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Lu J, Yassin MM, Guo Y, Yang Y, Cao F, Fang J, Zaman A, Hassan H, Zeng X, Miao X, Yang H, Cao A, Huang G, Han T, Luo Y, Kang Y. Ischemic perfusion radiomics: assessing neurological impairment in acute ischemic stroke. Front Neurol 2024; 15:1441055. [PMID: 39081344 PMCID: PMC11286473 DOI: 10.3389/fneur.2024.1441055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Accepted: 07/04/2024] [Indexed: 08/02/2024] Open
Abstract
Introduction Accurate neurological impairment assessment is crucial for the clinical treatment and prognosis of patients with acute ischemic stroke (AIS). However, the original perfusion parameters lack the deep information for characterizing neurological impairment, leading to difficulty in accurate assessment. Given the advantages of radiomics technology in feature representation, this technology should provide more information for characterizing neurological impairment. Therefore, with its rigorous methodology, this study offers practical implications for clinical diagnosis by exploring the role of ischemic perfusion radiomics features in assessing the degree of neurological impairment. Methods This study employs a meticulous methodology, starting with generating perfusion parameter maps through Dynamic Susceptibility Contrast-Perfusion Weighted Imaging (DSC-PWI) and determining ischemic regions based on these maps and a set threshold. Radiomics features are then extracted from the ischemic regions, and the t-test and least absolute shrinkage and selection operator (Lasso) algorithms are used to select the relevant features. Finally, the selected radiomics features and machine learning techniques are used to assess the degree of neurological impairment in AIS patients. Results The results show that the proposed method outperforms the original perfusion parameters, radiomics features of the infarct and hypoxic regions, and their combinations, achieving an accuracy of 0.926, sensitivity of 0.923, specificity of 0.929, PPV of 0.923, NPV of 0.929, and AUC of 0.923, respectively. Conclusion The proposed method effectively assesses the degree of neurological impairment in AIS patients, providing an objective auxiliary assessment tool for clinical diagnosis.
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Affiliation(s)
- Jiaxi Lu
- School of Applied Technology, Shenzhen University, Shenzhen, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
| | - Mazen M. Yassin
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Yingwei Guo
- School of Electrical and Information Engineering, Northeast Petroleum University, Daqing, China
| | - Yingjian Yang
- Department of Radiological Research and Development, Shenzhen Lanmage Medical Technology Co., Ltd., Shenzhen, China
| | - Fengqiu Cao
- School of Information Science and Engineering, Shenyang Polytechnic University, Shenyang, China
| | - Jiajing Fang
- Shenzhen Academy of Metrology and Quality Inspection, Shenzhen, China
| | - Asim Zaman
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Haseeb Hassan
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
| | - Xueqiang Zeng
- School of Applied Technology, Shenzhen University, Shenzhen, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
| | - Xiaoqiang Miao
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Huihui Yang
- School of Applied Technology, Shenzhen University, Shenzhen, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
| | - Anbo Cao
- School of Applied Technology, Shenzhen University, Shenzhen, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
| | - Guangtao Huang
- School of Applied Technology, Shenzhen University, Shenzhen, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
| | - Taiyu Han
- School of Applied Technology, Shenzhen University, Shenzhen, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
| | - Yu Luo
- Department of Radiology, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, Shanghai, China
| | - Yan Kang
- School of Applied Technology, Shenzhen University, Shenzhen, China
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
- Engineering Research Centre of Medical Imaging and Intelligent Analysis, Ministry of Education, Shenyang, China
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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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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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Xu J, Wiemken A, Langham MC, Rao H, Nabbout M, Caporale AS, Schwab RJ, Detre JA, Wehrli FW. Sleep-stage-dependent alterations in cerebral oxygen metabolism quantified by magnetic resonance. J Neurosci Res 2024; 102:e25313. [PMID: 38415989 DOI: 10.1002/jnr.25313] [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: 08/10/2023] [Revised: 01/25/2024] [Accepted: 02/09/2024] [Indexed: 02/29/2024]
Abstract
A key function of sleep is to provide a regular period of reduced brain metabolism, which is critical for maintenance of healthy brain function. The purpose of this work was to quantify the sleep-stage-dependent changes in brain energetics in terms of cerebral metabolic rate of oxygen (CMRO2 ) as a function of sleep stage using quantitative magnetic resonance imaging (MRI) with concurrent electroencephalography (EEG) during sleep in the scanner. Twenty-two young and older subjects with regular sleep hygiene and Pittsburgh Sleep Quality Index (PSQI) in the normal range were recruited for the study. Cerebral blood flow (CBF) and venous oxygen saturation (SvO2 ) were obtained simultaneously at 3 Tesla field strength and 2.7-s temporal resolution during an 80-min time series using OxFlow, an in-house developed imaging sequence. The method yields whole-brain CMRO2 in absolute physiologic units via Fick's Principle. Nineteen subjects yielded evaluable data free of subject motion artifacts. Among these subjects, 10 achieved slow-wave (N3) sleep, 16 achieved N2 sleep, and 19 achieved N1 sleep while undergoing the MRI protocol during scanning. Mean CMRO2 was 98 ± 7(μmol min-1 )/100 g awake, declining progressively toward deepest sleep stage: 94 ± 10.8 (N1), 91 ± 11.4 (N2), and 76 ± 9.0 μmol min-1 /100 g (N3), with each level differing significantly from the wake state. The technology described is able to quantify cerebral oxygen metabolism in absolute physiologic units along with non-REM sleep stage, indicating brain oxygen consumption to be closely associated with depth of sleep, with deeper sleep stages exhibiting progressively lower CMRO2 levels.
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Affiliation(s)
- Jing Xu
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Andrew Wiemken
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael C Langham
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Hengyi Rao
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Marianne Nabbout
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alessandra S Caporale
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurosciences, Imaging and Clinical Sciences, 'G. d'Annunzio University' of Chieti-Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies (ITAB), 'G. d'Annunzio University' of Chieti-Pescara, Chieti, Italy
| | - Richard J Schwab
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John A Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Felix W Wehrli
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Gou Y, Golden WC, Lin Z, Shepard J, Tekes A, Hu Z, Li X, Oishi K, Albert M, Lu H, Liu P, Jiang D. Automatic Rejection based on Tissue Signal (ARTS) for motion-corrected quantification of cerebral venous oxygenation in neonates and older adults. Magn Reson Imaging 2024; 105:92-99. [PMID: 37939974 PMCID: PMC10841989 DOI: 10.1016/j.mri.2023.11.008] [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: 08/22/2023] [Accepted: 11/04/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVE Cerebral venous oxygenation (Yv) is a key parameter for the brain's oxygen utilization and has been suggested to be a valuable biomarker in various brain diseases including hypoxic ischemic encephalopathy in neonates and Alzheimer's disease in older adults. T2-Relaxation-Under-Spin-Tagging (TRUST) MRI is a widely used technique to measure global Yv level and has been validated against gold-standard PET. However, subject motion during TRUST MRI scan can introduce considerable errors in Yv quantification, especially for noncompliant subjects. The aim of this study was to develop an Automatic Rejection based on Tissue Signal (ARTS) algorithm for automatic detection and exclusion of motion-contaminated images to improve the precision of Yv quantification. METHODS TRUST MRI data were collected from a neonatal cohort (N = 37, 16 females, gestational age = 39.12 ± 1.11 weeks, postnatal age = 1.89 ± 0.74 days) and an older adult cohort (N = 223, 134 females, age = 68.02 ± 9.01 years). Manual identification of motion-corrupted images was conducted for both cohorts to serve as a gold-standard. 9.3% of the images in the neonatal datasets and 0.4% of the images in the older adult datasets were manually identified as motion-contaminated. The ARTS algorithm was trained using the neonatal datasets. TRUST Yv values, as well as the estimation uncertainty (ΔR2) and test-retest coefficient-of-variation (CoV) of Yv, were calculated with and without ARTS motion exclusion. The ARTS algorithm was tested on datasets of older adults: first on the original adult datasets with little motion, and then on simulated adult datasets where the percentage of motion-corrupted images matched that of the neonatal datasets. RESULTS In the neonatal datasets, the ARTS algorithm exhibited a sensitivity of 0.95 and a specificity of 0.97 in detecting motion-contaminated images. Compared to no motion exclusion, ARTS significantly reduced the ΔR2 (median = 3.68 Hz vs. 4.89 Hz, P = 0.0002) and CoV (median = 2.57% vs. 6.87%, P = 0.0005) of Yv measurements. In the original older adult datasets, the sensitivity and specificity of ARTS were 0.70 and 1.00, respectively. In the simulated adult datasets, ARTS demonstrated a sensitivity of 0.91 and a specificity of 1.00. Additionally, ARTS significantly reduced the ΔR2 compared to no motion exclusion (median = 2.15 Hz vs. 3.54 Hz, P < 0.0001). CONCLUSION ARTS can improve the reliability of Yv estimation in noncompliant subjects, which may enhance the utility of Yv as a biomarker for brain diseases.
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Affiliation(s)
- Yifan Gou
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - W Christopher Golden
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zixuan Lin
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jennifer Shepard
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Aylin Tekes
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zhiyi Hu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Xin Li
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kumiko Oishi
- Center for Imaging Science, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; The Russell H. Morgan Department of Radiology & 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
| | - Peiying Liu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Dengrong Jiang
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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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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Mahmud SZ, Bashir A. Repeatability assessment for simultaneous measurement of arterial blood flow, venous oxygen saturation, and muscle perfusion following dynamic exercise. NMR IN BIOMEDICINE 2023; 36:e4872. [PMID: 36349386 DOI: 10.1002/nbm.4872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 11/04/2022] [Accepted: 11/05/2022] [Indexed: 06/16/2023]
Abstract
The purpose of the present study was to demonstrate a new sequence and determine the repeatability of simultaneous dynamic measurements of blood flow, venous oxygen saturation (SvO2 ), and relative perfusion (change from resting perfusion) in calf muscle during recovery from plantar flexion exercise. The feasibility of near simultaneous measurement of bio-energetic parameters was also demonstrated. A sequence was developed to simultaneously measure arterial blood flow using flow-encoded projection, SvO2 using susceptibility-based oximetry, and relative perfusion using arterial spin labeling in combination with dynamic plantar flexion exercise. The parameters were determined at rest and during recovery from single leg plantar flexion exercise. Test-retest repeatability was analyzed using Bland-Altman analysis and intraclass correlation coefficients (ICC). The mitochondrial capacity of skeletal muscle was also measured immediately afterwards with dynamic phosphorus magnetic resonance spectroscopy. Eight healthy subjects participated in the study for test-retest repeatability. Popliteal artery blood flow at rest was 1.79 ± 0.58 ml/s and increased to 11.18 ± 3.02 ml/s immediately after exercise. Popliteal vein SvO2 decreased to 45.93% ± 6.5% from a resting value of 70.46% ± 4.76% following exercise. Relative perfusion (change from rest value) was 51.83 ± 15.00 ml/100 g/min at the cessation of exercise. The recovery of blood flow and SvO2 was modeled as a single exponential with time constants of 38.03 ± 6.91 and 71.19 ± 14.53 s, respectively. All the measured parameters exhibited good repeatability with ICC ranging from 0.8 to 0.95. Bioenergetics measurements were within normal range, demonstrating the feasibility of near simultaneous measurement of hemodynamic and energetic parameters. Clinical feasibility was assessed with Barth syndrome patients, demonstrating reduced oxygen extraction from the blood and reduced mitochondrial oxidative capacity compared with healthy controls. The proposed protocol allows rapid imaging of multiple parameters in skeletal muscle that might be affected in disease.
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Affiliation(s)
- Sultan Z Mahmud
- Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama, USA
| | - Adil Bashir
- Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama, USA
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DeBeer T, Jordan LC, Waddle S, Lee C, Patel NJ, Garza M, Davis LT, Pruthi S, Jones S, Donahue MJ. Red cell exchange transfusions increase cerebral capillary transit times and may alter oxygen extraction in sickle cell disease. NMR IN BIOMEDICINE 2023; 36:e4889. [PMID: 36468659 PMCID: PMC10106384 DOI: 10.1002/nbm.4889] [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: 04/29/2022] [Revised: 11/30/2022] [Accepted: 12/02/2022] [Indexed: 05/17/2023]
Abstract
Persons with sickle cell disease (SCD) suffer from chronic hemolytic anemia, reduced blood oxygen content, and lifelong risk of silent and overt stroke. Major conventional stroke risk factors are absent in most individuals with SCD, yet nearly 50% have evidence of brain infarcts by the age of 30 years, indicating alternative etiologies for ischemia. We investigated whether radiological evidence of accelerated blood water transit through capillaries, visible on arterial spin labeling (ASL) magnetic resonance imaging, reduces following transfusion-induced increases in hemoglobin and relates to oxygen extraction fraction (OEF). Neurological evaluation along with anatomical and hemodynamic imaging with cerebral blood flow (CBF)-weighted pseudocontinuous ASL and OEF imaging with T2 -relaxation-under-spin-tagging were applied in sequence before and after blood transfusion therapy (n = 32) and in a comparator cohort of nontransfused SCD participants on hydroxyurea therapy scanned at two time points to assess stability without interim intervention (n = 13). OEF was calculated separately using models derived from human hemoglobin-F, hemoglobin-A, and hemoglobin-S. Gray matter CBF and dural sinus signal, indicative of rapid blood transit, were evaluated at each time point and compared with OEF using paired statistical tests (significance: two-sided p < 0.05). No significant change in sinus signal was observed in nontransfused participants (p = 0.650), but a reduction was observed in transfused participants (p = 0.034), consistent with slower red cell transit following transfusion. The dural sinus signal intensity was inversely associated with OEF pretransfusion (p = 0.011), but not posttransfusion. Study findings suggest that transfusion-induced increases in total hemoglobin may lengthen blood transit times through cerebral capillaries and alter cerebral OEF in SCD.
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Affiliation(s)
- Tonner DeBeer
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lori C. Jordan
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Spencer Waddle
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Chelsea Lee
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Niral J. Patel
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Maria Garza
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L. Taylor Davis
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sumit Pruthi
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sky Jones
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Manus J. Donahue
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
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Sandgaard AD, Shemesh N, Kiselev VG, Jespersen SN. Larmor frequency shift from magnetized cylinders with arbitrary orientation distribution. NMR IN BIOMEDICINE 2023; 36:e4859. [PMID: 36285793 PMCID: PMC10078263 DOI: 10.1002/nbm.4859] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 10/22/2022] [Accepted: 10/23/2022] [Indexed: 06/01/2023]
Abstract
The magnetic susceptibility of tissue can provide valuable information about its chemical composition and microstructural organization. However, the relation between the magnetic microstructure and the measurable Larmor frequency shift is understood only for a few idealized cases. Here we analyze the microstructure formed by magnetized, NMR-invisible infinite cylinders suspended in an NMR-reporting fluid. Through simulations, we scrutinize various geometries of mesoscopic Lorentz cavities and inclusions, and show that the cavity size should be approximately one order of magnitude larger than the width of the inclusions. We also analytically derive the Larmor frequency shift for a population of cylinders with arbitrary orientation dispersion and show that it is determined by the l = 2 Laplace expansion coefficients p 2 m of the cylinders' orientation distribution function. Our work underscores the need to account for microstructural organization when estimating magnetic tissue properties.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center for Functionally Integrative Neuroscience, Department of Clinical MedicineAarhus UniversityDenmark
| | - Noam Shemesh
- Champalimaud ResearchChampalimaud Centre for the UnknownLisbonPortugal
| | - Valerij G. Kiselev
- Division of Medical Physics, Department of RadiologyUniversity Medical Center FreiburgFreiburgGermany
| | - Sune Nørhøj Jespersen
- Center for Functionally Integrative Neuroscience, Department of Clinical MedicineAarhus UniversityDenmark
- Department of Physics and AstronomyAarhus UniversityDenmark
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10
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Li H, Wang C, Yu X, Luo Y, Wang H. Measurement of Cerebral Oxygen Extraction Fraction Using Quantitative BOLD Approach: A Review. PHENOMICS (CHAM, SWITZERLAND) 2023; 3:101-118. [PMID: 36939794 PMCID: PMC9883382 DOI: 10.1007/s43657-022-00081-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 09/29/2022] [Accepted: 10/11/2022] [Indexed: 12/12/2022]
Abstract
Quantification of brain oxygenation and metabolism, both of which are indicators of the level of brain activity, plays a vital role in understanding the cerebral perfusion and the pathophysiology of brain disorders. Magnetic resonance imaging (MRI), a widely used clinical imaging technique, which is very sensitive to magnetic susceptibility, has the possibility of substituting positron emission tomography (PET) in measuring oxygen metabolism. This review mainly focuses on the quantitative blood oxygenation level-dependent (qBOLD) method for the evaluation of oxygen extraction fraction (OEF) in the brain. Here, we review the theoretic basis of qBOLD, as well as existing acquisition and quantification methods. Some published clinical studies are also presented, and the pros and cons of qBOLD method are discussed as well.
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Affiliation(s)
- Hongwei Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 220 Handan Road, Yangpu District, Shanghai, 200433 China
| | - Chengyan Wang
- Human Phenome Institute, Fudan University, Shanghai, 201203 China
| | - Xuchen Yu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 220 Handan Road, Yangpu District, Shanghai, 200433 China
| | - Yu Luo
- Department of Radiology, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, Shanghai, 200434 China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 220 Handan Road, Yangpu District, Shanghai, 200433 China
- Human Phenome Institute, Fudan University, Shanghai, 201203 China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, (Fudan University), Ministry of Education, Shanghai, 200433 China
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11
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Wood TC, Cash D, MacNicol E, Simmons C, Kim E, Lythgoe DJ, Zelaya F, Turkheimer F. Non-Invasive measurement of the cerebral metabolic rate of oxygen using MRI in rodents. Wellcome Open Res 2022; 6:109. [PMID: 36081865 PMCID: PMC9428501 DOI: 10.12688/wellcomeopenres.16734.4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/16/2022] [Indexed: 11/20/2022] Open
Abstract
Malfunctions of oxygen metabolism are suspected to play a key role in a number of neurological and psychiatric disorders, but this hypothesis cannot be properly investigated without an in-vivo non-invasive measurement of brain oxygen consumption. We present a new way to measure the Cerebral Metabolic Rate of Oxygen (CMRO2) by combining two existing magnetic resonance imaging techniques, namely arterial spin-labelling and oxygen extraction fraction mapping. This method was validated by imaging rats under different anaesthetic regimes and was strongly correlated to glucose consumption measured by autoradiography.
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Affiliation(s)
- Tobias C Wood
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Diana Cash
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Eilidh MacNicol
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Camilla Simmons
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Eugene Kim
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - David J Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
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12
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Wood TC, Cash D, MacNicol E, Simmons C, Kim E, Lythgoe DJ, Zelaya F, Turkheimer F. Non-Invasive measurement of the cerebral metabolic rate of oxygen using MRI in rodents. Wellcome Open Res 2022; 6:109. [PMID: 36081865 PMCID: PMC9428501 DOI: 10.12688/wellcomeopenres.16734.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/08/2022] [Indexed: 08/17/2023] Open
Abstract
Malfunctions of oxygen metabolism are suspected to play a key role in a number of neurological and psychiatric disorders, but this hypothesis cannot be properly investigated without an in-vivo non-invasive measurement of brain oxygen consumption. We present a new way to measure the Cerebral Metabolic Rate of Oxygen (CMRO 2) by combining two existing magnetic resonance imaging techniques, namely arterial spin-labelling and oxygen extraction fraction mapping. This method was validated by imaging rats under different anaesthetic regimes and was strongly correlated to glucose consumption measured by autoradiography.
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Affiliation(s)
- Tobias C Wood
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Diana Cash
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Eilidh MacNicol
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Camilla Simmons
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Eugene Kim
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - David J Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF, UK
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13
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Wood TC, Cash D, MacNicol E, Simmons C, Kim E, Lythgoe DJ, Zelaya F, Turkheimer F. Non-Invasive measurement of the cerebral metabolic rate of oxygen using MRI in rodents. Wellcome Open Res 2022; 6:109. [DOI: 10.12688/wellcomeopenres.16734.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/08/2022] [Indexed: 11/20/2022] Open
Abstract
Malfunctions of oxygen metabolism are suspected to play a key role in a number of neurological and psychiatric disorders, but this hypothesis cannot be properly investigated without an in-vivo non-invasive measurement of brain oxygen consumption. We present a new way to measure the Cerebral Metabolic Rate of Oxygen (CMRO2) by combining two existing magnetic resonance imaging techniques, namely arterial spin-labelling and oxygen extraction fraction mapping. This method was validated by imaging rats under different anaesthetic regimes and was strongly correlated to glucose consumption measured by autoradiography.
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14
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Küppers F, Yun SD, Shah NJ. Development of a novel 10-echo multi-contrast sequence based on EPIK to deliver simultaneous quantification of T 2 and T 2 * with application to oxygen extraction fraction. Magn Reson Med 2022; 88:1608-1623. [PMID: 35657054 DOI: 10.1002/mrm.29305] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/14/2022] [Accepted: 04/26/2022] [Indexed: 11/05/2022]
Abstract
PURPOSE The simultaneous quantification of T2 and T2 * maps based on fast sequences for combined GE and SE acquisition has rekindled research and clinical interest by offering a wide range of attractive applications, e.g., dynamic tracking of oxygen extraction fraction (OEF). However, previously published methods based on EPI-readouts have been hindered by resolution and the number of acquired echoes. METHODS This work presents a novel 10-echo GE-SE EPIK (EPI with keyhole) sequence for the rapid quantification of T2 '. T2 /T2 * maps from the GE-SE EPIK sequence were validated using three phantoms and 15 volunteers at 3T. The incorporation of a sliding window approach, combined with the full sampling of the k-space center inherent to EPIK, enables a high effective temporal resolution. That is, for an eight-slice breath-hold experiment, a temporal sampling rate of eight reconstructed slices per 1.1 s. RESULTS In comparison with repeated single-echo SE, multi-echo GE, and spectroscopy methods, the GE-SE EPIK sequence shows good agreement in quantifying T2 /T2 * values, while the gray matter/white matter separation yielded the expected contrast differentiation. The OEF was calculated with a view to an initial application with clinical relevance, producing results comparable to those in the literature and with good sensitivity in breath-hold experiments. CONCLUSIONS GE-SE EPIK provides increased resolution and more echoes, including two SEs, than comparable sequences. Moreover, GE-SE EPIK achieves this within an acquisition time of 57 s for 20 slices (matrix size = 128×128; FOV = 24 cm) and with a reasonably short TE for the final echo (114 ms). The sequence can dynamically track OEF changes in a breath-hold experiment.
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Affiliation(s)
- Fabian Küppers
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany.,RWTH Aachen University, Aachen, Germany
| | - Seong Dae Yun
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany.,Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Jülich, Germany.,JARA - BRAIN - Translational Medicine, Aachen, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany
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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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Jang J, Kang J, Nam Y. [Brain Iron Imaging in Aging and Cognitive Disorders: MRI Approaches]. TAEHAN YONGSANG UIHAKHOE CHI 2022; 83:527-537. [PMID: 36238502 PMCID: PMC9514519 DOI: 10.3348/jksr.2022.0038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/09/2022] [Accepted: 05/16/2022] [Indexed: 11/23/2022]
Abstract
Iron has a vital role in the human body, including the central nervous system. Increased deposition of iron in the brain has been reported in aging and important neurodegenerative diseases. Owing to the unique magnetic resonance properties of iron, MRI has great potential for in vivo assessment of iron deposition, distribution, and non-invasive quantification. In this paper, we will review the MRI methods for iron assessment and their changes in aging and neurodegenerative diseases, focusing on Alzheimer's disease. In addition, we will summarize the limitations of current approaches and introduce new areas and MRI methods for iron imaging that are expected in the future.
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17
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Cho J, Zhang J, Spincemaille P, Zhang H, Hubertus S, Wen Y, Jafari R, Zhang S, Nguyen TD, Dimov AV, Gupta A, Wang Y. QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping. Magn Reson Med 2021; 87:1583-1594. [PMID: 34719059 DOI: 10.1002/mrm.29057] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 09/01/2021] [Accepted: 10/07/2021] [Indexed: 01/17/2023]
Abstract
PURPOSE To improve accuracy and speed of quantitative susceptibility mapping plus quantitative blood oxygen level-dependent magnitude (QSM+qBOLD or QQ) -based oxygen extraction fraction (OEF) mapping using a deep neural network (QQ-NET). METHODS The 3D multi-echo gradient echo images were acquired in 34 ischemic stroke patients and 4 healthy subjects. Arterial spin labeling and diffusion weighted imaging (DWI) were also performed in the patients. NET was developed to solve the QQ model inversion problem based on Unet. QQ-based OEF maps were reconstructed with previously introduced temporal clustering, tissue composition, and total variation (CCTV) and NET. The results were compared in simulation, ischemic stroke patients, and healthy subjects using a two-sample Kolmogorov-Smirnov test. RESULTS In the simulation, QQ-NET provided more accurate and precise OEF maps than QQ-CCTV with 150 times faster reconstruction speed. In the subacute stroke patients, OEF from QQ-NET had greater contrast-to-noise ratio (CNR) between DWI-defined lesions and their unaffected contralateral normal tissue than with QQ-CCTV: 1.9 ± 1.3 vs 6.6 ± 10.7 (p = 0.03). In healthy subjects, both QQ-CCTV and QQ-NET provided uniform OEF maps. CONCLUSION QQ-NET improves the accuracy of QQ-based OEF with faster reconstruction.
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Affiliation(s)
- Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Jinwei Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Hang Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Simon Hubertus
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Yan Wen
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Ramin Jafari
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Shun Zhang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Alexey V Dimov
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA.,Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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18
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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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19
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Cho J, Lee J, An H, Goyal MS, Su Y, Wang Y. Cerebral oxygen extraction fraction (OEF): Comparison of challenge-free gradient echo QSM+qBOLD (QQ) with 15O PET in healthy adults. J Cereb Blood Flow Metab 2021; 41:1658-1668. [PMID: 33243071 PMCID: PMC8221765 DOI: 10.1177/0271678x20973951] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We aimed to validate oxygen extraction fraction (OEF) estimations by quantitative susceptibility mapping plus quantitative blood oxygen-level dependence (QSM+qBOLD, or QQ) using 15O-PET. In ten healthy adult brains, PET and MRI were acquired simultaneously on a PET/MR scanner. PET was acquired using C[15O], O[15O], and H2[15O]. Image-derived arterial input functions and standard models of oxygen metabolism provided quantification of PET. MRI included T1-weighted imaging, time-of-flight angiography, and multi-echo gradient-echo imaging that was processed for QQ. Region of interest (ROI) analyses compared PET OEF and QQ OEF. In ROI analyses, the averaged OEF differences between PET and QQ were generally small and statistically insignificant. For whole brains, the average and standard deviation of OEF was 32.8 ± 6.7% for PET; OEF was 34.2 ± 2.6% for QQ. Bland-Altman plots quantified agreement between PET OEF and QQ OEF. The interval between the 95% limits of agreement was 16.9 ± 4.0% for whole brains. Our validation study suggests that respiratory challenge-free QQ-OEF mapping may be useful for non-invasive clinical assessment of regional OEF impairment.
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Affiliation(s)
- Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, USA
| | - John Lee
- Mallinkckrodt Institute of Radiology, Washington University School of Medicine, St Louis, USA
| | - Hongyu An
- Mallinkckrodt Institute of Radiology, Washington University School of Medicine, St Louis, USA
| | - Manu S Goyal
- Mallinkckrodt Institute of Radiology, Washington University School of Medicine, St Louis, USA
| | - Yi Su
- Computational Image Analysis, Banner Alzheimer's Institute, Phoenix, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, USA.,Department of Biomedical Engineering, Cornell University, Ithaca, USA
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20
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Cho J, Spincemaille P, Nguyen TD, Gupta A, Wang Y. Temporal clustering, tissue composition, and total variation for mapping oxygen extraction fraction using QSM and quantitative BOLD. Magn Reson Med 2021; 86:2635-2646. [PMID: 34110656 DOI: 10.1002/mrm.28875] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 05/02/2021] [Accepted: 05/10/2021] [Indexed: 12/11/2022]
Abstract
PURPOSE To improve the accuracy of quantitative susceptibility mapping plus quantitative blood oxygen level-dependent magnitude (QSM+qBOLD or QQ) based mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2 ) using temporal clustering, tissue composition, and total variation (CCTV). METHODS Three-dimensional multi-echo gradient echo and arterial spin labeling images were acquired from 11 healthy subjects and 33 ischemic stroke patients. Diffusion-weighted imaging (DWI) was also obtained from patients. The CCTV mapping was developed for incorporating tissue-type information into clustering of the previous cluster analysis of time evolution (CAT) and applying total variation (TV). The QQ-based OEF and CMRO2 were reconstructed with CAT, CAT+TV (CATV), and the proposed CCTV, and results were compared using region-of-interest analysis, Kruskal-Wallis test, and post hoc Wilcoxson rank sum test. RESULTS In simulation, CCTV provided more accurate and precise OEF than CAT or CATV. In healthy subjects, QQ-based OEF was less noisy and more uniform with CCTV than CAT. In subacute stroke patients, OEF with CCTV had a greater contrast-to-noise ratio between DWI-defined lesions and the unaffected contralateral side than with CAT or CATV: 1.9 ± 1.3 versus 1.1 ± 0.7 (P = .01) versus 0.7 ± 0.5 (P < .001). CONCLUSION The CCTV mapping significantly improves the robustness of QQ-based OEF against noise.
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Affiliation(s)
- Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA.,Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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21
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Madhusoodhanan S, Hagberg GE, Scheffler K, Paul JS. Multi-echo gradient-recalled-echo phase unwrapping using a Nyquist sampled virtual echo train in the presence of high-field gradients. Magn Reson Med 2021; 86:2220-2233. [PMID: 34028899 DOI: 10.1002/mrm.28841] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 04/23/2021] [Accepted: 04/23/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE To develop a spatio-temporal approach to accurately unwrap multi-echo gradient-recalled echo phase in the presence of high-field gradients. THEORY AND METHODS Using the virtual echo-based Nyquist sampled (VENyS) algorithm, the temporal unwrapping procedure is modified by introduction of one or more virtual echoes between the first lower and the immediate higher echo, so as to reinstate the Nyquist condition at locations with high-field gradients. An iterative extension of the VENyS algorithm maintains spatial continuity by adjusting the phase rotations to make the neighborhood phase differences less than π. The algorithm is evaluated using simulated data, Gadolinium contrast-doped phantom, and in vivo brain, abdomen, and chest data sets acquired at 3 T and 9.4 T. The unwrapping performance is compared with the standard temporal unwrapping algorithm used in the morphology-enabled dipole inversion-QSM pipeline as a benchmark for validation. RESULTS Quantitative evaluation using numerical phantom showed significant reduction in unwrapping errors in regions of large field gradients, and the unwrapped phase revealed an exact match with the linear concentration profile of vials in a gadolinium contrast-doped phantom data acquired at 9.4 T. Without the need for additional spatial unwrapping, the iterative VENyS algorithm was able to generate spatially continuous phase images. Application to in vivo data resulted in better unwrapping performance, especially in regions with large susceptibility changes such as the air/tissue interface. CONCLUSION The iterative VENyS algorithm serves as a robust unwrapping method for multi-echo gradient-recalled echo phase in the presence of high-field gradients.
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Affiliation(s)
- Sreekanth Madhusoodhanan
- Medical Image Computing and Signal Processing Laboratory, Indian Institute of Information Technology and Management, Thiruvananthapuram, Kerala, India
| | - Gisela E Hagberg
- High-Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany.,Biomedical Magnetic Resonance, Department of Radiology, Eberhard Karl's University and University Hospital, Tübingen, Germany
| | - Klaus Scheffler
- High-Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany.,Biomedical Magnetic Resonance, Department of Radiology, Eberhard Karl's University and University Hospital, Tübingen, Germany
| | - Joseph Suresh Paul
- Medical Image Computing and Signal Processing Laboratory, Indian Institute of Information Technology and Management, Thiruvananthapuram, Kerala, India.,School of Electronic Systems and Automation, The Kerala University of Digital Sciences Innovation and Technology, Thiruvananthapuram, Kerala, India
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22
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Wood TC, Cash D, MacNicol E, Simmons C, Kim E, Lythgoe DJ, Zelaya F, Turkheimer F. Non-Invasive measurement of the cerebral metabolic rate of oxygen using MRI in rodents. Wellcome Open Res 2021; 6:109. [DOI: 10.12688/wellcomeopenres.16734.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/05/2021] [Indexed: 11/20/2022] Open
Abstract
Malfunctions of oxygen metabolism are suspected to play a key role in a number of neurological and psychiatric disorders, but this hypothesis cannot be properly investigated without an in-vivo non-invasive measurement of brain oxygen consumption. We present a new way to measure the Cerebral Metabolic Rate of Oxygen (CMRO2) by combining two existing magnetic resonance imaging techniques, namely arterial spin-labelling and oxygen extraction fraction mapping. This method was validated by imaging rats under different anaesthetic regimes and was strongly correlated to glucose consumption measured by autoradiography.
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23
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Chai C, Wang H, Chu Z, Li J, Qian T, Mark Haacke E, Xia S, Shen W. Reduced regional cerebral venous oxygen saturation is a risk factor for the cognitive impairment in hemodialysis patients: a quantitative susceptibility mapping study. Brain Imaging Behav 2021; 14:1339-1349. [PMID: 30511117 DOI: 10.1007/s11682-018-9999-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The purpose of this study was to noninvasively evaluate the changes of regional cerebral venous oxygen saturation (rSvO2) in hemodialysis patients using quantitative susceptibility mapping (QSM) and investigate the relationship with clinical risk factors and neuropsychological testing. Fifty four (54) hemodialysis patients and 54 age, gender and education matched healthy controls (HCs) were recruited in this prospective study. QSM data were reconstructed from the original phase data of susceptibility weighted imaging to measure the susceptibility of cerebral regional major veins in all subjects and calculate their rSvO2. The differences in rSvO2 between hemodialysis patients and HCs were investigated using analysis of covariance adjusting for age and gender as covariates. Stepwise multiple regression and correlation analysis were performed between the cerebral rSvO2 and clinical factors including neuropsychological testing. The SvO2 of the bilateral cortical, thalamostriate, septal, cerebral internal and basal veins in hemodialysis patients was significantly lower than that in HCs (p < 0.001, Bonferroni corrected). The cerebral rSvO2 in all these veins was reduced by 1.67% to 2.30%. The hematocrit, iron, glucose, pre-and post-dialysis diastolic blood pressure (DBP) were independent predictive factors for the cerebral rSvO2 (all P < 0.05). The Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) scores were both lower in patients than those in HCs (both P < 0.05). The SvO2 of the left cerebral internal vein correlated with MoCA scores (r = 0.492; P = 0.02, FDR corrected). In conclusion, our study indicated that the cerebral rSvO2 was reduced in hemodialysis patients, which was the risk factor for neurocognitive impairment. The hematocrit, iron, glucose, pre-and post-dialysis DBP were independent risk factors for the cerebral rSvO2.
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Affiliation(s)
- Chao Chai
- Department of Radiology, Tianjin First Central Hospital, Tianjin, 300192, China
| | - Huiying Wang
- School of Graduates, Tianjin University of Traditional Chinese Medicine, Tianjin, 300193, China
| | - Zhiqiang Chu
- Department of Hemodialysis, Tianjin First Central Hospital, Tianjin, 300192, China
| | - Jinping Li
- Department of Hemodialysis, Tianjin First Central Hospital, Tianjin, 300192, China
| | - Tianyi Qian
- MR collaboration, Siemens Healthcare, Northeast Asia, Beijing, 100102, China
| | - E Mark Haacke
- Department of Radiology, Wayne State University, Detroit, MI, 48202, USA
| | - Shuang Xia
- Department of Radiology, Tianjin First Central Hospital, Tianjin, 300192, China.
| | - Wen Shen
- Department of Radiology, Tianjin First Central Hospital, Tianjin, 300192, China.
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Caporale A, Lee H, Lei H, Rao H, Langham MC, Detre JA, Wu PH, Wehrli FW. Cerebral metabolic rate of oxygen during transition from wakefulness to sleep measured with high temporal resolution OxFlow MRI with concurrent EEG. J Cereb Blood Flow Metab 2021; 41:780-792. [PMID: 32538283 PMCID: PMC7983504 DOI: 10.1177/0271678x20919287] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 03/03/2020] [Accepted: 03/20/2020] [Indexed: 01/29/2023]
Abstract
During slow-wave sleep, synaptic transmissions are reduced with a concomitant reduction in brain energy consumption. We used 3 Tesla MRI to noninvasively quantify changes in the cerebral metabolic rate of O2 (CMRO2) during wakefulness and sleep, leveraging the 'OxFlow' method, which provides venous O2 saturation (SvO2) along with cerebral blood flow (CBF). Twelve healthy subjects (31.3 ± 5.6 years, eight males) underwent 45-60 min of continuous scanning during wakefulness and sleep, yielding one image set every 3.4 s. Concurrent electroencephalography (EEG) data were available in eight subjects. Mean values of the metabolic parameters measured during wakefulness were stable, with coefficients of variation below 7% (average values: CMRO2 = 118 ± 12 µmol O2/min/100 g, SvO2 = 67.0 ± 3.7% HbO2, CBF = 50.6 ±4.3 ml/min/100 g). During sleep, on average, CMRO2 decreased 21% (range: 14%-32%; average nadir = 98 ± 16 µmol O2/min/100 g), while EEG slow-wave activity, expressed in terms of δ -power, increased commensurately. Following sleep onset, CMRO2 was found to correlate negatively with relative δ -power (r = -0.6 to -0.8, P < 0.005), and positively with heart rate (r = 0.5 to 0.8, P < 0.0005). The data demonstrate that OxFlow MRI can noninvasively measure dynamic changes in cerebral metabolism associated with sleep, which should open new opportunities to study sleep physiology in health and disease.
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Affiliation(s)
- Alessandra Caporale
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, University of Pennsylvania Perelman School of Medicine, PA, USA
| | - Hyunyeol Lee
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, University of Pennsylvania Perelman School of Medicine, PA, USA
| | - Hui Lei
- Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Hengyi Rao
- Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
- Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Michael C Langham
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, University of Pennsylvania Perelman School of Medicine, PA, USA
| | - John A Detre
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, University of Pennsylvania Perelman School of Medicine, PA, USA
- Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Pei-Hsin Wu
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, University of Pennsylvania Perelman School of Medicine, PA, USA
| | - Felix W Wehrli
- Laboratory for Structural Physiologic and Functional Imaging, Department of Radiology, University of Pennsylvania Perelman School of Medicine, PA, USA
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25
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McFadden JJ, Matthews JC, Scott LA, Parker GJM, Lohézic M, Parkes LM. Optimization of quantitative susceptibility mapping for regional estimation of oxygen extraction fraction in the brain. Magn Reson Med 2021; 86:1314-1329. [PMID: 33780045 DOI: 10.1002/mrm.28789] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 03/05/2021] [Accepted: 03/08/2021] [Indexed: 01/20/2023]
Abstract
PURPOSE We sought to determine the degree to which oxygen extraction fraction (OEF) estimated using quantitative susceptibility mapping (QSM) depends on two critical acquisition parameters that have a significant impact on acquisition time: voxel size and final echo time. METHODS Four healthy volunteers were imaged using a range of isotropic voxel sizes and final echo times. The 0.7 mm data were downsampled at different stages of QSM processing by a factor of 2 (to 1.4 mm), 3 (2.1 mm), or 4 (2.8 mm) to determine the impact of voxel size on each analysis step. OEF was estimated from 11 veins of varying diameter. Inter- and intra-session repeatability were estimated for the optimal protocol by repeat scanning in 10 participants. RESULTS Final echo time was found to have no significant effect on OEF. The effect of voxel size was significant, with larger voxel sizes underestimating OEF, depending on the proximity of the vein to the superficial surface of the brain and on vein diameter. The last analysis step of estimating vein OEF values from susceptibility images had the largest dependency on voxel size. Inter-session coefficients of variation on OEF estimates of between 5.2% and 8.7% are reported, depending on the vein. CONCLUSION QSM acquisition times can be minimized by reducing the final echo time but an isotropic voxel size no larger than 1 mm is needed to accurately estimate OEF in most medium/large veins in the brain. Such acquisitions can be achieved in under 4 min.
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Affiliation(s)
- John J McFadden
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Julian C Matthews
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Lauren A Scott
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Geoff J M Parker
- Bioxydyn Limited, Manchester, United Kingdom.,Centre for Medical Image Computing, Department of Computer Science and Department of Neuroinflammation, University College London, London, United Kingdom
| | - Maélène Lohézic
- Applications & Workflow, GE Healthcare, Manchester, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
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Cheng CM, Chou CC, Yeh TC, Chung HW. Measurements of venous oxygen saturation in the superior sagittal sinus using conventional 3D multiple gradient-echo MRI: Effects of flow velocity and acceleration. Magn Reson Med 2020; 85:995-1003. [PMID: 32815571 DOI: 10.1002/mrm.28474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 07/02/2020] [Accepted: 07/23/2020] [Indexed: 11/07/2022]
Abstract
PURPOSE This work investigates the effects of flow acceleration in the superior sagittal sinus on slice-dependent variations in venous oxygen saturation (SvO2 ) estimations using susceptibility-based MR oximetry. METHODS Three-dimensional multiple gradient-echo images, with first-order flow compensation along the anterior-posterior readout direction for the first echo, were acquired twice from 15 healthy volunteers. For all slices, phases within the superior sagittal sinus were fitted using linear regression across four TEs to obtain the Pearson's correlation coefficients (PCCs), the largest of which corresponded to minimum acceleration influence. SvO2 derived from odd echoes on this slice was used to assess interscan difference, and compared with the central 15th slice for slice-dependent difference, both using Bland-Altman analysis. Within-scan interslice SvO2 consistency was examined versus PCC. Multislice-averaged SvO2 values were then computed from slices with PCCs above a certain threshold. RESULTS Slice-dependent difference in SvO2 varied from -16.2% to 21.5% at two SDs, in agreement with a recent report, and about twice larger than interscan differences for the automatically selected slice (-7.5% to 10.3%) and for the central 15th slice (-8.0% to 8.8%). For slices with PCCs higher than -0.98, interslice SvO2 deviations were all found to be less than 5.0%. Multislice-averaged SvO2 with PCCs higher than -0.98 further reduced interscan difference to -4.7% to 8.2%. CONCLUSION Slice-dependent variations in SvO2 may partly be explained by the effects of flow acceleration. Our method may enable conventional 3D multiple gradient echo to be used for SvO2 estimations in the presence of pulsatile flow.
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Affiliation(s)
- Chou-Ming Cheng
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
- Integrated Brain Research Unit, Division of Clinical Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chih-Che Chou
- Integrated Brain Research Unit, Division of Clinical Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Tzu-Chen Yeh
- Integrated Brain Research Unit, Division of Clinical Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- Institute of Brain Science, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Hsiao-Wen Chung
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
- Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan
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Cho J, Ma Y, Spincemaille P, Pike GB, Wang Y. Cerebral oxygen extraction fraction: Comparison of dual-gas challenge calibrated BOLD with CBF and challenge-free gradient echo QSM+qBOLD. Magn Reson Med 2020; 85:953-961. [PMID: 32783233 DOI: 10.1002/mrm.28447] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 06/23/2020] [Accepted: 07/06/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To compare cortical gray matter oxygen extraction fraction (OEF) estimated from 2 MRI methods: (1) the quantitative susceptibility mapping (QSM) plus quantitative blood oxygen level dependent imaging (qBOLD) (QSM+qBOLD or QQ), and (2) the dual-gas calibrated-BOLD (DGCB) in healthy subjects; and to investigate the validity of iso-cerebral metabolic rate of oxygen consumption assumption during hypercapnia using QQ. METHODS In 10 healthy subjects, 3 tesla MRI including a multi-echo gradient echo sequence at baseline and hypercapnia for QQ, as well as an EPI dual-echo pseudo-continuous arterial spin labeling for DGCB, were performed under a hypercapnic and a hyperoxic condition. OEFs from QQ and DGCB were compared using region of interest analysis and paired t test. For QQ, cerebral metabolic rate of oxygen consumption = cerebral blood flow*OEF*arterial oxygen content was generated for both baseline and hypercapnia, which were compared. RESULTS Average OEF in cortical gray matter across 10 subjects from QQ versus DGCB was 35.5 ± 6.7% versus 38.0 ± 9.1% (P = .49) at baseline and 20.7 ± 4.4% versus 28.4 ± 7.6% (P = .02) in hypercapnia: OEF in cortical gray matter was significantly reduced as measured in QQ (P < .01) and in DGCB (P < .01). Cerebral metabolic rate of oxygen consumption (in μmol O2 /min/100 g) was 168.2 ± 54.1 at baseline from DGCB and was 153.1 ± 33.8 at baseline and 126.4 ± 34.2 (P < .01) in hypercapnia from QQ. CONCLUSION The differences in OEF obtained from QQ and DGCB are small and nonsignificant at baseline but are statistically significant during hypercapnia. In addition, QQ shows a cerebral metabolic rate of oxygen consumption decrease (17.4%) during hypercapnia.
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Affiliation(s)
- Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Yuhan Ma
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Gilbert Bruce Pike
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.,Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA.,Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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28
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Fan AP, An H, Moradi F, Rosenberg J, Ishii Y, Nariai T, Okazawa H, Zaharchuk G. Quantification of brain oxygen extraction and metabolism with [ 15O]-gas PET: A technical review in the era of PET/MRI. Neuroimage 2020; 220:117136. [PMID: 32634594 PMCID: PMC7592419 DOI: 10.1016/j.neuroimage.2020.117136] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/15/2020] [Accepted: 07/01/2020] [Indexed: 12/31/2022] Open
Abstract
Oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2) are key cerebral physiological parameters to identify at-risk cerebrovascular patients and understand brain health and function. PET imaging with [15O]-oxygen tracers, either through continuous or bolus inhalation, provides non-invasive assessment of OEF and CMRO2. Numerous tracer delivery, PET acquisition, and kinetic modeling approaches have been adopted to map brain oxygenation. The purpose of this technical review is to critically evaluate different methods for [15O]-gas PET and its impact on the accuracy and reproducibility of OEF and CMRO2 measurements. We perform a meta-analysis of brain oxygenation PET studies in healthy volunteers and compare between continuous and bolus inhalation techniques. We also describe OEF metrics that have been used to detect hemodynamic impairment in cerebrovascular disease. For these patients, advanced techniques to accelerate the PET scans and potential synthesis with MRI to avoid arterial blood sampling would facilitate broader use of [15O]-oxygen PET for brain physiological assessment.
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Affiliation(s)
- Audrey P Fan
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Biomedical Engineering and Department of Neurology, University of California Davis, Davis, CA, USA.
| | - Hongyu An
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Farshad Moradi
- Department of Radiology, Stanford University, Stanford, CA, USA
| | | | - Yosuke Ishii
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Tadashi Nariai
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hidehiko Okazawa
- Biomedical Imaging Research Center, University of Fukui, Fukui, Japan
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
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29
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Jiang D, Lin Z, Liu P, Sur S, Xu C, Hazel K, Pottanat G, Yasar S, Rosenberg P, Albert M, Lu H. Normal variations in brain oxygen extraction fraction are partly attributed to differences in end-tidal CO 2. J Cereb Blood Flow Metab 2020; 40:1492-1500. [PMID: 31382788 PMCID: PMC7308520 DOI: 10.1177/0271678x19867154] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Cerebral oxygen extraction fraction is an important physiological index of the brain's oxygen consumption and supply and has been suggested to be a potential biomarker for a number of diseases such as stroke, Alzheimer's disease, multiple sclerosis, sickle cell disease, and metabolic disorders. However, in order for oxygen extraction fraction to be a sensitive biomarker for personalized disease diagnosis, inter-subject variations in normal subjects must be minimized or accounted for, which will otherwise obscure its interpretation. Therefore, it is essential to investigate the physiological underpinnings of normal differences in oxygen extraction fraction. This work used two studies, one discovery study and one verification study, to examine the extent to which an individual's end-tidal CO2 can explain variations in oxygen extraction fraction. It was found that, across normal subjects, oxygen extraction fraction is inversely correlated with end-tidal CO2. Approximately 50% of the inter-subject variations in oxygen extraction fraction can be attributed to end-tidal CO2 differences. In addition, oxygen extraction fraction was found to be positively associated with age and systolic blood pressure. By accounting for end-tidal CO2, age, and systolic blood pressure of the subjects, normal variations in oxygen extraction fraction can be reduced by 73%, which is expected to substantially enhance the utility of oxygen extraction fraction as a disease biomarker.
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Affiliation(s)
- Dengrong Jiang
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zixuan Lin
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peiying Liu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sandeepa Sur
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Cuimei Xu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kaisha Hazel
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - George Pottanat
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sevil Yasar
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Paul Rosenberg
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,The Russell H. Morgan Department of Radiology & 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
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30
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Cho J, Zhang S, Kee Y, Spincemaille P, Nguyen TD, Hubertus S, Gupta A, Wang Y. Cluster analysis of time evolution (CAT) for quantitative susceptibility mapping (QSM) and quantitative blood oxygen level-dependent magnitude (qBOLD)-based oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO 2 ) mapping. Magn Reson Med 2020; 83:844-857. [PMID: 31502723 PMCID: PMC6879790 DOI: 10.1002/mrm.27967] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Revised: 07/07/2019] [Accepted: 08/04/2019] [Indexed: 01/01/2023]
Abstract
PURPOSE To improve the accuracy of QSM plus quantitative blood oxygen level-dependent magnitude (QSM + qBOLD or QQ)-based mapping of the oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2 ) using cluster analysis of time evolution (CAT). METHODS 3D multi-echo gradient echo and arterial spin labeling images were acquired in 11 healthy subjects and 5 ischemic stroke patients. DWI was also carried out on patients. CAT was developed for analyzing signal evolution over TE. QQ-based OEF and CMRO2 were reconstructed with and without CAT, and results were compared using region of interest analysis and a paired t-test. RESULTS Simulations demonstrated that CAT substantially reduced noise error in QQ-based OEF. In healthy subjects, QQ-based OEF appeared less noisy and more uniform with CAT than without CAT; average OEF with and without CAT in cortical gray matter was 32.7 ± 4.0% and 37.9 ± 4.5%, with corresponding CMRO2 of 148.4 ± 23.8 and 171.4 ± 22.4 μmol/100 g/min, respectively. In patients, regions of low OEF were confined within the ischemic lesions defined on DWI when using CAT, which was not observed without CAT. CONCLUSION The cluster analysis of time evolution (CAT) significantly improves the robustness of QQ-based OEF against noise.
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Affiliation(s)
- Junghun Cho
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Shun Zhang
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
- Department of Radiology, Tongji Hospital, Wuhan 430030, China
| | - Youngwook Kee
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Thanh D. Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Simon Hubertus
- Computer Assisted Clinical Medicine, Heidelberg University, Mannheim 68167, Germany
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Yi Wang
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
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31
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Tao Q, Zhang L, Han X, Chen H, Ji X, Zhang X. Magnetic Susceptibility Difference-Induced Nucleus Positioning in Gradient Ultrahigh Magnetic Field. Biophys J 2019; 118:578-585. [PMID: 31952800 PMCID: PMC7004839 DOI: 10.1016/j.bpj.2019.12.020] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 12/07/2019] [Accepted: 12/18/2019] [Indexed: 01/18/2023] Open
Abstract
Despite the importance of magnetic properties of biological samples for biomagnetism and related fields, the exact magnetic susceptibilities of most biological samples in their physiological conditions are still unknown. Here we used superconducting quantum interferometer device to detect the magnetic properties of nonfixed, nondehydrated live cell and cellular fractions at a physiological temperature of 37°C (310 K). It is obvious that there are paramagnetic components within human nasopharyngeal carcinoma CNE-2Z cells. More importantly, the magnetic properties of the cytoplasm and nucleus are different. Although within a single cell, the magnetic susceptibility difference between cellular fractions (nucleus and cytoplasm) could only cause ∼41-130 pN forces to the nucleus by gradient ultrahigh magnetic fields of 13.1-23.5 T (92-160 T/m), these forces are enough to cause a relative position shift of the nucleus within the cell. This not only demonstrates the importance of magnetic susceptibility in the biological effects of magnetic field but also illustrates the potential application of high magnetic fields in biomedicine.
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Affiliation(s)
- Qingping Tao
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China; Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Lei Zhang
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.
| | - Xuyao Han
- School of Pharmacy, Anhui Medical University, Hefei, Anhui Province, China
| | - Hanxiao Chen
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China; Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Xinmiao Ji
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Xin Zhang
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China; Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China; Institutes of Physical Science and Information Technology, Anhui University, Hefei, China.
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32
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van Zijl P, Knutsson L. In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2019; 306:55-65. [PMID: 31377150 PMCID: PMC6703925 DOI: 10.1016/j.jmr.2019.07.034] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 06/19/2019] [Accepted: 07/08/2019] [Indexed: 05/07/2023]
Abstract
Over the past decades, the field of in vivo magnetic resonance (MR) has built up an impressive repertoire of data acquisition and analysis technologies for anatomical, functional, physiological, and molecular imaging, the description of which requires many book volumes. As such it is impossible for a few authors to have an authoritative overview of the field and for a brief article to be inclusive. We will therefore focus mainly on data acquisition and attempt to give some insight into the principles underlying current advanced methods in the field and the potential for further innovation. In our view, the foreseeable future is expected to show continued rapid progress, for instance in imaging of microscopic tissue properties in vivo, assessment of functional and anatomical connectivity, higher resolution physiologic and metabolic imaging, and even imaging of receptor binding. In addition, acquisition speed and information content will continue to increase due to the continuous development of approaches for parallel imaging (including simultaneous multi-slice imaging), compressed sensing, and MRI fingerprinting. Finally, artificial intelligence approaches are becoming more realistic and will have a tremendous effect on both acquisition and analysis strategies. Together, these developments will continue to provide opportunity for scientific discovery and, in combination with large data sets from other fields such as genomics, allow the ultimate realization of precision medicine in the clinic.
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Affiliation(s)
- Peter van Zijl
- Department of Radiology, Johns Hopkins University, F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
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Jang J, Oh SH, Nam Y, Lee K, Choi HS, Jung SL, Ahn KJ, Park KN, Kim BS. Prognostic value of phase information of 2D T2*-weighted gradient echo brain imaging in cardiac arrest survivors: A preliminary study. Resuscitation 2019; 140:142-149. [PMID: 31153942 DOI: 10.1016/j.resuscitation.2019.05.026] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 05/20/2019] [Accepted: 05/23/2019] [Indexed: 11/17/2022]
Abstract
BACKGROUND Predicting neurological outcomes after cardiac arrest is important to guide therapeutic decisions. We assessed the prognostic value of phase information of 2D T2*-weighted gradient echo imaging (T2*WI) of the brain in CA survivors. METHODS This study included cardiac arrest survivors who had undergone MRI for prognostication. After application of homodyne filtering to T2*WI phase images, the contrast of three venous structures was assessed as normal (score 0) or abnormal (score 1): the superior sagittal sinus, the cortical veins, and the thalamostriate veins. The scores were summarized into a gradient-recalled echo (GRE) summary score. The prognostic performances of T2*WI, diffusion-weighted imaging (DWI), electroencephalography and serum biomarkers were evaluated using receiver operating characteristic (ROC) curves. RESULTS Of the 39 enrolled patients, 12 (31%) had good outcomes and 27 (69%) had poor outcomes. ROC curve analysis showed that T2*WI had good prognostic performance; the area under the curve (AUC) of the GRE summary score (0.980, 95% confidence interval CI 0.950-1.000) was comparable to those of conventional outcome predictors, including DWI patterns (0.949, 95% CI 0.889-1.000). The AUC increased when the summary GRE score was added to DWI patterns (0.991, 95% CI 0.973-1.000), although the difference was not statistically significant (P=0.117). Most subjects with isoelectric electroencephalography (5/6) showed abnormally high phase contrast in the cerebral veins. CONCLUSIONS Filtered phase images of T2*WI showed good prognostic value and can reveal various features of the cerebral metabolic consequences of cardiac arrest, such as decreased neuronal activity and brain death-like patterns.
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Affiliation(s)
- Jinhee Jang
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sang Hoon Oh
- Department of Emergency Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
| | - Yoonho Nam
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kijeong Lee
- Department of Neurology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyun Seok Choi
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - So-Lyung Jung
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kook-Jin Ahn
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kyu Nam Park
- Department of Emergency Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Bum-Soo Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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Möller HE, Bossoni L, Connor JR, Crichton RR, Does MD, Ward RJ, Zecca L, Zucca FA, Ronen I. Iron, Myelin, and the Brain: Neuroimaging Meets Neurobiology. Trends Neurosci 2019; 42:384-401. [PMID: 31047721 DOI: 10.1016/j.tins.2019.03.009] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 03/12/2019] [Accepted: 03/26/2019] [Indexed: 12/31/2022]
Abstract
Although iron is crucial for neuronal functioning, many aspects of cerebral iron biology await clarification. The ability to quantify specific iron forms in the living brain would open new avenues for diagnosis, therapeutic monitoring, and understanding pathogenesis of diseases. A modality that allows assessment of brain tissue composition in vivo, in particular of iron deposits or myelin content on a submillimeter spatial scale, is magnetic resonance imaging (MRI). Multimodal strategies combining MRI with complementary analytical techniques ex vivo have emerged, which may lead to improved specificity. Interdisciplinary collaborations will be key to advance beyond simple correlative analyses in the biological interpretation of MRI data and to gain deeper insights into key factors leading to iron accumulation and/or redistribution associated with neurodegeneration.
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Affiliation(s)
- Harald E Möller
- Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig, Germany.
| | - Lucia Bossoni
- Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands
| | - James R Connor
- Department of Neurosurgery, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | | | - Mark D Does
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Roberta J Ward
- Centre for Neuroinflammation and Neurodegeneration, Department of Medicine, Hammersmith Hospital Campus, Imperial College London, London, UK
| | - Luigi Zecca
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, Milan, Italy; Department of Psychiatry, Columbia University Medical Center, New York State Psychiatric Institute, New York, NY, USA
| | - Fabio A Zucca
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, Milan, Italy
| | - Itamar Ronen
- Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands
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Lin Z, Sur S, Soldan A, Pettigrew C, Miller M, Oishi K, Bilgel M, Moghekar A, Pillai JJ, Albert M, Lu H. Brain Oxygen Extraction by Using MRI in Older Individuals: Relationship to Apolipoprotein E Genotype and Amyloid Burden. Radiology 2019; 292:140-148. [PMID: 31012816 DOI: 10.1148/radiol.2019182726] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Background Apolipoprotein E4 (APOE4) is a major genetic risk factor for late-onset Alzheimer disease. However, the mechanisms by which APOE4 affects the brain, underpinning this risk, have not been fully elucidated. Purpose To investigate the influence of APOE4 on global cerebral oxygen extraction fraction (OEF) and possible mediation through amyloid burden by using MRI-based brain oxygen extraction technique. Materials and Methods Participants were enrolled from a longitudinal prospective study, the Biomarkers for Older Controls at Risk for Dementia study (data collected from January 2015 to December 2017), of whom 35% (50 of 143 participants) were APOE4 carriers. OEF was measured by using a T2-relaxation-under-spin-tagging MRI technique with a 3.0-T MRI system. PET acquired with carbon 11-labeled Pittsburgh compound B tracer was available in 119 participants to measure amyloid burden. Cognitive performance was assessed by using domain-specific composite scores including executive function, episodic memory, visual-spatial processing, and language. Linear regression analysis was performed to investigate the relationship between APOE4, OEF, and amyloid burden. The association between OEF and cognitive function was studied for the entire study cohort and separately for the APOE4 carriers and noncarriers. Results A total of 143 cognitively healthy individuals (mean age 6 standard deviation, 69.1 years 6 8.2; 57 men and 86 women) were studied. APOE4 genetic status was associated with lower OEF (noncarriers, 41.1% 6 5.8; one E4 allele, 40.1% 6 4.9; two E4 alleles, 36.7% 6 4.5; P = .03). Furthermore, among APOE4 carriers, lower OEF correlated with lower executive function scores (b = 0.079 z score for each percent change in OEF; P = .03). Amyloid burden and OEF were independently associated with APOE4 but were not associated with one another, suggesting that the effect of APOE4 on OEF is not mediated by amyloid. Conclusion MRI-based brain oxygen extraction shows that cognitively healthy carriers of the apolipoprotein E4 gene manifest diminished brain oxygen extraction capacity independent of amyloid burden. ©RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Zixuan Lin
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Sandeepa Sur
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Anja Soldan
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Corinne Pettigrew
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Michael Miller
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Kenichi Oishi
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Murat Bilgel
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Abhay Moghekar
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Jay J Pillai
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Marilyn Albert
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
| | - Hanzhang Lu
- From the Department of Biomedical Engineering (Z.L., M.M., H.L.), The Russell H. Morgan Department of Radiology and Radiological Science (Z.L., S.S., K.O., J.J.P., H.L.), and Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 322, Baltimore, Md; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Md (M.B.); and F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md (H.L.)
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Choi Y, Jang J, Nam Y, Shin NY, Choi HS, Jung SL, Ahn KJ, Kim BS. Relationship between Abnormal Hyperintensity on T2-Weighted Images Around Developmental Venous Anomalies and Magnetic Susceptibility of Their Collecting Veins: In-Vivo Quantitative Susceptibility Mapping Study. Korean J Radiol 2019; 20:662-670. [PMID: 30887748 PMCID: PMC6424825 DOI: 10.3348/kjr.2018.0685] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 12/31/2018] [Indexed: 11/20/2022] Open
Abstract
Objective A developmental venous anomaly (DVA) is a vascular malformation of ambiguous clinical significance. We aimed to quantify the susceptibility of draining veins (χvein) in DVA and determine its significance with respect to oxygen metabolism using quantitative susceptibility mapping (QSM). Materials and Methods Brain magnetic resonance imaging of 27 consecutive patients with incidentally detected DVAs were retrospectively reviewed. Based on the presence of abnormal hyperintensity on T2-weighted images (T2WI) in the brain parenchyma adjacent to DVA, the patients were grouped into edema (E+, n = 9) and non-edema (E−, n = 18) groups. A 3T MR scanner was used to obtain fully flow-compensated gradient echo images for susceptibility-weighted imaging with source images used for QSM processing. The χvein was measured semi-automatically using QSM. The normalized χvein was also estimated. Clinical and MR measurements were compared between the E+ and E− groups using Student's t-test or Mann-Whitney U test. Correlations between the χvein and area of hyperintensity on T2WI and between χvein and diameter of the collecting veins were assessed. The correlation coefficient was also calculated using normalized veins. Results The DVAs of the E+ group had significantly higher χvein (196.5 ± 27.9 vs. 167.7 ± 33.6, p = 0.036) and larger diameter of the draining veins (p = 0.006), and patients were older (p = 0.006) than those in the E− group. The χvein was also linearly correlated with the hyperintense area on T2WI (r = 0.633, 95% confidence interval 0.333–0.817, p < 0.001). Conclusion DVAs with abnormal hyperintensity on T2WI have higher susceptibility values for draining veins, indicating an increased oxygen extraction fraction that might be associated with venous congestion.
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Affiliation(s)
- Yangsean Choi
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jinhee Jang
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
| | - Yoonho Nam
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Na Young Shin
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Hyun Seok Choi
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - So Lyung Jung
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Kook Jin Ahn
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Bum Soo Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
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Lin F, Prince MR, Spincemaille P, Wang Y. Patents on Quantitative Susceptibility Mapping (QSM) of Tissue Magnetism. Recent Pat Biotechnol 2018; 13:90-113. [PMID: 30556508 DOI: 10.2174/1872208313666181217112745] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 12/04/2018] [Accepted: 12/11/2018] [Indexed: 01/06/2023]
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) depicts biodistributions of tissue magnetic susceptibility sources, including endogenous iron and calcifications, as well as exogenous paramagnetic contrast agents and probes. When comparing QSM with simple susceptibility weighted MRI, QSM eliminates blooming artifacts and shows reproducible tissue susceptibility maps independent of field strength and scanner manufacturer over a broad range of image acquisition parameters. For patient care, QSM promises to inform diagnosis, guide surgery, gauge medication, and monitor drug delivery. The Bayesian framework using MRI phase data and structural prior knowledge has made QSM sufficiently robust and accurate for routine clinical practice. OBJECTIVE To address the lack of a summary of US patents that is valuable for QSM product development and dissemination into the MRI community. METHOD We searched the USPTO Full-Text and Image Database for patents relevant to QSM technology innovation. We analyzed the claims of each patent to characterize the main invented method and we investigated data on clinical utility. RESULTS We identified 17 QSM patents; 13 were implemented clinically, covering various aspects of QSM technology, including the Bayesian framework, background field removal, numerical optimization solver, zero filling, and zero-TE phase. CONCLUSION Our patent search identified patents that enable QSM technology for imaging the brain and other tissues. QSM can be applied to study a wide range of diseases including neurological diseases, liver iron disorders, tissue ischemia, and osteoporosis. MRI manufacturers can develop QSM products for more seamless integration into existing MRI scanners to improve medical care.
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Affiliation(s)
- Feng Lin
- School of Law, City University of Hong Kong, Hong Kong, China
| | - Martin R Prince
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States
| | - Pascal Spincemaille
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States
| | - Yi Wang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States.,Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
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Yang E, Kirkham AA, Grenier J, Thompson RB. Measurement and correction of the bulk magnetic susceptibility effects of fat: application in venous oxygen saturation imaging. Magn Reson Med 2018; 81:3124-3137. [PMID: 30549088 DOI: 10.1002/mrm.27640] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 11/23/2018] [Accepted: 11/26/2018] [Indexed: 12/21/2022]
Abstract
PURPOSE To develop a correction method for the effects of the magnetic susceptibility of fat (χFat ) on the calculation of venous oxygen saturation (SvO2 ). THEORY The magnetic field shifts associated with the magnetic susceptibility of deoxyhemoglobin can be used to estimate SvO2 , a measure of oxygen extraction and metabolism. However, the distinct magnetic susceptibility of fat surrounding targeted veins will give rise to magnetic field perturbations that will extend into the vein and surrounding tissues, potentially confounding the calculation of SvO2 . METHODS Multi-echo modified Dixon fat-water separated imaging was used to quantify fat-water distributions around the superficial femoral vein (venous return from the lower leg). Fat fraction images were used to generate χFat images, to calculate and remove the associated fat-susceptibility-induced magnetic field shifts before the estimation of SvO2 . This approach was evaluated at rest and with plantar flexion exercise to evaluate calf muscle oxygen extraction in 10 healthy subjects. RESULTS The presence of fat around the vein resulted in complex magnetic field shifts and errors in estimated SvO2 . Corrected resting SvO2 values were significantly larger than those measured with conventional methods, at rest (72.6 ± 11.0% vs. 65.2 ± 12.2%, P < 0.05) and post-exercise (37.4 ± 12.3% vs. 31.7 ± 12.7%, P < 0.05), with larger errors in individuals and/or regions with increased fat volumes. Estimation and removal of the field-effects from χFat enabled the use of fat tissues for the measurement and removal of the background magnetic field. CONCLUSIONS The magnetic susceptibility effects of fat can confound SvO2 estimation, but the susceptibility field effects can estimated and removed with the use of modified Dixon fat-water separated imaging.
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Affiliation(s)
- Esther Yang
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Amy A Kirkham
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Justin Grenier
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Richard B Thompson
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
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Zhang Y, Wei H, Sun Y, Cronin MJ, He N, Xu J, Zhou Y, Liu C. Quantitative susceptibility mapping (QSM) as a means to monitor cerebral hematoma treatment. J Magn Reson Imaging 2018; 48:907-915. [PMID: 29380461 PMCID: PMC6066470 DOI: 10.1002/jmri.25957] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 01/10/2018] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) offers a consistent hemorrhage volume measurement independent of imaging parameters. PURPOSE To investigate the magnetic susceptibility of intracerebral hemorrhage (ICH) as a quantitative measurement for monitoring treatment in hematoma patients. STUDY TYPE Prospective. POPULATION Twenty-six patients with acute ICH were recruited and enrolled in treatment including surgery or medication (mannitol) for 1 week. FIELD STRENGTH/SEQUENCE A 3D gradient echo sequence at 3.0T. ASSESSMENT The hematoma volumes on computed tomography (CT) and QSM were calculated and used for correlation analysis. Magnetic susceptibility changes from pre- to posttreatment were calculated and compared to the National Institutes of Health stroke scale (NIHSS) measure of neurological deficit for each patient. STATISTICAL TESTS Mean susceptibility values were calculated over each region of interest (ROI). A one-sample t-test was used to assess the changes of total volumes and mean magnetic susceptibility of ICH identified between pre- and posttreatment images (P < 0.05 was considered significant) and the Bland-Altman analysis with 95% limits of agreement (average difference, ±1.96 SD of the difference). Regression of volume measurements on QSM vs. CT and fitted linear regression of mean susceptibility vs. CT signal intensity for hematoma regions were conducted in all patients. RESULTS Good correlation was found between hemorrhage volumes calculated from CT and QSM (CT volume = 0.94*QSM volume, r = 0.98). Comparison of QSM pre- and posttreatment showed that the mean ICH volume was reduced by a statistically insignificant amount from 5.74 cm3 to 5.45 cm3 (P = 0.21), while mean magnetic susceptibility was reduced significantly from 0.48 ppm to 0.38 ppm (P = 0.004). A significant positive association was found between changes in magnetic susceptibility values and NIHSS following hematoma treatment (P < 0.01). DATA CONCLUSIONS QSM in hematoma assessment, as compared with CT, offers a comparably accurate volume measurement; however, susceptibility measurements may enable improved monitoring of ICH treatment compared to volume measurements alone. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:907-915.
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Affiliation(s)
- Yuyao Zhang
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Yawen Sun
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Matthew J. Cronin
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Naying He
- Department of Radiology, Rui Jin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jianrong Xu
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Zhou
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
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Abstract
Gaining insights into brain oxygen metabolism has been one of the key areas of research in neurosciences. Extensive efforts have been devoted to developing approaches capable of providing measures of brain oxygen metabolism not only under normal physiological conditions but, more importantly, in various pathophysiological conditions such as cerebral ischemia. In particular, quantitative measures of cerebral metabolic rate of oxygen using positron emission tomography (PET) have been shown to be capable of discerning brain tissue viability during ischemic insults. However, the complex logistics associated with oxygen-15 PET have substantially hampered its wide clinical applicability. In contrast, magnetic resonance imaging (MRI)-based approaches have provided quantitative measures of cerebral oxygen metabolism similar to that obtained using PET. Given the wide availability, MRI-based approaches may have broader clinical impacts, particularly in cerebral ischemia, when time is a critical factor in deciding treatment selection. In this article, we review the pathophysiological basis of altered cerebral hemodynamics and oxygen metabolism in cerebral ischemia, how quantitative measures of cerebral metabolism were obtained using the Kety-Schmidt approach, the physical concepts of non-invasive oxygen metabolism imaging approaches, and, finally, clinical applications of the discussed imaging approaches.
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Affiliation(s)
- Weili Lin
- 1 Biomedical Research Imaging Center and Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,2 Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - William J Powers
- 2 Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Cho J, Kee Y, Spincemaille P, Nguyen TD, Zhang J, Gupta A, Zhang S, Wang Y. Cerebral metabolic rate of oxygen (CMRO 2 ) mapping by combining quantitative susceptibility mapping (QSM) and quantitative blood oxygenation level-dependent imaging (qBOLD). Magn Reson Med 2018. [PMID: 29516537 DOI: 10.1002/mrm.27135] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
PURPOSE To map the cerebral metabolic rate of oxygen (CMRO2 ) by estimating the oxygen extraction fraction (OEF) from gradient echo imaging (GRE) using phase and magnitude of the GRE data. THEORY AND METHODS 3D multi-echo gradient echo imaging and perfusion imaging with arterial spin labeling were performed in 11 healthy subjects. CMRO2 and OEF maps were reconstructed by joint quantitative susceptibility mapping (QSM) to process GRE phases and quantitative blood oxygen level-dependent (qBOLD) modeling to process GRE magnitudes. Comparisons with QSM and qBOLD alone were performed using ROI analysis, paired t-tests, and Bland-Altman plot. RESULTS The average CMRO2 value in cortical gray matter across subjects were 140.4 ± 14.9, 134.1 ± 12.5, and 184.6 ± 17.9 μmol/100 g/min, with corresponding OEFs of 30.9 ± 3.4%, 30.0 ± 1.8%, and 40.9 ± 2.4% for methods based on QSM, qBOLD, and QSM+qBOLD, respectively. QSM+qBOLD provided the highest CMRO2 contrast between gray and white matter, more uniform OEF than QSM, and less noisy OEF than qBOLD. CONCLUSION Quantitative CMRO2 mapping that fits the entire complex GRE data is feasible by combining QSM analysis of phase and qBOLD analysis of magnitude.
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Affiliation(s)
- Junghun Cho
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Youngwook Kee
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Jingwei Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Shun Zhang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA.,Department of Radiology, Tongji Hospital, Wuhan, China
| | - Yi Wang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Cornell Medical College, New York, New York, USA
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