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Alzaidi AA, Panek R, Blockley NP. Quantitative BOLD (qBOLD) imaging of oxygen metabolism and blood oxygenation in the human body: A scoping review. Magn Reson Med 2024; 92:1822-1837. [PMID: 39072791 DOI: 10.1002/mrm.30165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 05/06/2024] [Accepted: 05/08/2024] [Indexed: 07/30/2024]
Abstract
PURPOSE There are many approaches to the quantitative BOLD (qBOLD) technique described in the literature, differing in pulse sequences, MRI parameters and data processing. Thus, in this review, we summarized the acquisition methods, approaches used for oxygenation quantification and clinical populations investigated. METHODS Three databases were systematically searched (Medline, Embase, and Web of Science) for published research that used qBOLD methods for quantification of oxygen metabolism. Data extraction and synthesis were performed by one author and reviewed by a second author. RESULTS A total of 93 relevant papers were identified. Acquisition strategies were summarized, and oxygenation parameters were found to have been investigated in many pathologies such as steno-occlusive diseases, stroke, glioma, and multiple sclerosis disease. CONCLUSION A summary of qBOLD approaches for oxygenation measurements and applications could help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.
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Affiliation(s)
- Ahlam A Alzaidi
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, UK
- Radiology Department, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Rafal Panek
- Medical Physics and Clinical Engineering, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Nicholas P Blockley
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, UK
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Tomaszewski MR, Sukstanskii AL, Haley H, Meng X, Miller CO, Yablonskiy DA. Quantitative gradient recalled echo (qGRE) MRI enables in vivo measurement of pre-atrophic neurodegeneration in a mouse model of Alzheimer's disease. Neuroimage 2024; 298:120794. [PMID: 39173693 DOI: 10.1016/j.neuroimage.2024.120794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 08/09/2024] [Accepted: 08/14/2024] [Indexed: 08/24/2024] Open
Abstract
Robust methods are needed for preclinical evaluation of novel Alzheimer Disease (AD) therapies to accelerate drug discovery. Quantitative Gradient Recalled Echo (qGRE) MRI has shown promise to provide insight into neurodegeneration in AD prior to atrophy development in humans, highlighting areas of low neuronal density. In this study a novel qGRE method (20 echoes, TE=2-40ms) is shown to non-invasively measure the longitudinal neuronal loss in the hippocampus of a mouse model of AD tauopathy Tg4510. Tg4510 (n=10) and wild type (WT, n=6) mice underwent MRI (7T field strength) at 3-7 months old. 3D qGRE approach was used to generate brain-specific R2* maps free of magnetic field inhomogeneity artifacts. Light-sheet microscopy of the brains stained with NeuN and MBP served to visualize neuronal nuclei and myelin content respectively. Significant decrease in NeuN staining between 3mo and 5mo was observed in the hippocampus of Tg4510, validating the mouse AD model. Longitudinal analysis showed clear decreases in R2* metric of qGRE signal in the Tg4510 mice hippocampus undergoing neurodegeneration between 3 and 5 months old. Histogram analysis revealed an upward trend in patterns of low R2* value (Dark Matter, DM), and broadening of R2* distribution. These were quantified as significant increase in both DM Volume Fraction (DMVF) and R2* Standard Deviation (SD) in Tg4510 mice (p=0.004/p=0.016 DMVF/SD) but not in WT controls (p>0.25). Further monotonical increase was also observed in both metrics in time. A significant negative correlation was observed between the DMVF and myelin content (p=0.01, r=-0.76), suggesting sensitivity of the technique to the loss of myelinated axons. The presented qGRE technique, validated by histological measurements, can be readily applied as in vivo tool in preclinical models of neurodegeneration for pharmacodynamics and mechanism of action assessment.
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Affiliation(s)
| | - Alexander L Sukstanskii
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Hyking Haley
- Translational Imaging Department, Merck & Co., Inc., Rahway, NJ, USA
| | - Xiangjun Meng
- Translational Imaging Department, Merck & Co., Inc., Rahway, NJ, USA
| | - Corin O Miller
- Translational Imaging Department, Merck & Co., Inc., Rahway, NJ, USA
| | - Dmitriy A Yablonskiy
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
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Samara A, Xiang B, Judge B, Ciotti JR, Yablonskiy DA, Cross AH, Brier MR. Increased periventricular thalamic damage gradient in multiple sclerosis detected by quantitative gradient echo MRI. Mult Scler Relat Disord 2024; 90:105834. [PMID: 39208571 DOI: 10.1016/j.msard.2024.105834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 08/08/2024] [Accepted: 08/19/2024] [Indexed: 09/04/2024]
Abstract
OBJECTIVE Thalamic tissue damage in multiple sclerosis (MS) follows a 'surface-in' gradient from the ventricular surface. The clinical consequences of this gradient are not completely understood. Using quantitative gradient-recalled echo (qGRE) MRI, we evaluated a periventricular thalamic gradient of tissue integrity in MS and its relationship with clinical variables. METHODS Structural and qGRE MRI scans were acquired for a cohort of MS patients and healthy controls (HC). qGRE-derived R2t* values were used as a measure of tissue integrity. Thalamic segmentations were divided into 1-mm concentric bands radiating from the ventricular surface, excluding the CSF-adjacent band. Median R2t* values within these bands were used to calculate the periventricular thalamic gradient. RESULTS We included 44 MS patients and 17 HC. R2t* increased slightly with distance from the ventricular surface in HC. MS patients had a steeper periventricular thalamic gradient compared to HC (mean slope 0.55 vs. 0.36; p < 0.001), which correlated with longer disease duration (β = 0.001 /year; p = 0.027) and higher Expanded Disability Status Scale (EDSS) score (β = 0.07 /EDSS point; p = 0.019). Left and right thalamus were symmetrically affected. CONCLUSIONS We detected an increased thalamic gradient in MS in vivo using qGRE MRI, which correlated with disease duration and greater clinical disability. These findings further support the 'surface-in' pathology hypothesis in MS and suggest a CSF-mediated process given symmetric bi-thalamic involvement.
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Affiliation(s)
- Amjad Samara
- Department of Neurology, Washington University School of Medicine, St. Louis, St. Louis, MO 63110, USA
| | - Biao Xiang
- Department of Neurology, Washington University School of Medicine, St. Louis, St. Louis, MO 63110, USA
| | - Bradley Judge
- Department of Radiology, Washington University School of Medicine, St. Louis, St. Louis, MO 63110, USA
| | - John R Ciotti
- Department of Neurology, University of South Florida, Tampa, FL, USA
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University School of Medicine, St. Louis, St. Louis, MO 63110, USA
| | - Anne H Cross
- Department of Neurology, Washington University School of Medicine, St. Louis, St. Louis, MO 63110, USA
| | - Matthew R Brier
- Department of Neurology, Washington University School of Medicine, St. Louis, St. Louis, MO 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis, St. Louis, MO 63110, 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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Cho J, Zhang J, Spincemaille P, Zhang H, Nguyen TD, Zhang S, Gupta A, Wang Y. Multi-Echo Complex Quantitative Susceptibility Mapping and Quantitative Blood Oxygen Level-Dependent Magnitude (mcQSM + qBOLD or mcQQ) for Oxygen Extraction Fraction (OEF) Mapping. Bioengineering (Basel) 2024; 11:131. [PMID: 38391617 PMCID: PMC10886243 DOI: 10.3390/bioengineering11020131] [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: 12/22/2023] [Revised: 01/25/2024] [Accepted: 01/26/2024] [Indexed: 02/24/2024] Open
Abstract
Oxygen extraction fraction (OEF), the fraction of oxygen that tissue extracts from blood, is an essential biomarker used to directly assess tissue viability and function in neurologic disorders. In ischemic stroke, for example, increased OEF can indicate the presence of penumbra-tissue with low perfusion yet intact cellular integrity-making it a primary therapeutic target. However, practical OEF mapping methods are not currently available in clinical settings, owing to the impractical data acquisitions in positron emission tomography (PET) and the limitations of existing MRI techniques. Recently, a novel MRI-based OEF mapping technique, termed QQ, was proposed. It shows high potential for clinical use by utilizing a routine sequence and removing the need for impractical multiple gas inhalations. However, QQ relies on the assumptions of Gaussian noise in susceptibility and multi-echo gradient echo (mGRE) magnitude signals for OEF estimation. This assumption is unreliable in low signal-to-noise ratio (SNR) regions like disease-related lesions, risking inaccurate OEF estimation and potentially impacting clinical decisions. Addressing this, our study presents a novel multi-echo complex QQ (mcQQ) that models realistic Gaussian noise in mGRE complex signals. We implemented mcQQ using a deep learning framework (mcQQ-NET) and compared it with the existing QQ-NET in simulations, ischemic stroke patients, and healthy subjects, using identical training and testing datasets and schemes. In simulations, mcQQ-NET provided more accurate OEF than QQ-NET. In the subacute stroke patients, mcQQ-NET showed a lower average OEF ratio in lesions relative to unaffected contralateral normal tissue than QQ-NET. In the healthy subjects, mcQQ-NET provided uniform OEF maps, similar to QQ-NET, but without unrealistically high OEF outliers in areas of low SNR, such as SNR ≤ 15 (dB). Therefore, mcQQ-NET improves OEF accuracy by more accurately reflecting realistic Gaussian noise in complex mGRE signals. Its enhanced sensitivity to OEF abnormalities, based on more realistic biophysics modeling, suggests that mcQQ-NET has potential for investigating tissue variability in neurologic disorders.
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Affiliation(s)
- Junghun Cho
- Department of Biomedical Engineering, State University of New York at Buffalo, Buffalo, NY 14228, USA
| | - Jinwei Zhang
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | | | - Hang Zhang
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Shun Zhang
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, 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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Kahali S, Kothapalli SVVN, Xu X, Kamilov US, Yablonskiy DA. Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient-Recalled Echo (qGRE) magnetic resonance imaging metrics associated with human brain neuronal structure and hemodynamic properties. NMR IN BIOMEDICINE 2023; 36:e4883. [PMID: 36442839 DOI: 10.1002/nbm.4883] [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: 07/11/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 06/16/2023]
Abstract
The purpose of the current study was to introduce a Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) method for reconstructing quantitative maps of biological tissue cellular-specific, R2t*, and hemodynamic-specific, R2', metrics of quantitative gradient-recalled echo (qGRE) MRI. The DANSE method adapts a supervised learning paradigm to train a convolutional neural network for robust estimation of R2t* and R2' maps with significantly reduced sensitivity to noise and the adverse effects of macroscopic (B0 ) magnetic field inhomogeneities directly from the gradient-recalled echo (GRE) magnitude images. The R2t* and R2' maps for training were generated by means of a voxel-by-voxel fitting of a previously developed biophysical quantitative qGRE model accounting for tissue, hemodynamic, and B0 -inhomogeneities contributions to multigradient-echo GRE signal using a nonlinear least squares (NLLS) algorithm. We show that the DANSE model efficiently estimates the aforementioned qGRE maps and preserves all the features of the NLLS approach with significant improvements including noise suppression and computation speed (from many hours to seconds). The noise-suppression feature of DANSE is especially prominent for data with low signal-to-noise ratio (SNR ~ 50-100), where DANSE-generated R2t* and R2' maps had up to three times smaller errors than that of the NLLS method. The DANSE method enables fast reconstruction of qGRE maps with significantly reduced sensitivity to noise and magnetic field inhomogeneities. The DANSE method does not require any information about field inhomogeneities during application. It exploits spatial and gradient echo time-dependent patterns in the GRE data and previously gained knowledge from the biophysical model, thus producing high quality qGRE maps, even in environments with high noise levels. These features along with fast computational speed can lead to broad qGRE clinical and research applications.
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Affiliation(s)
- Sayan Kahali
- Department of Radiology, Washington University in Saint Louis, St. Louis, Missouri, USA
| | | | - Xiaojian Xu
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Ulugbek S Kamilov
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in Saint Louis, St. Louis, Missouri, USA
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Brier MR, Xiang B, Ciotti JR, Chahin S, Wu GF, Naismith RT, Yablonskiy D, Cross AH. Quantitative MRI identifies lesional and non-lesional abnormalities in MOGAD. Mult Scler Relat Disord 2023; 73:104659. [PMID: 37004272 PMCID: PMC10994694 DOI: 10.1016/j.msard.2023.104659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 03/19/2023] [Accepted: 03/22/2023] [Indexed: 04/04/2023]
Abstract
BACKGROUND Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a distinct central nervous system (CNS) disorder that shares features with multiple sclerosis (MS) and may be misdiagnosed as MS. MOGAD and MS share a frequently relapsing clinical course and lesions with inflammatory demyelinating pathology. One key feature of MS pathology is tissue damage in normal-appearing white matter (NAWM) outside of discrete lesions, whereas the extent to which similar non-lesional damage occurs in MOGAD is not known and could be assessed using qGRE. The goal of this study was to examine the brains of people with MOGAD using quantitative gradient-recalled echo (qGRE) magnetic resonance imaging and to compare tissue damage with MS patients matched for disability. METHODS MOGAD and MS patients were recruited to match in terms of age and disability. Similarly aged healthy control (HC) data were drawn from existing studies. qGRE brain imaging of HC (N = 15), MOGAD (N = 17), and MS (N = 15) patients was used to examine the severity and extent of tissue damage within and outside of discrete lesions. The qGRE metric R2t* is sensitive to changes in tissue microstructure and was measured in white matter lesions (WMLs), NAWM, cortical (CGM) and deep gray matter (DGM). Statistical inference was performed with linear models. RESULTS R2t* was reduced in CGM (p = 0.00047), DGM (p = 0.0055) and NAWM (p = 0.0019) in MOGAD and MS compared to similar regions in age-matched HCs. However, the degree of R2t* reduction in all these regions was less in the MOGAD patients compared with MS. WMLs in MOGAD demonstrated reduced R2t* compared to NAWM but this reduction was modest compared to changes associated with WMLs in MS (p = 0.026). CONCLUSION These results demonstrate abnormalities in lesional and non-lesional CNS tissues in MOGAD that are not detectable on standard MRI. The abnormalities seen in NAWM, CGM, and DGM were less severe in MOGAD compared to MS. MOGAD-related WMLs showed reduced R2t*, but were less abnormal than WMLs in MS. These data reveal damage to non-lesional tissues in two different demyelinating diseases, suggesting that damage outside of WMLs may be a common feature of demyelinating diseases. The lesser degree of R2t* abnormality in MOGAD tissues compared to MS suggests less underlying tissue damage and may underlie the greater propensity for recovery in MOGAD.
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Affiliation(s)
- Matthew R Brier
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
| | - Biao Xiang
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - John R Ciotti
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States; Department of Neurology, University of South Florida, Tampa, FL, United States
| | - Salim Chahin
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
| | - Gregory F Wu
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
| | - Robert T Naismith
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
| | - Dmitriy Yablonskiy
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Anne H Cross
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States.
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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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Edwards LJ, McColgan P, Helbling S, Zarkali A, Vaculčiaková L, Pine KJ, Dick F, Weiskopf N. Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis. Cereb Cortex 2022; 33:5704-5716. [PMID: 36520483 PMCID: PMC10152104 DOI: 10.1093/cercor/bhac453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/20/2022] [Accepted: 10/21/2022] [Indexed: 12/23/2022] Open
Abstract
Abstract
Quantitative magnetic resonance imaging (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (${R_{1}}$), effective transverse relaxation rate (${R_{2}}^{\ast }$), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (${R_{2}}^{\ast }$ at 3T, ${R_{1}}$ at 7T), endothelial cells (${R_{1}}$ and MTsat at 3T), microglia (${R_{1}}$ and MTsat at 3T, ${R_{1}}$ at 7T), and oligodendrocytes and oligodendrocyte precursor cells (${R_{1}}$ at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.
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Affiliation(s)
- Luke J Edwards
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Peter McColgan
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Huntington’s Disease Centre, University College London , London, UK
| | - Saskia Helbling
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Poeppel Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society , Frankfurt am Main, DE, Germany
| | - Angeliki Zarkali
- Dementia Research Centre, University College London , London, UK
| | - Lenka Vaculčiaková
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Fred Dick
- Birkbeck/UCL Centre for Neuroimaging (BUCNI) , London, UK
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University , Leipzig, DE, Germany
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11
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Using quantitative MRI to study the association of isocitrate dehydrogenase (IDH) status with oxygen metabolism and cellular structure changes in glioma. Eur J Radiol 2022; 155:110502. [PMID: 36049408 DOI: 10.1016/j.ejrad.2022.110502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 08/14/2022] [Accepted: 08/23/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To investigate the characteristics of oxygen metabolism and the cellular structure of glioma using quantitative MRI to predict the isocitrate dehydrogenase 1 (IDH1) status and to further understand the biological characteristics of gliomas. METHODS In this retrospective study, 94 patients with gliomas eventually received quantitative MRI measures to study oxygen metabolism. The oxygen metabolism biomarker maps (oxygen extraction fraction [OEF] and cerebral metabolic rate of oxygen [CMRO2]) and the tissue-cellular-specific (R2t*) MRI relaxation parameter were evaluated in different regions of glioma. RESULTS MRI results showed differences in oxygen metabolism measures in all patients with gliomas of different IDH1 statuses. Compared to patients with IDH1 mutant gliomas, patients with IDH1 wild type gliomas showed increased (P < 0.01) CMRO2, OEF, cerebral blood volume [CBF], and R2t* measures in tumor regions, while only OEF, CBF and R2t* were found to be increased (P < 0.05) in the peritumoral area. OEF achieved the best performance for distinguishing IDH1 wild type and mutant gliomas in the tumor area (AUC = 0.732, P < 0.001). R2t* values correlated with Ki-67(R = 0.35, P < 0.001) in the tumor area, while no significant correlations between Ki-67 and R2t* were found in the peritumoral area (R = 0.19, P = 0.072). CONCLUSION Quantitative MRI has potential applications in studying the tumor and peritumoral areas of glioma, and it has the ability to predict and reveal the characteristics of oxygen metabolism and cellular structure in different regions of gliomas.
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12
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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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13
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Levasseur VA, Xiang B, Salter A, Yablonskiy DA, Cross AH. Stronger Microstructural Damage Revealed in Multiple Sclerosis Lesions With Central Vein Sign by Quantitative Gradient Echo MRI. J Cent Nerv Syst Dis 2022; 14:11795735221084842. [PMID: 35370433 PMCID: PMC8973074 DOI: 10.1177/11795735221084842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Background Multiple sclerosis (MS) lesions typically form around a central vein that can be visualized with FLAIR* MRI, creating the central vein sign (CVS) which may reflect lesion pathophysiology. Herein we used gradient echo plural contrast imaging (GEPCI) MRI to simultaneously visualize CVS and measure tissue damage in MS lesions. We examined CVS in relation to tissue integrity in white matter (WM) lesions and among MS subtypes. Objective We aimed to determine if CVS positive lesions were specific to MS subtype, if CVS can be detected consistently among readers using the GEPCI method, and if there were differences in tissue damage in lesions with vs without CVS. Subjects and Methods Thirty relapsing-remitting MS (RRMS) subjects and 38 primary and secondary progressive MS (PMS) subjects were scanned with GEPCI protocol at 3T. GEPCI T2*-SWI images were generated to visualize CVS. Two investigators independently evaluated WM lesions for CVS and measured lesion volumes. To estimate tissue damage severity, total lesion volume, and mean lesion volume, R2t*-based tissue damage score (TDS) of individual lesions and tissue damage load (TDL) were measured for CVS+, CVS-, and confluent lesions. Spearman correlations were made between MRI and clinical data. One-way ANCOVA with age and sex as covariates was used to compare measurements of CVS+ vs CVS- lesions in each individual. Results 398 of 548 lesions meeting inclusion criteria showed CVS. Most patients had ≥40% CVS+ lesions. CVS+ lesions were present in similar proportion among MS subtypes. Interobserver agreement was high for CVS detection. CVS+ and confluent lesions had higher average and total volumes vs CVS- lesions. CVS+ and confluent lesions had more tissue damage than CVS- lesions based on TDL and mean TDS. Conclusion CVS occurred in RRMS and PMS in similar proportions. CVS+ lesions had greater tissue damage and larger size than CVS- lesions.
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Affiliation(s)
- Victoria A. Levasseur
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Biao Xiang
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Amber Salter
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA, USA
| | - Dmitriy A. Yablonskiy
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Anne H. Cross
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
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14
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Chiang GC, Cho J, Dyke J, Zhang H, Zhang Q, Tokov M, Nguyen T, Kovanlikaya I, Amoashiy M, de Leon M, Wang Y. Brain oxygen extraction and neural tissue susceptibility are associated with cognitive impairment in older individuals. J Neuroimaging 2022; 32:697-709. [PMID: 35294075 DOI: 10.1111/jon.12990] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 03/02/2022] [Accepted: 03/02/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND AND PURPOSE We investigated the effects of aging, white matter hyperintensities (WMH), and cognitive impairment on brain iron levels and cerebral oxygen metabolism, known to be altered in Alzheimer's disease (AD), using quantitative susceptibility mapping and MR-based cerebral oxygen extraction fraction (OEF). METHODS In 100 individuals over the age of 50 (68/32 cognitively impaired/intact), OEF and neural tissue susceptibility (χn ) were computed retrospectively from MRI multi-echo gradient echo data, obtained on a 3 Tesla MRI scanner. The effects of age and WMH on OEF and χn were assessed within groups, and OEF and χn were assessed between groups, using multivariate regression analyses. RESULTS Cognitively impaired subjects were found to have 19% higher OEF and 34% higher χn than cognitively intact subjects in the cortical gray matter and several frontal, temporal, and parietal regions (p < .05). Increased WMH burden was significantly associated with decreased OEF in the cognitively impaired, but not in the cognitively intact. Older age had a stronger association with decreased OEF in the cognitively intact group. Both older age and increased WMH burden were significantly associated with increased χn in temporoparietal regions in the cognitively impaired. CONCLUSIONS Higher brain OEF and χn in cognitively impaired older individuals may reflect altered oxygen metabolism and iron in areas with underlying AD pathology. Both age and WMH have associations with OEF and χn but are modified by the presence of cognitive impairment.
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Affiliation(s)
- Gloria C Chiang
- Department of Radiology, Division of Neuroradiology, Weill Cornell Medicine, NewYork-Presbyterian Hospital, New York, New York, USA
| | - Junghun Cho
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Jonathan Dyke
- Citigroup Biomedical Imaging Center, Weill Cornell Medicine, New York, New York, USA
| | - Hang Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Qihao Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Michael Tokov
- New York Institute of Technology College of Osteopathic Medicine, Glen Head, New York, USA
| | - Thanh Nguyen
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Ilhami Kovanlikaya
- Department of Radiology, Division of Neuroradiology, Weill Cornell Medicine, NewYork-Presbyterian Hospital, New York, New York, USA
| | - Michael Amoashiy
- Department of Neurology, Weill Cornell Medicine, New York, New York, USA
| | - Mony de Leon
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Yi Wang
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
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15
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Xu X, Kothapalli SVVN, Liu J, Kahali S, Gan W, Yablonskiy DA, Kamilov US. Learning-based motion artifact removal networks for quantitative R 2 ∗ mapping. Magn Reson Med 2022; 88:106-119. [PMID: 35257400 DOI: 10.1002/mrm.29188] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 01/11/2022] [Accepted: 01/18/2022] [Indexed: 11/12/2022]
Abstract
PURPOSE To introduce two novel learning-based motion artifact removal networks (LEARN) for the estimation of quantitative motion- and B 0 -inhomogeneity-corrected R 2 ∗ maps from motion-corrupted multi-Gradient-Recalled Echo (mGRE) MRI data. METHODS We train two convolutional neural networks (CNNs) to correct motion artifacts for high-quality estimation of quantitative B 0 -inhomogeneity-corrected R 2 ∗ maps from mGRE sequences. The first CNN, LEARN-IMG, performs motion correction on complex mGRE images, to enable the subsequent computation of high-quality motion-free quantitative R 2 ∗ (and any other mGRE-enabled) maps using the standard voxel-wise analysis or machine learning-based analysis. The second CNN, LEARN-BIO, is trained to directly generate motion- and B 0 -inhomogeneity-corrected quantitative R 2 ∗ maps from motion-corrupted magnitude-only mGRE images by taking advantage of the biophysical model describing the mGRE signal decay. RESULTS We show that both CNNs trained on synthetic MR images are capable of suppressing motion artifacts while preserving details in the predicted quantitative R 2 ∗ maps. Significant reduction of motion artifacts on experimental in vivo motion-corrupted data has also been achieved by using our trained models. CONCLUSION Both LEARN-IMG and LEARN-BIO can enable the computation of high-quality motion- and B 0 -inhomogeneity-corrected R 2 ∗ maps. LEARN-IMG performs motion correction on mGRE images and relies on the subsequent analysis for the estimation of R 2 ∗ maps, while LEARN-BIO directly performs motion- and B 0 -inhomogeneity-corrected R 2 ∗ estimation. Both LEARN-IMG and LEARN-BIO jointly process all the available gradient echoes, which enables them to exploit spatial patterns available in the data. The high computational speed of LEARN-BIO is an advantage that can lead to a broader clinical application.
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Affiliation(s)
- Xiaojian Xu
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Jiaming Liu
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Sayan Kahali
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Weijie Gan
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Ulugbek S Kamilov
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
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16
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Xiang B, Brier MR, Kanthamneni M, Wen J, Snyder AZ, Yablonskiy DA, Cross AH. Tissue damage detected by quantitative gradient echo MRI correlates with clinical progression in non-relapsing progressive MS. Mult Scler 2022; 28:1515-1525. [PMID: 35196933 DOI: 10.1177/13524585211073761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Imaging biomarkers of progressive multiple sclerosis (MS) are needed. Quantitative gradient recalled echo (qGRE) magnetic resonance imaging (MRI) evaluates microstructural tissue damage in MS. OBJECTIVE To evaluate qGRE-derived R2t* as an imaging biomarker of MS progression compared with atrophy and lesion burden. METHODS Twenty-three non-relapsing progressive MS (PMS), 22 relapsing-remitting MS (RRMS), and 18 healthy control participants underwent standard MS physical and cognitive neurological assessments and imaging with qGRE, FLAIR, and MPRAGE at 3T. PMS subjects were tested clinically and imaged every 9 months over 45 months. Imaging measures included lesion burden, atrophy, and R2t* in cortical gray matter (GM), deep GM, and normal-appearing white matter (NAWM). Longitudinal analysis of clinical performance and imaging biomarkers in PMS subjects was conducted via linear models with subject as repeated, within-subject factor. Relationship between imaging biomarkers and clinical scores was assessed by Spearman rank correlation. RESULTS R2t* reductions correlated with neurological impairment cross-sectionally and longitudinally. PMS patients with clinically defined disease progression (N = 13) showed faster decrease of R2t* in NAWM and deep GM compared with the clinically stable PMS group (N = 10). Importantly, tissue damage measured by R2t* outperformed lesion burden and atrophy as a biomarker of progression during the study period. CONCLUSION qGRE-derived R2t* is a potential imaging biomarker of MS progression.
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Affiliation(s)
- Biao Xiang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Matthew R Brier
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Manasa Kanthamneni
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA/School of Medicine, St. George's University, St. George, Grenada
| | - Jie Wen
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA/Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Anne H Cross
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
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17
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Ebrahimpour A, Tirgar F, Hajipour-Verdom B, Abbasi A, Hadjighassem M, Abdolmaleki P, Hosseindoost S, Javadi SAH, Hashemi H, Foroushani AR, Alam NR, Khoobi M. Detection of glioblastoma multiforme using quantitative molecular magnetic resonance imaging based on 5-aminolevulinic acid: in vitro and in vivo studies. MAGMA (NEW YORK, N.Y.) 2022; 35:3-15. [PMID: 34878619 DOI: 10.1007/s10334-021-00978-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 09/19/2021] [Accepted: 11/15/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVES We demonstrated a novel metabolic method based on sequential administration of 5-aminolevulinic acid (ALA) and iron supplement, and ferric ammonium citrate (FAC), for glioblastoma multiforme (GBM) detection using R2' and quantitative susceptibility mapping (QSM). MATERIALS AND METHODS Intra-cellular iron accumulation in glioblastoma cells treated with ALA and/or FAC was measured. Cell phantoms containing glioblastoma cells and Wistar rats bearing C6 glioblastoma were imaged using a 3 T MRI scanner after sequential administration of ALA and FAC. The relaxivity and QSM analysis were performed on the images. RESULTS The intra-cellular iron deposition was significantly higher in the glioma cells with sequential treatment of ALA and FAC for 6 h compared to those treated with the controls. The relaxivity and magnetic susceptibility values of the glioblastoma cells and rat brain tumors treated with ALA + FAC (115 ± 5 s-1 for R2', and 0.1 ± 0.02 ppm for magnetic susceptibility) were significantly higher than those treated with the controls (55 ± 18 (FAC), 45 ± 15 (ALA) s-1 for R2', p < 0.05, and 0.03 ± 0.03 (FAC), 0.02 ± 0.02 (ALA) ppm for magnetic susceptibility, p < 0.05). DISCUSSION Sequential administration of ALA and iron supplements increases the iron deposition in glioblastoma cells, enabling clinical 3 T MRI to detect GBM using R2' or QSM.
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Affiliation(s)
- Anita Ebrahimpour
- Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Tirgar
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Behnam Hajipour-Verdom
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Ardeshir Abbasi
- Department of Immunology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Mahmoudreza Hadjighassem
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Parviz Abdolmaleki
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Saereh Hosseindoost
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Amir Hossein Javadi
- Department of Neurosurgery, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Hassan Hashemi
- Department of Radiology, Faculty of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Abbas Rahimi Foroushani
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Nader Riyahi Alam
- Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
- Concordia University, PERFORM Center, Montreal, QC, Canada.
| | - Mehdi Khoobi
- Biomaterials Group, The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran.
- Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran.
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18
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Cho J, Nguyen TD, Huang W, Sweeney EM, Luo X, Kovanlikaya I, Zhang S, Gillen KM, Spincemaille P, Gupta A, Gauthier SA, Wang Y. Brain oxygen extraction fraction mapping in patients with multiple sclerosis. J Cereb Blood Flow Metab 2022; 42:338-348. [PMID: 34558996 PMCID: PMC9122515 DOI: 10.1177/0271678x211048031] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
We aimed to demonstrate the feasibility of whole brain oxygen extraction fraction (OEF) mapping for measuring lesion specific and regional OEF abnormalities in multiple sclerosis (MS) patients. In 22 MS patients and 11 healthy controls (HC), OEF and neural tissue susceptibility (χn) maps were computed from MRI multi-echo gradient echo data. In MS patients, 80 chronic active lesions with hyperintense rim on quantitative susceptibility mapping were identified, and the mean OEF and χn within the rim and core were compared using linear mixed-effect model analysis. The rim showed higher OEF and χn than the core: relative to their adjacent normal appearing white matter, OEF contrast = -6.6 ± 7.0% vs. -9.8 ± 7.8% (p < 0.001) and χn contrast = 33.9 ± 20.3 ppb vs. 25.7 ± 20.5 ppb (p = 0.017). Between MS and HC, OEF and χn were compared using a linear regression model in subject-based regions of interest. In the whole brain, compared to HC, MS had lower OEF, 30.4 ± 3.3% vs. 21.4 ± 4.4% (p < 0.001), and higher χn, -23.7 ± 7.0 ppb vs. -11.3 ± 7.7 ppb (p = 0.018). Our feasibility study suggests that OEF may serve as a useful quantitative marker of tissue oxygen utilization in MS.
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Affiliation(s)
- Junghun Cho
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Weiyuan Huang
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Elizabeth M Sweeney
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Xianfu Luo
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | | | - Shun Zhang
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Kelly M Gillen
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | | | - Ajay Gupta
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Susan A Gauthier
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA.,Department of Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA.,Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA
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19
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Whole-brain 3D mapping of oxygen metabolism using constrained quantitative BOLD. Neuroimage 2022; 250:118952. [PMID: 35093519 PMCID: PMC9007034 DOI: 10.1016/j.neuroimage.2022.118952] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 12/24/2021] [Accepted: 01/25/2022] [Indexed: 12/02/2022] Open
Abstract
Quantitative BOLD (qBOLD) MRI permits noninvasive evaluation of hemodynamic and metabolic states of the brain by quantifying parametric maps of deoxygenated blood volume (DBV) and hemoglobin oxygen saturation level of venous blood (Yv), and along with a measurement of cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO2). The method, thus should have potential to provide important information on many neurological disorders as well as normal cerebral physiology. One major challenge in qBOLD is to separate de-oxyhemoglobin’s contribution to R2′ from other sources modulating the voxel signal, for instance, R2, R2′ from non-heme iron (R′2,nh), and macroscopic magnetic field variations. Further, even with successful separation of the several confounders, it is still challenging to extract DBV and Yv from the heme-originated R2′ because of limited sensitivity of the qBOLD model. These issues, which have not been fully addressed in currently practiced qBOLD methods, have so far precluded 3D whole-brain implementation of qBOLD. Thus, the purpose of this work was to develop a new 3D MRI oximetry technique that enables robust qBOLD parameter mapping across the entire brain. To achieve this goal, we employed a rapid, R2′-sensitive, steady-state 3D pulse sequence (termed ‘AUSFIDE’) for data acquisition, and implemented a prior-constrained qBOLD processing pipeline that exploits a plurality of preliminary parameters obtained via AUSFIDE, along with additionally measured cerebral venous blood volume. Numerical simulations and in vivo studies at 3 T were performed to evaluate the performance of the proposed, constrained qBOLD mapping in comparison to the parent qBOLD method. Measured parameters (Yv, DBV, R′2,nh, nonblood magnetic susceptibility) in ten healthy subjects demonstrate the expected contrast across brain territories, while yielding group-averages of 64.0 ± 2.3 % and 62.2 ± 3.1 % for Yv and 2.8 ± 0.5 % and 1.8 ± 0.4 % for DBV in cortical gray and white matter, respectively. Given the Yv measurements, additionally quantified CBF in seven of the ten study subjects enabled whole-brain 3D CMRO2 mapping, yielding group averages of 134.2 ± 21.1 and 79.4 ± 12.6 µmol/100 g/min for cortical gray and white matter, in good agreement with literature values. The results suggest feasibility of the proposed method as a practical and reliable means for measuring neurometabolic parameters over an extended brain coverage.
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20
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Kothapalli SV, Benzinger TL, Aschenbrenner AJ, Perrin RJ, Hildebolt CF, Goyal MS, Fagan AM, Raichle ME, Morris JC, Yablonskiy DA. Quantitative Gradient Echo MRI Identifies Dark Matter as a New Imaging Biomarker of Neurodegeneration that Precedes Tisssue Atrophy in Early Alzheimer's Disease. J Alzheimers Dis 2022; 85:905-924. [PMID: 34897083 PMCID: PMC8842777 DOI: 10.3233/jad-210503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/27/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Currently, brain tissue atrophy serves as an in vivo MRI biomarker of neurodegeneration in Alzheimer's disease (AD). However, postmortem histopathological studies show that neuronal loss in AD exceeds volumetric loss of tissue and that loss of memory in AD begins when neurons and synapses are lost. Therefore, in vivo detection of neuronal loss prior to detectable atrophy in MRI is essential for early AD diagnosis. OBJECTIVE To apply a recently developed quantitative Gradient Recalled Echo (qGRE) MRI technique for in vivo evaluation of neuronal loss in human hippocampus. METHODS Seventy participants were recruited from the Knight Alzheimer Disease Research Center, representing three groups: Healthy controls [Clinical Dementia Rating® (CDR®) = 0, amyloid β (Aβ)-negative, n = 34]; Preclinical AD (CDR = 0, Aβ-positive, n = 19); and mild AD (CDR = 0.5 or 1, Aβ-positive, n = 17). RESULTS In hippocampal tissue, qGRE identified two types of regions: one, practically devoid of neurons, we designate as "Dark Matter", and the other, with relatively preserved neurons, "Viable Tissue". Data showed a greater loss of neurons than defined by atrophy in the mild AD group compared with the healthy control group; neuronal loss ranged between 31% and 43%, while volume loss ranged only between 10% and 19%. The concept of Dark Matter was confirmed with histopathological study of one participant who underwent in vivo qGRE 14 months prior to expiration. CONCLUSION In vivo qGRE method identifies neuronal loss that is associated with impaired AD-related cognition but is not recognized by MRI measurements of tissue atrophy, therefore providing new biomarkers for early AD detection.
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Affiliation(s)
| | - Tammie L. Benzinger
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Andrew J. Aschenbrenner
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Richard J. Perrin
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Manu S. Goyal
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Anne M. Fagan
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Marcus E. Raichle
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - John C. Morris
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Dmitriy A. Yablonskiy
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
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21
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Kahali S, Raichle ME, Yablonskiy DA. The Role of the Human Brain Neuron-Glia-Synapse Composition in Forming Resting-State Functional Connectivity Networks. Brain Sci 2021; 11:1565. [PMID: 34942867 PMCID: PMC8699258 DOI: 10.3390/brainsci11121565] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 11/17/2022] Open
Abstract
While significant progress has been achieved in studying resting-state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain's cellular constituents remain. Here, we use quantitative Gradient-Recalled Echo (qGRE) MRI for mapping the human brain cellular composition and BOLD (blood-oxygen level-dependent) MRI to explore how the brain cellular constituents relate to resting-state functional networks. Results show that the BOLD signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the between-functional units' connectivity strength is also influenced by the glia and synaptic components of brain tissue cellular constituents. These mechanisms lead to a rather broad distribution of resting-state functional network properties. Visual networks with the highest neuronal density (but lowest density of glial cells and synapses) exhibit the strongest coherence of the BOLD signal as well as the strongest intra-network connectivity. The Default Mode Network (DMN) is positioned near the opposite part of the spectrum with relatively low coherence of the BOLD signal but with a remarkably balanced cellular contents, enabling DMN to have a prominent role in the overall organization of the brain and hierarchy of functional networks.
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Affiliation(s)
- Sayan Kahali
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
| | - Marcus E. Raichle
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
- Department of Neurology, Washington University in Saint Louis, Saint Louis, MO 63110, USA
| | - Dmitriy A. Yablonskiy
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
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22
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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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23
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Yablonskiy DA, Wen J, Kothapalli SVVN, Sukstanskii AL. In vivo evaluation of heme and non-heme iron content and neuronal density in human basal ganglia. Neuroimage 2021; 235:118012. [PMID: 33838265 PMCID: PMC10468262 DOI: 10.1016/j.neuroimage.2021.118012] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 03/24/2021] [Accepted: 03/25/2021] [Indexed: 12/16/2022] Open
Abstract
Non-heme iron is an important element supporting the structure and functioning of biological tissues. Imbalance in non-heme iron can lead to different neurological disorders. Several MRI approaches have been developed for iron quantification relying either on the relaxation properties of MRI signal or measuring tissue magnetic susceptibility. Specific quantification of the non-heme iron can, however, be constrained by the presence of the heme iron in the deoxygenated blood and contribution of cellular composition. The goal of this paper is to introduce theoretical background and experimental MRI method allowing disentangling contributions of heme and non-heme irons simultaneously with evaluation of tissue neuronal density in the iron-rich basal ganglia. Our approach is based on the quantitative Gradient Recalled Echo (qGRE) MRI technique that allows separation of the total R2* metric characterizing decay of GRE signal into tissue-specific (R2t*) and the baseline blood oxygen level-dependent (BOLD) contributions. A combination with the QSM data (also available from the qGRE signal phase) allowed further separation of the tissue-specific R2t* metric in a cell-specific and non-heme-iron-specific contributions. It is shown that the non-heme iron contribution to R2t* relaxation can be described with the previously developed Gaussian Phase Approximation (GPA) approach. qGRE data were obtained from 22 healthy control participants (ages 26-63 years). Results suggest that the ferritin complexes are aggregated in clusters with an average radius about 100nm comprising approximately 2600 individual ferritin units. It is also demonstrated that the concentrations of heme and non-heme iron tend to increase with age. The strongest age effect was seen in the pallidum region, where the highest age-related non-heme iron accumulation was observed.
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Affiliation(s)
- Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States.
| | - Jie Wen
- Department of Radiology, The First Affiliated Hospital of USTC, Hefei, Anhui 230001, China
| | - Satya V V N Kothapalli
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States
| | - Alexander L Sukstanskii
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States
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24
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Brammerloh M, Morawski M, Friedrich I, Reinert T, Lange C, Pelicon P, Vavpetič P, Jankuhn S, Jäger C, Alkemade A, Balesar R, Pine K, Gavriilidis F, Trampel R, Reimer E, Arendt T, Weiskopf N, Kirilina E. Measuring the iron content of dopaminergic neurons in substantia nigra with MRI relaxometry. Neuroimage 2021; 239:118255. [PMID: 34119638 PMCID: PMC8363938 DOI: 10.1016/j.neuroimage.2021.118255] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 06/02/2021] [Accepted: 06/07/2021] [Indexed: 12/19/2022] Open
Abstract
Dopaminergic neurons dominate effective transverse relaxation in nigrosome 1. Ion beam microscopy reveals highest iron concentrations in dopaminergic neurons. Developed biophysical model links MRI parameters to cellular iron content. Ferritin- and neuromelanin-bound iron impact MRI parameters differently. Quantitative MRI provides a potential biomarker of iron in dopaminergic neurons.
In Parkinson’s disease, the depletion of iron-rich dopaminergic neurons in nigrosome 1 of the substantia nigra precedes motor symptoms by two decades. Methods capable of monitoring this neuronal depletion, at an early disease stage, are needed for early diagnosis and treatment monitoring. Magnetic resonance imaging (MRI) is particularly suitable for this task due to its sensitivity to tissue microstructure and in particular, to iron. However, the exact mechanisms of MRI contrast in the substantia nigra are not well understood, hindering the development of powerful biomarkers. In the present report, we illuminate the contrast mechanisms in gradient and spin echo MR images in human nigrosome 1 by combining quantitative 3D iron histology and biophysical modeling with quantitative MRI on post mortem human brain tissue. We show that the dominant contribution to the effective transverse relaxation rate (R2*) in nigrosome 1 originates from iron accumulated in the neuromelanin of dopaminergic neurons. This contribution is appropriately described by a static dephasing approximation of the MRI signal. We demonstrate that the R2* contribution from dopaminergic neurons reflects the product of cell density and cellular iron concentration. These results demonstrate that the in vivo monitoring of neuronal density and iron in nigrosome 1 may be feasible with MRI and provide directions for the development of biomarkers for an early detection of dopaminergic neuron depletion in Parkinson’s disease.
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Affiliation(s)
- Malte Brammerloh
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany.
| | - Markus Morawski
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, Leipzig, 04103, Germany
| | - Isabel Friedrich
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, Leipzig, 04103, Germany
| | - Tilo Reinert
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany
| | - Charlotte Lange
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany
| | - Primož Pelicon
- Jožef Stefan Institute, Jamova 39, Ljubljana SI-1000, Slovenia
| | - Primož Vavpetič
- Jožef Stefan Institute, Jamova 39, Ljubljana SI-1000, Slovenia
| | - Steffen Jankuhn
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, Leipzig, 04103, Germany
| | - Anneke Alkemade
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, Nieuwe Achtergracht 129B, 1001 NK Amsterdam, The Netherlands
| | - Rawien Balesar
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, Nieuwe Achtergracht 129B, 1001 NK Amsterdam, The Netherlands; The Netherlands Institute for Neuroscience, Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands
| | - Kerrin Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany
| | - Filippos Gavriilidis
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany
| | - Enrico Reimer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany
| | - Thomas Arendt
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, Leipzig, 04103, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Center for Cognitive Neuroscience Berlin, Free University Berlin, Habelschwerdter Allee 45, Berlin, 14195, Germany
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25
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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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26
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Liu Y, Ye Q, Zeng F, Jiang X, Cai B, Lv W, Wen J. Library-driven approach for fast implementation of the voxel spread function to correct magnetic field inhomogeneity artifacts for gradient-echo sequences. Med Phys 2021; 48:3714-3720. [PMID: 33914914 DOI: 10.1002/mp.14904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 03/15/2021] [Accepted: 04/12/2021] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Previously developed Voxel Spread Function (VSF) method (Yablonskiy, et al, MRM, 2013;70:1283) provides solution to correct artifacts induced by macroscopic magnetic field inhomogeneity in the images obtained by multi-Gradient-Recalled-Echo (mGRE) techniques. The goal of this study was to develop a library-driven approach for fast VSF implementation. METHODS The VSF approach describes the contribution of the magnetic field inhomogeneity effects on the mGRE signal decay in terms of the F-function calculated from mGRE phase and magnitude images. A pre-calculated library accounting for a variety of background field gradients caused by magnetic field inhomogeneity was used herein to speed up the calculation of F-function. Quantitative R2* maps from the mGRE data collected from two healthy volunteers were generated using the library as validation. RESULTS As compared with direct calculation of the F-function based on a voxel-wise approach, the new library-driven method substantially reduces computational time from several hours to few minutes, while, at the same time, providing similar accuracy of R2* mapping. CONCLUSION The new procedure proposed in this study provides a fast post-processing algorithm that can be incorporated in the quantitative analysis of mGRE data to account for background field inhomogeneity artifacts, thus can facilitate the applications of mGRE-based quantitative techniques in clinical practices.
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Affiliation(s)
- Ying Liu
- Department of Radiology, The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Qiong Ye
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, China
| | - Feiyan Zeng
- Department of Radiology, The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Xiaohua Jiang
- The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Bin Cai
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, USA
| | - Weifu Lv
- Department of Radiology, The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Jie Wen
- Department of Radiology, The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
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27
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Steidle G, Schick F. A new concept for improved quantitative analysis of reversible transverse relaxation in tissues with variable microscopic field distribution. Magn Reson Med 2020; 85:1493-1506. [PMID: 33000529 DOI: 10.1002/mrm.28534] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 09/03/2020] [Accepted: 09/03/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE The intravoxel distribution of the magnetic field strongly influences signal dephasing after RF excitation and the resulting signal decay in gradient echo-based MRI. In this work, several different field distribution models were applied and tested for analysis of microscopic field characteristics within pixels. THEORY A flexible model for improved pixel-wise characterization of the underlying field distribution is introduced. The proposed symmetric alpha-stable (SαS) distribution covers Lorentzian, Gaussian, and intermediate field distributions in a continuous way using a two-parametric (width and shape) function. METHODS The new model was applied on human brain, potatoes (homogeneous isotropic tissue), and stems of pineapple (anisotropic fibrous tissue). Effects of microscopic structure and background gradients on the shape and the widths of the microscopic field distribution were analyzed using gradient echo sampling of the spin echo and multigradient-echo sequences. Effects of non-Lorentzian shapes of microscopic field distributions on the results of common T 2 ∗ measurements with mono-exponential fitting of signal values were tested. RESULTS Many pixels of the examined objects showed field characteristics in between Lorentzian and Gaussian shapes. Microscopic field inhomogeneities caused by microscopic susceptibility effects and background gradients sometimes led to rather Gaussian than Lorentzian field distribution. In cases with nearly Gaussian field distribution, mono-exponential fitting of the signal decay resulted in different T 2 ∗ values, depending on the sampling points. CONCLUSIONS Using the concept of more flexible distributions for characterization of microscopic susceptibility effects in tissue provides better fitting of data and nearly sampling point-independent results than common T 2 ∗ measurements with mono-exponential fitting.
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Affiliation(s)
- Günter Steidle
- Section of Experimental Radiology, Department of Diagnostic and Interventional Radiology, Universitätsklinikum Tübingen, Tübingen, Germany
| | - Fritz Schick
- Section of Experimental Radiology, Department of Diagnostic and Interventional Radiology, Universitätsklinikum Tübingen, Tübingen, Germany
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28
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Torop M, Kothapalli SVVN, Sun Y, Liu J, Kahali S, Yablonskiy DA, Kamilov US. Deep learning using a biophysical model for robust and accelerated reconstruction of quantitative, artifact-free and denoised R 2 * images. Magn Reson Med 2020; 84:2932-2942. [PMID: 32767489 DOI: 10.1002/mrm.28344] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2020] [Revised: 05/12/2020] [Accepted: 05/13/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To introduce a novel deep learning method for Robust and Accelerated Reconstruction (RoAR) of quantitative and B0-inhomogeneity-corrected R 2 * maps from multi-gradient recalled echo (mGRE) MRI data. METHODS RoAR trains a convolutional neural network (CNN) to generate quantitative R 2 ∗ maps free from field inhomogeneity artifacts by adopting a self-supervised learning strategy given (a) mGRE magnitude images, (b) the biophysical model describing mGRE signal decay, and (c) preliminary-evaluated F-function accounting for contribution of macroscopic B0 field inhomogeneities. Importantly, no ground-truth R 2 * images are required and F-function is only needed during RoAR training but not application. RESULTS We show that RoAR preserves all features of R 2 * maps while offering significant improvements over existing methods in computation speed (seconds vs. hours) and reduced sensitivity to noise. Even for data with SNR = 5 RoAR produced R 2 * maps with accuracy of 22% while voxel-wise analysis accuracy was 47%. For SNR = 10 the RoAR accuracy increased to 17% vs. 24% for direct voxel-wise analysis. CONCLUSIONS RoAR is trained to recognize the macroscopic magnetic field inhomogeneities directly from the input magnitude-only mGRE data and eliminate their effect on R 2 ∗ measurements. RoAR training is based on the biophysical model and does not require ground-truth R 2 * maps. Since RoAR utilizes signal information not just from individual voxels but also accounts for spatial patterns of the signals in the images, it reduces the sensitivity of R 2 * maps to the noise in the data. These features plus high computational speed provide significant benefits for the potential usage of RoAR in clinical settings.
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Affiliation(s)
- Max Torop
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Yu Sun
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Jiaming Liu
- Department of Electrical and Systems Engineering, University in St. Louis, St. Louis, MO, USA
| | - Sayan Kahali
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Ulugbek S Kamilov
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, USA.,Department of Electrical and Systems Engineering, University in St. Louis, St. Louis, MO, USA
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29
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Kaczmarz S, Hyder F, Preibisch C. Oxygen extraction fraction mapping with multi-parametric quantitative BOLD MRI: Reduced transverse relaxation bias using 3D-GraSE imaging. Neuroimage 2020; 220:117095. [PMID: 32599265 PMCID: PMC7730517 DOI: 10.1016/j.neuroimage.2020.117095] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 06/11/2020] [Accepted: 06/18/2020] [Indexed: 01/22/2023] Open
Abstract
Magnetic resonance imaging (MRI)-based quantification of the blood-oxygenation-level-dependent (BOLD) effect allows oxygen extraction fraction (OEF) mapping. The multi-parametric quantitative BOLD (mq-BOLD) technique facilitates relative OEF (rOEF) measurements with whole brain coverage in clinically applicable scan times. Mq-BOLD requires three separate scans of cerebral blood volume and transverse relaxation rates measured by gradient-echo (1/T2*) and spin-echo (1/T2). Although the current method is of clinical merit in patients with stroke, glioma and internal carotid artery stenosis (ICAS), there are relaxation measurement artefacts that impede the sensitivity of mq-BOLD and artificially elevate reported rOEF values. We posited that T2-related biases caused by slice refocusing imperfections during rapid 2D-GraSE (Gradient and Spin Echo) imaging can be reduced by applying 3D-GraSE imaging sequences, because the latter requires no slice selective pulses. The removal of T2-related biases would decrease overestimated rOEF values measured by mq-BOLD. We characterized effects of T2-related bias in mq-BOLD by comparing the initially employed 2D-GraSE and two proposed 3D-GraSE sequences to multiple single spin-echo reference measurements, both in vitro and in vivo. A phantom and 25 participants, including young and elderly healthy controls as well as ICAS-patients, were scanned. We additionally proposed a procedure to reliably identify and exclude artefact affected voxels. In the phantom, 3D-GraSE derived T2 values had 57% lower deviation from the reference. For in vivo scans, the formerly overestimated rOEF was reduced by −27% (p < 0.001). We obtained rOEF = 0.51, which is much closer to literature values from positron emission tomography (PET) measurements. Furthermore, increased sensitivity to a focal rOEF elevation in an ICAS-patient was demonstrated. In summary, the application of 3D-GraSE improves the mq-BOLD-based rOEF quantification while maintaining clinically feasible scan times. Thus, mq-BOLD with non-slice selective T2 imaging is highly promising to improve clinical diagnostics of cerebrovascular diseases such as ICAS.
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Affiliation(s)
- Stephan Kaczmarz
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Departments of Radiology & Biomedical Imaging and of Biomedical Engineering, Magnetic Resonance Research Center, Yale University, New Haven, CT, 06520, USA; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Munich, Germany.
| | - Fahmeed Hyder
- Departments of Radiology & Biomedical Imaging and of Biomedical Engineering, Magnetic Resonance Research Center, Yale University, New Haven, CT, 06520, USA
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Neurology, Munich, Germany
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30
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Xiang B, Wen J, Lu HC, Schmidt RE, Yablonskiy DA, Cross AH. In vivo evolution of biopsy-proven inflammatory demyelination quantified by R2t* mapping. Ann Clin Transl Neurol 2020; 7:1055-1060. [PMID: 32367692 PMCID: PMC7317639 DOI: 10.1002/acn3.51052] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/22/2020] [Accepted: 04/10/2020] [Indexed: 11/09/2022] Open
Abstract
A 35‐year‐old man with an enhancing tumefactive brain lesion underwent biopsy, revealing inflammatory demyelination. We used quantitative Gradient‐Recalled‐Echo (qGRE) MRI to visualize and measure tissue damage in the lesion. Two weeks after biopsy, qGRE showed significant R2t* reduction in the left optic radiation and surrounding tissue, consistent with the histopathological and clinical findings. qGRE was repeated 6 and 14 months later, demonstrating partially recovered optic radiation R2t*, in concert with improvement of the hemianopia to ultimately involve only the lower right visual quadrant. These results support qGRE metrics as in vivo biomarkers for tissue damage and longitudinal monitoring of demyelinating disease.
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Affiliation(s)
- Biao Xiang
- Department of Radiology, Washington University, St. Louis, Missouri, 63110
| | - Jie Wen
- Department of Radiology, Washington University, St. Louis, Missouri, 63110
| | - Hsiang-Chih Lu
- Department of Pathology & Immunology, Washington University, St. Louis, Missouri, 63110
| | - Robert E Schmidt
- Department of Pathology & Immunology, Washington University, St. Louis, Missouri, 63110
| | | | - Anne H Cross
- Department of Neurology, Washington University, St. Louis, Missouri, 63110
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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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Astafiev SV, Wen J, Brody DL, Cross AH, Anokhin AP, Zinn KL, Corbetta M, Yablonskiy DA. A Novel Gradient Echo Plural Contrast Imaging Method Detects Brain Tissue Abnormalities in Patients With TBI Without Evident Anatomical Changes on Clinical MRI: A Pilot Study. Mil Med 2019; 184:218-227. [PMID: 30901451 DOI: 10.1093/milmed/usy394] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 10/10/2018] [Accepted: 11/21/2018] [Indexed: 01/06/2023] Open
Abstract
RESEARCH OBJECTIVES It is widely accepted that mild traumatic brain injury (mTBI) causes injury to the white matter, but the extent of gray matter (GM) damage in mTBI is less clear. METHODS We tested 26 civilian healthy controls and 14 civilian adult subacute-chronic mTBI patients using quantitative features of MRI-based Gradient Echo Plural Contrast Imaging (GEPCI) technique. GEPCI data were reconstructed using previously developed algorithms allowing the separation of R2t*, a cellular-specific part of gradient echo MRI relaxation rate constant, from global R2* affected by BOLD effect and background gradients. RESULTS Single-subject voxel-wise analysis (comparing each mTBI patient to the sample of 26 control subjects) revealed GM abnormalities that were not visible on standard MRI images (T1w and T2w). Analysis of spatial overlap for voxels with low R2t* revealed tissue abnormalities in multiple GM regions, especially in the frontal and temporal regions, that are frequently damaged after mTBI. The left posterior insula was the region with abnormalities found in the highest proportion (50%) of mTBI patients. CONCLUSIONS Our data suggest that GEPCI quantitative R2t* metric has potential to detect abnormalities in GM cellular integrity in individual TBI patients, including abnormalities that are not detectable by a standard clinical MRI.
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Affiliation(s)
- Serguei V Astafiev
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO.,Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8134, St. Louis, MO
| | - Jie Wen
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO
| | - David L Brody
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8111, St. Louis, MO.,Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD
| | - Anne H Cross
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8111, St. Louis, MO
| | - Andrey P Anokhin
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8134, St. Louis, MO
| | - Kristina L Zinn
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8111, St. Louis, MO
| | - Maurizio Corbetta
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8111, St. Louis, MO.,Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Palazzina Neuroscienze, Via Giustiniani, 2, Padova, Italy
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO
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Papazoglou S, Streubel T, Ashtarayeh M, Pine KJ, Edwards LJ, Brammerloh M, Kirilina E, Morawski M, Jäger C, Geyer S, Callaghan MF, Weiskopf N, Mohammadi S. Biophysically motivated efficient estimation of the spatially isotropic R 2 * component from a single gradient-recalled echo measurement. Magn Reson Med 2019; 82:1804-1811. [PMID: 31293007 PMCID: PMC6771860 DOI: 10.1002/mrm.27863] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 05/03/2019] [Accepted: 05/25/2019] [Indexed: 01/29/2023]
Abstract
Purpose To propose and validate an efficient method, based on a biophysically motivated signal model, for removing the orientation‐dependent part of R2* using a single gradient‐recalled echo (GRE) measurement. Methods The proposed method utilized a temporal second‐order approximation of the hollow‐cylinder‐fiber model, in which the parameter describing the linear signal decay corresponded to the orientation‐independent part of R2*. The estimated parameters were compared to the classical, mono‐exponential decay model for R2* in a sample of an ex vivo human optic chiasm (OC). The OC was measured at 16 distinct orientations relative to the external magnetic field using GRE at 7T. To show that the proposed signal model can remove the orientation dependence of R2*, it was compared to the established phenomenological method for separating R2* into orientation‐dependent and ‐independent parts. Results Using the phenomenological method on the classical signal model, the well‐known separation of R2* into orientation‐dependent and ‐independent parts was verified. For the proposed model, no significant orientation dependence in the linear signal decay parameter was observed. Conclusions Since the proposed second‐order model features orientation‐dependent and ‐independent components at distinct temporal orders, it can be used to remove the orientation dependence of R2* using only a single GRE measurement.
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Affiliation(s)
- Sebastian Papazoglou
- Department of Systems NeurosciencesUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Tobias Streubel
- Department of Systems NeurosciencesUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Mohammad Ashtarayeh
- Department of Systems NeurosciencesUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Kerrin J. Pine
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Luke J. Edwards
- Department of Systems NeurosciencesUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Malte Brammerloh
- Department of Systems NeurosciencesUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Evgeniya Kirilina
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Neurocomputation and Neuroimaging Unit, Department of Education and PsychologyFreie Universität BerlinBerlinGermany
| | - Markus Morawski
- Paul Flechsig Institute of Brain ResearchUniversity of LeipzigLeipzigGermany
| | - Carsten Jäger
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Stefan Geyer
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Martina F. Callaghan
- Wellcome Centre for Human NeuroimagingUCL Institute of NeurologyLondonUnited Kingdom
| | - Nikolaus Weiskopf
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Siawoosh Mohammadi
- Department of Systems NeurosciencesUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
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Hubertus S, Thomas S, Cho J, Zhang S, Wang Y, Schad LR. Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD. Magn Reson Med 2019; 82:2199-2211. [PMID: 31273828 DOI: 10.1002/mrm.27882] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 05/28/2019] [Accepted: 06/05/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-Newton (QN) method for numerical optimization. METHODS Random combinations of OEF, deoxygenated blood volume ( ν ), R2 , and nonblood magnetic susceptibility ( χ nb ) with each parameter following a Gaussian distribution that represented physiological gray matter and white matter values were used to simulate quantitative BOLD signals and QSM values. An ANN was trained with the simulated data with added Gaussian noise. The ANN was applied to multigradient echo brain data of 7 healthy subjects, and the reconstructed parameters and maps were compared to QN results using Student t test and Bland-Altman analysis. RESULTS Intersubject means and SDs of gray matter were OEF = 43.5 ± 0.8 %, R 2 = 13.5 ± 0.3 Hz, ν = 3.4 ± 0.1 %, χ nb = - 25 ± 5 ppb for ANN; and OEF = 43.8 ± 5.2 %, R 2 = 12.2 ± 0.8 Hz, ν = 4.2 ± 0.6 %, χ nb = - 39 ± 7 ppb for QN, with a significant difference ( P < 0.05 ) for R 2 , ν , and χ nb . For white matter, they were OEF = 47.5 ± 1.1 %, R 2 = 17.1 ± 0.4 Hz, ν = 2.5 ± 0.2 %, χ nb = - 38 ± 5 ppb for ANN; and OEF = 42.3 ± 5.6 %, R 2 = 16.7 ± 0.7 Hz, ν = 2.9 ± 0.3 %, χ nb = - 45 ± 9 ppb for QN, with a significant difference ( P < 0.05 ) for OEF and ν . ANN revealed more gray-white matter contrast but less intersubject variation in OEF than QN. In contrast to QN, the ANN reconstruction did not need an additional sequence for parameter initialization and took approximately 1 s rather than roughly 1 h. CONCLUSION ANNs allow faster and, with regard to initialization, more robust reconstruction of OEF maps with lower intersubject variation than QN approaches.
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Affiliation(s)
- Simon Hubertus
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sebastian Thomas
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Junghun Cho
- Department of Biomedical Engineering, Cornell University, Ithaca, New York
| | - Shun Zhang
- Department of Radiology, Weill Cornell Medical College, New York, New York.,Department of Radiology, Tongji Hospital, Wuhan, China
| | - Yi Wang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York.,Department of Radiology, Weill Cornell Medical College, New York, New York
| | - Lothar Rudi Schad
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Abstract
The authors selected some interesting current topics among many in the field of functional MRI (fMRI) of the brain. The selection was based on authours' immediate interests in exploring these aspects further; the topics are presented and discussed along with their perspectives. If progress can be made in these areas, it would be very advantageous to the field of brain research. The topics are (I) Detectable MRI signals in response to functional activity of the brain, including the current status of neurocurrent MRI; (II) Vascular-dependent and vascular-independent MRI signals, leading to the distinction of functional and structural MRI; (III) Functional specificity and functional connectivity of local sites, including differences between task-fMRI and resting state fMRI; (IV) Functional networks: an example of application to assessing the vocational aptitude test by fMRI; (V) Neural oscillation relevant to the formation of fMRI signals and of networks; (VI) Upgrading fMRI to "information-content-reflecting" fMRI, discussed as one of the prospects of near-future fMRI.
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Pur DR, Eagleson RA, de Ribaupierre A, Mella N, de Ribaupierre S. Moderating Effect of Cortical Thickness on BOLD Signal Variability Age-Related Changes. Front Aging Neurosci 2019; 11:46. [PMID: 30914944 PMCID: PMC6422923 DOI: 10.3389/fnagi.2019.00046] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2018] [Accepted: 02/18/2019] [Indexed: 11/13/2022] Open
Abstract
The time course of neuroanatomical structural and functional measures across the lifespan is commonly reported in association with aging. Blood oxygen-level dependent signal variability, estimated using the standard deviation of the signal, or "BOLDSD," is an emerging metric of variability in neural processing, and has been shown to be positively correlated with cognitive flexibility. Generally, BOLDSD is reported to decrease with aging, and is thought to reflect age-related cognitive decline. Additionally, it is well established that normative aging is associated with structural changes in brain regions, and that these predict functional decline in various cognitive domains. Nevertheless, the interaction between alterations in cortical morphology and BOLDSD changes has not been modeled quantitatively. The objective of the current study was to investigate the influence of cortical morphology metrics [i.e., cortical thickness (CT), gray matter (GM) volume, and cortical area (CA)] on age-related BOLDSD changes by treating these cortical morphology metrics as possible physiological confounds using linear mixed models. We studied these metrics in 28 healthy older subjects scanned twice at approximately 2.5 years interval. Results show that BOLDSD is confounded by cortical morphology metrics. Respectively, changes in CT but not GM volume nor CA, show a significant interaction with BOLDSD alterations. Our study highlights that CT changes should be considered when evaluating BOLDSD alternations in the lifespan.
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Affiliation(s)
- Daiana R. Pur
- School of Biomedical Engineering, Western University, London, ON, Canada
| | - Roy A. Eagleson
- School of Biomedical Engineering, Western University, London, ON, Canada
- Department of Electrical and Computer Engineering, Western University, London, ON, Canada
| | | | - Nathalie Mella
- Department of Psychology, University of Geneva, Geneva, Switzerland
| | - Sandrine de Ribaupierre
- School of Biomedical Engineering, Western University, London, ON, Canada
- Department of Clinical Neurological Sciences, Schulich School of Medicine, Western University, London, ON, Canada
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Ruuth R, Kuusela L, Mäkelä T, Melkas S, Korvenoja A. Comparison of reconstruction and acquisition choices for quantitative T2* maps and synthetic contrasts. Eur J Radiol Open 2019; 6:42-48. [PMID: 30619919 PMCID: PMC6314103 DOI: 10.1016/j.ejro.2018.12.006] [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] [Received: 08/10/2018] [Revised: 12/19/2018] [Accepted: 12/19/2018] [Indexed: 11/23/2022] Open
Abstract
Phase images have artifacts if reconstructed with a vendor’s sum of squares mode. Quantitative T2* values can be obtained from DICOM data instead of k-space data. Reconstruction from DICOM data does not reduce white matter/gray matter contrast.
Aim and scope A Gradient Echo Plural Contrast Imaging technique (GEPCI) is a post-processing method, which can be used to obtain quantitative T2* values and generate multiple synthetic contrasts from a single acquisition. However, scan duration and image reconstruction from k-space data present challenges in a clinical workflow. This study aimed at optimizing image reconstruction and acquisition duration to facilitate a post-processing method for synthetic image contrast creation in clinical settings. Materials and methods This study consists of tests using the American College of Radiology (ACR) image quality phantom, two healthy volunteers, four mild traumatic brain injury patients and four small vessel disease patients. The measurements were carried out on a 3.0 T scanner with multiple echo times. Reconstruction from k-space data and DICOM data with two different coil-channel combination modes were investigated. Partial Fourier techniques were tested to optimize the scanning time. Conclusions Sum of squares coil-channel combination produced artifacts in phase images, but images created with adaptive combination were artifact-free. The voxel-wise median signed difference of T2* between the vendor’s adaptive channel combination and k-space reconstruction modes was 2.9 ± 0.7 ms for white matter and 4.5 ± 0.6 ms for gray matter. Relative white matter/gray matter contrast of all synthetic images and contrast-to-noise ratio of synthetic T1-weighted images were almost equal between reconstruction modes. Our results indicate that synthetic contrasts can be generated from the vendor’s DICOM data with the adaptive combination mode without affecting the quantitative T2* values or white matter/gray matter contrast.
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Affiliation(s)
- Riikka Ruuth
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland
- Department of Physics, Faculty of Science, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland
- Corresponding author at: HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland.
| | - Linda Kuusela
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland
- Department of Physics, Faculty of Science, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland
| | - Teemu Mäkelä
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland
- Department of Physics, Faculty of Science, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland
| | - Susanna Melkas
- Clinical Neurosciences, Neurology, University of Helsinki and Helsinki University Hospital, P.O. Box 302, FI-00029, HUS, Finland
| | - Antti Korvenoja
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland
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Harris RJ, Yao J, Chakhoyan A, Raymond C, Leu K, Liau LM, Nghiemphu PL, Lai A, Salamon N, Pope WB, Cloughesy TF, Ellingson BM. Simultaneous pH-sensitive and oxygen-sensitive MRI of human gliomas at 3 T using multi-echo amine proton chemical exchange saturation transfer spin-and-gradient echo echo-planar imaging (CEST-SAGE-EPI). Magn Reson Med 2018; 80:1962-1978. [PMID: 29626359 PMCID: PMC6107417 DOI: 10.1002/mrm.27204] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/05/2018] [Accepted: 03/11/2018] [Indexed: 01/09/2023]
Abstract
PURPOSE To introduce a new pH-sensitive and oxygen-sensitive MRI technique using amine proton CEST echo spin-and-gradient echo (SAGE) EPI (CEST-SAGE-EPI). METHODS pH-weighting was obtained using CEST estimations of magnetization transfer ratio asymmetry (MTRasym ) at 3 ppm, and oxygen-weighting was obtained using R2' measurements. Glutamine concentration, pH, and relaxation rates were varied in phantoms to validate simulations and estimate relaxation rates. The values of MTRasym and R2' in normal-appearing white matter, T2 hyperintensity, contrast enhancement, and macroscopic necrosis were measured in 47 gliomas. RESULTS Simulation and phantom results confirmed an increase in MTRasym with decreasing pH. The CEST-SAGE-EPI estimates of R2 , R2*, and R2' varied linearly with gadolinium diethylenetriamine penta-acetic acid concentration (R2 = 6.2 mM-1 ·sec-1 and R2* = 6.9 mM-1 ·sec-1 ). The CEST-SAGE-EPI and Carr-Purcell-Meiboom-Gill estimates of R2 (R2 = 0.9943) and multi-echo gradient-echo estimates of R2* (R2 = 0.9727) were highly correlated. T2 lesions had lower R2' and higher MTRasym compared with normal-appearing white matter, suggesting lower hypoxia and high acidity, whereas contrast-enhancement tumor regions had elevated R2' and MTRasym , indicating high hypoxia and acidity. CONCLUSION The CEST-SAGE-EPI technique provides simultaneous pH-sensitive and oxygen-sensitive image contrasts for evaluation of the brain tumor microenvironment. Advantages include fast whole-brain acquisition, in-line B0 correction, and simultaneous estimation of CEST effects, R2 , R2*, and R2' at 3 T.
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Affiliation(s)
- Robert J. Harris
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA
| | - Ararat Chakhoyan
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Kevin Leu
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Linda M. Liau
- UCLA Brain Research Institute (BRI), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Phioanh L. Nghiemphu
- Dept. of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Albert Lai
- Dept. of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- UCLA Brain Research Institute (BRI), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Noriko Salamon
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Whitney B. Pope
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Timothy F. Cloughesy
- Dept. of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- UCLA Brain Research Institute (BRI), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
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Microstructural imaging of human neocortex in vivo. Neuroimage 2018; 182:184-206. [DOI: 10.1016/j.neuroimage.2018.02.055] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 02/13/2018] [Accepted: 02/26/2018] [Indexed: 12/12/2022] Open
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Abstract
fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI. Herein we investigate these questions by using a multimodality approach that includes quantitative gradient recalled echo (qGRE), volumetric and functional connectivity MRI, and gene expression data from the Allen Human Brain Atlas. We demonstrate that in vivo measurement of the major baseline component of a GRE signal decay rate parameter (R2t*) provides a unique genetic perspective into the cellular constituents of the human cortex and serves as a previously unidentified link between cortical tissue composition and fMRI signal. Data show that areas of the brain cortex characterized by higher R2t* have high neuronal density and have stronger functional connections to other brain areas. Interestingly, these areas have a relatively smaller concentration of synapses and glial cells, suggesting that myelinated cortical axons are likely key cortical structures that contribute to functional connectivity. Given these associations, R2t* is expected to be a useful signal in assessing microstructural changes in the human brain during development and aging in health and disease.
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Xiang B, Wen J, Cross AH, Yablonskiy DA. Single scan quantitative gradient recalled echo MRI for evaluation of tissue damage in lesions and normal appearing gray and white matter in multiple sclerosis. J Magn Reson Imaging 2018; 49:487-498. [PMID: 30155934 DOI: 10.1002/jmri.26218] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 05/22/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Multiple sclerosis (MS) is a chronic disease affecting the human central nervous system (CNS) and leading to neurologic disability. Although conventional MRI techniques can readily detect focal white matter (WM) lesions, it remains challenging to quantify tissue damage in normal-appearing gray matter (GM) and WM. PURPOSE To demonstrate that a new MRI biomarker, R2t*, can provide quantitative analysis of tissue damage across the brain in MS patients in a single scan. STUDY TYPE Prospective. SUBJECTS Forty-four MS patients and 19 healthy controls (HC). FIELD STRENGTH/SEQUENCE 3T, quantitative gradient-recalled-echo (qGRE), Magnetization-prepared rapid gradient-echo, fluid-attenuated inversion recovery. ASSESSMENT Severity of tissue damage was assessed by reduced R2t*. Tissue atrophy was assessed by cortical thickness and cervical spinal cord cross-sectional area (CSA). Multiple Sclerosis Functional Composite was used for clinical assessment. RESULTS R2t* in cortical GM was more sensitive to MS damage than cortical atrophy. Using more than two standard deviations (SD) reduction versus age-matched HC as the cutoff, 48% of MS patients showed lower R2t*, versus only 9% with lower cortical thickness. Significant correlations between severities of tissue injury were identified among 1) upper cervical cord and several cortical regions, including motor cortex (P < 0.001), and 2) adjacent regions of GM and subcortical WM (P < 0.001). R2t*-defined tissue cellular damage in cortical GM was greater relative to adjacent WM. Reductions in cortical R2t* correlated with cognitive impairment (P < 0.01). Motor-related clinical signs correlated most with cervical cord CSA (P < 0.001). DATA CONCLUSION Reductions in R2t* within cortical GM was more sensitive to tissue damage than atrophy, potentially allowing a reduced sample size in clinical trials. R2t* together with structural morphometry suggested topographic patterns of regions showing correlated tissue damage throughout the brain and the cervical spinal cord of MS patients. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:487-498.
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Affiliation(s)
- Biao Xiang
- Department of Chemistry, Washington University, St. Louis, Missouri, USA
| | - Jie Wen
- Department of Radiology, Washington University, St. Louis, Missouri, USA
| | - Anne H Cross
- Department of Neurology, Washington University, St. Louis, Missouri, 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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Vessel radius mapping in an extended model of transverse relaxation. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2018; 31:531-551. [DOI: 10.1007/s10334-018-0677-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Revised: 01/14/2018] [Accepted: 01/15/2018] [Indexed: 10/18/2022]
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Wen J, Yablonskiy DA, Salter A, Cross AH. Limbic system damage in MS: MRI assessment and correlations with clinical testing. PLoS One 2017; 12:e0187915. [PMID: 29121642 PMCID: PMC5679614 DOI: 10.1371/journal.pone.0187915] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 10/27/2017] [Indexed: 12/21/2022] Open
Abstract
Volume loss in some limbic region structures has been observed in multiple sclerosis (MS) patients. However, in vivo evaluation of existing tissue cellular microstructure integrity has received less attention. The goal of studies reported here was to quantitatively assess loss of limbic system volumes and tissue integrity, and to evaluate associations of these measures with cognitive and physical dysfunction in MS patients. Thirty-one healthy controls (HC) and 80 MS patients, including 32 relapsing remitting (RRMS), 32 secondary progressive (SPMS) and 16 primary progressive (PPMS), participated in this study. Tissue cellular integrity was evaluated by means of recently introduced tissue-specific parameter R2t* that was calculated from multi-gradient-echo MRI signals using a recently developed method that separates R2t* from BOLD (blood oxygen level dependent) contributions to GRE signal decay rate constant (R2*), and accounting for physiological fluctuations and artifacts from background gradients. Volumes in limbic system regions, normalized to skull size (NV), were measured from standard MPRAGE images. MS patients had lower R2t* and smaller normalized volumes in the hippocampus, amygdala, and several other limbic system regions, compared to HC. Alterations in R2t* of several limbic system regions correlated with clinical and neurocognitive test scores in MS patients. In contrast, smaller normalized volumes in MS were only correlated with neurocognitive test scores in the hippocampus and amygdala. This study reports the novel finding that R2t*, a measure that estimates tissue integrity, is more sensitive to tissue damage in limbic system structures than is atrophy. R2t* measurements can serve as a biomarker that is distinct from and complementary to volume measurements.
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Affiliation(s)
- Jie Wen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Dmitriy A. Yablonskiy
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Amber Salter
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Anne H. Cross
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States of America
- * E-mail:
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45
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Niesporek SC, Umathum R, Lommen JM, Behl NG, Paech D, Bachert P, Ladd ME, Nagel AM. Reproducibility of CMRO2determination using dynamic17O MRI. Magn Reson Med 2017; 79:2923-2934. [DOI: 10.1002/mrm.26952] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Revised: 09/07/2017] [Accepted: 09/10/2017] [Indexed: 12/15/2022]
Affiliation(s)
- Sebastian C. Niesporek
- Division of Medical Physics in Radiology; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - Reiner Umathum
- Division of Medical Physics in Radiology; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - Jonathan M. Lommen
- Division of Medical Physics in Radiology; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - Nicolas G.R. Behl
- Division of Medical Physics in Radiology; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - Daniel Paech
- Division of Radiology; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology; German Cancer Research Center (DKFZ); Heidelberg Germany
- Faculty of Physics and Astronomy; University of Heidelberg; Heidelberg Germany
| | - Mark E. Ladd
- Division of Medical Physics in Radiology; German Cancer Research Center (DKFZ); Heidelberg Germany
- Faculty of Physics and Astronomy; University of Heidelberg; Heidelberg Germany
- Faculty of Medicine; University of Heidelberg; Heidelberg Germany
| | - Armin M. Nagel
- Division of Medical Physics in Radiology; German Cancer Research Center (DKFZ); Heidelberg Germany
- Institute of Radiology; University Hospital Erlangen; Erlangen Germany
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Zhang J, Cho J, Zhou D, Nguyen TD, Spincemaille P, Gupta A, Wang Y. Quantitative susceptibility mapping-based cerebral metabolic rate of oxygen mapping with minimum local variance. Magn Reson Med 2017; 79:172-179. [PMID: 28295523 DOI: 10.1002/mrm.26657] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2016] [Revised: 01/05/2017] [Accepted: 02/03/2017] [Indexed: 12/14/2022]
Abstract
PURPOSE The objective of this study was to demonstrate the feasibility of a cerebral metabolic rate of oxygen (CMRO2 ) mapping method based on its minimum local variance (MLV) without vascular challenge using quantitative susceptibility mapping (QSM) and cerebral blood flow (CBF). METHODS Three-dimensional multi-echo gradient echo imaging and arterial spin labeling were performed in 11 healthy subjects to calculate QSM and CBF. Minimum local variance was used to compute whole-brain CMRO2 map from QSM and CBF. The MLV method was compared with a reference method using the caffeine challenge. Their agreement within the cortical gray matter (CGM) was assessed on CMRO2 and oxygen extraction fraction (OEF) maps at both baseline and challenge states. RESULTS Mean CMRO2 (in µmol/100 g/min) obtained in CGM using the caffeine challenge and MLV were 142 ± 16.5 and 139 ± 14.8 µmol/100 g/min, respectively; the corresponding baseline OEF were 33.0 ± 4.0% and 31.8 ± 3.2%, respectively. The MLV and caffeine challenge methods showed no statistically significant differences across subjects with small ( < 4%) biases in CMRO2 and OEF values. CONCLUSIONS Minimum local variance-based CMRO2 mapping without vascular challenge using QSM and arterial spin labeling is feasible in healthy subjects. Magn Reson Med 79:172-179, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Jingwei Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Junghun Cho
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Dong Zhou
- 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
| | - Pascal Spincemaille
- 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 Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Cornell Medical College, New York, New York, USA
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Zhao Y, Raichle ME, Wen J, Benzinger TL, Fagan AM, Hassenstab J, Vlassenko AG, Luo J, Cairns NJ, Christensen JJ, Morris JC, Yablonskiy DA. In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging. Neuroimage 2016; 148:296-304. [PMID: 27989773 DOI: 10.1016/j.neuroimage.2016.12.026] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 12/08/2016] [Accepted: 12/10/2016] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Alzheimer disease (AD) affects at least 5 million individuals in the USA alone stimulating an intense search for disease prevention and treatment therapies as well as for diagnostic techniques allowing early identification of AD during a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals. METHODS Our approach to developing such techniques is based on the Gradient Echo Plural Contrast Imaging (GEPCI) technique that provides quantitative in vivo measurements of several brain-tissue-specific characteristics of the gradient echo MRI signal (GEPCI metrics) that depend on the integrity of brain tissue cellular structure. Preliminary data were obtained from 34 participants selected from the studies of aging and dementia at the Knight Alzheimer's Disease Research Center at Washington University in St. Louis. Cognitive status was operationalized with the Clinical Dementia Rating (CDR) scale. The participants, assessed as cognitively normal (CDR=0; n=23) or with mild AD dementia (CDR=0.5 or 1; n=11) underwent GEPCI MRI, a collection of cognitive performance tests and CSF amyloid (Aβ) biomarker Aβ42. A subset of 19 participants also underwent PET PiB studies to assess their brain Aβ burden. According to the Aβ status, cognitively normal participants were divided into normal (Aβ negative; n=13) and preclinical (Aβ positive; n=10) groups. RESULTS GEPCI quantitative measurements demonstrated significant differences between all the groups: normal and preclinical, normal and mild AD, and preclinical and mild AD. GEPCI quantitative metrics characterizing tissue cellular integrity in the hippocampus demonstrated much stronger correlations with psychometric tests than the hippocampal atrophy. Importantly, GEPCI-determined changes in the hippocampal tissue cellular integrity were detected even in the hippocampal areas not affected by the atrophy. Our studies also uncovered strong correlations between GEPCI brain tissue metrics and beta-amyloid (Aβ) burden defined by positron emission tomography (PET) - the current in vivo gold standard for detection of cortical Aβ, thus supporting GEPCI as a potential surrogate marker for Aβ imaging - a known biomarker of early AD. Remarkably, the data show significant correlations not only in the areas of high Aβ accumulation (e.g. precuneus) but also in some areas of medial temporal lobe (e.g. parahippocampal cortex), where Aβ accumulation is relatively low. CONCLUSION We have demonstrated that GEPCI provides a new approach for the in vivo evaluation of AD-related tissue pathology in the preclinical and early symptomatic stages of AD. Since MRI is a widely available technology, the GEPCI surrogate markers of AD pathology have a potential for improving the quality of AD diagnostic, and the evaluation of new disease-modifying therapies.
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Affiliation(s)
- Yue Zhao
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Marcus E Raichle
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jie Wen
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Tammie L Benzinger
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Andrei G Vlassenko
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jie Luo
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Nigel J Cairns
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jon J Christensen
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - John C Morris
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA.
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48
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Zhang J, Zhou D, Nguyen TD, Spincemaille P, Gupta A, Wang Y. Cerebral metabolic rate of oxygen (CMRO2) mapping with hyperventilation challenge using quantitative susceptibility mapping (QSM). Magn Reson Med 2016; 77:1762-1773. [DOI: 10.1002/mrm.26253] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Revised: 03/06/2016] [Accepted: 03/31/2016] [Indexed: 11/09/2022]
Affiliation(s)
- Jingwei Zhang
- Department of Biomedical EngineeringCornell University301 Weill HallIthaca New York, USA
- Department of RadiologyWeill Cornell Medical College515 East 71st St, Suite 104New York, USA
| | - Dong Zhou
- Department of RadiologyWeill Cornell Medical College515 East 71st St, Suite 104New York, USA
| | - Thanh D. Nguyen
- Department of RadiologyWeill Cornell Medical College515 East 71st St, Suite 104New York, USA
| | - Pascal Spincemaille
- Department of RadiologyWeill Cornell Medical College515 East 71st St, Suite 104New York, USA
| | - Ajay Gupta
- Department of RadiologyWeill Cornell Medical College515 East 71st St, Suite 104New York, USA
| | - Yi Wang
- Department of Biomedical EngineeringCornell University301 Weill HallIthaca New York, USA
- Department of RadiologyWeill Cornell Medical College515 East 71st St, Suite 104New York, USA
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Shu CY, Sanganahalli BG, Coman D, Herman P, Hyder F. New horizons in neurometabolic and neurovascular coupling from calibrated fMRI. PROGRESS IN BRAIN RESEARCH 2016; 225:99-122. [PMID: 27130413 DOI: 10.1016/bs.pbr.2016.02.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Neurovascular coupling relates changes in neuronal activity to constriction/dilation of microvessels. However neurometabolic coupling, which is less well known, relates alterations in neuronal activity with metabolic demands. The link between the blood oxygenation level dependent (BOLD) signal and neural activity opened doors for functional MRI (fMRI) to be a powerful neuroimaging tool in the neurosciences. But due to the complex makeup of BOLD contrast, researchers began to investigate the relationship between BOLD signal and blood flow and/or volume changes during functional brain activation, which together provided the tools to measure oxygen consumption on the basis of the biophysical model of BOLD. This field is called calibrated fMRI, thereby allowed probing of both neurometabolic and neurovascular couplings for a variety of health conditions in animals and humans. Calibrated fMRI may provide brain disorder biomarkers that could be used for monitoring effective therapies.
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Affiliation(s)
- C Y Shu
- Yale University, New Haven, CT, United States
| | - B G Sanganahalli
- Yale University, New Haven, CT, United States; Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, United States
| | - D Coman
- Yale University, New Haven, CT, United States; Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, United States
| | - P Herman
- Yale University, New Haven, CT, United States; Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, United States
| | - F Hyder
- Yale University, New Haven, CT, United States; Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, United States.
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Sukstanskii AL, Wen J, Cross AH, Yablonskiy DA. Simultaneous multi-angular relaxometry of tissue with MRI (SMART MRI): Theoretical background and proof of concept. Magn Reson Med 2016; 77:1296-1306. [PMID: 26991525 DOI: 10.1002/mrm.26176] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Revised: 01/29/2016] [Accepted: 01/31/2016] [Indexed: 01/09/2023]
Abstract
PURPOSE Accurate measurement of tissue-specific relaxation parameters is an ultimate goal of quantitative MRI. The objective of this study is to introduce a new technique, simultaneous multiangular relaxometry of tissue with MRI (SMART MRI), which provides naturally coregistered quantitative spin density, longitudinal and transverse relaxation rate constant maps along with parameters characterizing magnetization transfer (MT) effects. THEORY AND METHODS SMART MRI is based on a gradient-recalled echo MRI sequence with multiple flip angles and multiple gradient echoes and a derived theoretical expression for the MR signal generated in this experimental conditions. The theory, based on Bloch-McConnell equations, takes into consideration cross-relaxation between two water pools: "free" and "bound" to macromolecules. It describes the role of cross-relaxation effects in formation of longitudinal and transverse relaxation of "free" water signal, thus providing background for measurements of these effects without using MT pulses. Bayesian analysis is used to optimize SMART MRI sequence parameters. RESULTS Data obtained on three participants demonstrate feasibility of the proposed approach. CONCLUSION SMART MRI provides quantitative measurements of longitudinal and transverse relaxation rate constants of "free" water signal affected by cross-relaxation effects. It also provides information on some essential MT parameters without requiring off-resonance MT pulses. Magn Reson Med 77:1296-1306, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
| | - Jie Wen
- Department of Radiology, Washington University, St. Louis, Missouri, USA
| | - Anne H Cross
- Department of Radiology, Washington University, St. Louis, Missouri, USA
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