Tracer kinetic modelling for DCE-MRI quantification of subtle blood–brain barrier permeability
Open accessAbstract
There is evidence that subtle breakdown of the blood-brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n=201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a "sham" DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and K(Trans) estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low-permeability states, which has the potential to provide valuable information regarding BBB integrity in a range of diseases. However, absolute values of the resulting tracer kinetic parameters should be interpreted with extreme caution, and the size and influence of signal drift should be measured where possible.
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PS is thought to quantify BBB leakage from the small parenchymal vessels, mostly the capillaries.
“PS is thought to quantify BBB leakage from the small parenchymal vessels, mostly the capillaries.32”
From In Vivo Imaging of Blood-Brain Barrier Leakage Using a Contrast Agent in Patients With Cerebral Amyloid Angiopathy: An Exploratory Study (2025) · cites this paper as [32]
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 [248]
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Blood-brain barrier breakdown in the aging human hippocampus
Montagne, A., Barnes, S. R., Sweeney, M. D., Halliday, M. R., Sagare, A. P., Zhao, Z., Toga, A. W., Jacobs, R. E., Liu, C. Y., Amezcua, L., et al. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.032 · Cited by 2,102 · see citing works
Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging
Wardlaw, J. M., Smith, C., & Dichgans, M. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70060-7 · Cited by 1,657 · see citing works
Self-citationNeuropathologic correlates of white matter hyperintensities
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BackgroundCerebral Perfusion and Cerebrovascular Reactivity Are Reduced in White Matter Hyperintensities
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- Authors
- Heye, A. K., Thrippleton, M. J., Armitage, P. A., Valdés Hernández, M. D. C., Makin, S. D., Glatz, A., Sakka, E., & Wardlaw, J. M.
- Affiliations
- University of Edinburgh (GB)
- University of Sheffield (GB)
- Corresponding author
- Thrippleton, Michael J.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 125
- Pages
- 446-455
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4692516
- OpenAlex
- W2117465877
- Cited by
- 187
- References
- 6
- Citations by year
- 2026: 16 · 2025: 15 · 2024: 20 · 2023: 22 · 2022: 18 · 2021: 18 · 2020: 24 · 2019: 19 · 2018: 14 · 2017: 11 · 2016: 10
- FWCI
- 9.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- NeuroImage (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion, cc-by)
- Aberdeen University Research Archive (Aberdeen University) (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (088134/Z/09/A)
- Row Fogo Charitable Trust
- Age UK
- NHS Lothian Research and Development Office
- Scottish Funding Council
- Chief Scientist Office of Scotland
- 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 › Advanced Neuroimaging Techniques and Applications
- Keywords
- blood-brain barrier permeability, Patlak model, dynamic contrast-enhanced MRI, cerebral small vessel disease, minor stroke, volume of distribution, transfer constant, model selection, Akaike information criterion, numerical simulation
- MeSH terms
- Aged, Blood-Brain Barrier, Brain Mapping, Capillary Permeability, Contrast Media, Female, Humans, Image Enhancement, Image Processing, Computer-Assisted, Kinetics, Magnetic Resonance Imaging, Male, Middle Aged, Stroke, Neuronavigation
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