Evidence map›Paper›PMID 31602086›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2019

Consideration of Cerebrospinal Fluid Intensity Variation in Diffusion Weighted MRI.

Colin B Hansen, Vishwesh Nath, Allison E Hainline, Kurt G Schilling, Prasanna Parvathaneni, Roza G Bayrak, Justin A Blaber, Owen Williams, Susan Resnick, Lori Beason-Held and 5 more

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. 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

15 authors.

Colin B HansenComputer Science, Vanderbilt University, Nashville, TN, USA.
Vishwesh NathComputer Science, Vanderbilt University, Nashville, TN, USA.
Allison E HainlineBiostatistics, Vanderbilt University, Nashville, TN, USA.
Kurt G SchillingDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN USA.
Prasanna ParvathaneniElectrical Engineering, Vanderbilt University, Nashville, TN, USA.
Roza G BayrakComputer Science, Vanderbilt University, Nashville, TN, USA.
Justin A BlaberElectrical Engineering, Vanderbilt University, Nashville, TN, USA.
Owen WilliamsNational Institutes of Health, Bethesda, MD.
Susan ResnickNational Institutes of Health, Bethesda, MD.
Lori Beason-HeldNational Institutes of Health, Bethesda, MD.
Okan IrfanogluNational Institute of Biomedical Imaging and Bioengineering, Bethesda MD USA.
Carlo PierpaoliNational Institute of Biomedical Imaging and Bioengineering, Bethesda MD USA.
Adam W AndersonDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN USA.
Baxter P RogersDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN USA.
Bennett A LandmanComputer Science, Vanderbilt University, Nashville, TN, USA.

Funding

VANDERBILT UNIVERSITY CTSA FOR PEDIATRIC RESEARCHUL1RR024975 · NCRR · VANDERBILT UNIVERSITY · PI BERNARD, GORDON RAPHAEL · 2007 to 2011
$45.7M
The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Postdoctoral Training in Biomedical MRI and MRST32EB001628 · NIBIB · VANDERBILT UNIVERSITY MEDICAL CENTER · PI John C Gore · 2003 to 2026
$7.0M
Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRIR01EB017230 · NIBIB · VANDERBILT UNIVERSITY · PI LANDMAN, BENNETT A. · 2015 to 2024
$5.1M
NCATS NIH HHS UL1 TR000445NCRR NIH HHS UL1 RR024975NIBIB NIH HHS R01 EB017230NIBIB NIH HHS T32 EB001628
6 · The paper itself

Abstract

Diffusion weighted MRI (DW-MRI) depends on accurate quantification signal intensities that reflect directional apparent diffusion coefficients (ADC). Signal drift and fluctuations during imaging can cause systematic non-linearities that manifest as ADC changes if not corrected. Here, we present a case study on a large longitudinal dataset of typical diffusion tensor imaging. We investigate observed variation in the cerebral spinal fluid (CSF) regions of the brain, which should represent compartments with isotropic diffusivity. The study contains 3949 DW-MRI acquisitions of the human brain with 918 subjects and 542 with repeated scan sessions. We provide an analysis of the inter-scan, inter-session, and intra-session variation and an analysis of the associations with the applied diffusion gradient directions. We investigate a hypothesis that CSF models could be used in lieu of an interspersed minimally diffusion-weighted image (b0) correction. Variation in CSF signal is not largely attributable to within-scan dynamic anatomical changes (3.6%), but rather has substantial variation across scan sessions (10.6%) and increased variation across individuals (26.6%). Unfortunately, CSF intensity is not solely explained by a main drift model or a gradient model, but rather has statistically significant associations with both possible explanations. Further exploration is necessary for CSF drift to be used as an effective harmonization technique.

Indexed as

BLSACSFDiffusionvariation

Identifiers

PMID31602086
PMCPMC6786778

What OpenQuestion holds

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Registered trials

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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.