Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability

Anna K Heye, Michael J Thrippleton, Paul A Armitage, Maria del C Valdes Hernandez, Stephen D Makin, Andreas Glatz, Eleni Sakka, Joanna M Wardlaw

Research output: Contribution to journalArticle

42 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)446-455
Number of pages10
JournalNeuroimage
Volume125
DOIs
Publication statusPublished - 15 Jan 2016

Fingerprint

Blood-Brain Barrier
Permeability
Cerebral Small Vessel Diseases
Contrast Media
Healthy Volunteers
Extracellular Space
Brain Neoplasms
Dementia
Perfusion
Stroke
Brain

Keywords

  • Aged
  • Blood-Brain Barrier/*pathology
  • Brain Mapping/*methods
  • Capillary Permeability/physiology
  • Contrast Image Processing, Computer-Assisted/*methods
  • Media
  • Female humans
  • Image Enhancement/methods
  • Kinetics
  • Magnetic Resonance Imaging/methods
  • Male
  • Neuronavigation/*methods
  • Stroke/*pathology
  • Blood-brain barrier
  • Cerebral small vessel disease
  • Dynamic contrast-enhanced MRI
  • Tracer kinetic modelling
  • Middle Aged

Cite this

Heye, A. K., Thrippleton, M. J., Armitage, P. A., Valdes Hernandez, M. D. C., Makin, S. D., Glatz, A., ... Wardlaw, J. M. (2016). Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability. Neuroimage, 125, 446-455. https://doi.org/10.1016/j.neuroimage.2015.10.018

Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability. / Heye, Anna K; Thrippleton, Michael J; Armitage, Paul A; Valdes Hernandez, Maria del C; Makin, Stephen D; Glatz, Andreas; Sakka, Eleni ; Wardlaw, Joanna M.

In: Neuroimage, Vol. 125, 15.01.2016, p. 446-455.

Research output: Contribution to journalArticle

Heye, AK, Thrippleton, MJ, Armitage, PA, Valdes Hernandez, MDC, Makin, SD, Glatz, A, Sakka, E & Wardlaw, JM 2016, 'Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability', Neuroimage, vol. 125, pp. 446-455. https://doi.org/10.1016/j.neuroimage.2015.10.018
Heye, Anna K ; Thrippleton, Michael J ; Armitage, Paul A ; Valdes Hernandez, Maria del C ; Makin, Stephen D ; Glatz, Andreas ; Sakka, Eleni ; Wardlaw, Joanna M. / Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability. In: Neuroimage. 2016 ; Vol. 125. pp. 446-455.
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N1 - Heye, Anna K Thrippleton, Michael J Armitage, Paul A Valdes Hernandez, Maria Del C Makin, Stephen D Glatz, Andreas Sakka, Eleni Wardlaw, Joanna M eng MR/K026992/1/Medical Research Council/United Kingdom 088134/Z/09/A/Wellcome Trust/United Kingdom Research Support, Non-U.S. Gov't 2015/10/20 06:00 Neuroimage. 2016 Jan 15;125:446-455. doi: 10.1016/j.neuroimage.2015.10.018. Epub 2015 Oct 20.

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N2 - 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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KW - Aged

KW - Blood-Brain Barrier/pathology

KW - Brain Mapping/methods

KW - Capillary Permeability/physiology

KW - Contrast Image Processing, Computer-Assisted/methods

KW - Media

KW - Female humans

KW - Image Enhancement/methods

KW - Kinetics

KW - Magnetic Resonance Imaging/methods

KW - Male

KW - Neuronavigation/methods

KW - Stroke/pathology

KW - Blood-brain barrier

KW - Cerebral small vessel disease

KW - Dynamic contrast-enhanced MRI

KW - Tracer kinetic modelling

KW - Middle Aged

U2 - 10.1016/j.neuroimage.2015.10.018

DO - 10.1016/j.neuroimage.2015.10.018

M3 - Article

VL - 125

SP - 446

EP - 455

JO - Neuroimage

JF - Neuroimage

SN - 1053-8119

ER -