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

Overview

  1. McMaster School of Biomedical Engineering McMaster University Hamilton Ontario Canada
  2. Imaging Research Centre, St. Joseph's Healthcare Hamilton Ontario Canada
  3. Department of Medical Imaging McMaster University Hamilton Ontario Canada
  4. PreOperative Performance Toronto Ontario Canada
  5. Department of Electrical and Computer Engineering McMaster University Hamilton Ontario Canada
Journal: Magnetic resonance in medicine, volume 96, issue 1, pages 339-348
Dates: received 17 November 2025; accepted 18 February 2026; published online 6 March 2026; in print July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1002/mrm.70330 · PMID 41792587 · PMCID PMC13156440 · OpenAlex W7134133613
Open access: hybrid, a free copy (OpenAlex)
Status: code on request
Categories: structural MRI / diffusion (modality), human (organism)
Methods: Smoothing, state filtering, decompositions, Statistics, fMRI & imaging, Physiology & signal measures
Keywords: anisotropic phantom, constrained spherical deconvolution, diffusion kurtosis imaging, diffusion MRI, diffusion tensor imaging, quality assurance
MeSH: Diffusion Magnetic Resonance Imaging*, Diffusion Tensor Imaging*, Image Processing, Computer-Assisted*, Phantoms, Imaging*, White Matter*, Algorithms, Anisotropy, Brain, Humans, Reproducibility of Results (* major topic)
Journal subjects: Biophysics and Basic Biomedical Research
Topic: Advanced Neuroimaging Techniques and Applications (Radiology, Nuclear Medicine and Imaging, Medicine), according to OpenAlex
Funding: Southern Ontario Pharmaceutical and Health Innovation Ecosystem (SOPHIE)
Citations: not cited yet (Europe PMC); 50 references in the paper

Abstract

Purpose: Diffusion 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.

Methods: The 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/mm2), 60 and 90‐direction High Angular Resolution Diffusion Imaging (HARDI; b = 1300s/mm2), and 30‐direction Diffusion Kurtosis Imaging (DKI; b = 250, 500, 750, 1000, 1500, 2000, 2500, 3000 s/mm2). Repeatability was quantified using coefficient of variation (CoV) and intraclass correlation coefficient (ICC) for scalar diffusion metrics across six regions of interest. Fiber orientation distribution functions (fODFs) were analyzed to assess crossing fiber resolution accuracy.

Results: DTI‐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.

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

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper says that its authors' code is available on request: it was not published with the paper, so there is nothing to verify.

The paper's code and data availability statement is in the Data section.

Tracing map

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Data

No dataset and no data link were found in the paper.

Data Availability Statement

Original DICOM data and analysis code will be made available upon request to the corresponding author.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 6 keywords, 10 MeSH terms, 1 funder, 49 references.

Cite

This paper

Stephens, L., Chavez, S., Kerins, F., & Noseworthy, M. D. (2026). Assessing Measurement Repeatability of a Novel Anisotropic Phantom for Advanced Diffusion MRI Models. Magnetic resonance in medicine, 96(1), 339-348. https://doi.org/10.1002/mrm.70330

BibTeX

@article{stephens2026assessing,
author = {Stephens, Lauren and Chavez, Sofia and Kerins, Fergal and Noseworthy, Michael D.},
title = {{Assessing Measurement Repeatability of a Novel Anisotropic Phantom for Advanced Diffusion MRI Models}},
journal = {Magnetic resonance in medicine},
year = {2026},
month = mar,
volume = {96},
number = {1},
pages = {339--348},
publisher = {Wiley},
issn = {0740-3194},
doi = {10.1002/mrm.70330},
url = {https://doi.org/10.1002/mrm.70330},
pmid = {41792587},
pmcid = {PMC13156440}
}

RIS

TY - JOUR
AU - Stephens, Lauren
AU - Chavez, Sofia
AU - Kerins, Fergal
AU - Noseworthy, Michael D.
TI - Assessing Measurement Repeatability of a Novel Anisotropic Phantom for Advanced Diffusion MRI Models
T2 - Magnetic resonance in medicine
J2 - Magn Reson Med
PY - 2026
DA - 2026/03/06
VL - 96
IS - 1
SP - 339
EP - 348
SN - 0740-3194
PB - Wiley
DO - 10.1002/mrm.70330
UR - https://doi.org/10.1002/mrm.70330
LA - en
ER -

CSL-JSON

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