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Alzaidi AA, Panek R, Blockley NP. Quantitative BOLD (qBOLD) imaging of oxygen metabolism and blood oxygenation in the human body: A scoping review. Magn Reson Med 2024; 92:1822-1837. [PMID: 39072791 DOI: 10.1002/mrm.30165] [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: 10/19/2023] [Revised: 05/06/2024] [Accepted: 05/08/2024] [Indexed: 07/30/2024]
Abstract
PURPOSE There are many approaches to the quantitative BOLD (qBOLD) technique described in the literature, differing in pulse sequences, MRI parameters and data processing. Thus, in this review, we summarized the acquisition methods, approaches used for oxygenation quantification and clinical populations investigated. METHODS Three databases were systematically searched (Medline, Embase, and Web of Science) for published research that used qBOLD methods for quantification of oxygen metabolism. Data extraction and synthesis were performed by one author and reviewed by a second author. RESULTS A total of 93 relevant papers were identified. Acquisition strategies were summarized, and oxygenation parameters were found to have been investigated in many pathologies such as steno-occlusive diseases, stroke, glioma, and multiple sclerosis disease. CONCLUSION A summary of qBOLD approaches for oxygenation measurements and applications could help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.
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Affiliation(s)
- Ahlam A Alzaidi
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, UK
- Radiology Department, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Rafal Panek
- Medical Physics and Clinical Engineering, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Nicholas P Blockley
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, UK
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2
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Li Y, Li W, Paez A, Cao D, Sun Y, Gu C, Zhang K, Miao X, Liu P, Li W, Pillai J, Lu H, van Zijl PCM, Earley C, Li X, Hua J. Imaging arterial and venous vessels using Iron Dextran enhanced multi-echo 3D gradient echo MRI at 7T. NMR IN BIOMEDICINE 2024:e5251. [PMID: 39187441 DOI: 10.1002/nbm.5251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 08/04/2024] [Accepted: 08/16/2024] [Indexed: 08/28/2024]
Abstract
Iron Dextran is a widely used iron oxide compound to treat iron-deficiency anemia patients in the clinic. Similar to other iron oxide compounds such as Ferumoxytol, it can also be used off-label as an intravascular magnetic resonance imaging (MRI) contrast agent due to its strong iron-induced T2 and T2* shortening effects. In this study, we seek to evaluate the feasibility of using Iron Dextran enhanced multi-echo susceptibility weighted imaging (SWI) MRI at 7T to image arterial and venous blood vessels in the human brain. Phantom experiments were performed to measure the r2* relaxivity for Iron Dextran in blood, based on which the SWI sequence was optimized. Pre- and post-infusion MR images were acquired in human subjects from which maps of arteries and veins were extracted. The post-contrast SWI images showed enhanced susceptibility difference between blood and the surrounding tissue in both arteries and veins. Our results showed that the proposed Iron Dextran enhanced multi-echo SWI approach allowed the visualization of blood vessels with diameters down to ~100 μm, including small blood vessels supplying and draining small brain structures such as the hippocampus. We conclude that Iron Dextran can be an alternative iron-based MRI contrast agent for blood vessel imaging in the human brain.
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Affiliation(s)
- Yinghao Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Wei Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, International Science and Technology, Cooperation base of Child development and Critical Disorders, Chongqing Key Laboratory of Child, Neurodevelopment and Cognitive Disorders, Chongqing, China
| | - Adrian Paez
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Di Cao
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yuanqi Sun
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Chunming Gu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Kaihua Zhang
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- School of Psychology, Shandong Normal University, Jinan, China
| | - Xinyuan Miao
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Peiying Liu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Wenbo Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jay Pillai
- Division of Neuroradiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hanzhang Lu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Christopher Earley
- Department of Neurology, 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
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jun Hua
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Sørland KI, Trimble CG, Wu CY, Bathen TF, Elschot M, Cloos MA. Reducing femoral flow artefacts in radial magnetic resonance fingerprinting of the prostate using region-optimised virtual coils. NMR IN BIOMEDICINE 2024; 37:e5136. [PMID: 38514929 DOI: 10.1002/nbm.5136] [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: 05/05/2023] [Revised: 01/19/2024] [Accepted: 02/07/2024] [Indexed: 03/23/2024]
Abstract
High acceleration factors in radial magnetic resonance fingerprinting (MRF) of the prostate lead to strong streak-like artefacts from flow in the femoral blood vessels, possibly concealing important anatomical information. Region-optimised virtual (ROVir) coils is a beamforming-based framework to create virtual coils that maximise signal in a region of interest while minimising signal in a region of interference. In this study, the potential of removing femoral flow streak artefacts in prostate MRF using ROVir coils is demonstrated in silico and in vivo. The ROVir framework was applied to radial MRF k-space data in an automated pipeline designed to maximise prostate signal while minimising signal from the femoral vessels. The method was tested in 15 asymptomatic volunteers at 3 T. The presence of streaks was visually assessed and measurements of whole prostate T1, T2 and signal-to-noise ratio (SNR) with and without streak correction were examined. In addition, a purpose-built simulation framework in which blood flow through the femoral vessels can be turned on and off was used to quantitatively evaluate ROVir's ability to suppress streaks in radial prostate MRF. In vivo it was shown that removing selected ROVir coils visibly reduces streak-like artefacts from the femoral blood flow, without increasing the reconstruction time. On average, 80% of the prostate SNR was retained. A similar reduction of streaks was also observed in silico, while the quantitative accuracy of T1 and T2 mapping was retained. In conclusion, ROVir coils efficiently suppress streaking artefacts from blood flow in radial MRF of the prostate, thereby improving the visual clarity of the images, without significant sacrifices to acquisition time, reconstruction time and accuracy of quantitative values. This is expected to help enable T1 and T2 mapping of prostate cancer in clinically viable times, aiding differentiation between prostate cancer from noncancer and healthy prostate tissue.
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Affiliation(s)
- Kaia I Sørland
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Christopher G Trimble
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hostpital, Trondheim, Norway
| | - Chia-Yin Wu
- Centre for Advanced Imaging, The University of Queensland, St Lucia, Queensland, Australia
- ARC Training Centre for Innovation on Biomedical Imaging Technology (CIBIT), The University of Queensland, St Lucia, Queensland, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, St Lucia, Queensland, Australia
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hostpital, Trondheim, Norway
| | - Mattijs Elschot
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hostpital, Trondheim, Norway
| | - Martijn A Cloos
- Centre for Advanced Imaging, The University of Queensland, St Lucia, Queensland, Australia
- ARC Training Centre for Innovation on Biomedical Imaging Technology (CIBIT), The University of Queensland, St Lucia, Queensland, Australia
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Huang J, Chen Z, van Zijl PCM, Law LH, Pemmasani Prabakaran RS, Park SW, Xu J, Chan KWY. Effect of inhaled oxygen level on dynamic glucose-enhanced MRI in mouse brain. Magn Reson Med 2024; 92:57-68. [PMID: 38308151 PMCID: PMC11055662 DOI: 10.1002/mrm.30035] [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: 08/31/2023] [Revised: 12/23/2023] [Accepted: 01/15/2024] [Indexed: 02/04/2024]
Abstract
PURPOSE To investigate the effect of inhaled oxygen level on dynamic glucose enhanced (DGE) MRI in mouse brain tissue and CSF at 3 T. METHODS DGE data of brain tissue and CSF from mice under normoxia or hyperoxia were acquired in independent and interleaved experiments using on-resonance variable delay multi-pulse (onVDMP) MRI. A bolus of 0.15 mL filtered 50% D-glucose was injected through the tail vein over 1 min during DGE acquisition. MRS was acquired before and after DGE experiments to confirm the presence of D-glucose. RESULTS A significantly higher DGE effect under normoxia than under hyperoxia was observed in brain tissue (p = 0.0001 and p = 0.0002 for independent and interleaved experiments, respectively), but not in CSF (p > 0.3). This difference is attributed to the increased baseline MR tissue signal under hyperoxia induced by a shortened T1 and an increased BOLD effect. When switching from hyperoxia to normoxia without glucose injection, a signal change of ˜3.0% was found in brain tissue and a signal change of ˜1.5% was found in CSF. CONCLUSIONS DGE signal was significantly lower under hyperoxia than that under normoxia in brain tissue, but not in CSF. The reason is that DGE effect size of brain tissue is affected by the baseline signal, which could be influenced by T1 change and BOLD effect. Therefore, DGE experiments in which the oxygenation level is changed from baseline need to be interpreted carefully.
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Affiliation(s)
- Jianpan Huang
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| | - Zilin Chen
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Peter CM van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lok Hin Law
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Rohith Saai Pemmasani Prabakaran
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Se Weon Park
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kannie WY Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Tung Biomedical Science Centre, City University of Hong Kong, Hong Kong, China
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5
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Wehrli FW. Recent Advances in MR Imaging-based Quantification of Brain Oxygen Metabolism. Magn Reson Med Sci 2024; 23:377-403. [PMID: 38866481 PMCID: PMC11234951 DOI: 10.2463/mrms.rev.2024-0028] [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] [Indexed: 06/14/2024] Open
Abstract
The metabolic rate of oxygen (MRO2) is fundamental to tissue metabolism. Determination of MRO2 demands knowledge of the arterio-venous difference in hemoglobin-bound oxygen concentration, typically expressed as oxygen extraction fraction (OEF), and blood flow rate (BFR). MRI is uniquely suited for measurement of both these quantities, yielding MRO2 in absolute physiologic units of µmol O2 min-1/100 g tissue. Two approaches are discussed, both relying on hemoglobin magnetism. Emphasis will be on cerebral oxygen metabolism expressed in terms of the cerebral MRO2 (CMRO2), but translation of the relevant technologies to other organs, including kidney and placenta will be touched upon as well. The first class of methods exploits the blood's bulk magnetic susceptibility, which can be derived from field maps. The second is based on measurement of blood water T2, which is modulated by diffusion and exchange in the local-induced fields within and surrounding erythrocytes. Some whole-organ methods achieve temporal resolution adequate to permit time-series studies of brain energetics, for instance, during sleep in the scanner with concurrent electroencephalogram (EEG) sleep stage monitoring. Conversely, trading temporal for spatial resolution has led to techniques for spatially resolved approaches based on quantitative blood oxygen level dependent (BOLD) or calibrated BOLD models, allowing regional assessment of vascular-metabolic parameters, both also exploiting deoxyhemoglobin paramagnetism like their whole-organ counterparts.
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Affiliation(s)
- Felix W Wehrli
- Laboratory for Structural, Physiologic and Functional Imaging (LSPFI), Department of Radiology, Perelman School of Medicine, University Pennsylvania, Philadelphia, Pennsylvania, USA
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6
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T AR, K K, Paul JS. Unveiling metabolic patterns in dementia: Insights from high-resolution quantitative blood-oxygenation-level-dependent MRI. Med Phys 2024. [PMID: 38888202 DOI: 10.1002/mp.17173] [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: 11/08/2023] [Revised: 04/12/2024] [Accepted: 05/08/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Oxygen extraction fraction (OEF) and deoxyhemoglobin (DoHb) levels reflect variations in cerebral oxygen metabolism in demented patients. PURPOSE Delineating the metabolic profiles evident throughout different phases of dementia necessitates an integrated analysis of OEF and DoHb levels. This is enabled by leveraging high-resolution quantitative blood oxygenation level dependent (qBOLD) analysis of magnitude images obtained from a multi-echo gradient-echo MRI (mGRE) scan performed on a 3.0 Tesla scanner. METHODS Achieving superior spatial resolution in qBOLD necessitates the utilization of an mGRE scan with only four echoes, which in turn limits the number of measurements compared to the parameters within the qBOLD model. Consequently, it becomes imperative to discard non-essential parameters to facilitate further analysis. This process entails transforming the qBOLD model into a format suitable for fitting the log-magnitude difference (L-MDif) profiles of the four echo magnitudes present in each brain voxel. In order to bolster spatial specificity, the log-difference qBOLD model undergoes refinement into a representative form, termed as r-qBOLD, particularly when applied to class-averaged L-MDif signals derived through k-means clustering of L-MDif signals from all brain voxels into a predetermined number of clusters. The agreement between parameters estimated using r-qBOLD for different cluster sizes is validated using Bland-Altman analysis, and the model's goodness-of-fit is evaluated using aχ 2 ${\chi ^2}$ -test. Retrospective MRI data of Alzheimer's disease (AD), mild cognitive impairment (MCI), and non-demented patients without neuropathological disorders, pacemakers, other implants, or psychiatric disorders, who completed a minimum of three visits prior to MRI enrolment, are utilized for the study. RESULTS Utilizing a cohort comprising 30 demented patients aged 65-83 years in stages 4-6 representing mild, moderate, and severe stages according to the clinical dementia rating (CDR), matched with an age-matched non-demented control group of 18 individuals, we conducted joint observations of OEF and DoHb levels estimated using r-qBOLD. The observations elucidate metabolic signatures in dementia based on OEF and DoHb levels in each voxel. Our principal findings highlight the significance of spatial patterns of metabolic profiles (metabolic patterns) within two distinct regimes: OEF levels exceeding the normal range (S1-regime), and OEF levels below the normal range (S2-regime). The S1-regime, accompanied by low DoHb levels, predominantly manifests in fronto-parietal and perivascular regions with increase in dementia severity. Conversely, the S2-regime, accompanied by low DoHb levels, is observed in medial temporal (MTL) regions. Other regions with abnormal metabolic patterns included the orbitofrontal cortex (OFC), medial-orbital prefrontal cortex (MOPFC), hypothalamus, ventro-medial prefrontal cortex (VMPFC), and retrosplenial cortex (RSP). Dysfunction in the OFC and MOPFC indicated cognitive and emotional impairment, while hypothalamic involvement potentially indicated preclinical dementia. Reduced metabolic activity in the RSP suggested early-stage AD related functional abnormalities. CONCLUSIONS Integrated analysis of OEF and DoHb levels using r-qBOLD reveals distinct metabolic signatures across dementia phases, highlighting regions susceptible to neuronal loss, vascular involvement, and preclinical indicators.
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Affiliation(s)
- Arun Raj T
- Division of Medical Informatics, School of Informatics, Kerala University of Digital Sciences Innovation & Technology (DUK), Trivandrum, Kerala, India
| | - Karthik K
- Department of Neuroimaging & Interventional Radiology, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bengaluru, Karnataka, India
| | - Joseph Suresh Paul
- Division of Medical Informatics, School of Informatics, Kerala University of Digital Sciences Innovation & Technology (DUK), Trivandrum, Kerala, India
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Gu C, Li Y, Cao D, Miao X, Paez AG, Sun Y, Cai J, Li W, Li X, Pillai JJ, Earley CJ, van Zijl PC, Hua J. On the optimization of 3D inflow-based vascular-space-occupancy (iVASO) MRI for the quantification of arterial cerebral blood volume (CBVa). Magn Reson Med 2024; 91:1893-1907. [PMID: 38115573 PMCID: PMC10950541 DOI: 10.1002/mrm.29971] [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: 11/01/2023] [Revised: 11/20/2023] [Accepted: 11/25/2023] [Indexed: 12/21/2023]
Abstract
PURPOSE The inflow-based vascular-space-occupancy (iVASO) MRI was originally developed in a single-slice mode to measure arterial cerebral blood volume (CBVa). When vascular crushers are applied in iVASO, the signals can be sensitized predominantly to small pial arteries and arterioles. The purpose of this study is to perform a systematic optimization and evaluation of a 3D iVASO sequence on both 3 T and 7 T for the quantification of CBVa values in the human brain. METHODS Three sets of experiments were performed in three separate cohorts. (1) 3D iVASO MRI protocols were compared to single-slice iVASO, and the reproducibility of whole-brain 3D iVASO MRI was evaluated. (2) The effects from different vascular crushers in iVASO were assessed. (3) 3D iVASO MRI results were evaluated in arterial and venous blood vessels identified using ultrasmall-superparamagnetic-iron-oxides-enhanced MRI to validate its arterial origin. RESULTS 3D iVASO scans showed signal-to-noise ratio (SNR) and CBVa measures consistent with single-slice iVASO with reasonable intrasubject reproducibility. Among the iVASO scans performed with different vascular crushers, the whole-brain 3D iVASO scan with a motion-sensitized-driven-equilibrium preparation with two binomial refocusing pulses and an effective TE of 50 ms showed the best suppression of macrovascular signals, with a relatively low specific absorption rate. When no vascular crusher was applied, the CBVa maps from 3D iVASO scans showed large CBVa values in arterial vessels but well-suppressed signals in venous vessels. CONCLUSION A whole-brain 3D iVASO MRI scan was optimized for CBVa measurement in the human brain. When only microvascular signals are desired, a motion-sensitized-driven-equilibrium-based vascular crusher with binomial refocusing pulses can be applied in 3D iVASO.
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Affiliation(s)
- Chunming Gu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Yinghao Li
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Di Cao
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Xinyuan Miao
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Adrian G. Paez
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Yuanqi Sun
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Jitong Cai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Wenbo Li
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Xu Li
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Jay J. Pillai
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Division of Neuroradiology, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
| | - Christopher J. Earley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Peter C.M. van Zijl
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Jun Hua
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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8
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Deshpande RS, Langham MC, Lee H, Kamona N, Wehrli FW. Quantification of whole-organ individual and bilateral renal metabolic rate of oxygen. Magn Reson Med 2024; 91:2057-2073. [PMID: 38146669 PMCID: PMC10950521 DOI: 10.1002/mrm.29981] [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: 09/01/2023] [Revised: 11/21/2023] [Accepted: 12/01/2023] [Indexed: 12/27/2023]
Abstract
PURPOSE Renal metabolic rate of oxygen (rMRO2 ) is a potentially important biomarker of kidney function. The key parameters for rMRO2 quantification include blood flow rate (BFR) and venous oxygen saturation (SvO2 ) in a draining vessel. Previous approaches to quantify renal metabolism have focused on the single organ. Here, both kidneys are considered as one unit to quantify bilateral rMRO2 . A pulse sequence to facilitate bilateral rMRO2 quantification is introduced. METHODS To quantify bilateral rMRO2 , measurements of BFR and SvO2 are made along the inferior vena cava (IVC) at suprarenal and infrarenal locations. From the continuity equation, these four parameters can be related to derive an expression for bilateral rMRO2 . The recently reported K-MOTIVE pulse sequence was implemented at four locations: left kidney, right kidney, suprarenal IVC, and infrarenal IVC. A dual-band variant of K-MOTIVE (db-K-MOTIVE) was developed by incorporating simultaneous-multi-slice imaging principles. The sequence simultaneously measures BFR and SvO2 at suprarenal and infrarenal locations in a single pass of 21 s, yielding bilateral rMRO2 . RESULTS SvO2 and BFR are higher in suprarenal versus infrarenal IVC, and the renal veins are highly oxygenated (SvO2 >90%). Bilateral rMRO2 quantified in 10 healthy subjects (8 M, 30 ± 8 y) was found to be 291 ± 247 and 349 ± 300 (μmolO2 /min)/100 g, derived from K-MOTIVE and db-K-MOTIVE, respectively. In comparison, total rMRO2 from combining left and right was 329 ± 273 (μmolO2 /min)/100 g. CONCLUSION The present work demonstrates that bilateral rMRO2 quantification is feasible with fair reproducibility and physiological plausibility. The indirect method is a promising approach to compute bilateral rMRO2 when individual rMRO2 quantification is difficult.
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Affiliation(s)
- Rajiv S. Deshpande
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Michael C. Langham
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Hyunyeol Lee
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
- School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea
| | - Nada Kamona
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Felix W. Wehrli
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
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9
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Deshpande RS, Langham MC, Susztak K, Wehrli FW. MRI-based quantification of whole-organ renal metabolic rate of oxygen. NMR IN BIOMEDICINE 2024; 37:e5036. [PMID: 37750009 PMCID: PMC10841084 DOI: 10.1002/nbm.5036] [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: 06/28/2023] [Revised: 08/02/2023] [Accepted: 08/21/2023] [Indexed: 09/27/2023]
Abstract
During the early stages of diabetes, kidney oxygen utilization increases. The mismatch between oxygen demand and supply contributes to tissue hypoxia, a key driver of chronic kidney disease. Thus, whole-organ renal metabolic rate of oxygen (rMRO2 ) is a potentially valuable biomarker of kidney function. The key parameters required to determine rMRO2 include the renal blood flow rate (RBF) in the feeding artery and oxygen saturation in the draining renal vein (SvO2 ). However, there is currently no noninvasive method to quantify rMRO2 in absolute physiologic units. Here, a new MRI pulse sequence, Kidney Metabolism of Oxygen via T2 and Interleaved Velocity Encoding (K-MOTIVE), is described, along with evaluation of its performance in the human kidney in vivo. K-MOTIVE interleaves a phase-contrast module before a background-suppressed T2 -prepared balanced steady-state-free-precession (bSSFP) readout to measure RBF and SvO2 in a single breath-hold period of 22 s, yielding rMRO2 via Fick's principle. Variants of K-MOTIVE to evaluate alternative bSSFP readout strategies were studied. Kidney mass was manually determined from multislice gradient recalled echo images. Healthy subjects were recruited to quantify rMRO2 of the left kidney at 3-T field strength (N = 15). Assessments of repeat reproducibility and comparisons with individual measurements of RBF and SvO2 were performed, and the method's sensitivity was evaluated with a high-protein meal challenge (N = 8). K-MOTIVE yielded the following metabolic parameters: T2 = 157 ± 19 ms; SvO2 = 92% ± 6%; RBF = 400 ± 110 mL/min; and rMRO2 = 114 ± 117(μmol O2 /min)/100 g tissue. Reproducibility studies of T2 and RBF (parameters directly measured by K-MOTIVE) resulted in coefficients of variation less than 10% and intraclass correlation coefficients more than 0.75. The high-protein meal elicited an increase in rMRO2 , which was corroborated by serum biomarkers. The K-MOTIVE sequence measures SvO2 and RBF, the parameters necessary to quantify whole-organ rMRO2 , in a single breath-hold. The present work demonstrates that rMRO2 quantification is feasible with good reproducibility. rMRO2 is a potentially valuable physiological biomarker.
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Affiliation(s)
- Rajiv S. Deshpande
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Michael C. Langham
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Katalin Susztak
- Department of Nephrology and Hypertension, Perelman School of Medicine, University of Pennsylvania, PA, USA
- Department of Medicine and Genetics, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Felix W. Wehrli
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
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10
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Biondetti E, Cho J, Lee H. Cerebral oxygen metabolism from MRI susceptibility. Neuroimage 2023; 276:120189. [PMID: 37230206 PMCID: PMC10335841 DOI: 10.1016/j.neuroimage.2023.120189] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/26/2023] [Accepted: 05/23/2023] [Indexed: 05/27/2023] Open
Abstract
This article provides an overview of MRI methods exploiting magnetic susceptibility properties of blood to assess cerebral oxygen metabolism, including the tissue oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2). The first section is devoted to describing blood magnetic susceptibility and its effect on the MRI signal. Blood circulating in the vasculature can have diamagnetic (oxyhemoglobin) or paramagnetic properties (deoxyhemoglobin). The overall balance between oxygenated and deoxygenated hemoglobin determines the induced magnetic field which, in turn, modulates the transverse relaxation decay of the MRI signal via additional phase accumulation. The following sections of this review then illustrate the principles underpinning susceptibility-based techniques for quantifying OEF and CMRO2. Here, it is detailed whether these techniques provide global (OxFlow) or local (Quantitative Susceptibility Mapping - QSM, calibrated BOLD - cBOLD, quantitative BOLD - qBOLD, QSM+qBOLD) measurements of OEF or CMRO2, and what signal components (magnitude or phase) and tissue pools they consider (intravascular or extravascular). Validations studies and potential limitations of each method are also described. The latter include (but are not limited to) challenges in the experimental setup, the accuracy of signal modeling, and assumptions on the measured signal. The last section outlines the clinical uses of these techniques in healthy aging and neurodegenerative diseases and contextualizes these reports relative to results from gold-standard PET.
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Affiliation(s)
- Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy
| | - Junghun Cho
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, New York, USA
| | - Hyunyeol Lee
- School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
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11
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van Gelderen P, Li X, de Zwart JA, Beck ES, Okar SV, Huang Y, Lai K, Sulam J, van Zijl PCM, Reich DS, Duyn JH, Liu J. Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R 2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T. Neuroimage 2023; 270:119992. [PMID: 36858332 PMCID: PMC10278242 DOI: 10.1016/j.neuroimage.2023.119992] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023] Open
Abstract
MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.
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Affiliation(s)
- Peter van Gelderen
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Jacco A de Zwart
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Erin S Beck
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York City, NY, United States of America
| | - Serhat V Okar
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - KuoWei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America; Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Daniel S Reich
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America.
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12
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Gao T, Korb JP, Lukšič M, Mériguet G, Malikova N, Rollet AL. Ion influence on surface water dynamics and proton exchange at protein surfaces - A unified model for transverse and longitudinal NMR relaxation dispersion. J Mol Liq 2022; 367:120451. [PMID: 37790165 PMCID: PMC10544814 DOI: 10.1016/j.molliq.2022.120451] [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] [Indexed: 12/01/2022]
Abstract
In all biologically relevant media, proteins interact in the presence of surrounding ions, and such interactions are water-mediated. Water molecules play a crucial role in the restructuring of proteins in solution and indeed in their biological activity. Surface water dynamics and proton exchange at protein surfaces is investigated here using NMR relaxometry, for two well-known globular proteins, lysozyme and bovine serum albumin, with particular attention to the role of surface ions. We present a unified model of surface water dynamics and proton exchange, accounting simultaneously for the observed longitudinal and transverse relaxation rates. The most notable effect of salt (0.1 M) concerns the slow surface water dynamics, related to rare water molecules embedded in energy wells on the protein surface. This response is protein-specific. On the other hand, the proton exchange time between labile protein-protons and water-protons at the protein surface seems to be very similar for the two proteins and is insensitive to the addition of salts at the concentration studied.
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Affiliation(s)
- Tadeja Gao
- Sorbonne Université/CNRS, Laboratoire Physico-Chimie des Électrolytes et Nano-Systèmes Interfaciaux (PHENIX), 4 place Jussieu, Paris, France
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, Večna pot 113, Ljubljana SI-1000, Slovenia
| | - Jean-Pierre Korb
- Sorbonne Université/CNRS, Laboratoire Physico-Chimie des Électrolytes et Nano-Systèmes Interfaciaux (PHENIX), 4 place Jussieu, Paris, France
| | - Miha Lukšič
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, Večna pot 113, Ljubljana SI-1000, Slovenia
| | - Guillaume Mériguet
- Sorbonne Université/CNRS, Laboratoire Physico-Chimie des Électrolytes et Nano-Systèmes Interfaciaux (PHENIX), 4 place Jussieu, Paris, France
| | - Natalie Malikova
- Sorbonne Université/CNRS, Laboratoire Physico-Chimie des Électrolytes et Nano-Systèmes Interfaciaux (PHENIX), 4 place Jussieu, Paris, France
| | - Anne-Laure Rollet
- Sorbonne Université/CNRS, Laboratoire Physico-Chimie des Électrolytes et Nano-Systèmes Interfaciaux (PHENIX), 4 place Jussieu, Paris, France
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13
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Theillet FX, Luchinat E. In-cell NMR: Why and how? PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2022; 132-133:1-112. [PMID: 36496255 DOI: 10.1016/j.pnmrs.2022.04.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 04/19/2022] [Accepted: 04/27/2022] [Indexed: 06/17/2023]
Abstract
NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.
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Affiliation(s)
- Francois-Xavier Theillet
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France.
| | - Enrico Luchinat
- Dipartimento di Scienze e Tecnologie Agro-Alimentari, Alma Mater Studiorum - Università di Bologna, Piazza Goidanich 60, 47521 Cesena, Italy; CERM - Magnetic Resonance Center, and Neurofarba Department, Università degli Studi di Firenze, 50019 Sesto Fiorentino, Italy
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14
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Li W, Xu F, Zhu D, van Zijl PCM, Qin Q. T 2 -oximetry-based cerebral venous oxygenation mapping using Fourier-transform-based velocity-selective pulse trains. Magn Reson Med 2022; 88:1292-1302. [PMID: 35608208 PMCID: PMC9247032 DOI: 10.1002/mrm.29300] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 04/19/2022] [Accepted: 04/20/2022] [Indexed: 12/14/2022]
Abstract
Purpose To develop a T2‐oximetry method for quantitative mapping of cerebral venous oxygenation fraction (Yv) using Fourier‐transform–based velocity‐selective (FT‐VS) pulse trains. Methods The venous isolation preparation was achieved by using an FT‐VS inversion plus a nonselective inversion (NSI) pulse to null the arterial blood signal while minimally affected capillary blood flows out into the venular vasculature during the outflow time (TO), and then applying an Fourier transform based velocity selective saturation (FT‐VSS) pulse to suppress the tissue signal. A multi‐echo readout was employed to obtain venous T2 (T2,v) efficiently with the last echo used to detect the residual CSF signal and correct its contamination in the fitting. Here we compared the performance of this FT‐VS–based venous isolation preparations with a traditional velocity‐selective saturation (VSS)–based approach (quantitative imaging of extraction of oxygen and tissue consumption [QUIXOTIC]) with different cutoff velocities for Yv mapping on 6 healthy volunteers at 3 Tesla. Results The FT‐VS–based methods yielded higher venous blood signal and temporal SNR with less CSF contamination than the velocity‐selective saturation–based results. The averaged Yv values across the whole slice measured in different experiments were close to the global Yv measured from the individual internal jugular vein. Conclusion The feasibility of the FT‐VS–based Yv estimation was demonstrated on healthy volunteers. The obtained high venous signal as well as the mitigation of CSF contamination led to a good agreement between the T2,v and Yv measured in the proposed method with the values in the literature. Click here for author‐reader discussions
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Affiliation(s)
- Wenbo Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Feng Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Dan Zhu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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15
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Jiang D, Lu H. Cerebral oxygen extraction fraction MRI: Techniques and applications. Magn Reson Med 2022; 88:575-600. [PMID: 35510696 PMCID: PMC9233013 DOI: 10.1002/mrm.29272] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/20/2022] [Accepted: 03/29/2022] [Indexed: 12/20/2022]
Abstract
The human brain constitutes 2% of the body's total mass but uses 20% of the oxygen. The rate of the brain's oxygen utilization can be derived from a knowledge of cerebral blood flow and the oxygen extraction fraction (OEF). Therefore, OEF is a key physiological parameter of the brain's function and metabolism. OEF has been suggested to be a useful biomarker in a number of brain diseases. With recent advances in MRI techniques, several MRI-based methods have been developed to measure OEF in the human brain. These MRI OEF techniques are based on the T2 of blood, the blood signal phase, the magnetic susceptibility of blood-containing voxels, the effect of deoxyhemoglobin on signal behavior in extravascular tissue, and the calibration of the BOLD signal using gas inhalation. Compared to 15 O PET, which is considered the "gold standard" for OEF measurement, MRI-based techniques are non-invasive, radiation-free, and are more widely available. This article provides a review of these emerging MRI-based OEF techniques. We first briefly introduce the role of OEF in brain oxygen homeostasis. We then review the methodological aspects of different categories of MRI OEF techniques, including their signal mechanisms, acquisition methods, and data analyses. The strengths and limitations of the techniques are discussed. Finally, we review key applications of these techniques in physiological and pathological conditions.
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Affiliation(s)
- Dengrong Jiang
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
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16
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van Dorth D, Venugopal K, Poot DHJ, Hirschler L, de Bresser J, Smits M, Hernandez‐Tamames JA, Debacker CS, van Osch MJP. Dependency of R 2 and R 2 * relaxation on Gd-DTPA concentration in arterial blood: Influence of hematocrit and magnetic field strength. NMR IN BIOMEDICINE 2022; 35:e4653. [PMID: 34816501 PMCID: PMC9285940 DOI: 10.1002/nbm.4653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 10/27/2021] [Accepted: 10/28/2021] [Indexed: 06/13/2023]
Abstract
Dynamic susceptibility contrast (DSC) MRI is clinically used to measure brain perfusion by monitoring the dynamic passage of a bolus of contrast agent through the brain. For quantitative analysis of the DSC images, the arterial input function is required. It is known that the original assumption of a linear relation between the R2(*) relaxation and the arterial contrast agent concentration is invalid, although the exact relation is as of yet unknown. Studying this relation in vitro is time-consuming, because of the widespread variations in field strengths, MRI sequences, contrast agents, and physiological conditions. This study aims to simulate the R2(*) versus contrast concentration relation under varying physiological and technical conditions using an adapted version of an open-source simulation tool. The approach was validated with previously acquired data in human whole blood at 1.5 T by means of a gradient-echo sequence (proof-of-concept). Subsequently, the impact of hematocrit, field strength, and oxygen saturation on this relation was studied for both gradient-echo and spin-echo sequences. The results show that for both gradient-echo and spin-echo sequences, the relaxivity increases with hematocrit and field strength, while the hematocrit dependency was nonlinear for both types of MRI sequences. By contrast, oxygen saturation has only a minor effect. In conclusion, the simulation setup has proven to be an efficient method to rapidly calibrate and estimate the relation between R2(*) and gadolinium concentration in whole blood. This knowledge will be useful in future clinical work to more accurately retrieve quantitative information on brain perfusion.
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Affiliation(s)
- Daniëlle van Dorth
- C. J. Gorter Center for High‐Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Krishnapriya Venugopal
- Department of Radiology and Nuclear MedicineErasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Dirk H. J. Poot
- Department of Radiology and Nuclear MedicineErasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Lydiane Hirschler
- C. J. Gorter Center for High‐Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Jeroen de Bresser
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear MedicineErasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Juan A. Hernandez‐Tamames
- Department of Radiology and Nuclear MedicineErasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Clément S. Debacker
- GHU ParisInstitut de Psychiatrie et Neurosciences, Hôpital Sainte‐AnneParisFrance
| | - Matthias J. P. van Osch
- C. J. Gorter Center for High‐Field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
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17
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An autism spectrum disorder adaptive identification based on the Elimination of brain connections: a proof of long-range underconnectivity. Soft comput 2022. [DOI: 10.1007/s00500-022-06890-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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18
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Han Z, Chen C, Xu X, Bai R, Staedtke V, Huang J, Chan KW, Xu J, Kamson DO, Wen Z, Knutsson L, van Zijl PC, Liu G. Dynamic contrast-enhanced CEST MRI using a low molecular weight dextran. NMR IN BIOMEDICINE 2022; 35:e4649. [PMID: 34779550 PMCID: PMC8828685 DOI: 10.1002/nbm.4649] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 09/27/2021] [Accepted: 10/19/2021] [Indexed: 05/25/2023]
Abstract
Natural and synthetic sugars have great potential for developing highly biocompatible and translatable chemical exchange saturation transfer (CEST) MRI contrast agents. In this study, we aimed to develop the smallest clinically available form of dextran, Dex1 (molecular weight, MW ~ 1 kDa), as a new CEST agent. We first characterized the CEST properties of Dex1 in vitro at 11.7 T and showed that the Dex1 had a detectable CEST signal at ~1.2 ppm, attributed to hydroxyl protons. In vivo CEST MRI studies were then carried out on C57BL6 mice bearing orthotopic GL261 brain tumors (n = 5) using a Bruker BioSpec 11.7 T MRI scanner. Both steady-state full Z-spectral images and single offset (1.2 ppm) dynamic dextran-enhanced (DDE) images were acquired before and after the intravenous injection of Dex1 (2 g/kg). The steady-state Z-spectral analysis showed a significantly higher CEST contrast enhancement in the tumor than in contralateral brain (∆MTRasym1.2 ppm = 0.010 ± 0.006 versus 0.002 ± 0.008, P = 0.0069) at 20 min after the injection of Dex1. Pharmacokinetic analyses of DDE were performed using the area under the curve (AUC) in the first 10 min after Dex1 injection, revealing a significantly higher uptake of Dex1 in the tumor than in brain tissue for tumor-bearing mice (AUC[0-10 min] = 21.9 ± 4.2 versus 5.3 ± 6.4%·min, P = 0.0294). In contrast, no Dex1 uptake was foundling in the brains of non-tumor-bearing mice (AUC[0-10 min] = -1.59 ± 2.43%·min). Importantly, the CEST MRI findings were consistent with the measurements obtained using DCE MRI and fluorescence microscopy, demonstrating the potential of Dex1 as a highly translatable CEST MRI contrast agent for assessing tumor hemodynamics.
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Affiliation(s)
- Zheng Han
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Chuheng Chen
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
| | - Xiang Xu
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Renyuan Bai
- Department of Neurology and Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - Verena Staedtke
- Department of Neurology and Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Kannie W.Y. Chan
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Jiadi Xu
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - David O. Kamson
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University, Baltimore, MD, USA
| | - Zhibo Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Linda Knutsson
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Peter C.M. van Zijl
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Guanshu Liu
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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19
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Thomas DG, Galvosas P, Tzeng YC, Harrison FG, Berry MJ, Teal PD, Wright GA, Obruchkov S. Oxygen saturation-dependent effects on blood transverse relaxation at low fields. MAGMA (NEW YORK, N.Y.) 2022; 35:805-815. [PMID: 35107697 PMCID: PMC9463268 DOI: 10.1007/s10334-021-00993-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 11/28/2021] [Accepted: 12/15/2021] [Indexed: 11/28/2022]
Abstract
Objective Blood oxygenation can be measured using magnetic resonance using the paramagnetic effect of deoxy-haemoglobin, which decreases the \documentclass[12pt]{minimal}
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\begin{document}$$\textit{T}_{2}$$\end{document}T2 relaxation time of blood. This \documentclass[12pt]{minimal}
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\begin{document}$$\textit{T}_{2}$$\end{document}T2 contrast has been well characterised at the \documentclass[12pt]{minimal}
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\begin{document}$$\textit{B}_{{0}}$$\end{document}B0 fields used in MRI (1.5 T and above). However, few studies have characterised this effect at lower magnetic fields. Here, the feasibility of blood oximetry at low field based on \documentclass[12pt]{minimal}
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\begin{document}$$\textit{T}_{2}$$\end{document}T2 changes that are within a physiological relevant range is explored. This study could be used for specifying requirements for construction of a monitoring device based on low field permanent magnet systems. Methods A continuous flow circuit was used to control parameters such as oxygen saturation and temperature in a sample of blood. It flowed through a variable field magnet, where CPMG experiments were performed to measure its \documentclass[12pt]{minimal}
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\begin{document}$$\textit{T}_{2}$$\end{document}T2. In addition, the oxygen saturation was monitored by an optical sensor for comparison with the \documentclass[12pt]{minimal}
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\begin{document}$$\textit{T}_{2}$$\end{document}T2 changes. Results These results show that at low \documentclass[12pt]{minimal}
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\begin{document}$$\textit{B}_{{0}}$$\end{document}B0 fields, the change in blood \documentclass[12pt]{minimal}
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\begin{document}$$\textit{T}_{2}$$\end{document}T2 due to oxygenation is small, but still detectable. The data measured at low fields are also in agreement with theoretical models for the oxy-deoxy \documentclass[12pt]{minimal}
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\begin{document}$$\textit{T}_{2}$$\end{document}T2 effect. Conclusion \documentclass[12pt]{minimal}
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\begin{document}$$\textit{T}_{2}$$\end{document}T2 changes in blood due to oxygenation were observed at fields as low as 0.1 T. These results suggest that low field NMR relaxometry devices around 0.3 T could be designed to detect changes in blood oxygenation.
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Affiliation(s)
- Dion G Thomas
- School of Chemical and Physical Sciences and MacDiarmid Institute for Advanced Materials, Victoria University of Wellington, Wellington, New Zealand
| | - Petrik Galvosas
- School of Chemical and Physical Sciences and MacDiarmid Institute for Advanced Materials, Victoria University of Wellington, Wellington, New Zealand
| | - Yu-Chieh Tzeng
- Centre for Translational Research, University of Otago, Wellington, New Zealand
| | - Freya G Harrison
- Centre for Translational Research, University of Otago, Wellington, New Zealand
| | - Mary J Berry
- Centre for Translational Research and Department of Paediatrics and Child Health, University of Otago, Wellington, New Zealand
| | - Paul D Teal
- School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand
| | - Graham A Wright
- Sunnybrook Research Institute and University of Toronto, Toronto, ON, Canada
| | - Sergei Obruchkov
- Robinson Research Institute, Victoria University of Wellington, Wellington, New Zealand.
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20
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Jiang D, Koehler RC, Liu X, Kulikowicz E, Lee JK, Lu H, Liu P. Quantitative validation of MRI mapping of cerebral venous oxygenation with direct blood sampling: A graded-O 2 study in piglets. Magn Reson Med 2021; 86:1445-1453. [PMID: 33755253 PMCID: PMC8184598 DOI: 10.1002/mrm.28786] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 02/12/2021] [Accepted: 03/08/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE To validate two neonatal cerebral venous oxygenation (Yv ) MRI techniques, T2 relaxation under phase contrast (TRUPC) and accelerated TRUPC (aTRUPC) MRI, with oxygenation measured with direct blood sampling. METHODS In vivo experiments were performed on seven healthy newborn piglets. For each piglet, a catheter was placed in the superior sagittal sinus to obtain venous blood samples for blood gas oximetry measurement as a gold standard. During the MRI experiment, three to five venous oxygenation levels were achieved in each piglet by varying inhaled O2 content and breathing rate. Under each condition, Yv values of the superior sagittal sinus measured by TRUPC, aTRUPC, and blood gas oximetry were obtained. The Yv quantification in TRUPC and aTRUPC used a standard bovine blood calibration model. The aTRUPC scan was repeated twice to assess its reproducibility. Agreements among TRUPC Yv , aTRUPC Yv , and blood gas oximetry were evaluated by intraclass correlation coefficient (ICC) and paired Student's t-test. RESULTS The mean hematocrit was 23.6 ± 6.5% among the piglets. Across all measurements, Yv values were 51.9 ± 21.3%, 54.1 ± 18.8%, and 53.7 ± 19.2% for blood gas oximetry, TRUPC and aTRUPC, respectively, showing no significant difference between any two methods (P > .3). There were good correlations between TRUPC and blood gas Yv (ICC = 0.801; P < .0001), between aTRUPC and blood gas Yv (ICC = 0.809; P < .0001), and between aTRUPC and TRUPC Yv (ICC = 0.887; P < .0001). The coefficient of variation of aTRUPC Yv was 8.1 ± 9.9%. CONCLUSION The values of Yv measured by TRUPC and aTRUPC were in good agreement with blood gas oximetry. These findings suggest that TRUPC and aTRUPC can provide accurate quantifications of Yv in major cerebral veins.
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Affiliation(s)
- Dengrong Jiang
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Raymond C. Koehler
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xiuyun Liu
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Ewa Kulikowicz
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jennifer K. Lee
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Peiying Liu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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21
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Wei Z, Xu J, Chen L, Hirschler L, Barbier EL, Li T, Wong PC, Lu H. Brain metabolism in tau and amyloid mouse models of Alzheimer's disease: An MRI study. NMR IN BIOMEDICINE 2021; 34:e4568. [PMID: 34050996 PMCID: PMC9574887 DOI: 10.1002/nbm.4568] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 05/17/2021] [Accepted: 05/20/2021] [Indexed: 06/12/2023]
Abstract
Alzheimer's disease (AD) is the leading cause of cognitive impairment and dementia in elderly individuals. According to the current biomarker framework for "unbiased descriptive classification", biomarkers of neurodegeneration, "N", constitute a critical component in the tri-category "A/T/N" system. Current biomarkers of neurodegeneration suffer from potential drawbacks such as requiring invasive lumbar puncture, involving ionizing radiation, or representing a late, irreversible marker. Recent human studies have suggested that reduced brain oxygen metabolism may be a new functional marker of neurodegeneration in AD, but the heterogeneity and the presence of mixed pathology in human patients did not allow a full understanding of the role of oxygen extraction and metabolism in AD. In this report, global brain oxygen metabolism and related physiological parameters were studied in two AD mouse models with relatively pure pathology, using advanced MRI techniques including T2 -relaxation-under-spin-tagging (TRUST) and phase contrast (PC) MRI. Additionally, regional cerebral blood flow (CBF) was determined with pseudocontinuous arterial spin labeling. Reduced global oxygen extraction fraction (by -18.7%, p = 0.008), unit-mass cerebral metabolic rate of oxygen (CMRO2 ) (by -17.4%, p = 0.04) and total CMRO2 (by -30.8%, p < 0.001) were observed in Tau4RΔK mice-referred to as the tau AD model-which manifested pronounced neurodegeneration, as measured by diminished brain volume (by -15.2%, p < 0.001). Global and regional CBF in these mice were not different from those of wild-type mice (p > 0.05), suggesting normal vascular function. By contrast, in B6;SJL-Tg [APPSWE]2576Kha (APP) mice-referred to as the amyloid AD model-no brain volume reduction, as well as relatively intact brain oxygen extraction and metabolism, were found (p > 0.05). Consistent with the imaging data, behavioral measures of walking distance were impaired in Tau4RΔK mice (p = 0.004), but not in APP mice (p = 0.88). Collectively, these findings support the hypothesis that noninvasive MRI measurement of brain oxygen metabolism may be a promising biomarker of neurodegeneration in AD.
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Affiliation(s)
- Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, China
| | - Lydiane Hirschler
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Emmanuel L. Barbier
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Tong Li
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Philip C. Wong
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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22
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van Zijl PCM, Brindle K, Lu H, Barker PB, Edden R, Yadav N, Knutsson L. Hyperpolarized MRI, functional MRI, MR spectroscopy and CEST to provide metabolic information in vivo. Curr Opin Chem Biol 2021; 63:209-218. [PMID: 34298353 PMCID: PMC8384704 DOI: 10.1016/j.cbpa.2021.06.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 06/12/2021] [Accepted: 06/15/2021] [Indexed: 12/13/2022]
Abstract
Access to metabolic information in vivo using magnetic resonance (MR) technologies has generally been the niche of MR spectroscopy (MRS) and spectroscopic imaging (MRSI). Metabolic fluxes can be studied using the infusion of substrates labeled with magnetic isotopes, with the use of hyperpolarization especially powerful. Unfortunately, these promising methods are not yet accepted clinically, where fast, simple, and reliable measurement and diagnosis are key. Recent advances in functional MRI and chemical exchange saturation transfer (CEST) MRI allow the use of water imaging to study oxygen metabolism and tissue metabolite levels. These, together with the use of novel data analysis approaches such as machine learning for all of these metabolic MR approaches, are increasing the likelihood of their clinical translation.
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Affiliation(s)
- Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA.
| | - Kevin Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Richard Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Nirbhay Yadav
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Medical Radiation Physics, Lund University, Lund, Sweden
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23
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Amini M, Pedram MM, Moradi A, Jamshidi M, Ouchani M. Single and Combined Neuroimaging Techniques for Alzheimer's Disease Detection. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2021; 2021:9523039. [PMID: 34335726 PMCID: PMC8292054 DOI: 10.1155/2021/9523039] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 06/04/2021] [Accepted: 06/30/2021] [Indexed: 02/07/2023]
Abstract
Alzheimer's disease (AD) consists of the gradual process of decreasing volume and quality of neuron connection in the brain, which consists of gradual synaptic integrity and loss of cognitive functions. In recent years, there has been significant attention in AD classification and early detection with machine learning algorithms. There are different neuroimaging techniques for capturing data and using it for the classification task. Input data as images will help machine learning models to detect different biomarkers for AD classification. This marker has a more critical role for AD detection than other diseases because beta-amyloid can extract complex structures with some metal ions. Most researchers have focused on using 3D and 4D convolutional neural networks for AD classification due to reasonable amounts of data. Also, combination neuroimaging techniques like functional magnetic resonance imaging and positron emission tomography for AD detection have recently gathered much attention. However, gathering a combination of data can be expensive, complex, and tedious. For time consumption reasons, most patients prefer to throw one of the neuroimaging techniques. So, in this review article, we have surveyed different research studies with various neuroimaging techniques and ML methods to see the effect of using combined data as input. The result has shown that the use of the combination method would increase the accuracy of AD detection. Also, according to the sensitivity metrics from different machine learning methods, MRI and fMRI showed promising results.
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Affiliation(s)
- Morteza Amini
- Department of Cognitive Modeling, Institute for Cognitive Science Studies, Shahid Beheshti University, Tehran, Iran
| | - Mir Mohsen Pedram
- Department of Electrical and Computer Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran
- Department of Cognitive Modeling, Institute for Cognitive Science Studies, Tehran, Iran
| | - Alireza Moradi
- Department of Clinical Psychology, Faculty of Psychology and Educational Science, Kharazmi University, Tehran, Iran
- Department of Cognitive Psychology, Institute for Cognitive Science Studies, Tehran, Iran
| | - Mahdieh Jamshidi
- Department of Mathematical Sciences, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
| | - Mahshad Ouchani
- Institute for Cognitive and Brain Science, Shahid Beheshti University, Tehran, Iran
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24
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Li W, Liu D, van Zijl PCM, Qin Q. Three-dimensional whole-brain mapping of cerebral blood volume and venous cerebral blood volume using Fourier transform-based velocity-selective pulse trains. Magn Reson Med 2021; 86:1420-1433. [PMID: 33955583 DOI: 10.1002/mrm.28815] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 03/28/2021] [Accepted: 04/01/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE To develop 3D MRI methods for cerebral blood volume (CBV) and venous cerebral blood volume (vCBV) estimation with whole-brain coverage using Fourier transform-based velocity-selective (FT-VS) pulse trains. METHODS For CBV measurement, FT-VS saturation pulse trains were used to suppress static tissue, whereas CSF contamination was corrected voxel-by-voxel using a multi-readout acquisition and a fast CSF T2 scan. The vCBV mapping was achieved by inserting an arterial-nulling module that included a FT-VS inversion pulse train. Using these methods, CBV and vCBV maps were obtained on 6 healthy volunteers at 3 T. RESULTS The mean CBV and vCBV values in gray matter and white matter in different areas of the brain showed high correlation (r = 0.95 and P < .0001). The averaged CBV and vCBV values of the whole brain were 5.4 ± 0.6 mL/100 g and 2.5 ± 0.3 mL/100 g in gray matter, and 2.6 ± 0.5 mL/100 g and 1.5 ± 0.2 mL/100 g in white matter, respectively, comparable to the literature. CONCLUSION The feasibility of FT-VS-based CBV and vCBV estimation was demonstrated for 3D acquisition with large spatial coverage.
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Affiliation(s)
- Wenbo Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Dapeng Liu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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25
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Pérez-Rodas M, Pohmann R, Scheffler K, Heule R. Intravascular BOLD signal characterization of balanced SSFP experiments in human blood at high to ultrahigh fields. Magn Reson Med 2020; 85:2055-2068. [PMID: 33140871 DOI: 10.1002/mrm.28575] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 10/08/2020] [Accepted: 10/09/2020] [Indexed: 11/08/2022]
Abstract
PURPOSE To investigate the intravascular contribution to the overall balanced SSFP (bSSFP) BOLD effect in human blood at high to ultrahigh field strengths (3 T, 9.4 T, and 14.1 T). METHODS Venous blood prepared at two different oxygenation levels (deoxygenated: Y ≈ 71%, oxygenated: Y ≈ 94%) was measured with phase-cycled bSSFP for varying TRs/flip angles at 3 T, 9.4 T, and 14.1 T. The oxygen sensitivity was analyzed by intrinsic MIRACLE (motion-insensitive rapid configuration relaxometry)-R2 estimation and passband signal differences. The intravascular BOLD-related signal change was extracted from the measured data for microvasculature and macrovasculature, and compared with the extravascular contribution obtained by Monte Carlo simulations. RESULTS The MIRACLE-R2 values showed a characteristic increase with longer TRs in deoxygenated blood, corroborating that SE-R2 data cannot be used to assess the intravascular bSSFP BOLD effect. Passband bSSFP signal differences measured at optimal flip angles of 30° at 3 T and 20° at 9.4 T/14.1 T revealed considerable relative intravascular contributions of 95%/70% at 3 T, 74%/43% at 9.4 T, 66%/46% at 14.1 T for TR = 5 ms, and 90%/65% at 3 T, 36%/27% at 9.4 T, 13%/15% at 14.1 T for TR = 10 ms in macrovascular/microvascular regimes. CONCLUSION The results indicate that intravascular effects have to be considered to better understand the origin of bSSFP BOLD contrast in functional MRI experiments, especially at short TRs. The MIRACLE-R2 method demonstrated the ability to quantify the apparent decrease in R2 due to rapid RF refocusing.
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Affiliation(s)
- Marlon Pérez-Rodas
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Graduate Training Centre of Neuroscience, IMPRS for Cognitive and Systems Neuroscience, University of Tübingen, Tübingen, Germany
| | - Rolf Pohmann
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Klaus Scheffler
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Rahel Heule
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
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26
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Wei Z, Wang Q, Modi HR, Cho SM, Geocadin R, Thakor NV, Lu H. Acute-stage MRI cerebral oxygen consumption biomarkers predict 24-hour neurological outcome in a rat cardiac arrest model. NMR IN BIOMEDICINE 2020; 33:e4377. [PMID: 32662593 PMCID: PMC7541582 DOI: 10.1002/nbm.4377] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 06/15/2020] [Accepted: 06/19/2020] [Indexed: 05/13/2023]
Abstract
Brain injury following cardiac arrest (CA) is thought to be caused by a sudden loss of blood flow resulting in disruption in oxygen delivery, neural function and metabolism. However, temporal trajectories of the brain's physiology in the first few hours following CA have not been fully characterized. Furthermore, the extent to which these early measures can predict future neurological outcomes has not been determined. The present study sought to perform dynamic measurements of cerebral blood flow (CBF), oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2 ) with MRI in the first 3 hours following the return of spontaneous circulation (ROSC) in a rat CA model. It was found that CBF, OEF and CMRO2 all revealed a time-dependent increase during the first 3 hours after the ROSC. Furthermore, the temporal trajectories of CBF and CMRO2 , but not OEF, were different across rats and related to neurologic outcomes at a later time (24 hours after the ROSC) (P < .001). Rats who manifested better outcomes revealed faster increases in CBF and CMRO2 during the acute stage. When investigating physiological parameters measured at a single time point, CBF (ρ = 0.82, P = .004) and CMRO2 (ρ = 0.80, P = .006) measured at ~ 3 hours post-ROSC were positively associated with neurologic outcome scores at 24 hours. These findings shed light on brain physiological changes following CA, and suggest that MRI measures of brain perfusion and metabolism may provide a potential biomarker to guide post-CA management.
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Affiliation(s)
- Zhiliang Wei
- Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Qihong Wang
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Center for Blood Oxygen Transport and Hemostasis, Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Hiren R. Modi
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sung-Min Cho
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Romergryko Geocadin
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nitish V. Thakor
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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27
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Schidlowski M, Boland M, Rüber T, Stöcker T. Blood-brain barrier permeability measurement by biexponentially modeling whole-brain arterial spin labeling data with multiple T 2 -weightings. NMR IN BIOMEDICINE 2020; 33:e4374. [PMID: 32715563 DOI: 10.1002/nbm.4374] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 06/24/2020] [Accepted: 06/26/2020] [Indexed: 06/11/2023]
Abstract
Blood-brain barrier (BBB) permeability assessment remains of ongoing interest in clinical practice and research. Transitions between intravascular (IV) and extravascular (EV) gray matter (GM) compartments may provide information regarding the microstructural status of the BBB. Due to different transverse relaxation times (T2 ) of water protons in vessels and GM, it is possible to determine the compartment in which these protons are located. This work presents and investigates the feasibility of a simplified analytical approach for compartmentalizing the proportions of magnetically marked water protons into IV and EV GM components by biexponentially modeling T2 -weighted arterial spin labeling (ASL) data. Numerous model assumptions were used to stabilize the fit and achieve in vivo applicability. Particularly, transverse relaxation times of IV and EV water protons were determined from the analysis of two supporting T2 -weighted ASL measurements, utilizing a monoexponential signal model. This stabilized a two-parameter biexponential fit of ASL data with T2 preparation (PLD = 0.9/1.2/1.5/1.8 s, TET2Prep = 0/30/40/60/80/120/160 ms), which thereby robustly provided estimates of the IV and EV compartment fractions. Experiments were conducted with three healthy volunteers in a 3 T scanner. Averaged over all subjects, the labeled water protons inherit T2,IV = 200 ± 18 ms initially and adapt T2,EV = 91 ± 2 ms with a longer retention time in cerebral structures. Accordingly, the EVlocated ASL signal fraction rises with increasing PLD from 0.31 ± 0.11 at the shortest PLD of 0.9 s to 0.73 ± 0.02 at the longest PLD of 1.8s. These results indicate a transition of the water protons from IV to EV space. The findings support the potential of biexponential modeling for compartmentalizing ASL spin fractions between IV and EV space. The novel integration of monoexponential parameter estimates stabilizes the two-compartment model fit, suggesting that this technique is suitable for robustly estimating the BBB permeability in vivo.
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Affiliation(s)
- Martin Schidlowski
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Markus Boland
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Theodor Rüber
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
- Epilepsy Center Frankfurt Rhine-Main, Department of Neurology, Goethe University Frankfurt, Frankfurt/Main, Germany
- Center for Personalized Translational Epilepsy Research (CePTER), Goethe University Frankfurt, Frankfurt/Main, Germany
| | - Tony Stöcker
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Physics and Astronomy, University of Bonn, Bonn, Germany
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Erratum. NMR IN BIOMEDICINE 2020; 33:e4329. [PMID: 32638465 DOI: 10.1002/nbm.4329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
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Kaczmarz S, Hyder F, Preibisch C. Oxygen extraction fraction mapping with multi-parametric quantitative BOLD MRI: Reduced transverse relaxation bias using 3D-GraSE imaging. Neuroimage 2020; 220:117095. [PMID: 32599265 PMCID: PMC7730517 DOI: 10.1016/j.neuroimage.2020.117095] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 06/11/2020] [Accepted: 06/18/2020] [Indexed: 01/22/2023] Open
Abstract
Magnetic resonance imaging (MRI)-based quantification of the blood-oxygenation-level-dependent (BOLD) effect allows oxygen extraction fraction (OEF) mapping. The multi-parametric quantitative BOLD (mq-BOLD) technique facilitates relative OEF (rOEF) measurements with whole brain coverage in clinically applicable scan times. Mq-BOLD requires three separate scans of cerebral blood volume and transverse relaxation rates measured by gradient-echo (1/T2*) and spin-echo (1/T2). Although the current method is of clinical merit in patients with stroke, glioma and internal carotid artery stenosis (ICAS), there are relaxation measurement artefacts that impede the sensitivity of mq-BOLD and artificially elevate reported rOEF values. We posited that T2-related biases caused by slice refocusing imperfections during rapid 2D-GraSE (Gradient and Spin Echo) imaging can be reduced by applying 3D-GraSE imaging sequences, because the latter requires no slice selective pulses. The removal of T2-related biases would decrease overestimated rOEF values measured by mq-BOLD. We characterized effects of T2-related bias in mq-BOLD by comparing the initially employed 2D-GraSE and two proposed 3D-GraSE sequences to multiple single spin-echo reference measurements, both in vitro and in vivo. A phantom and 25 participants, including young and elderly healthy controls as well as ICAS-patients, were scanned. We additionally proposed a procedure to reliably identify and exclude artefact affected voxels. In the phantom, 3D-GraSE derived T2 values had 57% lower deviation from the reference. For in vivo scans, the formerly overestimated rOEF was reduced by −27% (p < 0.001). We obtained rOEF = 0.51, which is much closer to literature values from positron emission tomography (PET) measurements. Furthermore, increased sensitivity to a focal rOEF elevation in an ICAS-patient was demonstrated. In summary, the application of 3D-GraSE improves the mq-BOLD-based rOEF quantification while maintaining clinically feasible scan times. Thus, mq-BOLD with non-slice selective T2 imaging is highly promising to improve clinical diagnostics of cerebrovascular diseases such as ICAS.
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Affiliation(s)
- Stephan Kaczmarz
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Departments of Radiology & Biomedical Imaging and of Biomedical Engineering, Magnetic Resonance Research Center, Yale University, New Haven, CT, 06520, USA; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Munich, Germany.
| | - Fahmeed Hyder
- Departments of Radiology & Biomedical Imaging and of Biomedical Engineering, Magnetic Resonance Research Center, Yale University, New Haven, CT, 06520, USA
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Neurology, Munich, Germany
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Wei Z, Chen L, Hou X, van Zijl PCM, Xu J, Lu H. Age-Related Alterations in Brain Perfusion, Venous Oxygenation, and Oxygen Metabolic Rate of Mice: A 17-Month Longitudinal MRI Study. Front Neurol 2020; 11:559. [PMID: 32595596 PMCID: PMC7304368 DOI: 10.3389/fneur.2020.00559] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 05/15/2020] [Indexed: 12/31/2022] Open
Abstract
Background: Characterization of physiological parameters of the aging brain, such as perfusion and brain metabolism, is important for understanding brain function and diseases. Aging studies on human brain have mostly been based on the cross-sectional design, while the few longitudinal studies used relatively short follow-up time compared to the lifespan. Objectives: To determine the longitudinal time courses of cerebral physiological parameters across the adult lifespan in mice. Methods: The present work examined longitudinal changes in cerebral blood flow (CBF), cerebral venous oxygenation (Yv), and cerebral metabolic rate of oxygen (CMRO2) using MRI in healthy C57BL/6 mice from 3 to 20 months of age. Each mouse received 16 imaging sessions at an ~1-month interval. Results: Significant increases with age were observed in CBF (p = 0.017) and CMRO2 (p < 0.001). Meanwhile, Yv revealed a significant decrease (p = 0.002) with a non-linear pattern (p = 0.013). The rate of change was 0.87, 2.26, and -0.24% per month for CBF, CMRO2, and Yv, respectively. On the other hand, systemic parameters such as heart rate did not show a significant age dependence (p = 0.47). No white-matter-hyperintensities (WMH) were observed on the T2-weighted image at any age of the mice. Conclusion: With age, the mouse brain revealed an increase in oxygen consumption. This observation is consistent with previous findings in humans using a cross-sectional design and suggests a degradation of the brain's energy production or utilization machinery. Cerebral perfusion remains relatively intact in aged mice, at least until 20 months of age, consistent with the absence of WMH in mice.
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Affiliation(s)
- Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Xirui Hou
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MA, United States
| | - Peter C. M. van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MA, United States
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Zong X, Lian C, Jimenez J, Yamashita K, Shen D, Lin W. Morphology of perivascular spaces and enclosed blood vessels in young to middle-aged healthy adults at 7T: Dependences on age, brain region, and breathing gas. Neuroimage 2020; 218:116978. [PMID: 32447015 PMCID: PMC7485170 DOI: 10.1016/j.neuroimage.2020.116978] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 05/16/2020] [Accepted: 05/18/2020] [Indexed: 12/30/2022] Open
Abstract
Perivascular spaces (PVSs) are fluid-filled spaces surrounding penetrating blood vessels in the brain and are an integral pathway of the glymphatic system. A PVS and the enclosed blood vessel are commonly visualized as a single vessel-like complex (denoted as PVSV) in high-resolution MRI images. Quantitative characterization of the PVSV morphology in MRI images in healthy subjects may serve as a reference for detecting disease related PVS and/or blood vessel alterations in patients with brain diseases. To this end, we evaluated the age dependences, spatial heterogeneities, and dynamic properties of PVSV morphological features in 45 healthy subjects (21–55 years old), using an ultra-high-resolution three-dimensional transverse relaxation time weighted MRI sequence (0.41 × 0.41 × 0.4 mm3) at 7T. Quantitative PVSV parameters, including apparent diameter, count, volume fraction (VF), and relative contrast to noise ratio (rCNR) were calculated in the white matter and subcortical structures. Dynamic changes were induced by carbogen breathing which are known to induce vasodilation and increase the blood oxygenation level in the brain. PVSV count and VF significantly increased with age in basal ganglia (BG), so did rCNR in BG, midbrain, and white matter (WM). Apparent PVSV diameter also showed a positive association with age in the three brain regions, although it did not reach statistical significance. The PVSV VF and count showed large inter-subject variations, with coefficients of variation ranging from 0.17 to 0.74 after regressing out age and gender effects. Both apparent diameter and VF exhibited significant spatial heterogeneity, which cannot be explained solely by radio-frequency field inhomogeneities. Carbogen breathing significantly increased VF in BG and WM, and rCNR in thalamus, BG, and WM compared to air breathing. Our results are consistent with gradual dilation of PVSs with age in healthy adults. The PVSV morphology exhibited spatial heterogeneity and large inter-subject variations and changed during carbogen breathing compared to air breathing.
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Affiliation(s)
- Xiaopeng Zong
- Biomedical Research Imaging Center, Chapel Hill, NC, USA; Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Chunfeng Lian
- Biomedical Research Imaging Center, Chapel Hill, NC, USA; Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jordan Jimenez
- Biomedical Research Imaging Center, Chapel Hill, NC, USA
| | - Koji Yamashita
- Biomedical Research Imaging Center, Chapel Hill, NC, USA; Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dinggang Shen
- Biomedical Research Imaging Center, Chapel Hill, NC, USA; Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Weili Lin
- Biomedical Research Imaging Center, Chapel Hill, NC, USA; Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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