Evidence map›Paper›PMID 41937625›Full record

ArticleNMR in biomedicine2026

Monte Carlo Assessment of Accuracy for Mean Kärger Model Water Exchange Rate Estimates From Diffusional Kurtosis Time Dependence.

Jens H Jensen, Ricardo Coronado-Leija, Els Fieremans

Abstract read
In one paragraph

Article in NMR in biomedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Jens H JensenCenter for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID https://orcid.org/0000-0003-3219-4287
Ricardo Coronado-LeijaDepartment of Radiology, New York University School of Medicine, New York, New York, USA.
Els FieremansDepartment of Radiology, New York University School of Medicine, New York, New York, USA.ORCID https://orcid.org/0000-0002-1384-8591

Funding

Quantitative Neuroimaging Assessment of White Matter Integrity in the Context of Aging and ADR01AG054159 · NIA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Andreana Benitez · 2017 to 2026
$8.9M
Diffusion and Functional MRI Monitoring of Therapy Response in Alzheimer’s Disease Mouse ModelR01AG057602 · NIA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI MARIA F FALANGOLA, JENS H JENSEN · 2023 to 2026
$2.7M
NIA NIH HHS R01 AG054159NIH HHS R01AG054159NIH HHS R01AG057602
6 · The paper itself

Abstract

Intercompartmental water exchange in brain and other biological tissue can be probed in vivo with diffusion MRI (dMRI). We assess the accuracy of a recently proposed method for estimating a mean exchange rate by performing Monte Carlo simulations of random walkers through a packing of permeable, randomly placed, parallel cylinders to model water exchange within axonal fiber bundles. The diffusivity and kurtosis of the full system are calculated for a broad range of diffusion times and model parameters. The mean exchange rate is estimated from the logarithmic derivative of the kurtosis with respect to the diffusion time and compared with the exchange rate predicted by the Kärger model (KM), which is exact in certain limits. The mean exchange rate is also compared with the reciprocal exchange time obtained by conventional fitting of the kurtosis time dependence to a two-compartment KM, with a high correlation being found between the two quantities. The estimates from the logarithmic derivative are in good agreement with the KM predictions when the exchange time is long in comparison to the compartment traversal times, which corresponds to barrier-limited exchange. Compared to the standard procedure of fitting the kurtosis to the KM over a broad range of diffusion times, using the logarithmic derivative reduces the data acquisition burden by only requiring a narrow range of times and increases generality in that number of compartments need not be specified. This method may be useful for estimating the mean exchange rate from the kurtosis time dependence measured with dMRI.

Indexed as

Diffusion Magnetic Resonance ImagingMonte Carlo MethodWaterBrainComputer SimulationDiffusionHumansReproducibility of ResultsTime FactorsWaterbraindiffusionKärger modelkurtosisMonte CarloMRInumerical simulationswater exchange

Identifiers

PMID41937625
PMCPMC13051334

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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.