Evidence map›Paper›PMID 38997324›Full record

ArticleScientific reports2024

Changes of in vivo electrical conductivity in the brain and torso related to age, fat fraction and sex using MRI.

Zhongzheng He, Paul Soullié, Pauline Lefebvre, Khalid Ambarki, Jacques Felblinger, Freddy Odille

Registry-linked trialAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04645628 (Optimization of the Acquisition Sequence to Improve the Quality and Comfort of Magnetic Resonance Imaging Exam), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

NCT04645628 narecruitingnot on this map

Optimization of the Acquisition Sequence to Improve the Quality and Comfort of Magnetic Resonance Imaging Exam

TypeinterventionalSponsorCentral Hospital, Nancy, FranceRan2020 to 2028Enrolled720ConditionsHealthy Subjects, Patient Performing an MRI ExaminationArmsMRI examination
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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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

6 authors.

Zhongzheng He *IADI U1254, INSERM and Université de Lorraine, Nancy, France.
Paul Soullié *IADI U1254, INSERM and Université de Lorraine, Nancy, France. paul.soullie@univ-lorraine.fr.
Pauline LefebvreIADI U1254, INSERM and Université de Lorraine, Nancy, France.
Khalid AmbarkiSiemens Healthcare SAS, Saint Denis, France.
Jacques FelblingerIADI U1254, INSERM and Université de Lorraine, Nancy, France.
Freddy OdilleIADI U1254, INSERM and Université de Lorraine, Nancy, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work was inspired by the observation that a majority of MR-electrical properties tomography studies are based on direct comparisons with ex vivo measurements carried out on post-mortem samples in the 90's. As a result, the in vivo conductivity values obtained from MRI in the megahertz range in different types of tissues (brain, liver, tumors, muscles, etc.) found in the literature may not correspond to their ex vivo equivalent, which still serves as a reference for electromagnetic modelling. This study aims to pave the way for improving current databases since the definition of personalized electromagnetic models (e.g. for Specific Absorption Rate estimation) would benefit from better estimation. Seventeen healthy volunteers underwent MRI of both brain and thorax/abdomen using a three-dimensional ultrashort echo-time (UTE) sequence. We estimated conductivity (S/m) in several classes of macroscopic tissue using a customized reconstruction method from complex UTE images, and give general statistics for each of these regions (mean-median-standard deviation). These values are used to find possible correlations with biological parameters such as age, sex, body mass index and/or fat volume fraction, using linear regression analysis. In short, the collected in vivo values show significant deviations from the ex vivo values in conventional databases, and we show significant relationships with the latter parameters in certain organs for the first time, e.g. a decrease in brain conductivity with age.

Indexed as

BrainElectric ConductivityMagnetic Resonance ImagingTorsoAdipose TissueAdultAgedAge FactorsFemaleHumansMaleMiddle AgedSex FactorsYoung Adult

Identifiers

PMID38997324
PMCPMC11245625

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Registered trials

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.