disease (AD), may enhance predictive accuracy as well as guide early interventions. One promising avenue to determine this relationship consists of looking for reliable and sensitive

Indexed as

AgedAged, 80 and overBrain MappingCardiovascular DiseasesCognitive DysfunctionCorpus CallosumDisease ProgressionFemaleHumansImaging, Three-DimensionalMagnetic Resonance ImagingMaleRisk FactorsStatistics as TopicAlzheimer's diseaseCardiovascular diseaseCognitive disordersCorpus callosumDementiaDTIMild cognitive impairmentT1

Identifiers

PMID28210541
PMCPMC5299209
OpenAlexW2562780308

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.