Evidence map›Paper›PMID 41792587›Full record

ArticleMagnetic resonance in medicine2026

Assessing Measurement Repeatability of a Novel Anisotropic Phantom for Advanced Diffusion MRI Models.

Lauren Stephens, Sofia Chavez, Fergal Kerins, Michael D Noseworthy

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 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

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

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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

4 authors.

Lauren StephensMcMaster School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.ORCID 0000-0003-4580-4603
Sofia ChavezPreOperative Performance, Toronto, Ontario, Canada.ORCID 0000-0002-6532-911X
Fergal KerinsPreOperative Performance, Toronto, Ontario, Canada.ORCID 0009-0008-1555-1899
Michael D NoseworthyMcMaster School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.ORCID 0000-0003-1464-159X

Funding

Southern Ontario Pharmaceutical and Health Innovation Ecosystem (SOPHIE)
6 · The paper itself

Abstract

purposeDiffusion MRI is widely used to characterize tissue microstructure, but standardization remains challenging, particularly for advanced models or regions with crossing fibers. Phantoms provide controlled environments to assess measurement repeatability independent of biological variability. This study evaluated the repeatability of higher-order diffusion tensor metrics using a novel anisotropic diffusion phantom designed to mimic white matter tract geometry.

methodsThe phantom, containing linear, crossing (30°, 45°, 90°), and bifurcating synthetic fiber bundles, was scanned seven times using a GE Healthcare 3.0 T MRI system. Four acquisition protocols were evaluated: 30-direction DTI (b = 1000s/mm

resultsDTI-derived metrics demonstrated excellent repeatability, with fractional anisotropy (FA) CoV < 10% and mean, axial, and radial diffusivities < 3%. DKI-derived metrics exhibited greater variability, though kurtosis FA remained stable (CoV ∼7%). Generalized FA showed improved reliability with increased angular resolution (ICC = 0.8445 for 90-direction HARDI). fODFs accurately resolved crossing fibers at 90° (RMSE = 3.49°) and 45° (RMSE = 8.92°) but failed at 30° separation.

conclusionThe phantom provides reliable repeatability for standard DTI metrics and demonstrates utility for quality assurance of advanced diffusion models with high angular resolution protocols.

Indexed as

Diffusion Magnetic Resonance ImagingDiffusion Tensor ImagingImage Processing, Computer-AssistedPhantoms, ImagingWhite MatterAlgorithmsAnisotropyBrainHumansReproducibility of Resultsanisotropic phantomconstrained spherical deconvolutiondiffusion kurtosis imagingdiffusion MRIdiffusion tensor imagingquality assurance

Identifiers

PMID41792587
PMCPMC13156440

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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.