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Cited by 115Advanced MRI Techniques and ApplicationsBarrier Structure and Function StudiesMedical Imaging Techniques and Applications

Optimal acquisition and modeling parameters for accurate assessment of low Ktrans blood-brain barrier permeability using dynamic contrast-enhanced MRI: Optimal Parameters for Accurate Low Permeability DCE-MRI Estimation

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Barnes, Samuel R., Ng, Thomas S. C., Montagne, Axel, Law, Meng, Zlokovic, Berislav V., Jacobs, Russell E.·2016·Magnetic Resonance in Medicine
DOI 10.1002/mrm.25793PMC PMC4726482
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Abstract

PURPOSE: To determine optimal parameters for acquisition and processing of dynamic contrast-enhanced MRI (DCE-MRI) to detect small changes in near normal low blood-brain barrier (BBB) permeability. METHODS: Using a contrast-to-noise ratio metric (K-CNR) for Ktrans precision and accuracy, the effects of kinetic model selection, scan duration, temporal resolution, signal drift, and length of baseline on the estimation of low permeability values was evaluated with simulations. RESULTS: The Patlak model was shown to give the highest K-CNR at low Ktrans . The Ktrans transition point, above which other models yielded superior results, was highly dependent on scan duration and tissue extravascular extracellular volume fraction (ve ). The highest K-CNR for low Ktrans was obtained when Patlak model analysis was combined with long scan times (10-30 min), modest temporal resolution (<60 s/image), and long baseline scans (1-4 min). Signal drift as low as 3% was shown to affect the accuracy of Ktrans estimation with Patlak analysis. CONCLUSION: DCE acquisition and modeling parameters are interdependent and should be optimized together for the tissue being imaged. Appropriately optimized protocols can detect even the subtlest changes in BBB integrity and may be used to probe the earliest changes in neurodegenerative diseases such as Alzheimer's disease and multiple sclerosis.

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  • Patlak analysis allows detection of subtle changes in BBB permeability.

    “These studies used Patlak analysis (46, 47, 466), which allows detection of subtle changes in BBB permeability (46, 248, 418, 421).”

    From Blood-Brain Barrier: From Physiology to Disease and Back (2019) · cites this paper as [46]

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Authors
Barnes, S. R., Ng, T. S. C., Montagne, A., Law, M., Zlokovic, B. V., & Jacobs, R. E.
Affiliations
  • California Institute of Technology (US)
  • University of Southern California (US)
  • Zilkha Neurogenetic Institute and Department of Physiology and Biophysics; Keck School of Medicine, University of Southern California; Los Angeles California USA
Corresponding author
Barnes, Samuel R.
ORCID
Venue
Magnetic Resonance in Medicine
Publisher
Wiley
Published
2015-06-16
Volume
75
Issue
5
Pages
1967-1977
ISSN
0740-3194 (ISSN-L)
DOI
10.1002/mrm.25793
PMC
PMC4726482
OpenAlex
W1612848838
Cited by
115
References
5
Citations by year
2026: 8 · 2025: 11 · 2024: 7 · 2023: 8 · 2022: 14 · 2021: 14 · 2020: 12 · 2019: 12 · 2018: 13 · 2017: 6 · 2016: 9 · 2015: 1
FWCI
7.83
Type
journal article
Language
en
Open access
Licence
Locations
  • Magnetic Resonance in Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion)
Funders
  • NIBIB (EB000993)
  • The Beckman Institute, Grant sponsor: NINDS (R37NS34467)
  • NIA (R37AG23084, R01AG039452)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
  • Life Sciences › Neuroscience › Neurology › Barrier Structure and Function Studies
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
Keywords
blood-brain barrier permeability, Ktrans, dynamic contrast-enhanced MRI, Patlak model, kinetic model selection, contrast-to-noise ratio, scan time, temporal resolution, signal drift, extravascular extracellular volume, blood-brain barrier integrity, neurodegenerative disease imaging
MeSH terms
Adult, Aged, Algorithms, Alzheimer Disease, Blood-Brain Barrier, Computer Simulation, Contrast Media, Female, Humans, Image Processing, Computer-Assisted, Kinetics, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis, Permeability, Signal Processing, Computer-Assisted, Reproducibility of Results, Normal Distribution, Neurodegenerative Diseases, Young Adult

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