Evidence map›Paper›PMID 25485790›Full record

ArticleMagnetic resonance imaging2015

Lateral ventricular cerebrospinal fluid diffusivity as a potential neuroimaging marker of brain temperature in multiple sclerosis: a hypothesis and implications.

Khader M Hasan, John A Lincoln, Flavia M Nelson, Jerry S Wolinsky, Ponnada A Narayana

Open access · greenAbstract read
In one paragraph

Article in Magnetic resonance imaging, 2015. 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
1.0field-weighted citation impact, top 24% 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, 15 citations in OpenAlex.

  1. Trial
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  5. CanBrain communications · 2019
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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

5 authors at 1 institution in 1 country.

Khader M HasanThe University of Texas Health Science Center at Houston, Department of Diagnostic & Interventional Imaging, 6431 Fannin Street, Houston, Texas 77030. Electronic address: Khader.M.Hasan@uth.tmc.edu.
John A LincolnThe University of Texas Health Science Center at Houston, Department of Neurology, 6431 Fannin Street, Houston, Texas 77030.
Flavia M NelsonThe University of Texas Health Science Center at Houston, Department of Neurology, 6431 Fannin Street, Houston, Texas 77030.
Jerry S WolinskyThe University of Texas Health Science Center at Houston, Department of Neurology, 6431 Fannin Street, Houston, Texas 77030.
Ponnada A NarayanaThe University of Texas Health Science Center at Houston, Department of Diagnostic & Interventional Imaging, 6431 Fannin Street, Houston, Texas 77030.
The University of Texas Health Science Center at Houston · US

Funding

Center for Clinical and Translational Sciences (CCTS)UL1TR000371 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCPHERSON, DAVID D · 2012 to 2016
$13.4M
MR Image Analysis in MS: Identification of a SurrogateR01EB002095 · NIBIB · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI NARAYANA, PONNADA A · 2003 to 2011
$5.2M
Lesion Activity and Atrophy in Multiple Sclerosis: Analysis of Multi-center MRIR01NS078244 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI NARAYANA, PONNADA A · 2012 to 2016
$1.6M
Diffusion Tensor Imaging of Wallerian Degeneration in MSR01NS052505 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HASAN, KHADER M · 2006 to 2009
$1.2M
Detection of MS Related Cognitive Impairment: In Search of MRI Surrogate MarkersK23NS072134 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI NELSON, FLAVIA M · 2011 to 2014
$679k
MRS: NEUROLOGICAL DVMT &DISORDERS: LEARNING, READING, COGNITIVE, APHASIA, DYSLES10RR019186 · NCRR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI NARAYANA, PONNADA A · 2004 to 2004
$500k
NCATS NIH HHS UL1 TR000371NCRR NIH HHS S10 RR019186NCRR NIH HHS S10 RR19186NIBIB NIH HHS EB002095NIBIB NIH HHS R01 EB002095NINDS NIH HHS 1 R01 NS078244-01A1NINDS NIH HHS 5K23NS072134-02NINDS NIH HHS K23 NS072134NINDS NIH HHS R01 NS052505NINDS NIH HHS R01-NS052505NINDS NIH HHS R01 NS078244
6 · The paper itself

Abstract

In this retrospective study we tested the hypothesis that the net effect of impaired electrical conduction and therefore increased heat dissipation in multiple sclerosis (MS) results in elevated lateral ventricular (LV) cerebrospinal fluid (CSF) diffusivity as a measure of brain temperature estimated in vivo using diffusion tensor imaging (DTI). We used validated DTI-based segmentation methods to obtain normalized LV-CSF volume and its corresponding CSF diffusivity in 108 MS patients and 103 healthy controls in the age range of 21-63 years. The LV CSF diffusivity was ~2% higher in MS compared to controls that correspond to a temperature rise of ~1°C that could not be explained by changes in the CSF viscosity due to altered CSF protein content in MS. The LV diffusivity decreased with age in healthy controls (r=-0.29; p=0.003), but not in MS (r=0.15; p=0.11), possibly related to MS pathology. Age-adjusted LV diffusivity increased with lesion load (r=0.518; p=1×10(-8)). Our data suggest that the total brain lesion load is the primary contributor to the increase in LV CSF diffusivity in MS. These findings suggest that LV diffusivity is a potential in vivo biomarker of the mismatch between heat generation and dissipation in MS. We also discuss limitations and possible confounders.

Indexed as

Diffusion Tensor ImagingAdultAlgorithmsBrainCerebrospinal FluidFemaleHumansImage Processing, Computer-AssistedLinear ModelsMagnetic Resonance ImagingMaleMiddle AgedMultiple SclerosisPhantoms, ImagingRetrospective StudiesTemperatureAgeCerebrospinal fluidDiffusion tensor imagingLateral ventriclesMultiple sclerosisTemperature

Identifiers

PMID25485790
PMCPMC4324333
OpenAlexW2108325907

What OpenQuestion holds

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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.