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Thomson EL, Powell E, Gandini Wheeler-Kingshott CAM, Parker GJM. Quantification of water exchange across the blood-brain barrier using noncontrast MR fingerprinting. Magn Reson Med 2024; 92:1392-1403. [PMID: 38725240 DOI: 10.1002/mrm.30127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 04/03/2024] [Accepted: 04/05/2024] [Indexed: 07/23/2024]
Abstract
PURPOSE A method is proposed to quantify cerebral blood volume (v b $$ {v}_b $$ ) and intravascular water residence time (τ b $$ {\tau}_b $$ ) using MR fingerprinting (MRF), applied using a spoiled gradient echo sequence without the need for contrast agent. METHODS An in silico study optimized an acquisition protocol to maximize the sensitivity of the measurement tov b $$ {v}_b $$ andτ b $$ {\tau}_b $$ changes. Its accuracy in the presence of variations inT 1 , t $$ {\mathrm{T}}_{1,t} $$ ,T 1 , b $$ {\mathrm{T}}_{1,b} $$ , andB 1 $$ {\mathrm{B}}_1 $$ was evaluated. The optimized protocol (scan time of 19 min) was then tested in a exploratory healthy volunteer study (10 volunteers, mean age 24± $$ \pm $$ 3, six males) at 3 T with a repeat scan taken after repositioning to allow estimation of repeatability. RESULTS Simulations show that assuming literature values forT 1 , b $$ {\mathrm{T}}_{1,b} $$ andT 1 , t $$ {\mathrm{T}}_{1,t} $$ , no variation inB 1 $$ {\mathrm{B}}_1 $$ , while fitting onlyv b $$ {v}_b $$ andτ b $$ {\tau}_b $$ , leads to large errors in quantification ofv b $$ {v}_b $$ andτ b $$ {\tau}_b $$ , regardless of noise levels. However, simulations also show that matchingT 1 , t $$ {\mathrm{T}}_{1,t} $$ ,T 1 , b $$ {\mathrm{T}}_{1,b} $$ ,B 1 + $$ {\mathrm{B}}_1^{+} $$ ,v b $$ {v}_b $$ andτ b $$ {\tau}_b $$ , simultaneously is feasible at clinically achievable noise levels. Across the healthy volunteers, all parameter quantifications fell within the expected literature range. In addition, the maps show good agreement between hemispheres suggesting physiologically relevant information is being extracted. Expected differences between white and gray matterT 1 , t $$ {\mathrm{T}}_{1,t} $$ (p < 0.0001) andv b $$ {v}_b $$ (p < 0.0001) are observed,T 1 , b $$ {\mathrm{T}}_{1,b} $$ andτ b $$ {\tau}_b $$ show no significant differences, p = 0.4 and p = 0.6, respectively. Moderate to excellent repeatability was seen between repeat scans: mean intra-class correlation coefficient ofT 1 , t : 0 . 91 $$ {\mathrm{T}}_{1,t}:0.91 $$ ,T 1 , b : 0 . 58 $$ {\mathrm{T}}_{1,b}:0.58 $$ ,v b : 0 . 90 $$ {v}_b:0.90 $$ , andτ b : 0 . 96 $$ {\tau}_b:0.96 $$ . CONCLUSION We demonstrate that regional simultaneous quantification ofv b $$ {v}_b $$ ,τ b $$ {\tau}_b $$ ,T 1 , b , T 1 , t $$ {\mathrm{T}}_{1,b},{T}_{1,t} $$ , andB 1 + $$ {\mathrm{B}}_1^{+} $$ using MRF is feasible in vivo.
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Affiliation(s)
- Emma L Thomson
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, London, UK
| | - Elizabeth Powell
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, London, UK
- Department of Brain & Behavioural Sciences, University of Pavia, Pavia, Italy
- IRCCS Mondino Foundation, Pavia, Italy
| | - Geoff J M Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, London, UK
- Bioxydyn Limited, Manchester, UK
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Cai TX, Williamson NH, Ravin R, Basser PJ. The Diffusion Exchange Ratio (DEXR): A minimal sampling of diffusion exchange spectroscopy to probe exchange, restriction, and time-dependence. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2024; 366:107745. [PMID: 39126819 DOI: 10.1016/j.jmr.2024.107745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Revised: 07/31/2024] [Accepted: 08/02/2024] [Indexed: 08/12/2024]
Abstract
Water exchange is increasingly recognized as an important biological process that can affect the study of biological tissue using diffusion MR. Methods to measure exchange, however, remain immature as opposed to those used to characterize restriction, with no consensus on the optimal pulse sequence (s) or signal model (s). In general, the trend has been towards data-intensive fitting of highly parameterized models. We take the opposite approach and show that a judicious sub-sample of diffusion exchange spectroscopy (DEXSY) data can be used to robustly quantify exchange, as well as restriction, in a data-efficient manner. This sampling produces a ratio of two points per mixing time: (i) one point with equal diffusion weighting in both encoding periods, which gives maximal exchange contrast, and (ii) one point with the same total diffusion weighting in just the first encoding period, for normalization. We call this quotient the Diffusion EXchange Ratio (DEXR). Furthermore, we show that it can be used to probe time-dependent diffusion by estimating the velocity autocorrelation function (VACF) over intermediate to long times (∼2-500ms). We provide a comprehensive theoretical framework for the design of DEXR experiments in the case of static or constant gradients. Data from Monte Carlo simulations and experiments acquired in fixed and viable ex vivo neonatal mouse spinal cord using a permanent magnet system are presented to test and validate this approach. In viable spinal cord, we report the following apparent parameters from just 6 data points: τk=17±4ms, fNG=0.72±0.01, Reff=1.05±0.01μm, and κeff=0.19±0.04μm/ms, which correspond to the exchange time, restricted or non-Gaussian signal fraction, an effective spherical radius, and permeability, respectively. For the VACF, we report a long-time, power-law scaling with ≈t-2.4, which is approximately consistent with disordered domains in 3-D. Overall, the DEXR method is shown to be highly efficient, capable of providing valuable quantitative diffusion metrics using minimal MR data.
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Affiliation(s)
- Teddy X Cai
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, 20892, MD, USA
| | - Nathan H Williamson
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, 20892, MD, USA
| | - Rea Ravin
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, 20892, MD, USA; Celoptics, Inc., Rockville, 20850, MD, USA
| | - Peter J Basser
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, 20892, MD, USA.
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Abdennadher M, Jacobellis S, Václavů L, Juttukonda M, Inati S, Goldstein L, van Osch MJP, Rosen B, Hua N, Theodore W. Water exchange across the blood-brain barrier and epilepsy: Review on pathophysiology and neuroimaging. Epilepsia Open 2024; 9:1123-1135. [PMID: 38884502 PMCID: PMC11296120 DOI: 10.1002/epi4.12994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 04/30/2024] [Accepted: 05/23/2024] [Indexed: 06/18/2024] Open
Abstract
The blood-brain barrier (BBB) is a barrier protecting the brain and a milieu of continuous exchanges between blood and brain. There is emerging evidence that the BBB plays a major role in epileptogenesis and drug-resistant epilepsy, through several mechanisms, such as water homeostasis dysregulation, overexpression of drug transporters, and inflammation. Studies have shown abnormal water homeostasis in epileptic tissue and altered aquaporin-4 water channel expression in animal epilepsy models. This review focuses on abnormal water exchange in epilepsy and describes recent non-invasive MRI methods of quantifying water exchange. PLAIN LANGUAGE SUMMARY: Abnormal exchange between blood and brain contribute to seizures and epilepsy. The authors describe why correct water balance is necessary for healthy brain functioning and how it is impacted in epilepsy. This review also presents recent MRI methods to measure water exchange in human brain. These measures would improve our understanding of factors leading to seizures.
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Affiliation(s)
- Myriam Abdennadher
- Neurology Department, Boston Medical CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Sara Jacobellis
- Boston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Lena Václavů
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Meher Juttukonda
- Athinoula A. Martinos Center of Biomedical Imaging, Department of Radiology, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Sara Inati
- National Institute of Neurological Disorders and Stroke, NIHBethesdaMarylandUSA
| | - Lee Goldstein
- Psychiatry and Neurology DepartmentBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Matthias J. P. van Osch
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Bruce Rosen
- Athinoula A. Martinos Center of Biomedical Imaging, Department of Radiology, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Ning Hua
- Radiology Department, Boston Medical CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - William Theodore
- National Institute of Neurological Disorders and Stroke, NIHBethesdaMarylandUSA
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Shin HG, Li X, Heo HY, Knutsson L, Szczepankiewicz F, Nilsson M, van Zijl PCM. Compartmental anisotropy of filtered exchange imaging (FEXI) in human white matter: What is happening in FEXI? Magn Reson Med 2024; 92:660-675. [PMID: 38525601 PMCID: PMC11142880 DOI: 10.1002/mrm.30086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/30/2024] [Accepted: 02/28/2024] [Indexed: 03/26/2024]
Abstract
PURPOSE To investigate the effects of compartmental anisotropy on filtered exchange imaging (FEXI) in white matter (WM). THEORY AND METHODS FEXI signals were measured using multiple combinations of diffusion filter and detection directions in five healthy volunteers. Additional filters, including a trace-weighted diffusion filter with trapezoidal gradients, a spherical b-tensor encoded diffusion filter, and a T2 filter, were tested with trace-weighted diffusion detection. RESULTS A large range of apparent exchange rates (AXR) and both positive and negative filter efficiencies (σ) were found depending on the mutual orientation of the filter and detection gradients relative to WM fiber orientation. The data demonstrated that the fast-diffusion compartment suppressed by diffusional filtering is not exclusively extra-cellular, but also intra-cellular. While not comprehensive, a simple two-compartment diffusion tensor model with water exchange was able to account qualitatively for the trends in positive and negative filtering efficiencies, while standard model imaging (SMI) without exchange could not. This two-compartment diffusion tensor model also demonstrated smaller AXR variances across subjects. When employing trace-weighted diffusion detection, AXR values were on the order of the R1 (=1/T1) of water at 3T for crossing fibers, while being less than R1 for parallel fibers. CONCLUSION Orientation-dependent AXR and σ values were observed when using multi-orientation filter and detection gradients in FEXI, indicating that WM FEXI models need to account for compartmental anisotropy. When using trace-weighted detection, AXR values were on the order of or less than R1, complicating the interpretation of FEXI results in WM in terms of biological exchange properties. These findings may contribute toward better understanding of FEXI results in WM.
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Affiliation(s)
- Hyeong-Geol Shin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hye-Young Heo
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Linda Knutsson
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Filip Szczepankiewicz
- Department of Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Markus Nilsson
- Department of Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Wu D, Lee HH, Ba R, Turnbill V, Wang X, Luo Y, Walczak P, Fieremans E, Novikov DS, Martin LJ, Northington FJ, Zhang J. In vivo mapping of cellular resolution neuropathology in brain ischemia with diffusion MRI. SCIENCE ADVANCES 2024; 10:eadk1817. [PMID: 39018390 PMCID: PMC466947 DOI: 10.1126/sciadv.adk1817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 06/11/2024] [Indexed: 07/19/2024]
Abstract
Noninvasive mapping of cellular pathology can provide critical diagnostic and prognostic information. Recent advances in diffusion magnetic resonance imaging enabled in vivo examination of tissue microstructures well beyond the imaging resolution. Here, we proposed to use diffusion time-dependent diffusion kurtosis imaging (tDKI) to simultaneously assess cellular morphology and transmembrane permeability in hypoxic-ischemic (HI) brain injury. Through numerical simulations and organoid imaging, we demonstrated the feasibility of capturing effective size and permeability changes using tDKI. In vivo MRI of HI-injured mouse brains detected a shift of the tDKI peak to longer diffusion times, suggesting swelling of the cellular processes. Furthermore, we observed a faster decrease of the tDKI tail, reflecting increased transmembrane permeability associated with up-regulated water exchange or necrosis. Such information, unavailable from a single diffusion time, can predict salvageable tissues. Preliminary applications of tDKI in patients with ischemic stroke suggested increased transmembrane permeability in stroke regions, illustrating tDKI's potential for detecting pathological changes in the clinics.
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Affiliation(s)
- Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Department of Radiology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
- Binjiang Institute of Zhejiang University, Hangzhou, Zhejiang, China
| | - Hong-Hsi Lee
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Ruicheng Ba
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Victoria Turnbill
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Xiaoli Wang
- School of Medical Imaging, Weifang Medical School, Weifang, Shandong, China
| | - Yu Luo
- Department of Radiology, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Piotr Walczak
- Department of Radiology, University of Maryland, Baltimore, MD, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Dmitry S. Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Lee J. Martin
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Frances J. Northington
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jiangyang Zhang
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
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Lasič S, Chakwizira A, Lundell H, Westin CF, Nilsson M. Tuned exchange imaging: Can the filter exchange imaging pulse sequence be adapted for applications with thin slices and restricted diffusion? NMR IN BIOMEDICINE 2024:e5208. [PMID: 38961745 DOI: 10.1002/nbm.5208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 06/04/2024] [Accepted: 06/06/2024] [Indexed: 07/05/2024]
Abstract
Filter exchange imaging (FEXI) is a double diffusion-encoding (DDE) sequence that is specifically sensitive to exchange between sites with different apparent diffusivities. FEXI uses a diffusion-encoding filtering block followed by a detection block at varying mixing times to map the exchange rate. Long mixing times enhance the sensitivity to exchange, but they pose challenges for imaging applications that require a stimulated echo sequence with crusher gradients. Thin imaging slices require strong crushers, which can introduce significant diffusion weighting and bias exchange rate estimates. Here, we treat the crushers as an additional encoding block and consider FEXI as a triple diffusion-encoding sequence. This allows the bias to be corrected in the case of multi-Gaussian diffusion, but not easily in the presence of restricted diffusion. Our approach addresses challenges in the presence of restricted diffusion and relies on the ability to independently gauge sensitivities to exchange and restricted diffusion for arbitrary gradient waveforms. It follows two principles: (i) the effects of crushers are included in the forward model using signal cumulant expansion; and (ii) timing parameters of diffusion gradients in filter and detection blocks are adjusted to maintain the same level of restriction encoding regardless of the mixing time. This results in the tuned exchange imaging (TEXI) protocol. The accuracy of exchange mapping with TEXI was assessed through Monte Carlo simulations in spheres of identical sizes and gamma-distributed sizes, and in parallel hexagonally packed cylinders. The simulations demonstrate that TEXI provides consistent exchange rates regardless of slice thickness and restriction size, even with strong crushers. However, the accuracy depends on b-values, mixing times, and restriction geometry. The constraints and limitations of TEXI are discussed, including suggestions for protocol adaptations. Further studies are needed to optimize the precision of TEXI and assess the approach experimentally in realistic, heterogeneous substrates.
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Affiliation(s)
- Samo Lasič
- Department of Diagnostic Radiology, Lund University, Lund, Sweden
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Arthur Chakwizira
- Department of Medical Radiation Physics, Lund, Lund University, Lund, Sweden
| | - Henrik Lundell
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- MR Section, DTU Health Tech, Technical University of Denmark, Lyngby, Denmark
| | - Carl-Fredrik Westin
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Markus Nilsson
- Department of Clinical Sciences Lund, Radiology, Lund University, Lund, Sweden
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Li X, Lin Z, Liu C, Bai R, Wu D, Yang J. Glymphatic Imaging in Pediatrics. J Magn Reson Imaging 2024; 59:1523-1541. [PMID: 37819198 DOI: 10.1002/jmri.29040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/25/2023] [Accepted: 09/26/2023] [Indexed: 10/13/2023] Open
Abstract
The glymphatic system, which facilitates cerebrospinal fluid (CSF) flow through the brain parenchyma, is important for brain development and waste clearance. Advances in imaging techniques, particularly magnetic resonance imaging, have make it possible to evaluate glymphatic structures and functions in vivo. Recently, several studies have focused on the development and alterations of the glymphatic system in pediatric disorders. This review discusses the development of the glymphatic system, advances of imaging techniques and their applications in pediatric disorders. First, the results of the reviewed studies indicate that the development of the glymphatic system is a long-lasting process that continues into adulthood. Second, there is a need for improved glymphatic imaging techniques that are non-invasive and fast to improve suitability for pediatric applications, as some of existing methods use contrast injection and are susceptible to motion artifacts from long scanning times. Several novel techniques are potentially feasible for pediatric patients and may be used in the future. Third, the glymphatic dysfunction is associated with a large number of pediatric disorders, although only a few have recently been investigated. In conclusion, research on the pediatric glymphatic system remains an emerging field. The preliminary applications of glymphatic imaging techniques have provided unique insight into the pathological mechanism of pediatric diseases, but mainly limited in visualization of enlarged perivascular spaces and morphological measurements on CSF volumes. More in-depth studies on glymphatic functions are required to improve our understanding of the mechanisms underlying brain development and pediatric diseases. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Xianjun Li
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zixuan Lin
- Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Congcong Liu
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ruiliang Bai
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Dan Wu
- Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Jian Yang
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Engineering Research Center of Computational Imaging and Medical Intelligence, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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Wang Z, Wang B, Li Z, Han G, Meng C, Jiao B, Guo K, Hsu YC, Sun Y, Liu Y, Bai R. The Consistence of Dynamic Contrast-Enhanced MRI and Filter-Exchange Imaging in Measuring Water Exchange Across the Blood-Brain Barrier in High-Grade Glioma. J Magn Reson Imaging 2023; 58:1850-1860. [PMID: 37021659 DOI: 10.1002/jmri.28729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 03/28/2023] [Accepted: 03/28/2023] [Indexed: 04/07/2023] Open
Abstract
BACKGROUND Water exchange across blood-brain barrier (BBB) (WEXBBB ) is an emerging biomarker of BBB dysfunction with potential applications in many brain diseases. Several MRI methods have been proposed to measure WEXBBB , but evidence remains scarce whether different methods can produce comparable WEXBBB . PURPOSE To explore whether dynamic contrast-enhanced (DCE)-MRI and vascular water exchange imaging (VEXI) could produce comparable WEXBBB in high-grade glioma (HGG) patients. STUDY TYPE Prospective cross-sectional. SUBJECTS 13 HGG patients (58.4 ± 9.4 years, 9 females, 4 WHO III and 9 WHO IV). FIELD STRENGTH/SEQUENCE A 3 T, spoiled gradient-recalled-echo DCE-MRI and VEXI containing two pulsed-gradient spin-echo blocks separated by a mixing block. ASSESSMENTS The enhanced tumor and contralateral normal-appearing white matter (cNAWM) volume-of-interests (VOIs) were drew by two neuroradiologists. And whole-brain NAWM and normal-appearing gray matter (NAGM) without tumor-affected regions were segmented by automated segmentation algorithm in FSL. STATISTICAL TESTS Student's t-test was used to evaluate parameters difference between cNAWM and tumor, NAGM and NAWM, respectively. The correlation between vascular water efflux rate constant (kbo ) from DCE-MRI and apparent exchange rate across BBB (AXRBBB ) from VEXI was evaluated by Pearson correlation. P < 0.05 was considered statistically significant. RESULTS Compared with cNAWM, both kbo and AXRBBB were significantly reduced in tumor (kbo = 3.50 ± 1.18 sec-1 vs. 1.03 ± 0.75 sec-1 ; AXRBBB = 3.54 ± 1.11 sec-1 vs. 1.94 ± 1.04 sec-1 ). Both kbo and AXRBBB showed significantly higher values in NAWM than NAGM (kbo = 3.50 ± 0.59 sec-1 vs. 2.10 ± 0.56 sec-1 ; AXRBBB = 3.35 ± 0.77 sec-1 vs. 2.07 ± 0.52 sec-1 ). The VOI-averaged kbo and AXRBBB were also linearly correlated in tumor, NAWM, and NAGM (r = 0.59). DATA CONCLUSION DCE-MRI and VEXI showed comparable and correlated WEXBBB in HGG patients, suggesting that the consistence and reliability of these two MRI methods in measuring WEXBBB . EVIDENCE LEVEL 2. TECHNICAL EFFICACY Stage 1.
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Affiliation(s)
- Zejun Wang
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Run Shaw Hospital and Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Bao Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Zhaoqing Li
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Run Shaw Hospital and Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Guangxu Han
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Run Shaw Hospital and Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Cheng Meng
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Bingjie Jiao
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Run Shaw Hospital and Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Kaiyue Guo
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare, Shanghai, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare, Shanghai, China
| | - Yingchao Liu
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Ruiliang Bai
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Run Shaw Hospital and Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
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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 IN BIOMEDICINE 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] [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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10
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Yang Z, Fang C, Li JR. Incorporating interface permeability into the diffusion MRI signal representation while using impermeable Laplace eigenfunctions. Phys Med Biol 2023; 68:175036. [PMID: 37579758 DOI: 10.1088/1361-6560/acf022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 08/14/2023] [Indexed: 08/16/2023]
Abstract
Objective. The complex-valued transverse magnetization due to diffusion-encoding magnetic field gradients acting on a permeable medium can be modeled by the Bloch-Torrey partial differential equation. The diffusion magnetic resonance imaging (MRI) signal has a representation in the basis of the Laplace eigenfunctions of the medium. However, in order to estimate the permeability coefficient from diffusion MRI data, it is desirable that the forward solution can be calculated efficiently for many values of permeability.Approach. In this paper we propose a new formulation of the permeable diffusion MRI signal representation in the basis of the Laplace eigenfunctions of the same medium where the interfaces are made impermeable.Main results.We proved the theoretical equivalence between our new formulation and the original formulation in the case that the full eigendecomposition is used. We validated our method numerically and showed promising numerical results when a partial eigendecomposition is used. Two diffusion MRI sequences were used to illustrate the numerical validity of our new method.Significance.Our approach means that the same basis (the impermeable set) can be used for all permeability values, which reduces the computational time significantly, enabling the study of the effects of the permeability coefficient on the diffusion MRI signal in the future.
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Affiliation(s)
- Zheyi Yang
- Equipe IDEFIX, INRIA Saclay, UMA, ENSTA PARIS, Palaiseau, France
| | - Chengran Fang
- Equipe IDEFIX, INRIA Saclay, UMA, ENSTA PARIS, Palaiseau, France
| | - Jing-Rebecca Li
- Equipe IDEFIX, INRIA Saclay, UMA, ENSTA PARIS, Palaiseau, France
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11
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Wu D, Turnbill V, Lee HH, Wang X, Ba R, Walczak P, Martin LJ, Fieremans E, Novikov DS, Northington FJ, Zhang J. In vivo Mapping of Cellular Resolution Neuropathology in Brain Ischemia by Diffusion MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.08.552374. [PMID: 37609182 PMCID: PMC10441332 DOI: 10.1101/2023.08.08.552374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Non-invasive mapping of cellular pathology can provide critical diagnostic and prognostic information. Recent developments in diffusion MRI have produced new tools for examining tissue microstructure at a level well below the imaging resolution. Here, we report the use of diffusion time ( t )-dependent diffusion kurtosis imaging ( t DKI) to simultaneously assess the morphology and transmembrane permeability of cells and their processes in the context of pathological changes in hypoxic-ischemic brain (HI) injury. Through Monte Carlo simulations and cell culture organoid imaging, we demonstrate feasibility in measuring effective size and permeability changes based on the peak and tail of t DKI curves. In a mouse model of HI, in vivo imaging at 11.7T detects a marked shift of the t DKI peak to longer t in brain edema, suggesting swelling and beading associated with the astrocytic processes and neuronal neurites. Furthermore, we observed a faster decrease of the t DKI tail in injured brain regions, reflecting increased membrane permeability that was associated with upregulated water exchange upon astrocyte activation at acute stage as well as necrosis with disrupted membrane integrity at subacute stage. Such information, unavailable with conventional diffusion MRI at a single t, can predict salvageable tissues. For a proof-of-concept, t DKI at 3T on an ischemic stroke patient suggested increased membrane permeability in the stroke region. This work therefore demonstrates the potential of t DKI for in vivo detection of the pathological changes in microstructural morphology and transmembrane permeability after ischemic injury using a clinically translatable protocol.
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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] [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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Zhang Y, Wang Y, Li Z, Wang Z, Cheng J, Bai X, Hsu YC, Sun Y, Li S, Shi J, Sui B, Bai R. Vascular-water-exchange MRI (VEXI) enables the detection of subtle AXR alterations in Alzheimer's disease without MRI contrast agent, which may relate to BBB integrity. Neuroimage 2023; 270:119951. [PMID: 36805091 DOI: 10.1016/j.neuroimage.2023.119951] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 02/14/2023] [Accepted: 02/16/2023] [Indexed: 02/21/2023] Open
Abstract
Blood-brain barrier (BBB) impairment is an important pathophysiological process in Alzheimer's disease (AD) and a potential biomarker for early diagnosis of AD. However, most current neuroimaging methods assessing BBB function need the injection of exogenous contrast agents (or tracers), which limits the application of these methods in a large population. In this study, we aim to explore the feasibility of vascular water exchange MRI (VEXI), a diffusion-MRI-based method proposed to assess the BBB permeability to water molecules without using a contrast agent, in the detection of the BBB breakdown in AD. We tested VEXI on a 3T MRI scanner on three groups: AD patients (AD group), mild cognitive impairment (MCI) patients due to AD (MCI group), and the age-matched normal cognition subjects (NC group). Interestingly, we find that the apparent water exchange across the BBB (AXRBBB) measured by VEXI shows higher values in MCI compared with NC, and this higher AXRBBB happens specifically in the hippocampus. This increase in AXRBBB value gets larger and extends to more brain regions (medial orbital frontal cortex and thalamus) from MCI group to the AD group. Furthermore, we find that the AXRBBB values of these three regions is correlated significantly with the impairment of respective cognitive domains independent of age, sex and education. These results suggest VEXI is a promising method to assess the BBB breakdown in AD.
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Affiliation(s)
- Yifan Zhang
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Yue Wang
- National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhaoqing Li
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Zejun Wang
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Juange Cheng
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xiaoyan Bai
- Tiantan Neuroimaging Center of Excellence, China National Clinical Research Center for Neurological Diseases, Beijing, China; Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing Neurosurgical Institute, Beijing, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare, Shanghai, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare, Shanghai, China
| | - Shiping Li
- National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Jiong Shi
- National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Binbin Sui
- National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
| | - Ruiliang Bai
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University.
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14
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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] [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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15
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Li C, Fieremans E, Novikov DS, Ge Y, Zhang J. Measuring water exchange on a preclinical MRI system using filter exchange and diffusion time dependent kurtosis imaging. Magn Reson Med 2023; 89:1441-1455. [PMID: 36404493 PMCID: PMC9892228 DOI: 10.1002/mrm.29536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 11/01/2022] [Accepted: 11/02/2022] [Indexed: 11/22/2022]
Abstract
PURPOSE Filter exchange imaging (FEXI) and diffusion time (t)-dependent diffusion kurtosis imaging (DKI(t)) are both sensitive to water exchange between tissue compartments. The restrictive effects of tissue microstructure, however, introduce bias to the exchange rate obtained by these two methods, as their interpretation conventionally rely on the Kärger model of barrier limited exchange between Gaussian compartments. Here, we investigated whether FEXI and DKI(t) can provide comparable exchange rates in ex vivo mouse brains. THEORY AND METHODS FEXI and DKI(t) data were acquired from ex vivo mouse brains on a preclinical MRI system. Phase cycling and negative slice prewinder gradients were used to minimize the interferences from imaging gradients. RESULTS In the corpus callosum, apparent exchange rate (AXR) from FEXI correlated with the exchange rate (the inverse of exchange time, 1/τex ) from DKI(t) along the radial direction. In comparison, discrepancies between FEXI and DKI(t) were found in the cortex due to low filter efficiency and confounding effects from tissue microstructure. CONCLUSION The results suggest that FEXI and DKI(t) are sensitive to the same exchange processes in white matter when separated from restrictive effects of microstructure. The complex microstructure in gray matter, with potential exchange among multiple compartments and confounding effects of microstructure, still pose a challenge for FEXI and DKI(t).
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Affiliation(s)
- Chenyang Li
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA
| | - Els Fieremans
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA
| | - Dmitry S. Novikov
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA
| | - Yulin Ge
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA
| | - Jiangyang Zhang
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA
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16
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Jia Y, Xu S, Han G, Wang B, Wang Z, Lan C, Zhao P, Gao M, Zhang Y, Jiang W, Qiu B, Liu R, Hsu YC, Sun Y, Liu C, Liu Y, Bai R. Transmembrane water-efflux rate measured by magnetic resonance imaging as a biomarker of the expression of aquaporin-4 in gliomas. Nat Biomed Eng 2023; 7:236-252. [PMID: 36376487 DOI: 10.1038/s41551-022-00960-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 10/10/2022] [Indexed: 11/16/2022]
Abstract
The water-selective channel protein aquaporin-4 (AQP4) contributes to the migration and proliferation of gliomas, and to their resistance to therapy. Here we show, in glioma cell cultures, in subcutaneous and orthotopic gliomas in rats, and in glioma tumours in patients, that transmembrane water-efflux rate is a sensitive biomarker of AQP4 expression and can be measured via conventional dynamic-contrast-enhanced magnetic resonance imaging. Water-efflux rates correlated with stages of glioma proliferation as well as with changes in the heterogeneity of intra-tumoural and inter-tumoural AQP4 in rodent and human gliomas following treatment with temozolomide and with the AQP4 inhibitor TGN020. Regions with low water-efflux rates contained higher fractions of stem-like slow-cycling cells and therapy-resistant cells, suggesting that maps of water-efflux rates could be used to identify gliomas that are resistant to therapies.
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Affiliation(s)
- Yinhang Jia
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Shangchen Xu
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Guangxu Han
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Bao Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Zejun Wang
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Chuanjin Lan
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Peng Zhao
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Meng Gao
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yi Zhang
- Department of Radiology, Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Wenhong Jiang
- Zhejiang University School of Medicine, Hangzhou, China
| | - Biying Qiu
- Zhejiang University School of Medicine, Hangzhou, China
| | - Rui Liu
- Zhejiang University School of Medicine, Hangzhou, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare, Shanghai, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare, Shanghai, China
| | - Chong Liu
- MOE Frontier Science Center for Brain Science and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
| | - Yingchao Liu
- Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
- Shandong National Center for Applied Mathematics, Shandong University, Jinan, China.
| | - Ruiliang Bai
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, China.
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
- MOE Frontier Science Center for Brain Science and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China.
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17
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Harris WJ, Asselin MC, Hinz R, Parkes LM, Allan S, Schiessl I, Boutin H, Dickie BR. In vivo methods for imaging blood-brain barrier function and dysfunction. Eur J Nucl Med Mol Imaging 2023; 50:1051-1083. [PMID: 36437425 PMCID: PMC9931809 DOI: 10.1007/s00259-022-05997-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 10/09/2022] [Indexed: 11/29/2022]
Abstract
The blood-brain barrier (BBB) is the interface between the central nervous system and systemic circulation. It tightly regulates what enters and is removed from the brain parenchyma and is fundamental in maintaining brain homeostasis. Increasingly, the BBB is recognised as having a significant role in numerous neurological disorders, ranging from acute disorders (traumatic brain injury, stroke, seizures) to chronic neurodegeneration (Alzheimer's disease, vascular dementia, small vessel disease). Numerous approaches have been developed to study the BBB in vitro, in vivo, and ex vivo. The complex multicellular structure and effects of disease are difficult to recreate accurately in vitro, and functional aspects of the BBB cannot be easily studied ex vivo. As such, the value of in vivo methods to study the intact BBB cannot be overstated. This review discusses the structure and function of the BBB and how these are affected in diseases. It then discusses in depth several established and novel methods for imaging the BBB in vivo, with a focus on MRI, nuclear imaging, and high-resolution intravital fluorescence microscopy.
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Affiliation(s)
- William James Harris
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK
| | - Marie-Claude Asselin
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, UK
| | - Rainer Hinz
- Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
| | - Laura Michelle Parkes
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK
| | - Stuart Allan
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK
| | - Ingo Schiessl
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK
| | - Herve Boutin
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK.
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK.
- Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK.
| | - Ben Robert Dickie
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, UK
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18
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Khateri M, Reisert M, Sierra A, Tohka J, Kiselev VG. What does FEXI measure? NMR IN BIOMEDICINE 2022; 35:e4804. [PMID: 35892279 DOI: 10.1002/nbm.4804] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 06/22/2022] [Accepted: 07/23/2022] [Indexed: 06/15/2023]
Abstract
Filter-exchange imaging (FEXI) has already been utilized in several biomedical studies for evaluating the permeability of cell membranes. The method relies on suppressing the extracellular signal using strong diffusion weighting (the mobility filter causing a reduction in the overall diffusivity) and monitoring the subsequent diffusivity recovery. Using Monte Carlo simulations, we demonstrate that FEXI is sensitive not uniquely to the transcytolemmal exchange but also to the geometry of involved compartments: complex geometry offers locations where spins remain unaffected by the mobility filter; moving to other locations afterwards, such spins contribute to the diffusivity recovery without actually permeating any membrane. This exchange mechanism is a warning for those who aim to use FEXI in complex media such as brain gray matter and opens wide scope for investigation towards crystallizing the genuine membrane permeation and characterizing the compartment geometry.
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Affiliation(s)
- Mohammad Khateri
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Marco Reisert
- Medical Physics, Department of Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Stereotactic and Functional Neurosurgery, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Alejandra Sierra
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jussi Tohka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Valerij G Kiselev
- Medical Physics, Department of Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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19
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Role of Transmembrane Water Exchange in Glioma Invasion/Migration: In Vivo Preclinical Study by Relaxometry at Very Low Magnetic Field. Cancers (Basel) 2022; 14:cancers14174180. [PMID: 36077717 PMCID: PMC9454706 DOI: 10.3390/cancers14174180] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 08/24/2022] [Accepted: 08/26/2022] [Indexed: 11/17/2022] Open
Abstract
This work shows that the longitudinal relaxation differences observed at very low magnetic fields between invasion/migration and proliferation processes on glioma mouse models in vivo are related to differences in the transmembrane water exchange basically linked to the aquaporin expression changes. Three glioma mouse models were used: Glio6 and Glio96 as invasion/migration models and U87 as cell proliferation model. In vivo proton longitudinal relaxation-rate constants (R1) at very low fields were measured by fast field cycling NMR (FFC-NMR). The tumor contribution to the observed proton relaxation rate, R1tum (U87: 12.26 ± 0.64 s−1; Glio6: 3.76 ± 0.88 s−1; Glio96: 6.90 ± 0.64 s−1 at 0.01 MHz), and the intracellular water lifetime, τin (U87: 826 ± 19 ms; Glio6: 516 ± 8 ms; Glio96: 596 ± 15 ms), were found to be good diagnostic hallmarks to distinguish invasion/migration from proliferation (p < 0.01 and 0.001). Overexpression of AQP4 and AQP1 were assessed in invasion/migration models, highlighting the pathophysiological role of these two aquaporins in water exchange that, in turn, determine the lower values in the observed R1 relaxation rate constant in glioma invasion/migration. Overall, our findings demonstrate that τin and R1 (measured at very low fields) are relevant biomarkers, discriminating invasion/migration from proliferation in vivo. These results highlight the use of FFC-NMR and FFC-imaging to assess the efficiency of drugs that could modulate aquaporin functions.
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20
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Jelescu IO, de Skowronski A, Geffroy F, Palombo M, Novikov DS. Neurite Exchange Imaging (NEXI): A minimal model of diffusion in gray matter with inter-compartment water exchange. Neuroimage 2022; 256:119277. [PMID: 35523369 PMCID: PMC10363376 DOI: 10.1016/j.neuroimage.2022.119277] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 04/26/2022] [Accepted: 05/01/2022] [Indexed: 01/18/2023] Open
Abstract
Biophysical models of diffusion in white matter have been center-stage over the past two decades and are essentially based on what is now commonly referred to as the "Standard Model" (SM) of non-exchanging anisotropic compartments with Gaussian diffusion. In this work, we focus on diffusion MRI in gray matter, which requires rethinking basic microstructure modeling blocks. In particular, at least three contributions beyond the SM need to be considered for gray matter: water exchange across the cell membrane - between neurites and the extracellular space; non-Gaussian diffusion along neuronal and glial processes - resulting from structural disorder; and signal contribution from soma. For the first contribution, we propose Neurite Exchange Imaging (NEXI) as an extension of the SM of diffusion, which builds on the anisotropic Kärger model of two exchanging compartments. Using datasets acquired at multiple diffusion weightings (b) and diffusion times (t) in the rat brain in vivo, we investigate the suitability of NEXI to describe the diffusion signal in the gray matter, compared to the other two possible contributions. Our results for the diffusion time window 20-45 ms show minimal diffusivity time-dependence and more pronounced kurtosis decay with time, which is well fit by the exchange model. Moreover, we observe lower signal for longer diffusion times at high b. In light of these observations, we identify exchange as the mechanism that best explains these signal signatures in both low-b and high-b regime, and thereby propose NEXI as the minimal model for gray matter microstructure mapping. We finally highlight multi-b multi-t acquisition protocols as being best suited to estimate NEXI model parameters reliably. Using this approach, we estimate the inter-compartment water exchange time to be 15 - 60 ms in the rat cortex and hippocampus in vivo, which is of the same order or shorter than the diffusion time in typical diffusion MRI acquisitions. This suggests water exchange as an essential component for interpreting diffusion MRI measurements in gray matter.
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Affiliation(s)
- Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland; School of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland.
| | - Alexandre de Skowronski
- CIBM Center for Biomedical Imaging, Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | | | - Marco Palombo
- School of Psychology, Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK; School of Computer Science and Informatics, Cardiff University, Cardiff, UK; Department of Computer Science, Centre for Medical Image Computing, University College London, London, UK
| | - Dmitry S Novikov
- Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
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21
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Cai TX, Williamson NH, Ravin R, Basser PJ. Disentangling the effects of restriction and exchange with diffusion exchange spectroscopy. FRONTIERS IN PHYSICS 2022; 10:805793. [PMID: 37063496 PMCID: PMC10104504 DOI: 10.3389/fphy.2022.805793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Diffusion exchange spectroscopy (DEXSY) is a multidimensional NMR technique that can reveal how water molecules exchange between compartments within heterogeneous media, such as biological tissue. Data from DEXSY experiments is typically processed using numerical inverse Laplace transforms (ILTs) to produce a diffusion-diffusion spectrum. A tacit assumption of this ILT approach is that the signal behavior is Gaussian - i.e., the spin echo intensity decays exponentially with the degree of diffusion weighting. The assumptions that underlie Gaussian signal behavior may be violated, however, depending on the gradient strength applied and the sample under study. We argue that non-Gaussian signal behavior due to restrictions is to be expected in the study of biological tissue using diffusion NMR. Further, we argue that this signal behavior can produce confounding features in the diffusion-diffusion spectra obtained from numerical ILTs of DEXSY data - entangling the effects of restriction and exchange. Specifically, restricted signal behavior can result in broadening of peaks and in the appearance of illusory exchanging compartments with distributed diffusivities, which pearl into multiple peaks if not highly regularized. We demonstrate these effects on simulated data. That said, we suggest the use of features in the signal acquisition domain that can be used to rapidly probe exchange without employing an ILT. We also propose a means to characterize the non-Gaussian signal behavior due to restrictions within a sample using DEXSY measurements with a near zero mixing time or storage interval. We propose a combined acquisition scheme to independently characterize restriction and exchange with various DEXSY measurements, which we term Restriction and Exchange from Equally-weighted Double and Single Diffusion Encodings (REEDS-DE). We test this method on ex vivo neonatal mouse spinal cord - a sample consisting primarily of gray matter - using a low-field, static gradient NMR system. In sum, we highlight critical shortcomings of prevailing DEXSY analysis methods that conflate the effects of restriction and exchange, and suggest a viable experimental approach to disentangle them.
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Affiliation(s)
- Teddy X. Cai
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Nathan H. Williamson
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
- National Institute of General Medical Sciences, National Institutes of Health, Bethesda, Maryland, USA
| | - Rea Ravin
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
- Celoptics, Rockville, Maryland, USA
| | - Peter J. Basser
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
- Correspondence: Peter J. Basser, Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Building 13, Room 3W16, 13 South Drive, Bethesda, Maryland 20892-5772, USA,
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22
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Li Z, Pang Z, Cheng J, Hsu YC, Sun Y, Özarslan E, Bai R. The direction-dependence of apparent water exchange rate in human white matter. Neuroimage 2021; 247:118831. [PMID: 34923129 DOI: 10.1016/j.neuroimage.2021.118831] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 12/10/2021] [Accepted: 12/15/2021] [Indexed: 11/29/2022] Open
Abstract
Transmembrane water exchange is a potential biomarker in the diagnosis and understanding of cancers, brain disorders, and other diseases. Filter-exchange imaging (FEXI), a special case of diffusion exchange spectroscopy adapted for clinical applications, has the potential to reveal different physiological water exchange processes. However, it is still controversial whether modulating the diffusion encoding gradient direction can affect the apparent exchange rate (AXR) measurements of FEXI in white matter (WM) where water diffusion shows strong anisotropy. In this study, we explored the diffusion-encoding direction dependence of FEXI in human brain white matter by performing FEXI with 20 diffusion-encoding directions on a clinical 3T scanner in-vivo. The results show that the AXR values measured when the gradients are perpendicular to the fiber orientation (0.77 ± 0.13 s - 1, mean ± standard deviation of all the subjects) are significantly larger than the AXR estimates when the gradients are parallel to the fiber orientation (0.33 ± 0.14 s - 1, p < 0.001) in WM voxels with coherently-orientated fibers. In addition, no significant correlation is found between AXRs measured along these two directions, indicating that they are measuring different water exchange processes. What's more, only the perpendicular AXR rather than the parallel AXR shows dependence on axonal diameter, indicating that the perpendicular AXR might reflect transmembrane water exchange between intra-axonal and extra-cellular spaces. Further finite difference (FD) simulations having three water compartments (intra-axonal, intra-glial, and extra-cellular spaces) to mimic WM micro-environments also suggest that the perpendicular AXR is more sensitive to the axonal water transmembrane exchange than parallel AXR. Taken together, our results show that AXR measured along different directions could be utilized to probe different water exchange processes in WM.
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Affiliation(s)
- Zhaoqing Li
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Zhenfeng Pang
- Department of Chemistry, Zhejiang University, Hangzhou, China
| | - Juange Cheng
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare, Shanghai, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare, Shanghai, China
| | - Evren Özarslan
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
| | - Ruiliang Bai
- Department of Physical Medicine and Rehabilitation of the Affiliated Sir Run Shaw Hospital AND Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory of Biomedical Engineering of Education Ministry, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
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23
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Afzali M, Nilsson M, Palombo M, Jones DK. SPHERIOUSLY? The challenges of estimating sphere radius non-invasively in the human brain from diffusion MRI. Neuroimage 2021; 237:118183. [PMID: 34020013 PMCID: PMC8285594 DOI: 10.1016/j.neuroimage.2021.118183] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 04/25/2021] [Accepted: 05/16/2021] [Indexed: 11/16/2022] Open
Abstract
The Soma and Neurite Density Imaging (SANDI) three-compartment model was recently proposed to disentangle cylindrical and spherical geometries, attributed to neurite and soma compartments, respectively, in brain tissue. There are some recent advances in diffusion-weighted MRI signal encoding and analysis (including the use of multiple so-called 'b-tensor' encodings and analysing the signal in the frequency-domain) that have not yet been applied in the context of SANDI. In this work, using: (i) ultra-strong gradients; (ii) a combination of linear, planar, and spherical b-tensor encodings; and (iii) analysing the signal in the frequency domain, three main challenges to robust estimation of sphere size were identified: First, the Rician noise floor in magnitude-reconstructed data biases estimates of sphere properties in a non-uniform fashion. It may cause overestimation or underestimation of the spherical compartment size and density. This can be partly ameliorated by accounting for the noise floor in the estimation routine. Second, even when using the strongest diffusion-encoding gradient strengths available for human MRI, there is an empirical lower bound on the spherical signal fraction and radius that can be detected and estimated robustly. For the experimental setup used here, the lower bound on the sphere signal fraction was approximately 10%. We employed two different ways of establishing the lower bound for spherical radius estimates in white matter. The first, examining power-law relationships between the DW-signal and diffusion weighting in empirical data, yielded a lower bound of 7μm, while the second, pure Monte Carlo simulations, yielded a lower limit of 3μm and in this low radii domain, there is little differentiation in signal attenuation. Third, if there is sensitivity to the transverse intra-cellular diffusivity in cylindrical structures, e.g., axons and cellular projections, then trying to disentangle two diffusion-time-dependencies using one experimental parameter (i.e., change in frequency-content of the encoding waveform) makes spherical radii estimates particularly challenging. We conclude that due to the aforementioned challenges spherical radii estimates may be biased when the corresponding sphere signal fraction is low, which must be considered.
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Affiliation(s)
- Maryam Afzali
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
| | - Markus Nilsson
- Clinical Sciences Lund, Radiology, Lund University, Lund, Sweden.
| | - Marco Palombo
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
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24
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Ianus A, Alexander DC, Zhang H, Palombo M. Mapping complex cell morphology in the grey matter with double diffusion encoding MR: A simulation study. Neuroimage 2021; 241:118424. [PMID: 34311067 PMCID: PMC8961003 DOI: 10.1016/j.neuroimage.2021.118424] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 07/13/2021] [Accepted: 07/21/2021] [Indexed: 01/18/2023] Open
Abstract
This paper investigates the impact of cell body (namely soma) size and branching of cellular projections on diffusion MR imaging (dMRI) and spectroscopy (dMRS) signals for both standard single diffusion encoding (SDE) and more advanced double diffusion encoding (DDE) measurements using numerical simulations. The aim is to investigate the ability of dMRI/dMRS to characterize the complex morphology of brain cells focusing on these two distinctive features of brain grey matter. To this end, we employ a recently developed computational framework to create three dimensional meshes of neuron-like structures for Monte Carlo simulations, using diffusion coefficients typical of water and brain metabolites. Modelling the cellular structure as realistically connected spherical soma and cylindrical cellular projections, we cover a wide range of combinations of sphere radii and branching order of cellular projections, characteristic of various grey matter cells. We assess the impact of spherical soma size and branching order on the b-value dependence of the SDE signal as well as the time dependence of the mean diffusivity (MD) and mean kurtosis (MK). Moreover, we also assess the impact of spherical soma size and branching order on the angular modulation of DDE signal at different mixing times, together with the mixing time dependence of the apparent microscopic anisotropy (μA), a promising contrast derived from DDE measurements. The SDE results show that spherical soma size has a measurable impact on both the b-value dependence of the SDE signal and the MD and MK diffusion time dependence for both water and metabolites. On the other hand, we show that branching order has little impact on either, especially for water. In contrast, the DDE results show that spherical soma size has a measurable impact on the DDE signal's angular modulation at short mixing times and the branching order of cellular projections significantly impacts the mixing time dependence of the DDE signal's angular modulation as well as of the derived μA, for both water and metabolites. Our results confirm that SDE based techniques may be sensitive to spherical soma size, and most importantly, show for the first time that DDE measurements may be more sensitive to the dendritic tree complexity (as parametrized by the branching order of cellular projections), paving the way for new ways of characterizing grey matter morphology, non-invasively using dMRS and potentially dMRI.
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Affiliation(s)
- A Ianus
- Centre for Medical Image Computing and Department of Computer Science, University College London, London, United Kingdom; Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - D C Alexander
- Centre for Medical Image Computing and Department of Computer Science, University College London, London, United Kingdom
| | - H Zhang
- Centre for Medical Image Computing and Department of Computer Science, University College London, London, United Kingdom
| | - M Palombo
- Centre for Medical Image Computing and Department of Computer Science, University College London, London, United Kingdom.
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25
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Sanvito F, Castellano A, Falini A. Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors. Cancers (Basel) 2021; 13:cancers13030424. [PMID: 33498680 PMCID: PMC7865835 DOI: 10.3390/cancers13030424] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 01/15/2021] [Accepted: 01/19/2021] [Indexed: 12/14/2022] Open
Abstract
Simple Summary Advanced neuroimaging is gaining increasing relevance for the characterization and the molecular profiling of brain tumor tissue. On one hand, for some tumor types, the most widespread advanced techniques, investigating diffusion and perfusion features, have been proven clinically feasible and rather robust for diagnosis and prognosis stratification. In addition, 2-hydroxyglutarate spectroscopy, for the first time, offers the possibility to directly measure a crucial molecular marker. On the other hand, numerous innovative approaches have been explored for a refined evaluation of tumor microenvironments, particularly assessing microstructural and microvascular properties, and the potential applications of these techniques are vast and still to be fully explored. Abstract In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of “molecular imaging” and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.
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Affiliation(s)
- Francesco Sanvito
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, 20132 Milan, Italy; (F.S.); (A.F.)
- School of Medicine, Vita-Salute San Raffaele University, 20132 Milan, Italy
- Unit of Radiology, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Antonella Castellano
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, 20132 Milan, Italy; (F.S.); (A.F.)
- School of Medicine, Vita-Salute San Raffaele University, 20132 Milan, Italy
- Correspondence: ; Tel.: +39-02-2643-3015
| | - Andrea Falini
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, 20132 Milan, Italy; (F.S.); (A.F.)
- School of Medicine, Vita-Salute San Raffaele University, 20132 Milan, Italy
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26
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Henriques RN, Palombo M, Jespersen SN, Shemesh N, Lundell H, Ianuş A. Double diffusion encoding and applications for biomedical imaging. J Neurosci Methods 2020; 348:108989. [PMID: 33144100 DOI: 10.1016/j.jneumeth.2020.108989] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 09/25/2020] [Accepted: 10/20/2020] [Indexed: 12/11/2022]
Abstract
Diffusion Magnetic Resonance Imaging (dMRI) is one of the most important contemporary non-invasive modalities for probing tissue structure at the microscopic scale. The majority of dMRI techniques employ standard single diffusion encoding (SDE) measurements, covering different sequence parameter ranges depending on the complexity of the method. Although many signal representations and biophysical models have been proposed for SDE data, they are intrinsically limited by a lack of specificity. Advanced dMRI methods have been proposed to provide additional microstructural information beyond what can be inferred from SDE. These enhanced contrasts can play important roles in characterizing biological tissues, for instance upon diseases (e.g. neurodegenerative, cancer, stroke), aging, learning, and development. In this review we focus on double diffusion encoding (DDE), which stands out among other advanced acquisitions for its versatility, ability to probe more specific diffusion correlations, and feasibility for preclinical and clinical applications. Various DDE methodologies have been employed to probe compartment sizes (Section 3), decouple the effects of microscopic diffusion anisotropy from orientation dispersion (Section 4), probe displacement correlations, study exchange, or suppress fast diffusing compartments (Section 6). DDE measurements can also be used to improve the robustness of biophysical models (Section 5) and study intra-cellular diffusion via magnetic resonance spectroscopy of metabolites (Section 7). This review discusses all these topics as well as important practical aspects related to the implementation and contrast in preclinical and clinical settings (Section 9) and aims to provide the readers a guide for deciding on the right DDE acquisition for their specific application.
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Affiliation(s)
- Rafael N Henriques
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marco Palombo
- Centre for Medical Image Computing and Dept. of Computer Science, University College London, London, UK
| | - Sune N Jespersen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Henrik Lundell
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
| | - Andrada Ianuş
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.
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27
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Williamson NH, Ravin R, Cai TX, Benjamini D, Falgairolle M, O'Donovan MJ, Basser PJ. Real-time measurement of diffusion exchange rate in biological tissue. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 317:106782. [PMID: 32679514 PMCID: PMC7427561 DOI: 10.1016/j.jmr.2020.106782] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 06/22/2020] [Accepted: 06/26/2020] [Indexed: 05/05/2023]
Abstract
Diffusion exchange spectroscopy (DEXSY) provides a means to isolate the signal attenuation associated with exchange from other sources of signal loss. With the total diffusion weighting b1+b2=bs held constant, DEXSY signals acquired with b1=0 or b2=0 have no exchange weighting, while a DEXSY signal acquired with b1=b2 has maximal exchange weighting. The exchange rate can be estimated by fitting a diffusion exchange model to signals acquired with variable mixing times. Conventionally, acquired signals are normalized by a signal with b1=0 and b2=0 to remove the decay due to spin-lattice relaxation. Instead, division by a signal with equal bs but b1=0 or b2=0 reduces spin-lattice relaxation weighting of the apparent exchange rate (AXR). Furthermore, apparent diffusion-weighted R1 relaxation rates can be estimated from non-exchange-weighted DEXSY signals. Estimated R1 values are utilized to remove signal decay due to spin-lattice relaxation from exchange-weighted signals, permitting a more precise estimate of AXR with less data. Data reduction methods are proposed and tested with regards to statistical accuracy and precision of AXR estimates on simulated and experimental data. Simulations show that the methods are capable of accurately measuring the ground-truth exchange rate. The methods remain accurate even when the assumption that DEXSY signals attenuate with b is violated, as occurs for restricted diffusion. Experimental data was collected from fixed neonatal mouse spinal cord samples at 25 and 7°C using the strong static magnetic field gradient produced by a single-sided permanent magnet (i.e., an NMR MOUSE). The most rapid method for exchange measurements requires only five data points (an 80 s experiment as implemented) and achieves a similar level of accuracy and precision to the baseline method using 44 data points. This represents a significant improvement in acquisition speed, overcoming a barrier which has limited the use of DEXSY on living specimen.
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Affiliation(s)
- Nathan H Williamson
- National Institute of General Medical Sciences, National Institutes of Health, Bethesda, MD, USA; Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
| | - Rea Ravin
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA; Celoptics, Rockville, MD, USA
| | - Teddy X Cai
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Dan Benjamini
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA; The Center for Neuroscience and Regenerative Medicine, Uniformed Service University of the Health Sciences, Bethesda, MD 20814, USA
| | - Melanie Falgairolle
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Michael J O'Donovan
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Peter J Basser
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
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