Evidence map›Paper›PMID 33724547›Full record

ArticleMagnetic resonance in medicine2021

Parsimonious modeling of skeletal muscle perfusion: Connecting the stretched exponential and fractional Fickian diffusion.

David A Reiter, Fatemeh Adelnia, Donnie Cameron, Richard G Spencer, Luigi Ferrucci

Open access · greenAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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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 4 institutions in 3 countries.

David A ReiterDepartment of Radiology & Imaging Sciences, Emory University, Atlanta, Georgia, USA.ORCID 0000-0001-6047-3967
Fatemeh AdelniaVanderbilt University Institute of Imaging Sciences, Vanderbilt University, Medical center, Nashville, Tennessee, USA.
Donnie CameronNorwich Medical School, University of East Anglia, Norwich, United Kingdom.
Richard G SpencerNational Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA.
Luigi FerrucciNational Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA.
National Institutes of Health · USEmory University · USUniversity of East Anglia · GBVanderbilt University Medical Center · US

Funding

Multicompartment quantification of tissue in vitro and in vivo with magnetic resonance imaging and spectroscopyZIAAG000930 · NIA · NATIONAL INSTITUTE ON AGING · PI SPENCER, RICHARD · 2015 to 2025
$11.6M
Magnetic Resonance Analysis of Connective Tissue and MuscleZIAAG000924 · NIA · NATIONAL INSTITUTE ON AGING · PI SPENCER, RICHARD · 2009 to 2025
$3.2M
Intramural NIH HHS Z99 AG999999
6 · The paper itself

Abstract

purposeTo develop an anomalous (non-Gaussian) diffusion model for characterizing skeletal muscle perfusion using multi-b-value DWI. THEORY AND

methodsFick's first law was extended for describing tissue perfusion as anomalous superdiffusion, which is non-Gaussian diffusion exhibiting greater particle spread than that of the Gaussian case. This was accomplished using a space-fractional derivative that gives rise to a power-law relationship between mean squared displacement and time, and produces a stretched exponential signal decay as a function of b-value. Numerical simulations were used to estimate parameter errors under in vivo conditions, and examine the effect of limited SNR and residual fat signal. Stretched exponential DWI parameters, α and

resultsNumerical simulations showed low dispersion in parameter estimates within 1.5% and 1%, and bias errors within 3% and 10%, for α and

conclusionsThis model captures superdiffusive molecular motions consistent with perfusion, using a parsimonious representation of the DWI signal, providing approximations of microvascular volume fraction comparable with histological estimates. This signal model demonstrates low parameter-estimation errors, and therefore holds potential for a wide range of applications in skeletal muscle and elsewhere in the body.

Indexed as

Diffusion Magnetic Resonance ImagingMuscle, SkeletalDiffusionHumansNormal DistributionPerfusionanomalous diffusionfractional calculushyperemiaintravoxel incoherent motionmicrovascular volumesuperdiffusion

Identifiers

PMID33724547
PMCPMC8315038
OpenAlexW3139210106

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.