1
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Sawan H, Li C, Buch S, Bernitsas E, Haacke EM, Ge Y, Chen Y. Reduced oxygen extraction fraction in deep cerebral veins associated with cognitive impairment in multiple sclerosis. J Cereb Blood Flow Metab 2024; 44:1298-1305. [PMID: 38820447 DOI: 10.1177/0271678x241259551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/02/2024]
Abstract
Studying the relationship between cerebral oxygen utilization and cognitive impairment is essential to understanding neuronal functional changes in the disease progression of multiple sclerosis (MS). This study explores the potential of using venous susceptibility in internal cerebral veins (ICVs) as an imaging biomarker for cognitive impairment in relapsing-remitting MS (RRMS) patients. Quantitative susceptibility mapping derived from fully flow-compensated MRI phase data was employed to directly measure venous blood oxygen saturation levels (SvO2) in the ICVs. Results revealed a significant reduction in the susceptibility of ICVs (212.4 ± 30.8 ppb vs 239.4 ± 25.9 ppb) and a significant increase of SvO2 (74.5 ± 1.89% vs 72.4 ± 2.23%) in patients with RRMS compared with age- and sex-matched healthy controls. Both the susceptibility of ICVs (r = 0.508, p = 0.031) and the SvO2 (r = -0.498, p = 0.036) exhibited a moderate correlation with cognitive decline in these patients assessed by the Paced Auditory Serial Addition Test, while no significant correlation was observed with clinical disability measured by the Expanded Disability Status Scale. The findings suggest that venous susceptibility in ICVs has the potential to serve as a specific indicator of oxygen metabolism and cognitive function in RRMS. .
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Affiliation(s)
- Hasan Sawan
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Chenyang Li
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Sagar Buch
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Evanthia Bernitsas
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - E Mark Haacke
- Department of Radiology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Yulin Ge
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Yongsheng Chen
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
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2
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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. [PMID: 39072791 DOI: 10.1002/mrm.30165] [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: 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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3
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Engle J, Saberi P, Bain P, Ikram A, Selim M, Soman S. Oxygen extraction fraction (OEF) values and applications in neurological diseases. Neurol Sci 2024; 45:3007-3020. [PMID: 38367153 DOI: 10.1007/s10072-024-07362-6] [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: 10/29/2023] [Accepted: 01/22/2024] [Indexed: 02/19/2024]
Abstract
One of the goals of this systematic review is to provide a meta-analysis-derived mean OEF of healthy volunteers. Another aim of this study is to indicate the OEF ranges of various neurological pathologies. Potential clinical applications of OEF metrics are presented. Peer-reviewed studies reporting OEF metrics derived from computed tomography (CT)/positron emission tomography (PET) and/or magnetic resonance imaging (MRI) were considered. Databases utilized included MEDLINE, PubMed, EMBASE, Web of Science, and Google Scholar. The Newcastle-Ottawa scoring system was used for evaluating studies. R Studio was utilized for the meta-analysis calculations when appropriate. The GRADE framework was utilized to assess additional findings. Of 2267 potential studies, 165 met the inclusion criteria. The healthy volunteer meta-analysis included 339 subjects and found a mean OEF value of 38.87 (37.38, 40.36), with a prediction interval of 32.40-45.34. There were no statistical differences in OEF values derived from PET versus MRI. We provided a GRADE A certainty rating for the use of OEF metrics to predict stroke occurrence in patients with symptomatic carotid or cerebral vessel disease. We provided a GRADE B certainty rating for monitoring treatment response in Moyamoya disease. Use of OEF metrics in diagnosing and/or monitoring other conditions had a GRADE C certainty rating or less. OEF might have a role in diagnosing and monitoring patients with symptomatic carotid or cerebral vessel disease and Moyamoya disease. While we found insufficient evidence to support measuring OEF metrics in other patient populations, in many cases, further studies are warranted.
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Affiliation(s)
- Joshua Engle
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA.
| | - Parastoo Saberi
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA
| | - Paul Bain
- Harvard Medical School, Boston, MA, USA
| | - Asad Ikram
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA
| | - Magdy Selim
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA
| | - Salil Soman
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA
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Lee H, Xu J, Fernandez-Seara MA, Wehrli FW. Validation of a new 3D quantitative BOLD based cerebral oxygen extraction mapping. J Cereb Blood Flow Metab 2024; 44:1184-1198. [PMID: 38289876 PMCID: PMC11179617 DOI: 10.1177/0271678x231220332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 10/06/2023] [Accepted: 10/09/2023] [Indexed: 02/01/2024]
Abstract
Quantitative BOLD (qBOLD) MRI allows evaluation of oxidative metabolism of the brain based purely on an endogenous contrast mechanism. The method quantifies deoxygenated blood volume (DBV) and hemoglobin oxygen saturation level of venous blood (Yv), yielding oxygen extraction fraction (OEF), and along with a separate measurement of cerebral blood flow, cerebral metabolic rate of oxygen (CMRO2) maps. Here, we evaluated our recently reported 3D qBOLD method that rectifies a number of deficiencies in prior qBOLD approaches in terms of repeat reproducibility and sensitivity to hypercapnia on the metabolic parameters, and in comparison to dual-gas calibrated BOLD (cBOLD) MRI for determining resting-state oxygen metabolism. Results suggested no significant difference between test-retest qBOLD scans in either DBV and OEF. Exposure to hypercapnia yielded group averages of 38 and 28% for OEF and 151 and 146 µmol/min/100 g for CMRO2 in gray matter at baseline and hypercapnia, respectively. The decrease of OEF during hypercapnia was significant (p ≪ 0.01), whereas CMRO2 did not change significantly (p = 0.25). Finally, baseline OEF (37 vs. 39%) and CMRO2 (153 vs. 145 µmol/min/100 g) in gray matter using qBOLD and dual-gas cBOLD were found to be in good agreement with literature values, and were not significantly different from each other (p > 0.1).
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Affiliation(s)
- Hyunyeol Lee
- School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jing Xu
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Maria A Fernandez-Seara
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Radiology, Clinica Universidad de Navarra, Pamplona, Spain
| | - Felix W Wehrli
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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T AR, K K, Paul JS. Unveiling metabolic patterns in dementia: Insights from high-resolution quantitative blood-oxygenation-level-dependent MRI. Med Phys 2024. [PMID: 38888202 DOI: 10.1002/mp.17173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 04/12/2024] [Accepted: 05/08/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Oxygen extraction fraction (OEF) and deoxyhemoglobin (DoHb) levels reflect variations in cerebral oxygen metabolism in demented patients. PURPOSE Delineating the metabolic profiles evident throughout different phases of dementia necessitates an integrated analysis of OEF and DoHb levels. This is enabled by leveraging high-resolution quantitative blood oxygenation level dependent (qBOLD) analysis of magnitude images obtained from a multi-echo gradient-echo MRI (mGRE) scan performed on a 3.0 Tesla scanner. METHODS Achieving superior spatial resolution in qBOLD necessitates the utilization of an mGRE scan with only four echoes, which in turn limits the number of measurements compared to the parameters within the qBOLD model. Consequently, it becomes imperative to discard non-essential parameters to facilitate further analysis. This process entails transforming the qBOLD model into a format suitable for fitting the log-magnitude difference (L-MDif) profiles of the four echo magnitudes present in each brain voxel. In order to bolster spatial specificity, the log-difference qBOLD model undergoes refinement into a representative form, termed as r-qBOLD, particularly when applied to class-averaged L-MDif signals derived through k-means clustering of L-MDif signals from all brain voxels into a predetermined number of clusters. The agreement between parameters estimated using r-qBOLD for different cluster sizes is validated using Bland-Altman analysis, and the model's goodness-of-fit is evaluated using aχ 2 ${\chi ^2}$ -test. Retrospective MRI data of Alzheimer's disease (AD), mild cognitive impairment (MCI), and non-demented patients without neuropathological disorders, pacemakers, other implants, or psychiatric disorders, who completed a minimum of three visits prior to MRI enrolment, are utilized for the study. RESULTS Utilizing a cohort comprising 30 demented patients aged 65-83 years in stages 4-6 representing mild, moderate, and severe stages according to the clinical dementia rating (CDR), matched with an age-matched non-demented control group of 18 individuals, we conducted joint observations of OEF and DoHb levels estimated using r-qBOLD. The observations elucidate metabolic signatures in dementia based on OEF and DoHb levels in each voxel. Our principal findings highlight the significance of spatial patterns of metabolic profiles (metabolic patterns) within two distinct regimes: OEF levels exceeding the normal range (S1-regime), and OEF levels below the normal range (S2-regime). The S1-regime, accompanied by low DoHb levels, predominantly manifests in fronto-parietal and perivascular regions with increase in dementia severity. Conversely, the S2-regime, accompanied by low DoHb levels, is observed in medial temporal (MTL) regions. Other regions with abnormal metabolic patterns included the orbitofrontal cortex (OFC), medial-orbital prefrontal cortex (MOPFC), hypothalamus, ventro-medial prefrontal cortex (VMPFC), and retrosplenial cortex (RSP). Dysfunction in the OFC and MOPFC indicated cognitive and emotional impairment, while hypothalamic involvement potentially indicated preclinical dementia. Reduced metabolic activity in the RSP suggested early-stage AD related functional abnormalities. CONCLUSIONS Integrated analysis of OEF and DoHb levels using r-qBOLD reveals distinct metabolic signatures across dementia phases, highlighting regions susceptible to neuronal loss, vascular involvement, and preclinical indicators.
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Affiliation(s)
- Arun Raj T
- Division of Medical Informatics, School of Informatics, Kerala University of Digital Sciences Innovation & Technology (DUK), Trivandrum, Kerala, India
| | - Karthik K
- Department of Neuroimaging & Interventional Radiology, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bengaluru, Karnataka, India
| | - Joseph Suresh Paul
- Division of Medical Informatics, School of Informatics, Kerala University of Digital Sciences Innovation & Technology (DUK), Trivandrum, Kerala, India
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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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7
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Sawan H, Li C, Buch S, Bernitsas E, Haacke EM, Ge Y, Chen Y. Reduced Oxygen Extraction Fraction in Deep Cerebral Veins Associated with Cognitive Impairment in Multiple Sclerosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.10.24301049. [PMID: 38260542 PMCID: PMC10802653 DOI: 10.1101/2024.01.10.24301049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Studying the relationship between cerebral oxygen utilization and cognitive impairment is essential to understanding neuronal functional changes in the disease progression of multiple sclerosis (MS). This study explores the potential of using venous susceptibility in internal cerebral veins (ICVs) as an imaging biomarker for cognitive impairment in relapsing-remitting MS (RRMS) patients. Quantitative susceptibility mapping derived from fully flow-compensated MRI phase data was employed to directly measure venous blood oxygen saturation levels (SvO2) in the ICVs. Results revealed a significant reduction in the susceptibility of ICVs (212.4 ± 30.8 ppb vs 239.4 ± 25.9 ppb) and a significant increase of SvO2 (74.5 ± 1.89 % vs 72.4 ± 2.23 %) in patients with RRMS compared with age- and sex-matched healthy controls. Both the susceptibility of ICVs (r = 0.646, p = 0.004) and the SvO2 (r = -0.603, p = 0.008) exhibited a strong correlation with cognitive decline in these patients assessed by the Paced Auditory Serial Addition Test, while no significant correlation was observed with clinical disability measured by the Expanded Disability Status Scale. The findings suggest that venous susceptibility in ICVs has the potential to serve as a specific indicator of oxygen metabolism and cognitive function in RRMS.
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Affiliation(s)
- Hasan Sawan
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Chenyang Li
- Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Sagar Buch
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Evanthia Bernitsas
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - E. Mark Haacke
- Department of Radiology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Yulin Ge
- Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Yongsheng Chen
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
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van Grinsven EE, de Leeuw J, Siero JCW, Verhoeff JJC, van Zandvoort MJE, Cho J, Philippens MEP, Bhogal AA. Evaluating Physiological MRI Parameters in Patients with Brain Metastases Undergoing Stereotactic Radiosurgery-A Preliminary Analysis and Case Report. Cancers (Basel) 2023; 15:4298. [PMID: 37686575 PMCID: PMC10487230 DOI: 10.3390/cancers15174298] [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: 07/12/2023] [Revised: 08/17/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023] Open
Abstract
Brain metastases occur in ten to thirty percent of the adult cancer population. Treatment consists of different (palliative) options, including stereotactic radiosurgery (SRS). Sensitive MRI biomarkers are needed to better understand radiotherapy-related effects on cerebral physiology and the subsequent effects on neurocognitive functioning. In the current study, we used physiological imaging techniques to assess cerebral blood flow (CBF), oxygen extraction fraction (OEF), cerebral metabolic rate of oxygen (CMRO2) and cerebrovascular reactivity (CVR) before and three months after SRS in nine patients with brain metastases. The results showed improvement in OEF, CBF and CMRO2 within brain tissue that recovered from edema (all p ≤ 0.04), while CVR remained impacted. We observed a global post-radiotherapy increase in CBF in healthy-appearing brain tissue (p = 0.02). A repeated measures correlation analysis showed larger reductions within regions exposed to higher radiotherapy doses in CBF (rrm = -0.286, p < 0.001), CMRO2 (rrm = -0.254, p < 0.001), and CVR (rrm = -0.346, p < 0.001), but not in OEF (rrm = -0.004, p = 0.954). Case analyses illustrated the impact of brain metastases progression on the post-radiotherapy changes in both physiological MRI measures and cognitive performance. Our preliminary findings suggest no radiotherapy effects on physiological parameters occurred in healthy-appearing brain tissue within 3-months post-radiotherapy. Nevertheless, as radiotherapy can have late side effects, larger patient samples allowing meaningful grouping of patients and longer follow-ups are needed.
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Affiliation(s)
- Eva E. van Grinsven
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, 3584 CX Utrecht, The Netherlands
| | - Jordi de Leeuw
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (J.d.L.); (A.A.B.)
| | - Jeroen C. W. Siero
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (J.d.L.); (A.A.B.)
- Spinoza Center for Neuroimaging, 1105 BK Amsterdam, The Netherlands
| | - Joost J. C. Verhoeff
- Department of Radiation Oncology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands (M.E.P.P.)
| | - Martine J. E. van Zandvoort
- Department of Neurology & Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, 3584 CX Utrecht, The Netherlands
- Department of Experimental Psychology, Helmholtz Institute, Utrecht University, 3584 CS Utrecht, The Netherlands
| | - Junghun Cho
- Department of Biomedical Engineering, SUNY Buffalo, Buffalo, NY 14228, USA;
| | - Marielle E. P. Philippens
- Department of Radiation Oncology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands (M.E.P.P.)
| | - Alex A. Bhogal
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (J.d.L.); (A.A.B.)
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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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10
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Zhuang H, Cho J, Chiang GCY, Kovanlikaya I, Heier LA, Dyke JP, Wang Y. Cerebral oxygen extraction fraction declines with ventricular enlargement in patients with normal pressure hydrocephalus. Clin Imaging 2023; 97:22-27. [PMID: 36871361 PMCID: PMC10081162 DOI: 10.1016/j.clinimag.2023.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 01/16/2023] [Accepted: 02/02/2023] [Indexed: 02/11/2023]
Abstract
OBJECTIVE Normal pressure hydrocephalus (NPH) is a neurodegenerative disease that is potentially reversible by shunt surgery in approximately 60% of patients. Imaging may provide a means to investigate brain tissue viability and oxygen metabolism in NPH patients. METHODS Oxygen extraction fraction (OEF) mapping was generated from 3D multi-echo gradient echo MRI (mGRE) data using QQ-CCTV algorithm and cerebral blood flow (CBF) using 3D arterial spin labeling (ASL) MRI data, thereby calculating the cerebral metabolic rate of oxygen (CMRO2 = CBF × OEF × [H]a) in 16 NPH patients. Regression analyses using cortical gray matter and deep gray matter regions were conducted with age, gender, CSF stroke volume and normalized ventricular volume as independent variables. RESULTS OEF showed significant negative correlations with normalized brain ventricular volumes in the whole brain (p = 0.004, q = 0.01), cortical gray matter (p = 0.004, q = 0.01), caudate (p = 0.02, q = 0.04), and pallidum (p = 0.03, q = 0.04), but no significant correlation with CSF stroke volume (q > 0.05). There was no significant finding with CBF or CMRO2. CONCLUSION In NPH patients, low OEF in several regions was significantly correlated with large ventricular volumes, indicating decreased tissue oxygen metabolism with increased NPH severity. OEF mapping may provide a functional understanding of neurodegeneration in NPH and may improve monitoring of disease course and treatment outcomes.
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Affiliation(s)
- Hangwei Zhuang
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Junghun Cho
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Gloria Chia-Yi Chiang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Ilhami Kovanlikaya
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Linda Anne Heier
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Jonathan P Dyke
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Yi Wang
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
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11
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Differential regional cerebrovascular reactivity to end-tidal gas combinations commonly seen during anaesthesia: A blood oxygenation level-dependent MRI observational study in awake adult subjects. Ugeskr Laeger 2022; 39:774-784. [PMID: 35852545 DOI: 10.1097/eja.0000000000001716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND Regional cerebrovascular reactivity (rCVR) is highly variable in the human brain as measured by blood oxygenation level-dependent (BOLD) MRI to changes in both end-tidal CO 2 and O 2 . OBJECTIVES We examined awake participants under carefully controlled end-tidal gas concentrations to assess how regional CVR changes may present with end-tidal gas changes seen commonly with anaesthesia. DESIGN Observational study. SETTING Tertiary care centre, Winnipeg, Canada. The imaging for the study occurred in 2019. SUBJECTS Twelve healthy adult subjects. INTERVENTIONS Cerebral BOLD response was studied under two end-tidal gas paradigms. First end-tidal oxygen (ETO 2 ) maintained stable whereas ETCO 2 increased incrementally from hypocapnia to hypercapnia (CO 2 ramp); second ETCO 2 maintained stable whereas ETO 2 increased from normoxia to hyperoxia (O 2 ramp). BOLD images were modeled with end-tidal gas sequences split into two equal segments to examine regional CVR. MAIN OUTCOME MEASURES The voxel distribution comparing hypocapnia to mild hypercapnia and mild hyperoxia (mean F I O 2 = 0.3) to marked hyperoxia (mean F I O 2 = 0.7) were compared in a paired fashion ( P < 0.005 to reach threshold for voxel display). Additionally, type analysis was conducted on CO 2 ramp data. This stratifies the BOLD response to the CO 2 ramp into four categories of CVR slope based on segmentation (type A; +/+slope: normal response, type B +/-, type C -/-: intracranial steal, type D -/+.) Types B to D represent altered responses to the CO 2 stimulus. RESULTS Differential regional responsiveness was seen for both end-tidal gases. Hypocapnic regional CVR was more marked than hypercapnic CVR in 0.3% of voxels examined ( P < 0.005, paired comparison); the converse occurred in 2.3% of voxels. For O 2 , mild hyperoxia had more marked CVR in 0.2% of voxels compared with greater hyperoxia; the converse occurred in 0.5% of voxels. All subjects had altered regional CO 2 response based on Type Analysis ranging from 4 ± 2 to 7 ± 3% of voxels. CONCLUSION In awake subjects, regional differences and abnormalities in CVR were observed with changes in end-tidal gases common during the conduct of anaesthesia. On the basis of these findings, consideration could be given to minimising regional CVR fluctuations in patients-at-risk of neurological complications by tighter control of end-tidal gases near the individual's resting values.
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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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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: 2] [Impact Index Per Article: 0.7] [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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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: 14] [Impact Index Per Article: 4.7] [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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