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Dickie BR, Ahmed Z, Arvidsson J, Bell LC, Buckley DL, Debus C, Fedorov A, Floca R, Gutmann I, van der Heijden RA, van Houdt PJ, Sourbron S, Thrippleton MJ, Quarles C, Kompan IN. A community-endorsed open-source lexicon for contrast agent-based perfusion MRI: A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI). Magn Reson Med 2024; 91:1761-1773. [PMID: 37831600 DOI: 10.1002/mrm.29840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/25/2023] [Accepted: 08/04/2023] [Indexed: 10/15/2023]
Abstract
This manuscript describes the ISMRM OSIPI (Open Science Initiative for Perfusion Imaging) lexicon for dynamic contrast-enhanced and dynamic susceptibility-contrast MRI. The lexicon was developed by Taskforce 4.2 of OSIPI to provide standardized definitions of commonly used quantities, models, and analysis processes with the aim of reducing reporting variability. The taskforce was established in February 2020 and consists of medical physicists, engineers, clinicians, data and computer scientists, and DICOM (Digital Imaging and Communications in Medicine) standard experts. Members of the taskforce collaborated via a slack channel and quarterly virtual meetings. Members participated by defining lexicon items and reporting formats that were reviewed by at least two other members of the taskforce. Version 1.0.0 of the lexicon was subject to open review from the wider perfusion imaging community between January and March 2022, and endorsed by the Perfusion Study Group of the ISMRM in the summer of 2022. The initial scope of the lexicon was set by the taskforce and defined such that it contained a basic set of quantities, processes, and models to enable users to report an end-to-end analysis pipeline including kinetic model fitting. We also provide guidance on how to easily incorporate lexicon items and definitions into free-text descriptions (e.g., in manuscripts and other documentation) and introduce an XML-based pipeline encoding format to encode analyses using lexicon definitions in standardized and extensible machine-readable code. The lexicon is designed to be open-source and extendable, enabling ongoing expansion of its content. We hope that widespread adoption of lexicon terminology and reporting formats described herein will increase reproducibility within the field.
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Affiliation(s)
- Ben R Dickie
- Division of Informatics, Imaging, and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Center, Manchester Academic Health Science Center, The University of Manchester, Manchester, UK
| | - Zaki Ahmed
- Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA
| | - Jonathan Arvidsson
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Laura C Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | | | | | - Andrey Fedorov
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ralf Floca
- National Center for Radiation Research in Oncology, Heidelberg Institute for Radiation Oncology, Heidelberg, Germany
| | - Ingomar Gutmann
- Faculty of Physics, Physics of Functional Materials, University of Vienna, Vienna, Austria
| | - Rianne A van der Heijden
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Steven Sourbron
- Department of Infection, Immunity, and Cardiovascular Diseases, University of Sheffield, Sheffield, UK
| | - Michael J Thrippleton
- Edinburgh Imaging and Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Chad Quarles
- Department of Cancer Systems Imaging, UT MD Anderson Cancer Center, Houston, Texas, USA
| | - Ina N Kompan
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
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Powell E, Dickie BR, Ohene Y, Maskery M, Parker GJM, Parkes LM. Blood-brain barrier water exchange measurements using contrast-enhanced ASL. NMR Biomed 2023; 36:e5009. [PMID: 37666494 PMCID: PMC10909569 DOI: 10.1002/nbm.5009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 05/17/2023] [Accepted: 06/30/2023] [Indexed: 09/06/2023]
Abstract
A technique for quantifying regional blood-brain barrier (BBB) water exchange rates using contrast-enhanced arterial spin labelling (CE-ASL) is presented and evaluated in simulations and in vivo. The two-compartment ASL model describes the water exchange rate from blood to tissue,k b , but to estimatek b in practice it is necessary to separate the intra- and extravascular signals. This is challenging in standard ASL data owing to the small difference inT 1 values. Here, a gadolinium-based contrast agent is used to increase thisT 1 difference and enable the signal components to be disentangled. The optimal post-contrast bloodT 1 (T 1 , b post ) at 3 T was determined in a sensitivity analysis, and the accuracy and precision of the method quantified using Monte Carlo simulations. Proof-of-concept data were acquired in six healthy volunteers (five female, age range 24-46 years). The sensitivity analysis identified the optimalT 1 , b post at 3 T as 0.8 s. Simulations showed thatk b could be estimated in individual cortical regions with a relative error ϵ < 1 % and coefficient of variation CoV = 30 %; however, a high dependence on bloodT 1 was also observed. In volunteer data, mean parameter values in grey matter were: arterial transit timet A = 1 . 15 ± 0 . 49 s, cerebral blood flow f = 58 . 0 ± 14 . 3 mL blood/min/100 mL tissue and water exchange ratek b = 2 . 32 ± 2 . 49 s-1 . CE-ASL can provide regional BBB water exchange rate estimates; however, the clinical utility of the technique is dependent on the achievable accuracy of measuredT 1 values.
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Affiliation(s)
- Elizabeth Powell
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Ben R. Dickie
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
- Geoffrey Jefferson Brain Research CentreUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
| | - Yolanda Ohene
- Geoffrey Jefferson Brain Research CentreUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
| | - Mark Maskery
- Department of NeurologyLancashire Teaching Hospitals NHS Foundation TrustPrestonUK
| | - Geoff J. M. Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Queen Square MS Centre, Institute of NeurologyUniversity College LondonLondonUK
- Bioxydyn LimitedManchesterUnited Kingdom
| | - Laura M. Parkes
- Geoffrey Jefferson Brain Research CentreUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
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Bolan F, Dickie BR, Cook JR, Thomas JM, Pinteaux E, Allan SM, Saiani A, Lawrence CB. Intracerebral Administration of a Novel Self-Assembling Peptide Hydrogel Is Safe and Supports Cell Proliferation in Experimental Intracerebral Haemorrhage. Transl Stroke Res 2023:10.1007/s12975-023-01189-7. [PMID: 37853252 DOI: 10.1007/s12975-023-01189-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 08/08/2023] [Accepted: 08/15/2023] [Indexed: 10/20/2023]
Abstract
Intracerebral haemorrhage (ICH) is the deadliest form of stroke, but current treatment options are limited, meaning ICH survivors are often left with life-changing disabilities. The significant unmet clinical need and socioeconomic burden of ICH mean novel regenerative medicine approaches are gaining interest. To facilitate the regeneration of the ICH lesion, injectable biomimetic hydrogels are proposed as both scaffolds for endogenous repair and delivery platforms for pro-regenerative therapies. In this paper, the objective was to explore whether injection of a novel self-assembling peptide hydrogel (SAPH) Alpha2 was feasible, safe and could stimulate brain tissue regeneration, in a collagenase-induced ICH model in rats. Alpha2 was administered intracerebrally at 7 days post ICH and functional outcome measures, histological markers of damage and repair and RNA-sequencing were investigated for up to 8 weeks. The hydrogel Alpha2 was safe, well-tolerated and was retained in the lesion for several weeks, where it allowed infiltration of host cells. The hydrogel had a largely neutral effect on functional outcomes and expression of angiogenic and neurogenic markers but led to increased numbers of proliferating cells. RNAseq and pathway analysis showed that ICH altered genes related to inflammatory and phagocytic pathways, and these changes were also observed after administration of hydrogel. Overall, the results show that the novel hydrogel was safe when injected intracerebrally and had no negative effects on functional outcomes but increased cell proliferation. To elicit a regenerative effect, future studies could use a functionalised hydrogel or combine it with an adjunct therapy.
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Affiliation(s)
- Faye Bolan
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, The University of Manchester, Manchester, M13 9PT, UK
- Division of Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PT, UK
| | - Ben R Dickie
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, The University of Manchester, Manchester, M13 9PT, UK
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - James R Cook
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, The University of Manchester, Manchester, M13 9PT, UK
- Division of Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PT, UK
| | - Josephine M Thomas
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, The University of Manchester, Manchester, M13 9PT, UK
- Division of Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PT, UK
| | - Emmanuel Pinteaux
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, The University of Manchester, Manchester, M13 9PT, UK
- Division of Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PT, UK
| | - Stuart M Allan
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, The University of Manchester, Manchester, M13 9PT, UK
- Division of Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PT, UK
| | - Alberto Saiani
- Department of Materials, The University of Manchester, Manchester, M13 9PL, UK
- Manchester Institute of Biotechnology, The University of Manchester, Manchester, M13 9PL, UK
| | - Catherine B Lawrence
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, The University of Manchester, Manchester, M13 9PT, UK.
- Division of Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PT, UK.
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Powell E, Ohene Y, Battiston M, Dickie BR, Parkes LM, Parker GJM. Blood-brain barrier water exchange measurements using FEXI: Impact of modeling paradigm and relaxation time effects. Magn Reson Med 2023; 90:34-50. [PMID: 36892973 PMCID: PMC10962589 DOI: 10.1002/mrm.29616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 01/25/2023] [Accepted: 01/25/2023] [Indexed: 03/10/2023]
Abstract
PURPOSE To evaluate potential modeling paradigms and the impact of relaxation time effects on human blood-brain barrier (BBB) water exchange measurements using FEXI (BBB-FEXI), and to quantify the accuracy, precision, and repeatability of BBB-FEXI exchange rate estimates at 3 T $$ \mathrm{T} $$ . METHODS Three modeling paradigms were evaluated: (i) the apparent exchange rate (AXR) model; (ii) a two-compartment model (2 CM $$ 2\mathrm{CM} $$ ) explicitly representing intra- and extravascular signal components, and (iii) a two-compartment model additionally accounting for finite compartmentalT 1 $$ {\mathrm{T}}_1 $$ andT 2 $$ {\mathrm{T}}_2 $$ relaxation times (2 CM r $$ 2{\mathrm{CM}}_r $$ ). Each model had three free parameters. Simulations quantified biases introduced by the assumption of infinite relaxation times in the AXR and2 CM $$ 2\mathrm{CM} $$ models, as well as the accuracy and precision of all three models. The scan-rescan repeatability of all paradigms was quantified for the first time in vivo in 10 healthy volunteers (age range 23-52 years; five female). RESULTS The assumption of infinite relaxation times yielded exchange rate errors in simulations up to 42%/14% in the AXR/2 CM $$ 2\mathrm{CM} $$ models, respectively. Accuracy was highest in the compartmental models; precision was best in the AXR model. Scan-rescan repeatability in vivo was good for all models, with negligible bias and repeatability coefficients in grey matter ofRC AXR = 0 . 43 $$ {\mathrm{RC}}_{\mathrm{AXR}}=0.43 $$ s - 1 $$ {\mathrm{s}}^{-1} $$ ,RC 2 CM = 0 . 51 $$ {\mathrm{RC}}_{2\mathrm{CM}}=0.51 $$ s - 1 $$ {\mathrm{s}}^{-1} $$ , andRC 2 CM r = 0 . 61 $$ {\mathrm{RC}}_{2{\mathrm{CM}}_r}=0.61 $$ s - 1 $$ {\mathrm{s}}^{-1} $$ . CONCLUSION Compartmental modelling of BBB-FEXI signals can provide accurate and repeatable measurements of BBB water exchange; however, relaxation time and partial volume effects may cause model-dependent biases.
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Affiliation(s)
- Elizabeth Powell
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Yolanda Ohene
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science CentreUniversity of ManchesterManchesterUK
| | - Marco Battiston
- Queen Square MS CentreUCL Institute of Neurology, University College LondonLondonUK
| | - Ben R. Dickie
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science CentreUniversity of ManchesterManchesterUK
- Division of Informatics, Imaging and Data SciencesSchool of Health Sciences, Faculty of Biology, Medicine and Health, University of ManchesterManchesterUK
| | - Laura M. Parkes
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science CentreUniversity of ManchesterManchesterUK
| | - Geoff J. M. Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Queen Square MS CentreUCL Institute of Neurology, University College LondonLondonUK
- Bioxydyn LimitedManchesterUK
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Finlay CM, Parkinson JE, Zhang L, Chan BHK, Ajendra J, Chenery A, Morrison A, Kaymak I, Houlder EL, Murtuza Baker S, Dickie BR, Boon L, Konkel JE, Hepworth MR, MacDonald AS, Randolph GJ, Rückerl D, Allen JE. T helper 2 cells control monocyte to tissue-resident macrophage differentiation during nematode infection of the pleural cavity. Immunity 2023; 56:1064-1081.e10. [PMID: 36948193 DOI: 10.1016/j.immuni.2023.02.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 10/07/2022] [Accepted: 02/21/2023] [Indexed: 03/24/2023]
Abstract
The recent revolution in tissue-resident macrophage biology has resulted largely from murine studies performed in C57BL/6 mice. Here, using both C57BL/6 and BALB/c mice, we analyze immune cells in the pleural cavity. Unlike C57BL/6 mice, naive tissue-resident large-cavity macrophages (LCMs) of BALB/c mice failed to fully implement the tissue-residency program. Following infection with a pleural-dwelling nematode, these pre-existing differences were accentuated with LCM expansion occurring in C57BL/6, but not in BALB/c mice. While infection drove monocyte recruitment in both strains, only in C57BL/6 mice were monocytes able to efficiently integrate into the resident pool. Monocyte-to-macrophage conversion required both T cells and interleukin-4 receptor alpha (IL-4Rα) signaling. The transition to tissue residency altered macrophage function, and GATA6+ tissue-resident macrophages were required for host resistance to nematode infection. Therefore, during tissue nematode infection, T helper 2 (Th2) cells control the differentiation pathway of resident macrophages, which determines infection outcome.
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Affiliation(s)
- Conor M Finlay
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK; Trinity Health Kidney Centre, Trinity Translational Medicine Institute, Trinity College, Dublin D08 W9RT, Ireland.
| | - James E Parkinson
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Lili Zhang
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Brian H K Chan
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Jesuthas Ajendra
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Alistair Chenery
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Anya Morrison
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Irem Kaymak
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Emma L Houlder
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Syed Murtuza Baker
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Ben R Dickie
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Group, University of Manchester, Salford M6 8HD, UK
| | | | - Joanne E Konkel
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Matthew R Hepworth
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Andrew S MacDonald
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Gwendalyn J Randolph
- Department of Pathology & Immunology, Washington University, St. Louis, MO 63110, USA
| | - Dominik Rückerl
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK
| | - Judith E Allen
- Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK.
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Ohene Y, Harris WJ, Powell E, Wycech NW, Smethers KF, Lasič S, South K, Coutts G, Sharp A, Lawrence CB, Boutin H, Parker GJM, Parkes LM, Dickie BR. Filter exchange imaging with crusher gradient modelling detects increased blood-brain barrier water permeability in response to mild lung infection. Fluids Barriers CNS 2023; 20:25. [PMID: 37013549 PMCID: PMC10071630 DOI: 10.1186/s12987-023-00422-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 03/08/2023] [Indexed: 04/05/2023] Open
Abstract
Blood-brain barrier (BBB) dysfunction occurs in many brain diseases, and there is increasing evidence to suggest that it is an early process in dementia which may be exacerbated by peripheral infection. Filter-exchange imaging (FEXI) is an MRI technique for measuring trans-membrane water exchange. FEXI data is typically analysed using the apparent exchange rate (AXR) model, yielding estimates of the AXR. Crusher gradients are commonly used to remove unwanted coherence pathways arising from longitudinal storage pulses during the mixing period. We first demonstrate that when using thin slices, as is needed for imaging the rodent brain, crusher gradients result in underestimation of the AXR. To address this, we propose an extended crusher-compensated exchange rate (CCXR) model to account for diffusion-weighting introduced by the crusher gradients, which is able to recover ground truth values of BBB water exchange (kin) in simulated data. When applied to the rat brain, kin estimates obtained using the CCXR model were 3.10 s-1 and 3.49 s-1 compared to AXR estimates of 1.24 s-1 and 0.49 s-1 for slice thicknesses of 4.0 mm and 2.5 mm respectively. We then validated our approach using a clinically relevant Streptococcus pneumoniae lung infection. We observed a significant 70 ± 10% increase in BBB water exchange in rats during active infection (kin = 3.78 ± 0.42 s-1) compared to before infection (kin = 2.72 ± 0.30 s-1; p = 0.02). The BBB water exchange rate during infection was associated with higher levels of plasma von Willebrand factor (VWF), a marker of acute vascular inflammation. We also observed 42% higher expression of perivascular aquaporin-4 (AQP4) in infected animals compared to non-infected controls, while levels of tight junction proteins remain consistent between groups. In summary, we propose a modelling approach for FEXI data which removes the bias in estimated water-exchange rates associated with the use of crusher gradients. Using this approach, we demonstrate the impact of peripheral infection on BBB water exchange, which appears to be mediated by endothelial dysfunction and associated with an increase in perivascular AQP4.
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Affiliation(s)
- Yolanda Ohene
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK.
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
| | - William J Harris
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Elizabeth Powell
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering and Department of Neuroinflammation, UCL, London, UK
| | - Nina W Wycech
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Katherine F Smethers
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Samo Lasič
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
- Random Walk Imaging, Lund, Sweden
| | - Kieron South
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Graham Coutts
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Andrew Sharp
- Evotec (UK) Ltd., Alderley Park, Block 23F, Mereside, Cheshire, SK10 4TG, UK
| | - Catherine B Lawrence
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Hervé Boutin
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Geoff J M Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering and Department of Neuroinflammation, UCL, London, UK
- Bioxydyn Limited, Manchester, UK
| | - Laura M Parkes
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Ben R Dickie
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
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7
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Dickie BR, Jin T, Wang P, Hinz R, Harris W, Boutin H, Parker GJ, Parkes LM, Matthews JC. Quantitative kinetic modelling and mapping of cerebral glucose transport and metabolism using glucoCESL MRI. J Cereb Blood Flow Metab 2022; 42:2066-2079. [PMID: 35748031 PMCID: PMC9580170 DOI: 10.1177/0271678x221108841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Chemical-exchange spin-lock (CESL) MRI can map regional uptake and utilisation of glucose in the brain at high spatial resolution (i.e sub 0.2 mm3 voxels). We propose two quantitative kinetic models to describe glucose-induced changes in tissue R1ρ and apply them to glucoCESL MRI data acquired in tumour-bearing and healthy rats. When assuming glucose transport is saturable, the maximal transport capacity (Tmax) measured in normal tissue was 3.2 ± 0.6 µmol/min/mL, the half saturation constant (Kt) was 8.8 ± 2.2 mM, the metabolic rate of glucose consumption (MRglc) was 0.21 ± 0.13 µmol/min/mL, and the cerebral blood volume (vb) was 0.006 ± 0.005 mL/mL. Values in tumour were: Tmax = 7.1 ± 2.7 µmol/min/mL, Kt = 14 ± 1.7 mM, MRglc = 0.22 ± 0.09 µmol/min/mL, vb = 0.030 ± 0.035 mL/mL. Tmax and Kt were significantly higher in tumour tissue than normal tissue (p = 0.006 and p = 0.011, respectively). When assuming glucose uptake also occurs via free diffusion, the free diffusion rate (kd) was 0.061 ± 0.017 mL/min/mL in normal tissue and 0.12 ± 0.042 mL/min/mL in tumour. These parameter estimates agree well with literature values obtained using other approaches (e.g. NMR spectroscopy).
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ping Wang
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Rainer Hinz
- Division of Informatics, Imaging, and Data Science, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK
| | - William Harris
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Hervé Boutin
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Geoff Jm Parker
- Bioxydyn Limited, Manchester, UK.,Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of Neuroinflammation, University College London, London, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Julian C Matthews
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
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8
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Al-Ahmady ZS, Dickie BR, Aldred I, Jasim DA, Barrington J, Haley M, Lemarchand E, Coutts G, Kaur S, Bates J, Curran S, Goddard R, Walker M, Parry-jones A, Kostarelos K, Allan SM. Selective brain entry of lipid nanoparticles in haemorrhagic stroke is linked to biphasic blood-brain barrier disruption. Am J Cancer Res 2022; 12:4477-4497. [PMID: 35832077 PMCID: PMC9254235 DOI: 10.7150/thno.72167] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 04/29/2022] [Indexed: 11/05/2022] Open
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9
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Scott LA, Dickie BR, Rawson SD, Coutts G, Burnett TL, Allan SM, Parker GJ, Parkes LM. Characterisation of microvessel blood velocity and segment length in the brain using multi-diffusion-time diffusion-weighted MRI. J Cereb Blood Flow Metab 2021; 41:1939-1953. [PMID: 33325766 PMCID: PMC8323340 DOI: 10.1177/0271678x20978523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Multi-diffusion-time diffusion-weighted MRI can probe tissue microstructure, but the method has not been widely applied to the microvasculature. At long diffusion-times, blood flow in capillaries is in the diffusive regime, and signal attenuation is dependent on blood velocity (v) and capillary segment length (l). It is described by the pseudo-diffusion coefficient (D*=vl/6) of intravoxel incoherent motion (IVIM). At shorter diffusion-times, blood flow is in the ballistic regime, and signal attenuation depends on v, and not l. In theory, l could be estimated using D* and v. In this study, we compare the accuracy and repeatability of three approaches to estimating v, and therefore l: the IVIM ballistic model, the velocity autocorrelation model, and the ballistic approximation to the velocity autocorrelation model. Twenty-nine rat datasets from two strains were acquired at 7 T, with b-values between 0 and 1000 smm-2 and diffusion times between 11.6 and 50 ms. Five rats were scanned twice to assess scan-rescan repeatability. Measurements of l were validated using corrosion casting and micro-CT imaging. The ballistic approximation of the velocity autocorrelation model had lowest bias relative to corrosion cast estimates of l, and had highest repeatability.
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Affiliation(s)
- Lauren A Scott
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Ben R Dickie
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Shelley D Rawson
- The Henry Royce Institute, Department of Materials, The University of Manchester, Manchester, UK
| | - Graham Coutts
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Timothy L Burnett
- The Henry Royce Institute, Department of Materials, The University of Manchester, Manchester, UK
| | - Stuart M Allan
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Geoff Jm Parker
- The Henry Royce Institute, Department of Materials, The University of Manchester, Manchester, UK.,Bioxydyn Limited, Manchester, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
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10
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Dickie BR, Boutin H, Parker GJM, Parkes LM. Alzheimer's disease pathology is associated with earlier alterations to blood-brain barrier water permeability compared with healthy ageing in TgF344-AD rats. NMR Biomed 2021; 34:e4510. [PMID: 33723901 DOI: 10.1002/nbm.4510] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 02/06/2021] [Accepted: 02/26/2021] [Indexed: 06/12/2023]
Abstract
The effects of Alzheimer's disease (AD) and ageing on blood-brain barrier (BBB) breakdown are investigated in TgF344-AD and wild-type rats aged 13, 18 and 21 months. Permeability surface area products of the BBB to water (PSw ) and gadolinium-based contrast agent (PSg ) were measured in grey matter using multiflip angle multiecho dynamic contrast-enhanced MRI. At 13 months of age, there was no significant difference in PSw between TgF344-AD and wild-types (p = 0.82). Between 13 and 18 months, PSw increased in TgF344-AD rats (p = 0.027), but not in wild-types (p = 0.99), leading to significantly higher PSw in TgF344-AD rats at 18 months, as previously reported (p = 0.012). Between 18 and 21 months, PSw values increased in wild-types (p = 0.050), but not in TgF344-AD rats (p = 0.50). These results indicate that BBB water permeability is affected by both AD pathology and ageing, but that changes occur earlier in the presence of AD pathology. There were no significant genotype or ageing effects on PSg (p > 0.05). In conclusion, we detected increases in BBB water permeability with age in TgF344-AD and wild-type rats, and found that changes occurred at an earlier age in rats with AD pathology.
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Hervé Boutin
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
- Wolfson Molecular Imaging Centre, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, UK
| | - Geoff J M Parker
- Bioxydyn Ltd, Manchester, UK
- Centre for Medical Image Computing, Department of Computer Science and Department of Neuroinflammation, University College London, London, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
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11
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Kyrtata N, Emsley HCA, Sparasci O, Parkes LM, Dickie BR. A Systematic Review of Glucose Transport Alterations in Alzheimer's Disease. Front Neurosci 2021; 15:626636. [PMID: 34093108 PMCID: PMC8173065 DOI: 10.3389/fnins.2021.626636] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 04/22/2021] [Indexed: 12/12/2022] Open
Abstract
Introduction: Alzheimer's disease (AD) is characterized by cerebral glucose hypometabolism. Hypometabolism may be partly due to reduced glucose transport at the blood-brain barrier (BBB) and across astrocytic and neuronal cell membranes. Glucose transporters (GLUTs) are integral membrane proteins responsible for moving glucose from the bloodstream to parenchymal cells where it is metabolized, and evidence indicates vascular and non-vascular GLUTs are altered in AD brains, a process which could starve the brain of glucose and accelerate cognitive decline. Here we review the literature on glucose transport alterations in AD from human and rodent studies. Methods: Literature published between 1st January 1946 and 1st November 2020 within EMBASE and MEDLINE databases was searched for the terms "glucose transporters" AND "Alzheimer's disease". Human and rodent studies were included while reviews, letters, and in-vitro studies were excluded. Results: Forty-three studies fitting the inclusion criteria were identified, covering human (23 studies) and rodent (20 studies). Post-mortem studies showed consistent reductions in GLUT1 and GLUT3 in the hippocampus and cortex of AD brains, areas of the brain closely associated with AD pathology. Tracer studies in rodent models of AD and human AD also exhibit reduced uptake of glucose and glucose-analogs into the brain, supporting these findings. Longitudinal rodent studies clearly indicate that changes in GLUT1 and GLUT3 only occur after amyloid-β pathology is present, and several studies indicate amyloid-β itself may be responsible for GLUT changes. Furthermore, evidence from human and rodent studies suggest GLUT depletion has severe effects on brain function. A small number of studies show GLUT2 and GLUT12 are increased in AD. Anti-diabetic medications improved glucose transport capacity in AD subjects. Conclusions: GLUT1 and GLUT3 are reduced in hippocampal and cortical regions in patients and rodent models of AD, and may be caused by high levels of amyloid-β in these regions. GLUT3 reductions appear to precede the onset of clinical symptoms. GLUT2 and GLUT12 appear to increase and may have a compensatory role. Repurposing anti-diabetic drugs to modify glucose transport shows promising results in human studies of AD.
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Affiliation(s)
- Natalia Kyrtata
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
- University Hospitals of Morecambe Bay NHS Foundation Trust, Lancaster, United Kingdom
| | - Hedley C. A. Emsley
- Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
- Department of Neurology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom
| | - Oli Sparasci
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
- Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom
| | - Laura M. Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Ben R. Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
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12
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Dickie BR, Parker GJM, Parkes LM. Measuring water exchange across the blood-brain barrier using MRI. Prog Nucl Magn Reson Spectrosc 2020; 116:19-39. [PMID: 32130957 DOI: 10.1016/j.pnmrs.2019.09.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 09/04/2019] [Accepted: 09/09/2019] [Indexed: 05/11/2023]
Abstract
The blood-brain barrier (BBB) regulates the transfer of solutes and essential nutrients into the brain. Growing evidence supports BBB dysfunction in a range of acute and chronic brain diseases, justifying the need for novel research and clinical tools that can non-invasively detect, characterize, and quantify BBB dysfunction in-vivo. Many approaches already exist for measuring BBB dysfunction in man using positron emission tomography and magnetic resonance imaging (e.g. dynamic contrast-enhanced MRI measurements of gadolinium leakage). This review paper focusses on MRI measurements of water exchange across the BBB, which occurs through a wide range of pathways, and is likely to be a highly sensitive marker of BBB dysfunction. Key mathematical models and acquisition methods are discussed for the two main approaches: those that utilize contrast agents to enhance relaxation rate differences between the intravascular and extravascular compartments and so enhance the sensitivity of MRI signals to BBB water exchange, and those that utilize the dynamic properties of arterial spin labelling to first isolate signal from intravascular spins and then estimate the impact of water exchange on the evolving signal. Data from studies in healthy and pathological brain tissue are discussed, in addition to validation studies in rodents.
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, University of Manchester, Oxford Road, Manchester M13 9PT, United Kingdom.
| | - Geoff J M Parker
- Bioxydyn Limited, Manchester M15 6SZ, United Kingdom; Centre for Medical Image Computing, Department of Computer Science and Department of Neuroinflammation, University College London, London, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, University of Manchester, Oxford Road, Manchester M13 9PT, United Kingdom
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13
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Dickie BR, Vandesquille M, Ulloa J, Boutin H, Parkes LM, Parker GJM. Water-exchange MRI detects subtle blood-brain barrier breakdown in Alzheimer's disease rats. Neuroimage 2018; 184:349-358. [PMID: 30219292 DOI: 10.1016/j.neuroimage.2018.09.030] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 09/05/2018] [Accepted: 09/12/2018] [Indexed: 01/21/2023] Open
Abstract
Blood-brain barrier (BBB) breakdown has been hypothesized to play a key role in the onset and progression of Alzheimer's disease (AD). However, the question of whether AD itself contributes to loss of BBB integrity is still uncertain, as many in-vivo studies have failed to detect signs of AD-related BBB breakdown. We hypothesize AD-related BBB damage is subtle, and that these negative results arise from a lack of measurement sensitivity. With the aim of developing a more sensitive measure of BBB breakdown, we have designed a novel MRI scanning protocol to quantify the trans-BBB exchange of endogenous water. Using this method, we detect increased BBB water permeability in a rat model of AD that is associated with reduced expression of the tight junction protein occludin. BBB permeability to MRI contrast agent, assessed using dynamic contrast-enhanced (DCE)-MRI, did not differ between transgenic and wild-type animals and was uncorrelated with occludin expression. Our data supports the occurrence of AD-related BBB breakdown, and indicates that such BBB pathology is subtle and may be undetectable using existing 'tracer leakage' methods. Our validated water-exchange MRI method provides a new powerful tool with which to study BBB damage in-vivo.
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK.
| | - Matthias Vandesquille
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK
| | | | - Hervé Boutin
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK
| | - Geoff J M Parker
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK; Bioxydyn Ltd, Manchester, UK
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14
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Dickie BR, Rose CJ, Kershaw LE, Withey SB, Carrington BM, Davidson SE, Hutchison G, West CML. The prognostic value of dynamic contrast-enhanced MRI contrast agent transfer constant K trans in cervical cancer is explained by plasma flow rather than vessel permeability. Br J Cancer 2017; 116:1436-1443. [PMID: 28449009 PMCID: PMC5520098 DOI: 10.1038/bjc.2017.121] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Revised: 04/06/2017] [Accepted: 04/06/2017] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND The microvascular contrast agent transfer constant Ktrans has shown prognostic value in cervical cancer patients treated with chemoradiotherapy. This study aims to determine whether this is explained by the contribution to Ktrans of plasma flow (Fp), vessel permeability surface-area product (PS), or a combination of both. METHODS Pre-treatment dynamic contrast-enhanced MRI (DCE-MRI) data from 36 patients were analysed using the two-compartment exchange model. Estimates of Fp, PS, Ktrans, and fractional plasma and interstitial volumes (vp and ve) were made and used in univariate and multivariate survival analyses adjusting for clinicopathologic variables tumour stage, nodal status, histological subtype, patient age, tumour volume, and treatment type (chemoradiotherapy vs radiotherapy alone). RESULTS In univariate analyses, Fp (HR=0.25, P=0.0095) and Ktrans (HR=0.20, P=0.032) were significantly associated with disease-free survival while PS, vp and ve were not. In multivariate analyses adjusting for clinicopathologic variables, Fp and Ktrans significantly increased the accuracy of survival predictions (P=0.0089). CONCLUSIONS The prognostic value of Ktrans in cervical cancer patients treated with chemoradiotherapy is explained by microvascular plasma flow (Fp) rather than vessel permeability surface-area product (PS).
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Affiliation(s)
- Ben R Dickie
- Division of Molecular and Clinical Cancer Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester M20 4BX, UK.,Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester M20 4BX, UK
| | - Chris J Rose
- Centre for Imaging Sciences, Division of Informatics, Imaging, and Data Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9PG, UK
| | - Lucy E Kershaw
- Division of Molecular and Clinical Cancer Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester M20 4BX, UK.,Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester M20 4BX, UK
| | - Stephanie B Withey
- RRPPS, University Hospitals Birmingham NHS Foundation Trust, Birmingham B30 3HP, UK
| | - Bernadette M Carrington
- Department of Diagnostic Radiology, The Christie NHS Foundation Trust, Manchester M20 4BX, UK
| | - Susan E Davidson
- Department of Diagnostic Radiology, The Christie NHS Foundation Trust, Manchester M20 4BX, UK
| | - Gillian Hutchison
- Department of Radiology, Royal Bolton NHS Foundation Trust, Farnworth BL4 0JR, UK
| | - Catharine M L West
- Division of Molecular and Clinical Cancer Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester M20 4BX, UK
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15
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Dickie BR, Banerji A, Kershaw LE, McPartlin A, Choudhury A, West CM, Rose CJ. Improved accuracy and precision of tracer kinetic parameters by joint fitting to variable flip angle and dynamic contrast enhanced MRI data. Magn Reson Med 2015; 76:1270-81. [PMID: 26480291 DOI: 10.1002/mrm.26013] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2015] [Revised: 09/18/2015] [Accepted: 09/18/2015] [Indexed: 12/23/2022]
Abstract
PURPOSE To improve the accuracy and precision of tracer kinetic model parameter estimates for use in dynamic contrast enhanced (DCE) MRI studies of solid tumors. THEORY Quantitative DCE-MRI requires an estimate of precontrast T1 , which is obtained prior to fitting a tracer kinetic model. As T1 mapping and tracer kinetic signal models are both a function of precontrast T1 it was hypothesized that its joint estimation would improve the accuracy and precision of both precontrast T1 and tracer kinetic model parameters. METHODS Accuracy and/or precision of two-compartment exchange model (2CXM) parameters were evaluated for standard and joint fitting methods in well-controlled synthetic data and for 36 bladder cancer patients. Methods were compared under a number of experimental conditions. RESULTS In synthetic data, joint estimation led to statistically significant improvements in the accuracy of estimated parameters in 30 of 42 conditions (improvements between 1.8% and 49%). Reduced accuracy was observed in 7 of the remaining 12 conditions. Significant improvements in precision were observed in 35 of 42 conditions (between 4.7% and 50%). In clinical data, significant improvements in precision were observed in 18 of 21 conditions (between 4.6% and 38%). CONCLUSION Accuracy and precision of DCE-MRI parameter estimates are improved when signal models are fit jointly rather than sequentially. Magn Reson Med 76:1270-1281, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Ben R Dickie
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK. .,Institute of Cancer Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
| | - Anita Banerji
- Centre for Imaging Sciences, Institute of Population Health, Centre for Imaging Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Lucy E Kershaw
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK.,Institute of Cancer Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Andrew McPartlin
- Institute of Cancer Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.,Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - Ananya Choudhury
- Institute of Cancer Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.,Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - Catharine M West
- Institute of Cancer Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Chris J Rose
- Centre for Imaging Sciences, Institute of Population Health, Centre for Imaging Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
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