Cited by 285Advanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and ApplicationsNMR spectroscopy and applications

On the accuracy of T1 mapping: Searching for common ground

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Stikov, Nikola, Boudreau, Mathieu, Levesque, Ives R., Tardif, Christine L., Barral, Joëlle K., Pike, G. Bruce·2015·Magnetic Resonance in Medicine

Abstract

PURPOSE: There are many T1 mapping methods available, each of them validated in phantoms and reporting excellent agreement with literature. However, values in literature vary greatly, with T1 in white matter ranging from 690 to 1100 ms at 3 Tesla. This brings into question the accuracy of one of the most fundamental measurements in quantitative MRI. Our goal was to explain these variations and look into ways of mitigating them. THEORY AND METHODS: We evaluated the three most common T1 mapping methods (inversion recovery, Look-Locker, and variable flip angle) through Bloch simulations, a white matter phantom and the brains of 10 healthy subjects (single-slice). We pooled the T1 histograms of the subjects to determine whether there is a sequence-dependent bias and whether it is reproducible across subjects. RESULTS: We found good agreement between the three methods in phantoms, but poor agreement in vivo, with the white matter T1 histogram peak in healthy subjects varying by more than 30% depending on the method used. We also found that the pooled brain histograms displayed three distinct white matter peaks, with Look-Locker consistently underestimating, and variable flip angle overestimating the inversion recovery T1 values. The Bloch simulations indicated that incomplete spoiling and inaccurate B1 mapping could account for the observed differences. CONCLUSION: We conclude that the three most common T1 mapping protocols produce stable T1 values in phantoms, but not in vivo. To improve the accuracy of T1 mapping, we recommend that sites perform in vivo validation of their T1 mapping method against the inversion recovery reference method, as the first step toward developing a robust calibration scheme.

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References 51 · Cited by 285

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Authors
Stikov, N., Boudreau, M., Levesque, I. R., Tardif, C. L., Barral, J. K., & Pike, G. B.
Affiliations
  • Montreal Neurological Institute and Hospital (CA)
  • Stanford Medicine (US)
  • Max Planck Institute for Human Cognitive and Brain Sciences (DE)
  • Department of Electrical Engineering Stanford University Stanford, California USA
Corresponding author
Stikov, Nikola
Venue
Magnetic Resonance in Medicine
Publisher
Wiley
Published
2014-02-27
Volume
73
Issue
2
Pages
514-522
ISSN
  • 0740-3194 (ISSN-L)
  • 1522-2594
OpenAlex
W2152572524
Cited by
285
References
51
Citations by year
2026: 18 · 2025: 26 · 2024: 32 · 2023: 24 · 2022: 29 · 2021: 28 · 2020: 28 · 2019: 25 · 2018: 24 · 2017: 19 · 2016: 14 · 2015: 15 · 2014: 2
FWCI
13.04
Type
journal article
Language
en
Open access
Locations
  • Magnetic Resonance in Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • PolyPublie (École Polytechnique de Montréal) (submittedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
Keywords
T1 mapping, inversion recovery, variable flip angle, Bloch simulation, B1 mapping, measurement agreement, in vivo validation
MeSH terms
Adult, Algorithms, Brain, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Sensitivity and Specificity, Reproducibility of Results

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