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

被引:126
作者
Heye, Anna K. [1 ]
Thrippleton, Michael J. [1 ]
Armitage, Paul A. [1 ,2 ]
Hernandez, Maria del C. Valdes [1 ]
Makin, Stephen D. [1 ]
Glatz, Andreas [1 ]
Sakka, Eleni [1 ]
Wardlaw, Joanna M. [1 ]
机构
[1] Univ Edinburgh, Neuroimaging Sci, Edinburgh EH16 4SB, Midlothian, Scotland
[2] Univ Sheffield, Sch Med, Dept Cardiovasc Sci, Sheffield S10 2RX, S Yorkshire, England
基金
英国惠康基金;
关键词
Blood-brain barrier; Dynamic contrast-enhanced MRI; Tracer kinetic modelling; Cerebral small vessel disease; WHITE-MATTER LESIONS; SINGLE-PULSE OBSERVATION; SMALL VESSEL DISEASE; MULTIMODEL INFERENCE; HEALTHY-SUBJECTS; INPUT FUNCTION; IN-VIVO; T1; PERFUSION; VOLUME;
D O I
10.1016/j.neuroimage.2015.10.018
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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% perminute 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. (C) 2015 The Authors. Published by Elsevier Inc.
引用
收藏
页码:446 / 455
页数:10
相关论文
共 61 条
  • [1] The use of the Levenberg-Marquardt curve-fitting algorithm in pharmacokinetic modelling of DCE-MRI data
    Ahearn, TS
    Staff, RT
    Redpath, TW
    Semple, SIK
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2005, 50 (09) : N85 - N92
  • [2] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION
    AKAIKE, H
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) : 716 - 723
  • [3] Extracting and visualizing physiological parameters using dynamic contrast-enhanced magnetic resonance imaging of the breast
    Armitage, P
    Behrenbruch, C
    Brady, M
    Moore, N
    [J]. MEDICAL IMAGE ANALYSIS, 2005, 9 (04) : 315 - 329
  • [4] Use of dynamic contrast-enhanced MRI to measure subtle blood-brain barrier abnormalities
    Armitage, Paul A.
    Farrall, Andrew J.
    Carpenter, Trevor K.
    Doubal, Fergus N.
    Wardlaw, Joanna M.
    [J]. MAGNETIC RESONANCE IMAGING, 2011, 29 (03) : 305 - 314
  • [5] Barnes S. R., 2015, MAGN RESON MED
  • [6] Reduction in cerebral blood flow in areas appearing as white matter hyperintensities on magnetic resonance imaging
    Brickman, Adam M.
    Zahra, Amir
    Muraskin, Jordan
    Steffener, Jason
    Holland, Christopher M.
    Habeck, Christian
    Borogovac, Ajna
    Ramos, Marco A.
    Brown, Truman R.
    Asllani, Iris
    Stern, Yaakov
    [J]. PSYCHIATRY RESEARCH-NEUROIMAGING, 2009, 172 (02) : 117 - 120
  • [7] Pharmacokinetic analysis of tissue microcirculation using nested models: Multimodel inference and parameter identifiability
    Brix, Gunnar
    Zwick, Stefan
    Kiessling, Fabian
    Griebel, Juergen
    [J]. MEDICAL PHYSICS, 2009, 36 (07) : 2923 - 2933
  • [8] Brookes JA, 1999, JMRI-J MAGN RESON IM, V9, P163, DOI 10.1002/(SICI)1522-2586(199902)9:2<163::AID-JMRI3>3.0.CO
  • [9] 2-L
  • [10] Differential microstructure and physiology of brain and bone metastases in a rat breast cancer model by diffusion and dynamic contrast enhanced MRI
    Budde, Matthew D.
    Gold, Eric
    Jordan, E. Kay
    Frank, Joseph A.
    [J]. CLINICAL & EXPERIMENTAL METASTASIS, 2012, 29 (01) : 51 - 62