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Wehrli FW. Recent Advances in MR Imaging-based Quantification of Brain Oxygen Metabolism. Magn Reson Med Sci 2024; 23:377-403. [PMID: 38866481 PMCID: PMC11234951 DOI: 10.2463/mrms.rev.2024-0028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024] Open
Abstract
The metabolic rate of oxygen (MRO2) is fundamental to tissue metabolism. Determination of MRO2 demands knowledge of the arterio-venous difference in hemoglobin-bound oxygen concentration, typically expressed as oxygen extraction fraction (OEF), and blood flow rate (BFR). MRI is uniquely suited for measurement of both these quantities, yielding MRO2 in absolute physiologic units of µmol O2 min-1/100 g tissue. Two approaches are discussed, both relying on hemoglobin magnetism. Emphasis will be on cerebral oxygen metabolism expressed in terms of the cerebral MRO2 (CMRO2), but translation of the relevant technologies to other organs, including kidney and placenta will be touched upon as well. The first class of methods exploits the blood's bulk magnetic susceptibility, which can be derived from field maps. The second is based on measurement of blood water T2, which is modulated by diffusion and exchange in the local-induced fields within and surrounding erythrocytes. Some whole-organ methods achieve temporal resolution adequate to permit time-series studies of brain energetics, for instance, during sleep in the scanner with concurrent electroencephalogram (EEG) sleep stage monitoring. Conversely, trading temporal for spatial resolution has led to techniques for spatially resolved approaches based on quantitative blood oxygen level dependent (BOLD) or calibrated BOLD models, allowing regional assessment of vascular-metabolic parameters, both also exploiting deoxyhemoglobin paramagnetism like their whole-organ counterparts.
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Affiliation(s)
- Felix W Wehrli
- Laboratory for Structural, Physiologic and Functional Imaging (LSPFI), Department of Radiology, Perelman School of Medicine, University Pennsylvania, Philadelphia, Pennsylvania, USA
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2
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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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Li C, Buch S, Sun Z, Muccio M, Jiang L, Chen Y, Haacke EM, Zhang J, Wisniewski TM, Ge Y. In vivo mapping of hippocampal venous vasculature and oxygenation using susceptibility imaging at 7T. Neuroimage 2024; 291:120597. [PMID: 38554779 PMCID: PMC11115460 DOI: 10.1016/j.neuroimage.2024.120597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 03/19/2024] [Accepted: 03/28/2024] [Indexed: 04/02/2024] Open
Abstract
Mapping the small venous vasculature of the hippocampus in vivo is crucial for understanding how functional changes of hippocampus evolve with age. Oxygen utilization in the hippocampus could serve as a sensitive biomarker for early degenerative changes, surpassing hippocampal tissue atrophy as the main source of information regarding tissue degeneration. Using an ultrahigh field (7T) susceptibility-weighted imaging (SWI) sequence, it is possible to capture oxygen-level dependent contrast of submillimeter-sized vessels. Moreover, the quantitative susceptibility mapping (QSM) results derived from SWI data allow for the simultaneous estimation of venous oxygenation levels, thereby enhancing the understanding of hippocampal function. In this study, we proposed two potential imaging markers in a cohort of 19 healthy volunteers aged between 20 and 74 years. These markers were: 1) hippocampal venous density on SWI images and 2) venous susceptibility (Δχvein) in the hippocampus-associated draining veins (the inferior ventricular veins (IVV) and the basal veins of Rosenthal (BVR) using QSM images). They were chosen specifically to help characterize the oxygen utilization of the human hippocampus and medial temporal lobe (MTL). As part of the analysis, we demonstrated the feasibility of measuring hippocampal venous density and Δχvein in the IVV and BVR at 7T with high spatial resolution (0.25 × 0.25 × 1 mm3). Our results demonstrated the in vivo reconstruction of the hippocampal venous system, providing initial evidence regarding the presence of the venous arch structure within the hippocampus. Furthermore, we evaluated the age effect of the two quantitative estimates and observed a significant increase in Δχvein for the IVV with age (p=0.006, r2 = 0.369). This may suggest the potential application of Δχvein in IVV as a marker for assessing changes in atrophy-related hippocampal oxygen utilization in normal aging and neurodegenerative diseases such as AD and dementia.
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Affiliation(s)
- Chenyang Li
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA; Vilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA
| | - Sagar Buch
- Department of Neurology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Zhe Sun
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA; Vilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA
| | - Marco Muccio
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA
| | - Li Jiang
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA
| | - Yongsheng Chen
- Department of Neurology, Wayne State University School of Medicine, Detroit, MI, USA
| | - E Mark Haacke
- Department of Neurology, Wayne State University School of Medicine, Detroit, MI, USA; Department of Radiology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Jiangyang Zhang
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA
| | | | - Yulin Ge
- Department of Radiology, Center for Biomedical Imaging, NYU Grossman School of Medicine, New York, NY, USA.
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Kurian D, Hagberg GE, Scheffler K, Paul JS. A predictor-corrector phase unwrapping algorithm for temporally undersampled gradient-echo MRI. Magn Reson Med 2024; 91:1707-1722. [PMID: 38084410 DOI: 10.1002/mrm.29964] [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: 05/02/2023] [Revised: 11/18/2023] [Accepted: 11/19/2023] [Indexed: 02/03/2024]
Abstract
PURPOSE To develop a method for unwrapping temporally undersampled and nonlinear gradient recalled echo (GRE) phase. THEORY AND METHODS Temporal unwrapping is performed as a sequential one step prediction of the echo phase, followed by a correction to the nearest integer wrap-count. A spatio-temporal extension of the 1D predictor corrector unwrapping (PCU) algorithm improves the prediction accuracy, and thereby maintains spatial continuity. The proposed method is evaluated using numerical phantom, physical phantom, and in vivo brain data at both 3 T and 9.4 T. The unwrapping performance is compared with the state-of-the-art temporal and spatial unwrapping algorithms, and the spatio-temporal iterative virtual-echo based Nyquist sampled (iVENyS) algorithm. RESULTS Simulation results showed significant reduction in unwrapping errors at higher echoes compared with the state-of-the-art algorithms. Similar to the iVENyS algorithm, the PCU algorithm was able to generate spatially smooth phase images for in vivo data acquired at 3 T and 9.4 T, bypassing the use of additional spatial unwrapping step. A key advantage over iVENyS algorithm is the superior performance of PCU algorithm at higher echoes. CONCLUSION PCU algorithm serves as a robust phase unwrapping method for temporally undersampled and nonlinear GRE phase, particularly in the presence of high field gradients.
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Affiliation(s)
- Deepu Kurian
- School of Electronic Systems & Automation, Digital University Kerala, Trivandrum, Kerala, India
| | - Gisela E Hagberg
- High Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- Biomedical Magnetic Resonance, Department of Radiology, Eberhard Karl's University and University Hospital, Tübingen, Germany
| | - Klaus Scheffler
- High Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- Biomedical Magnetic Resonance, Department of Radiology, Eberhard Karl's University and University Hospital, Tübingen, Germany
| | - Joseph Suresh Paul
- School of Electronic Systems & Automation, Digital University Kerala, Trivandrum, Kerala, India
- School of Informatics, Digital University Kerala, 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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Amemiya T, Yokosawa S, Taniguchi Y, Sato R, Soutome Y, Ochi H, Shirai T. Simultaneous Arterial and Venous Imaging Using 3D Quantitative Parameter Mapping. Magn Reson Med Sci 2024; 23:56-65. [PMID: 36543227 PMCID: PMC10838721 DOI: 10.2463/mrms.mp.2021-0170] [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: 12/29/2021] [Accepted: 10/10/2022] [Indexed: 01/05/2024] Open
Abstract
PURPOSE To increase the number of images that can be acquired in MR examinations using quantitative parameters, we developed a method for obtaining arterial and venous images with mapping of proton density (PD), RF inhomogeneity (B1), longitudinal relaxation time (T1), apparent transverse relaxation time (T2*), and magnetic susceptibility through calculation, all with the same spatial resolution. METHODS The proposed method uses partially RF-spoiled gradient echo sequences to obtain 3D images of a subject with multiple scan parameters. The PD, B1, T1, T2*, and magnetic susceptibility maps are estimated using the quantification method we previously developed. Arterial images are obtained by adding images using optimized weights to emphasize the arteries. A morphology filter is used to obtain venous images from the magnetic susceptibility maps. For evaluation, images obtained from four out of five healthy volunteers were used to optimize the weights used in the arterial-image calculation, and the optimized weights were applied to the images from the fifth volunteer to obtain an arterial image. Arterial images of the five volunteers were calculated using the leave-one-out method, and the contrast between the arterial and background regions defined using the reference time-of-flight (TOF) method was evaluated using the area under the receiver operation characteristic curve (AUC). The contrast between venous and background regions defined by a reference quantitative susceptibility mapping (QSM) method was also evaluated for the venous image. RESULTS The AUC to discriminate blood vessels and background using the proposed method was 0.905 for the arterial image and 0.920 for the venous image. CONCLUSION The results indicate that the arterial images and venous images have high signal intensity at the same region as determined from the reference TOF and QSM methods, demonstrating the possibility of acquiring vasculature images with quantitative parameter mapping through calculation in an integrated manner.
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Affiliation(s)
- Tomoki Amemiya
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
| | - Suguru Yokosawa
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
| | - Yo Taniguchi
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
| | - Ryota Sato
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
| | - Yoshihisa Soutome
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
| | - Hisaaki Ochi
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
| | - Toru Shirai
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
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Jung YH, Park M, Joo B, Suh SH, Lee K, Ahn SJ. Prominent cerebral veins on susceptibility-weighted angiography in acute meningoencephalitis. Brain Behav 2023; 13:e3255. [PMID: 37721542 PMCID: PMC10636387 DOI: 10.1002/brb3.3255] [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: 05/10/2023] [Revised: 08/05/2023] [Accepted: 09/06/2023] [Indexed: 09/19/2023] Open
Abstract
BACKGROUND AND PURPOSE We have commonly observed prominent cerebral veins on susceptibility-weighted angiography (SWAN) in acute meningoencephalitis. This study aimed to investigate the clinical significance of these findings. METHODS Cerebral veins on SWAN of 98 patients with acute meningoencephalitis diagnosed from February 2016 through October 2020 were classified into three groups according to the degree of venous prominence (mild, 23; moderate, 53; and prominent, 22). Clinical variables and laboratory findings were compared between these groups. The influence of variables on the prediction of prominent cerebral veins was measured by random forest (RF) and gradient boosting machine (GBM). RESULTS As cerebral veins became more prominent, cerebrospinal fluid (CSF) glucose level decreased (69.61 ± 29.05 vs. 59.72 ± 22.57 vs. 48.36 ± 20.29 mg/dL, p = .01) and CSF protein level increased (100.73 ± 82.98 vs. 104.73 ± 70.99 vs. 159.12 ± 118.15 mg/dL, p = .03). The etiology of meningoencephalitis, neurological symptoms, and increased intracranial pressure (ICP) signs differed between groups (p < .05). RF and GBM demonstrated that CSF protein level was the variable with the highest power to predict the prominent cerebral vein (mean decrease in node impurity: 4.19, relative influence: 50.66). CONCLUSION The presence of prominent cerebral veins on SWAN in acute meningoencephalitis was significantly associated with a low CSF glucose level and a high CSF protein level, as well as ICP. Thus, the visual grade of the cerebral veins on SWAN may be utilized for the management of patients with acute meningoencephalitis.
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Affiliation(s)
- Yo Han Jung
- Department of Neurology, Gangnam Severance HospitalYonsei University, College of MedicineSeoulSouth Korea
- Severance Institute for Vascular and Metabolic ResearchYonsei University College of MedicineSeoulSouth Korea
| | - Mina Park
- Department of Radiology, Gangnam Severance HospitalYonsei University, College of MedicineSeoulSouth Korea
| | - Bio Joo
- Department of Radiology, Gangnam Severance HospitalYonsei University, College of MedicineSeoulSouth Korea
| | - Sang Hyun Suh
- Department of Radiology, Gangnam Severance HospitalYonsei University, College of MedicineSeoulSouth Korea
- Severance Institute for Vascular and Metabolic ResearchYonsei University College of MedicineSeoulSouth Korea
| | - Kyung‐Yul Lee
- Department of Neurology, Gangnam Severance HospitalYonsei University, College of MedicineSeoulSouth Korea
- Severance Institute for Vascular and Metabolic ResearchYonsei University College of MedicineSeoulSouth Korea
| | - Sung Jun Ahn
- Department of Radiology, Gangnam Severance HospitalYonsei University, College of MedicineSeoulSouth Korea
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Ikebe Y, Sato R, Amemiya T, Udo N, Matsushima M, Yabe I, Yamaguchi A, Sasaki M, Harada M, Matsukawa N, Kawata Y, Bito Y, Shirai T, Ochi H, Kudo K. Prediction of amyloid positron emission tomography positivity using multiple regression analysis of quantitative susceptibility mapping. Magn Reson Imaging 2023; 103:192-197. [PMID: 37558171 DOI: 10.1016/j.mri.2023.08.002] [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: 03/20/2023] [Revised: 08/04/2023] [Accepted: 08/06/2023] [Indexed: 08/11/2023]
Abstract
PURPOSE To develop a method for predicting amyloid positron emission tomography (PET) positivity based on multiple regression analysis of quantitative susceptibility mapping (QSM). MATERIALS AND METHODS This prospective study included 39 patients with suspected dementia from four centers. QSM images were obtained through a 3-T, three-dimensional radiofrequency-spoiled gradient-echo sequence with multiple echoes. The cortical standard uptake value ratio (SUVR) was obtained using amyloid PET with 18F-flutemetamol, and susceptibility in the brain regions was obtained using QSM. A multiple regression model to predict cortical SUVR was constructed based on susceptibilities in multiple brain regions, with the constraint that cortical SUVR and susceptibility were positively correlated. The discrimination performance of the Aβ-positive and Aβ-negative cohorts was evaluated based on the predicted SUVR using the area under the receiver operating characteristic curve (AUC) and Mann-Whitney U test. RESULTS The correlation coefficients between true and predicted SUVR were increased by incorporating the constraint, and the AUC to discriminate between the Aβ-positive and Aβ-negative cohorts reached to 0.79 (p < 0.01). CONCLUSION These preliminary results suggest that a QSM-based multiple regression model can predict amyloid PET positivity with fair accuracy.
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Affiliation(s)
- Yohei Ikebe
- Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Hokkaido, Japan; Center for Cause of Death Investigation, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Ryota Sato
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Hokkaido, Japan
| | - Tomoki Amemiya
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Niki Udo
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan
| | - Masaaki Matsushima
- Department of Neurology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Hokkaido, Japan
| | - Ichiro Yabe
- Department of Neurology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Hokkaido, Japan
| | - Akinori Yamaguchi
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Hokkaido, Japan
| | - Makoto Sasaki
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Iwate, Japan
| | - Masafumi Harada
- Department of Radiology, Tokushima University, Tokushima, Japan
| | | | - Yasuo Kawata
- Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Yoshitaka Bito
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Hokkaido, Japan; Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Toru Shirai
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Hokkaido, Japan; Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Hisaaki Ochi
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Hokkaido, Japan; Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Kohsuke Kudo
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Hokkaido, Japan.
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Shirai T, Sato R, Kawata Y, Bito Y, Ochi H. Region Expansion of Background Field Removal with Local Spherical Harmonics Approximation for Whole-brain Quantitative Susceptibility Mapping. Magn Reson Med Sci 2023; 22:497-514. [PMID: 36372397 PMCID: PMC10552664 DOI: 10.2463/mrms.mp.2021-0043] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 08/07/2022] [Indexed: 10/03/2023] Open
Abstract
PURPOSE Quantitative susceptibility mapping (QSM) is useful for obtaining biological information. To calculate susceptibility distribution, it is necessary to calculate the local field caused by the differences of susceptibility between the tissues. The local field can be obtained by removing a background field from a total field acquired by MR phase image. Conventional approaches based on spherical mean value (SMV) filtering, which are widely used for background field calculations, fail to calculate the background field of the brain surface region corresponding to the radius of the SMV kernel, and consequently cannot calculate the QSM of the brain surface region. Accordingly, a new method calculating the local field by expansively removing the background field is proposed for whole brain QSM. METHODS The proposed method consists of two steps. First, the background field of the brain surface is calculated from the total field using a locally polynomial approximation of spherical harmonics. Second, the whole brain local field is calculated by SMV filtering with a constraint term of the background field of the brain surface. The parameters of the approximation were optimized to reduce calculation errors through simulations using both a numerical phantom and a measured human brain. Performance of the proposed method with the optimized parameters was quantitatively and visually compared with conventional methods in an experiment of five healthy volunteers. RESULTS The proposed method showed the accurate local field over the expanded brain region in the simulation studies. It also showed consistent QSM with conventional methods inside of the brain surface and showed clear vein structures on the brain surface. CONCLUSION The proposed method enables accurate calculation of whole brain QSM without eroding the brain surface region while maintaining same values inside of the brain surface as the conventional methods.
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Affiliation(s)
- Toru Shirai
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
| | - Ryota Sato
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
| | - Yasuo Kawata
- Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Kashiwa, Chiba, Japan
| | - Yoshitaka Bito
- Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Kashiwa, Chiba, Japan
| | - Hisaaki Ochi
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Kokubunji, Tokyo, Japan
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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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Meng Y, Li CX, Zhang X. Quantitative Evaluation of Oxygen Extraction Fraction Changes in the Monkey Brain during Acute Stroke by Using Quantitative Susceptibility Mapping. Life (Basel) 2023; 13:1008. [PMID: 37109537 PMCID: PMC10146121 DOI: 10.3390/life13041008] [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: 03/02/2023] [Revised: 04/05/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023] Open
Abstract
BACKGROUND The oxygen extraction fraction (OEF) indicates the brain's oxygen consumption and can be estimated by using the quantitative susceptibility mapping (QSM) MRI technique. Recent studies have suggested that OEF alteration following stroke is associated with the viability of at-risk tissue. In the present study, the temporal evolution of OEF in the monkey brain during acute stroke was investigated using QSM. METHODS Ischemic stroke was induced in adult rhesus monkeys (n = 8) with permanent middle cerebral artery occlusion (pMCAO) by using an interventional approach. Diffusion-, T2-, and T2*-weighted images were conducted on day 0, day 2, and day 4 post-stroke using a clinical 3T scanner. Progressive changes in magnetic susceptibility and OEF, along with their correlations with the transverse relaxation rates and diffusion indices, were examined. RESULTS The magnetic susceptibility and OEF in injured gray matter of the brain significantly increased during the hyperacute phase, and then decreased significantly on day 2 and day 4. Moreover, the temporal changes of OEF in gray matter were moderately correlated with mean diffusivity (MD) (r = 0.52; p = 0.046) from day 0 to day 4. Magnetic susceptibility in white matter progressively increased (from negative values to near zero) during acute stroke, and significant increases were seen on day 2 (p = 0.08) and day 4 (p = 0.003) when white matter was significantly degenerated. However, significant reduction of OEF in white matter was not seen until day 4 post-stroke. CONCLUSION The preliminary results demonstrate that QSM-derived OEF is a robust approach to examine the progressive changes of gray matter in the ischemic brain from the hyperacute phase to the subacute phase of stroke. The changes of OEF in gray matter were more prominent than those in white matter following stroke insult. The findings suggest that QSM-derived OEF may provide complementary information for understanding the neuropathology of the brain tissue following stroke and predicting stroke outcomes.
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Affiliation(s)
- Yuguang Meng
- EPC Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, GA 30329, USA
| | - Chun-Xia Li
- EPC Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, GA 30329, USA
| | - Xiaodong Zhang
- EPC Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, GA 30329, USA
- Division of Neuropharmacology and Neurologic Diseases, Emory National Primate Research Center, Emory University, Atlanta, GA 30329, USA
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12
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Chiu FY, Yen Y. Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives. Biomark Res 2023; 11:35. [PMID: 36991494 DOI: 10.1186/s40364-023-00476-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/16/2023] [Indexed: 03/31/2023] Open
Abstract
Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.
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Affiliation(s)
- Fang-Ying Chiu
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Center for Brain and Neurobiology Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Teaching and Research Headquarters for Sustainable Development Goals, Tzu Chi University, Hualien City, 970374, Taiwan.
| | - Yun Yen
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Ph.D. Program for Cancer Biology and Drug Discovery, Taipei Medical University, Taipei City, 110301, Taiwan.
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei City, 110301, Taiwan.
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei City, 110301, Taiwan.
- Cancer Center, Taipei Municipal WanFang Hospital, Taipei City, 116081, Taiwan.
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13
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Wang X, Di Tanna GL, Moullaali TJ, Martin RH, Shipes VB, Robinson TG, Chalmers J, Suarez JI, Qureshi AI, Palesch YY, Anderson CS. J-shape relation of blood pressure reduction and outcome in acute intracerebral hemorrhage: A pooled analysis of INTERACT2 and ATACH-II individual participant data. Int J Stroke 2022; 17:1129-1136. [PMID: 34983270 DOI: 10.1177/17474930211064076] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE The aim of this study was to better define the shape of association between the degree ("magnitude") of early (< 1 h) reduction in systolic blood pressure (SBP) and outcomes in patients with acute intracerebral hemorrhage (ICH) through pooled analysis of the second Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial (INTERACT2) and second Antihypertensive Treatment of Acute Cerebral Hemorrhage (ATACH-II) datasets. METHODS Association of the continuous magnitude of SBP reduction described using cubic splines and an ordinal measure of the functional outcome on the modified Rankin scale (mRS) scores at 90 days were analyzed in generalized linear mixed models. Models were adjusted for achieved (mean) and variability (standard deviation, SD) of SBP between 1 and 24 h, various baseline covariates, and trial as a random effect. RESULTS Among 3796 patients (mean age 63.1 (SD = 13.0) years; female 37.4%), with a mean magnitude (< 1 h) of SBP reduction of 28.5 (22.8) mmHg, those with larger magnitude were more often non-Asian and female, had higher baseline SBP, received multiple blood pressure (BP) lowering agents, and achieved lower SBP levels in 1-24 h. Compared to those patients with no SBP reduction within 1 h (reference), the adjusted odds of unfavorable functional outcome, according to a shift in mRS scores, were lower for SBP reductions up to 60 mmHg with an inflection point between 32 and 46 mmHg, but significantly higher for SBP reductions > 70 mmHg. Similar J-shape associations were evident across various time epochs across 24 h and consistent according to baseline hematoma volume and SBP and history of hypertension. INTERPRETATION A moderate degree of rapid SBP lowering is associated with improved functional outcome after ICH, but large SBP reductions over 1 h (e.g. from > 200 to target < 140 mmHg) were associated with reduction, or reversal, of any such benefit.
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Affiliation(s)
- Xia Wang
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Gian Luca Di Tanna
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Tom J Moullaali
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Renee' H Martin
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Virginia B Shipes
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Thompson G Robinson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, UK
| | - John Chalmers
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Jose I Suarez
- Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Adnan I Qureshi
- Zeenat Qureshi Stroke Institutes and Department of Neurology, University of Missouri, Columbia, MO, USA
| | - Yuko Y Palesch
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Craig S Anderson
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
- Neurology Department, Royal Prince Alfred Hospital, Sydney Health Partners, Sydney, NSW, Australia
- The George Institute for Global Health, Peking University Health Science Center, Beijing, China
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14
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Yang L, Cho J, Chen T, Gillen KM, Li J, Zhang Q, Guo L, Wang Y. Oxygen extraction fraction (OEF) assesses cerebral oxygen metabolism of deep gray matter in patients with pre-eclampsia. Eur Radiol 2022; 32:6058-6069. [PMID: 35348866 DOI: 10.1007/s00330-022-08713-7] [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: 10/18/2021] [Revised: 02/21/2022] [Accepted: 03/01/2022] [Indexed: 01/19/2023]
Abstract
OBJECTIVES The objective of this study was to compare oxygen extraction fraction (OEF) values in the deep gray matter (GM) of pre-eclampsia (PE) patients, pregnant healthy controls (PHCs), and non-pregnant healthy controls (NPHCs) to explore their brain oxygen metabolism differences in GM. METHODS Forty-seven PE patients, forty NPHCs, and twenty-one PHCs were included. Brain OEF values were computed from quantitative susceptibility mapping (QSM) plus quantitative blood oxygen level-dependent magnitude (QSM + qBOLD = QQ)-based mapping. One-way ANOVA was used to compare mean OEF values in the three groups. The area under the curve of the mean OEF value in each region of interest was estimated using a receiver operating characteristic curve analysis. RESULTS We found that the mean OEF values in the thalamus, putamen, caudate nucleus, pallidum, and substantia nigra were significantly different in these three groups (F = 5.867, p = 0.004; F = 5.142, p = 0007; F = 6.158, p = 0.003; F = 6.319, p = 0.003; F = 5.491, p = 0.005). The mean OEF values for these 5 regions were higher in PE patients than in NPHCs and in PHCs (p < 0.05). The AUC of these ROIs ranged from 0.673 to 0.692 (p < 0.01) and cutoff values varied from 35.1 to 36.6%, indicating that the OEF values could discriminate patients with and without PE. Stepwise multivariate analysis revealed that the OEF values correlated with hematocrit in pregnant women (r = 0.353, p = 0.003). CONCLUSION OEF values in the brains of pregnant women can be measured in clinical practice using QQ-based OEF mapping for noninvasive assessment of hypertensive disorders. KEY POINTS • Pre-eclampsia is a hypertensive disorder associated with abnormalities in brain oxygen extraction. • Oxygen extraction fraction (OEF) is an indicator of brain tissue viability and function. QQ-based mapping of OEF is a new MRI technique that can noninvasively quantify brain oxygen metabolism. • OEF values in the brains of pregnant women can be measured for noninvasive assessment of hypertensive disorders in clinical practice.
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Affiliation(s)
- Linfeng Yang
- Jinan Maternity and Child Care Hospital, Jinan Maternity and Child Care Hospital Affiliated to Shandong First Medical University, 2 Jian-guo Xiao Jing-san Road, Jinan, 250001, Shandong, China
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, 407 East 61st Street, New York, NY, 10065, USA
| | - Tao Chen
- Jinan Maternity and Child Care Hospital, Jinan Maternity and Child Care Hospital Affiliated to Shandong First Medical University, 2 Jian-guo Xiao Jing-san Road, Jinan, 250001, Shandong, China
| | - Kelly M Gillen
- Department of Radiology, Weill Cornell Medical College, New York, 407 East 61st Street, New York, NY, 10065, USA
| | - Jing Li
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, 95 Yong-an Road, Xicheng District, Beijing, 100050, China
| | - Qihao Zhang
- Department of Radiology, Weill Cornell Medical College, New York, 407 East 61st Street, New York, NY, 10065, USA
| | - Lingfei Guo
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jing-wu Road, Jinan, 250021, Shandong, China.
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, 407 East 61st Street, New York, NY, 10065, USA
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15
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Murdoch R, Stotesbury H, Hales PW, Kawadler JM, Kölbel M, Clark CA, Kirkham FJ, Shmueli K. A Comparison of MRI Quantitative Susceptibility Mapping and TRUST-Based Measures of Brain Venous Oxygen Saturation in Sickle Cell Anaemia. Front Physiol 2022; 13:913443. [PMID: 36105280 PMCID: PMC9465016 DOI: 10.3389/fphys.2022.913443] [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] [Received: 04/05/2022] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
In recent years, interest has grown in the potential for magnetic resonance imaging (MRI) measures of venous oxygen saturation (Yv) to improve neurological risk prediction. T2-relaxation-under-spin-tagging (TRUST) is an MRI technique which has revealed changes in Yv in patients with sickle cell anemia (SCA). However, prior studies comparing Yv in patients with SCA relative to healthy controls have reported opposing results depending on whether the calibration model, developed to convert blood T2 to Yv, is based on healthy human hemoglobin (HbA), bovine hemoglobin (HbBV) or sickle hemoglobin (HbS). MRI Quantitative Susceptibility Mapping (QSM) is an alternative technique that may hold promise for estimating Yv in SCA as blood magnetic susceptibility is linearly dependent upon Yv, and no significant difference has been found between the magnetic susceptibility of HbA and HbS. Therefore, the aim of this study was to compare estimates of Yv using QSM and TRUST with five published calibration models in healthy controls and patients with SCA. 17 patients with SCA and 13 healthy controls underwent MRI. Susceptibility maps were calculated from a multi-parametric mapping acquisition and Yv was calculated from the mean susceptibility in a region of interest in the superior sagittal sinus. TRUST estimates of T2, within a similar but much smaller region, were converted to Yv using five different calibration models. Correlation and Bland-Altman analyses were performed to compare estimates of Yv between TRUST and QSM methods. For each method, t-tests were also used to explore group-wise differences between patients with SCA and healthy controls. In healthy controls, significant correlations were observed between QSM and TRUST measures of Yv, while in SCA, there were no such correlations. The magnitude and direction of group-wise differences in Yv varied with method. The TRUST-HbBV and QSM methods suggested decreased Yv in SCA relative to healthy controls, while the TRUST-HbS (p < 0.01) and TRUST-HbA models suggested increased Yv in SCA as in previous studies. Further validation of all MRI measures of Yv, relative to ground truth measures such as O15 PET and jugular vein catheterization, is required in SCA before QSM or TRUST methods can be considered for neurological risk prediction.
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Affiliation(s)
- Russell Murdoch
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Hanne Stotesbury
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Patrick W. Hales
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Jamie M. Kawadler
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Melanie Kölbel
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Christopher A. Clark
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Fenella J. Kirkham
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
- Clinical and Experimental Sciences, University of Southampton, Southampton, United Kingdom
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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16
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Uchida Y, Kan H, Sakurai K, Oishi K, Matsukawa N. Quantitative susceptibility mapping as an imaging biomarker for Alzheimer’s disease: The expectations and limitations. Front Neurosci 2022; 16:938092. [PMID: 35992906 PMCID: PMC9389285 DOI: 10.3389/fnins.2022.938092] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 07/14/2022] [Indexed: 11/25/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common type of dementia and a distressing diagnosis for individuals and caregivers. Researchers and clinical trials have mainly focused on β-amyloid plaques, which are hypothesized to be one of the most important factors for neurodegeneration in AD. Meanwhile, recent clinicopathological and radiological studies have shown closer associations of tau pathology rather than β-amyloid pathology with the onset and progression of Alzheimer’s symptoms. Toward a biological definition of biomarker-based research framework for AD, the 2018 National Institute on Aging–Alzheimer’s Association working group has updated the ATN classification system for stratifying disease status in accordance with relevant pathological biomarker profiles, such as cerebral β-amyloid deposition, hyperphosphorylated tau, and neurodegeneration. In addition, altered iron metabolism has been considered to interact with abnormal proteins related to AD pathology thorough generating oxidative stress, as some prior histochemical and histopathological studies supported this iron-mediated pathomechanism. Quantitative susceptibility mapping (QSM) has recently become more popular as a non-invasive magnetic resonance technique to quantify local tissue susceptibility with high spatial resolution, which is sensitive to the presence of iron. The association of cerebral susceptibility values with other pathological biomarkers for AD has been investigated using various QSM techniques; however, direct evidence of these associations remains elusive. In this review, we first briefly describe the principles of QSM. Second, we focus on a large variety of QSM applications, ranging from common applications, such as cerebral iron deposition, to more recent applications, such as the assessment of impaired myelination, quantification of venous oxygen saturation, and measurement of blood– brain barrier function in clinical settings for AD. Third, we mention the relationships among QSM, established biomarkers, and cognitive performance in AD. Finally, we discuss the role of QSM as an imaging biomarker as well as the expectations and limitations of clinically useful diagnostic and therapeutic implications for AD.
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Affiliation(s)
- Yuto Uchida
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- *Correspondence: Yuto Uchida,
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Keita Sakurai
- Department of Radiology, National Center for Geriatrics and Gerontology, Ōbu, Japan
| | - Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Noriyuki Matsukawa,
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17
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Rudilosso S, Chui E, Stringer MS, Thrippleton M, Chappell F, Blair GW, Garcia DJ, Doubal F, Hamilton I, Kopczak A, Ingrisch M, Kerkhofs D, Backes WH, Staals J, van Oostenbrugge R, Duering M, Dichgans M, Wardlaw JM. Prevalence and Significance of the Vessel-Cluster Sign on Susceptibility-Weighted Imaging in Patients With Severe Small Vessel Disease. Neurology 2022; 99:e440-e452. [PMID: 35606147 PMCID: PMC9421604 DOI: 10.1212/wnl.0000000000200614] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 03/15/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Magnetic resonance susceptibility-weighted imaging (SWI) can identify small brain blood vessels that contain deoxygenated blood due to its induced magnetic field disturbance. We observed focal clusters of possible dilated small vessels on SWI in white matter in severe small vessel disease (SVD). We assessed their prevalence, associations with SVD lesions, and vascular reactivity in patients with sporadic SVD and in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). METHODS Secondary cross-sectional analysis of a prospective multicenter observational study of patients with either sporadic SVD or CADASIL (INVESTIGATE-SVD) studied with 3 Tesla MRI including blood-oxygen-level-dependent MRI cerebrovascular reactivity (CVR). Two independent raters evaluated SWI sequences to identify "vessel-clusters" in white matter as focal low-signal dots/lines with small vessel appearance (interrater agreement, kappa statistic = 0.66). We assessed per-patient and per-cluster associations with SVD lesion type and severity on structural MRI sequences. We also assessed CVR within and at 2-voxel concentric intervals around the vessel-clusters using contralateral volumes as a reference. RESULTS Among the 77 patients enrolled, 76 had usable SWI sequences, 45 with sporadic SVD (mean age 64 years [SD 11], 26 men [58%]) and 31 with CADASIL (53 years [11], 15 men [48%]). We identified 94 vessel-clusters in 36 of the 76 patients (15/45 sporadic SVD, 21/31 CADASIL). In covariate-adjusted analysis, patients with vessel-clusters had more lacunes (OR, 95% CI) (1.30, 1.05-1.62), higher white matter hyperintensity (WMH) volume (per-log10 increase, 1.92, 1.04-3.56), and lower CVR in normal appearing white matter (per %/mm Hg, 0.77, 0.60-0.99), compared with patients without vessel-clusters. Fifty-seven of the 94 vessel-clusters (61%) corresponded to noncavitated or partially cavitated WMH on fluid-attenuated inversion recovery, and 37 of 94 (39%) to complete cavities. CVR magnitude was lower than in the corresponding contralateral volumes (mean difference [SD], t, p) within vessel-cluster volumes (-0.00046 [0.00088], -3.021, 0.005) and in the surrounding volume expansion shells up to 4 voxels (-0.00011 [0.00031], -2.140, 0.039; -0.00010 [0.00027], -2.295, 0.028) in vessel-clusters with complete cavities, but not in vessel-clusters without complete cavitation. DISCUSSION Vessel-clusters might correspond to maximally dilated vessels in white matter that are approaching complete tissue injury and cavitation. The pathophysiologic significance of this new feature warrants further longitudinal investigation.
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Affiliation(s)
- Salvatore Rudilosso
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Ernest Chui
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Michael S Stringer
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Michael Thrippleton
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Francesca Chappell
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Gordon W Blair
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Daniela Jaime Garcia
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Fergus Doubal
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Iona Hamilton
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Anna Kopczak
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Michael Ingrisch
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Danielle Kerkhofs
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Walter H Backes
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Julie Staals
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Robert van Oostenbrugge
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Marco Duering
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Martin Dichgans
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany
| | - Joanna M Wardlaw
- From the Comprehensive Stroke Center (S.R.), Department of Neuroscience, Hospital Clinic, University of Barcelona; August Pi i Sunyer Biomedical Research Institute (IDIBAPS)(S.R.), Barcelona, Spain; Centre for Clinical Brain Sciences (E.C., M.S.S., M.T., F.C., G.B., D.J.G., F.D., I.H., J.M.W.), UK Dementia Research Institute, University of Edinburgh, United Kingdom; Institute for Stroke and Dementia Research (A.K., M. Dichgans), University Hospital, LMU Munich; Department of Radiology (M.I.),Ludwig-Maximilians-University Hospital Munich, Germany; Department of Neurology (D.K., J.S., R.v.O.), CARIM-School for Cardiovascular Diseases Maastricht University Medical Center+, Maastricht,; Department of Radiology & Nuclear Medicine (W.H.B.), School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Netherlands; Institute for Stroke and Dementia Research (ISD) (M. Duering), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M. Duering), University of Basel, Switzerland; Munich Cluster for Systems Neurology (SyNergy) (M. Dichgans); and German Center for Neurodegenerative Diseases (DZNE) (M. Dichgans), Munich, Germany.
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Harada T, Kudo K, Fujima N, Yoshikawa M, Ikebe Y, Sato R, Shirai T, Bito Y, Uwano I, Miyata M. Quantitative Susceptibility Mapping: Basic Methods and Clinical Applications. Radiographics 2022; 42:1161-1176. [PMID: 35522577 DOI: 10.1148/rg.210054] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Quantitative susceptibility mapping (QSM), one of the advanced MRI techniques for evaluating magnetic susceptibility, offers precise quantitative measurements of spatial distributions of magnetic susceptibility. Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and is a substance-specific value. Recently, QSM has been widely used to estimate various levels of substances in the brain, including iron, hemosiderin, and deoxyhemoglobin (paramagnetism), as well as calcification (diamagnetism). By visualizing iron distribution in the brain, it is possible to identify anatomic structures that are not evident on conventional images and to evaluate various neurodegenerative diseases. It has been challenging to apply QSM in areas outside the brain because of motion artifacts from respiration and heartbeats, as well as the presence of fat, which has a different frequency to the proton. In this review, the authors provide a brief overview of the theoretical background and analyze methods of converting MRI phase images to QSM. Moreover, we provide an overview of the current clinical applications of QSM. Online supplemental material is available for this article. ©RSNA, 2022.
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Affiliation(s)
- Taisuke Harada
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Kohsuke Kudo
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Noriyuki Fujima
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Masato Yoshikawa
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Yohei Ikebe
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Ryota Sato
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Toru Shirai
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Yoshitaka Bito
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Ikuko Uwano
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Mari Miyata
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
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Li W, Xu F, Zhu D, van Zijl PCM, Qin Q. T 2 -oximetry-based cerebral venous oxygenation mapping using Fourier-transform-based velocity-selective pulse trains. Magn Reson Med 2022; 88:1292-1302. [PMID: 35608208 PMCID: PMC9247032 DOI: 10.1002/mrm.29300] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 04/19/2022] [Accepted: 04/20/2022] [Indexed: 12/14/2022]
Abstract
Purpose To develop a T2‐oximetry method for quantitative mapping of cerebral venous oxygenation fraction (Yv) using Fourier‐transform–based velocity‐selective (FT‐VS) pulse trains. Methods The venous isolation preparation was achieved by using an FT‐VS inversion plus a nonselective inversion (NSI) pulse to null the arterial blood signal while minimally affected capillary blood flows out into the venular vasculature during the outflow time (TO), and then applying an Fourier transform based velocity selective saturation (FT‐VSS) pulse to suppress the tissue signal. A multi‐echo readout was employed to obtain venous T2 (T2,v) efficiently with the last echo used to detect the residual CSF signal and correct its contamination in the fitting. Here we compared the performance of this FT‐VS–based venous isolation preparations with a traditional velocity‐selective saturation (VSS)–based approach (quantitative imaging of extraction of oxygen and tissue consumption [QUIXOTIC]) with different cutoff velocities for Yv mapping on 6 healthy volunteers at 3 Tesla. Results The FT‐VS–based methods yielded higher venous blood signal and temporal SNR with less CSF contamination than the velocity‐selective saturation–based results. The averaged Yv values across the whole slice measured in different experiments were close to the global Yv measured from the individual internal jugular vein. Conclusion The feasibility of the FT‐VS–based Yv estimation was demonstrated on healthy volunteers. The obtained high venous signal as well as the mitigation of CSF contamination led to a good agreement between the T2,v and Yv measured in the proposed method with the values in the literature. Click here for author‐reader discussions
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Affiliation(s)
- Wenbo Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Feng Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Dan Zhu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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20
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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: 24] [Impact Index Per Article: 12.0] [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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21
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Bartnik-Olson BL, Blood AB, Terry MH, Hanson SFL, Day C, Kido D, Kim P. Quantitative susceptibility mapping as a measure of cerebral oxygenation in neonatal piglets. J Cereb Blood Flow Metab 2022; 42:891-900. [PMID: 34878947 PMCID: PMC9254037 DOI: 10.1177/0271678x211065199] [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: 06/15/2021] [Revised: 11/01/2021] [Accepted: 11/05/2021] [Indexed: 11/15/2022]
Abstract
Prominence of cerebral veins using susceptibility weighted magnetic resonance imaging (SWI) has been used as a qualitative indicator of cerebral venous oxygenation (CvO2). Quantitative susceptibility mapping (QSM) adds more precision to the assessment of CvO2, but has not been applied to neonatal hypoxic ischemic injury (HII). We proposed to study QSM measures of venous susceptibility and their correlation with direct measures of brain oxygenation and cerebral blood flow (CBF) in the neonatal piglet. The association of QSM intravascular cerebral venous susceptibility, with brain tissue O2 tension, CBF, cortical tissue oxyhemoglobin saturation, and the partial pressure of oxygen in arterial blood measurement during various oxygenation states was determined by linear regression. Compared to normoxia, venous susceptibility in the straight sinus increased 56.8 ± 25.4% during hypoxia, while decreasing during hyperoxia (23.5 ± 32.9%) and hypercapnia (23.3 ± 73.1%), which was highly correlated to all other measures of oxygenation (p < 0.0001) but did not correlate to CBF (p = 0.82). These findings demonstrate a strong relationship between venous susceptibility and brain tissue O2 tension. Our results suggest that QSM-derived venous susceptibility is sensitive to cerebral oxygenation status across various oxygenation states.
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Affiliation(s)
| | - Arlin B Blood
- Department of Pediatrics, Loma Linda University School of
Medicine, Center for Perinatal Biology, Loma Linda, CA, USA
| | - Michael H Terry
- Department of Pulmonary & Critical Care, Loma Linda
University Medical Center, Loma Linda, CA, USA
| | - Shawn FL Hanson
- Center for Perinatal Biology, Loma Linda University School of
Medicine, Loma Linda, CA, USA
| | - Christopher Day
- Department of Pediatrics, Office of Graduate Medical Education,
Loma Linda, CA, USA
| | - Daniel Kido
- Department of Radiology, Loma Linda University Medical Center,
Loma Linda, CA, USA
| | - Paggie Kim
- Department of Radiology, Loma Linda University Medical Center,
Loma Linda, CA, USA
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22
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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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23
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Yamaguchi A, Kudo K, Sato R, Kawata Y, Udo N, Matsushima M, Yabe I, Sasaki M, Harada M, Matsukawa N, Shirai T, Ochi H, Bito Y. Efficacy of Quantitative Susceptibility Mapping with Brain Surface Correction and Vein Removal for Detecting Increase Magnetic Susceptibility in Patients with Alzheimer's Disease. Magn Reson Med Sci 2022; 22:87-94. [PMID: 35264494 PMCID: PMC9849412 DOI: 10.2463/mrms.mp.2021-0015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
PURPOSE Studies on quantitative susceptibility mapping (QSM) have reported an increase in magnetic susceptibilities in patients with Alzheimer's disease (AD). Despite the pathological importance of the brain surface areas, they are sometimes excluded in QSM analysis. This study aimed to reveal the efficacy of QSM analysis with brain surface correction (BSC) and/or vein removal (VR) procedures. METHODS Thirty-seven AD patients and 37 age- and sex-matched, cognitively normal (CN) subjects were included. A 3D-gradient echo sequence at 3T MRI was used to obtain QSM. QSM images were created with regularization enabled sophisticated harmonic artifact reduction for phase data (RESHARP) and constrained RESHARP with BSC and/or VR. We conducted ROI analysis between AD patients and CN subjects who did or did not undergo BSC and/or VR using a t-test, to compare the susceptibility values after gray matter weighting. RESULTS The susceptibility values in RESHARP without BSC were significantly larger in AD patients than in CN subjects in one region (precentral gyrus, 8.1 ± 2.9 vs. 6.5 ± 2.1 ppb) without VR and one region with VR (precentral gyrus, 7.5 ± 2.8 vs. 5.9 ± 2.0 ppb). Three regions in RESHARP with BSC had significantly larger susceptibilities without VR (precentral gyrus, 7.1 ± 2.0 vs. 5.9 ± 2.0 ppb; superior medial frontal gyrus, 5.7 ± 2.6 vs. 4.2 ± 3.1 ppb; putamen, 47,8 ± 16.5 vs. 40.0 ± 15.9 ppb). In contrast, six regions showed significantly larger susceptibilities with VR in AD patients than in CN subjects (precentral gyrus, 6.4 ± 1.9 vs. 4.9 ± 2.7 ppb; superior medial frontal gyrus, 5.3 ± 2.7 vs. 3.7 ± 3.3 ppb; orbitofrontal cortex, -2.1 ± 2.7 vs. -3.6 ± 3.2 ppb; parahippocampal gyrus, 0.1 ± 3.6 vs. -1.7 ± 3.7 ppb; putamen, 45.0 ± 14.9 vs. 37.6 ± 14.6 ppb; inferior temporal gyrus, -3.4 ± 1.5 vs. -4.4 ± 1.5 ppb). CONCLUSION RESHARP with BSC and VR showed more regions of increased susceptibility in AD patients than in CN subjects. This study highlights the efficacy of this method in facilitating the diagnosis of AD.
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Affiliation(s)
- Akinori Yamaguchi
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Kohsuke Kudo
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan,Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan,Corresponding author: Faculty of Medicine, Hokkaido University, Kita15, Nishi7, Kita-Ku, Sapporo, Hokkaido 060-8638, Japan. Phone: +81-11-706-7779, Fax: +81-11-706-7408, E-mail:
| | - Ryota Sato
- FUJIFILM Healthcare Corporation, Tokyo, Japan
| | | | - Niki Udo
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Masaaki Matsushima
- Department of Neurology, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Ichiro Yabe
- Department of Neurology, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Makoto Sasaki
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Morioka, Iwate, Japan
| | - Masafumi Harada
- Department of Radiology, Tokushima University Graduate School of Medicine, Tokushima, Tokushima, Japan
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, Japan
| | - Toru Shirai
- FUJIFILM Healthcare Corporation, Tokyo, Japan
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24
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Uchida Y, Kan H, Inoue H, Oomura M, Shibata H, Kano Y, Kuno T, Usami T, Takada K, Yamada K, Kudo K, Matsukawa N. Penumbra Detection With Oxygen Extraction Fraction Using Magnetic Susceptibility in Patients With Acute Ischemic Stroke. Front Neurol 2022; 13:752450. [PMID: 35222239 PMCID: PMC8873150 DOI: 10.3389/fneur.2022.752450] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 01/25/2022] [Indexed: 12/14/2022] Open
Abstract
Background The oxygen extraction fraction (OEF) has been applied to identify ischemic penumbral tissue, but is difficult to use in an urgent care setting. This study aimed to investigate whether an OEF map generated via magnetic resonance quantitative susceptibility mapping (QSM) could help identify the ischemic penumbra in patients with acute ischemic stroke. Materials and Methods This prospective imaging study included 21 patients with large anterior circulation vessel occlusion who were admitted <24 h after stroke onset and 21 age-matched healthy controls. We identified the ischemic penumbra as the region with a Tmax of >6 s during dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI) and calculated the perfusion-core mismatch ratio between the ischemic penumbra and infarct core volumes. The OEF values were measured based on magnetic susceptibility differences between the venous structures and brain tissues using rapid QSM acquisition. Volumes with increased OEF values were compared to the ischemic penumbra volumes using an anatomical template. Results Eleven patients had a perfusion-core mismatch ratio of ≥1.8, and reperfusion therapy was recommended. In these patients, the volumes with increased OEF values of >51.5%, which was defined using the anterior circulation territory OEF values from the 21 healthy controls, were positively correlated with the ischemic penumbra volumes (r = 0.636, 95% CI: 0.059 to 0.895, P = 0.035) and inversely correlated with the 30-day change in the National Institutes of Health Stroke Scale scores (r = −0.624, 95% CI: −0.891 to −0.039, P = 0.041). Conclusion Tissue volumes with increased OEF values could predict ischemic penumbra volumes based on DSC-MRI, highlighting the potential of the QSM-derived OEF map as a penumbra biomarker to guide treatment selection in patients with acute ischemic stroke.
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Affiliation(s)
- Yuto Uchida
- Department of Neurology, Nagoya City University, Nagoya, Japan
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University, Nagoya, Japan
| | - Hiroyasu Inoue
- Department of Neurology, Nagoya City University, Nagoya, Japan
| | - Masahiro Oomura
- Department of Neurology, Nagoya City University, Nagoya, Japan
| | - Haruto Shibata
- Department of Neurology, Nagoya City East Medical Center, Nagoya, Japan
| | - Yuya Kano
- Department of Neurology, Nagoya City East Medical Center, Nagoya, Japan
| | - Tomoyuki Kuno
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan
| | - Toshihiko Usami
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan
| | - Koji Takada
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan
| | - Kentaro Yamada
- Department of Neurology, Nagoya City East Medical Center, Nagoya, Japan
| | - Kohsuke Kudo
- Department of Diagnostic Imaging, Hokkaido University, Hokkaido, Japan
- Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Hokkaido, Japan
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University, Nagoya, Japan
- *Correspondence: Noriyuki Matsukawa
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25
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Lundberg A, Lind E, Olsson H, Helms G, Knutsson L, Wirestam R. Comparison of MRI methods for measuring whole‐brain oxygen extraction fraction under different geometric conditions at 7T. J Neuroimaging 2022; 32:442-458. [PMID: 35128747 PMCID: PMC9305937 DOI: 10.1111/jon.12975] [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: 08/20/2021] [Revised: 12/22/2021] [Accepted: 01/18/2022] [Indexed: 11/28/2022] Open
Abstract
Background and Purpose Methods Results Conclusion
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Affiliation(s)
- Anna Lundberg
- Department of Medical Radiation Physics Lund University Lund Sweden
| | - Emelie Lind
- Department of Medical Radiation Physics Lund University Lund Sweden
| | - Hampus Olsson
- Department of Medical Radiation Physics Lund University Lund Sweden
| | - Gunther Helms
- Department of Medical Radiation Physics Lund University Lund Sweden
| | - Linda Knutsson
- Department of Medical Radiation Physics Lund University Lund Sweden
- Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine Baltimore Maryland United States
| | - Ronnie Wirestam
- Department of Medical Radiation Physics Lund University Lund Sweden
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26
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Kufer J, Preibisch C, Epp S, Göttler J, Schmitzer L, Zimmer C, Hyder F, Kaczmarz S. Imaging effective oxygen diffusivity in the human brain with multiparametric magnetic resonance imaging. J Cereb Blood Flow Metab 2022; 42:349-363. [PMID: 34590895 PMCID: PMC8795223 DOI: 10.1177/0271678x211048412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Cerebrovascular diseases can impair blood circulation and oxygen extraction from the blood. The effective oxygen diffusivity (EOD) of the capillary bed is a potential biomarker of microvascular function that has gained increasing interest, both for clinical diagnosis and for elucidating oxygen transport mechanisms. Models of capillary oxygen transport link EOD to measurable oxygen extraction fraction (OEF) and cerebral blood flow (CBF). In this work, we confirm that two well established mathematical models of oxygen transport yield nearly equivalent EOD maps. Furthermore, we propose an easy-to-implement and clinically applicable multiparametric magnetic resonance imaging (MRI) protocol for quantitative EOD mapping. Our approach is based on imaging OEF and CBF with multiparametric quantitative blood oxygenation level dependent (mq-BOLD) MRI and pseudo-continuous arterial spin labeling (pCASL), respectively. We evaluated the imaging protocol by comparing MRI-EOD maps of 12 young healthy volunteers to PET data from a published study in different individuals. Our results show comparably good correlation between MRI- and PET-derived cortical EOD, OEF and CBF. Importantly, absolute values of MRI and PET showed high accordance for all three parameters. In conclusion, our data indicates feasibility of the proposed MRI protocol for EOD mapping, rendering the method promising for future clinical evaluation of patients with cerebrovascular diseases.
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Affiliation(s)
- Jan Kufer
- Department of Neuroradiology, School of Medicine, Technical University of Munich (TUM), Munich, Germany.,TUM Neuroimaging Center (TUM-NIC), Technical University of Munich (TUM), Munich, Germany
| | - Christine Preibisch
- Department of Neuroradiology, School of Medicine, Technical University of Munich (TUM), Munich, Germany.,TUM Neuroimaging Center (TUM-NIC), Technical University of Munich (TUM), Munich, Germany.,Clinic for Neurology, School of Medicine, Technical University of Munich (TUM), Munich, Germany
| | - Samira Epp
- Department of Neuroradiology, School of Medicine, Technical University of Munich (TUM), Munich, Germany.,TUM Neuroimaging Center (TUM-NIC), Technical University of Munich (TUM), Munich, Germany
| | - Jens Göttler
- Department of Neuroradiology, School of Medicine, Technical University of Munich (TUM), Munich, Germany.,TUM Neuroimaging Center (TUM-NIC), Technical University of Munich (TUM), Munich, Germany.,Department of Radiology & Biomedical Imaging (MRRC), Yale University, New Haven, CT, USA
| | - Lena Schmitzer
- Department of Neuroradiology, School of Medicine, Technical University of Munich (TUM), Munich, Germany.,TUM Neuroimaging Center (TUM-NIC), Technical University of Munich (TUM), Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University of Munich (TUM), Munich, Germany.,TUM Neuroimaging Center (TUM-NIC), Technical University of Munich (TUM), Munich, Germany
| | - Fahmeed Hyder
- Department of Radiology & Biomedical Imaging (MRRC), Yale University, New Haven, CT, USA
| | - Stephan Kaczmarz
- Department of Neuroradiology, School of Medicine, Technical University of Munich (TUM), Munich, Germany.,TUM Neuroimaging Center (TUM-NIC), Technical University of Munich (TUM), Munich, Germany.,Department of Radiology & Biomedical Imaging (MRRC), Yale University, New Haven, CT, USA.,Philips GmbH Market DACH, Hamburg, Germany
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27
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Li J, Nguyen TD, Zhang Q, Guo L, Wang Y. Cerebral Microbleeds Are Associated With Increased Brain Iron and Cognitive Impairment in Patients With Cerebral Small Vessel Disease: A Quantitative Susceptibility Mapping Study. J Magn Reson Imaging 2022; 56:904-914. [PMID: 35099829 DOI: 10.1002/jmri.28092] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/14/2022] [Accepted: 01/19/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Cerebral microbleeds (CMBs) have been recognized to play an important role in cognitive impairment of cerebral small vessel disease (CSVD) patients. However, the mechanism of this effect is still unclear. PURPOSE Comparing the susceptibility values in the selected subcortical gray matter structures of CSVD patients without CMBs (CSVD-N) and with CMBs (CSVD-C) as well as healthy controls (HCs). STUDY TYPE Prospective. SUBJECTS Sixty-nine CSVD patients and 28 HCs were included; 24 CSVD patients (34.78%) had CMBs and 45 CSVD patients (65.22%) had no CMBs. FIELD STRENGTH/SEQUENCE All subjects were imaged on a 3.0 T MR scanner. The protocol consisted of a three-dimensional (3D) T1-weighted sequence and a 3D multi-echo gradient echo (mGRE) sequence. Brain QSM maps were computed from mGRE data using the morphology-enabled dipole inversion with automatic uniform cerebrospinal fluid zero reference algorithm (MEDI+0). ASSESSMENT The mean susceptibility value within each region of interest was recorded. All participants underwent the cognitive assessment. Brain iron deposition burden of CMB lesions of every CSVD-C patient was computed. STATISTICAL TESTS One-way analysis of variance test followed by Tukey's honest significance test and Kruskal-Wallis test were used with significance level of 0.05. Stepwise multivariate linear analysis was used to explore the factors influencing cognitive scores. RESULTS Montreal cognitive assessment (MoCA), trail-making test (TMT)-A and TMT-B scores in the three groups were significantly different (all P < 0.05). Stepwise multivariate linear regression analysis revealed that the factors influenced MoCA scores were having CMBs (P < 0.05), white matter hyperintensities (P < 0.05), lacunes (P < 0.05) in brain, and the brain iron deposition burden of CMB lesions (P < 0.05) and for TMT scores (TMT-A + TMT-B), the influencing factors were age (P < 0.05), education years (P < 0.05), and the brain iron deposition burden of CMB lesions (P < 0.05). DATA CONCLUSION The higher iron deposition burden of CMB lesions in brain may be an imaging quantitative marker of cognitive decline in patients with CSVD-C. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Jing Li
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, 95 Yong-an Road, Beijing, 10050, China
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, 407 East 61st Street, New York, 10044, USA
| | - Qihao Zhang
- Department of Radiology, Weill Cornell Medical College, 407 East 61st Street, New York, 10044, USA
| | - Lingfei Guo
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jing-wu Road, Jinan, 250021, China
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, 407 East 61st Street, New York, 10044, USA
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28
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Straub S, Stiegeler J, El-Sanosy E, Bendszus M, Ladd ME, Schneider TM. A novel gradient echo data based vein segmentation algorithm and its application for the detection of regional cerebral differences in venous susceptibility. Neuroimage 2022; 250:118931. [PMID: 35085764 DOI: 10.1016/j.neuroimage.2022.118931] [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: 10/11/2021] [Revised: 01/14/2022] [Accepted: 01/23/2022] [Indexed: 11/18/2022] Open
Abstract
Accurate segmentation of cerebral venous vasculature from gradient echo data is of central importance in several areas of neuroimaging such as for the susceptibility-based assessment of brain oxygenation or planning of electrode placement in deep brain stimulation. In this study, a vein segmentation algorithm for single- and multi-echo gradient echo data is proposed. First, susceptibility maps, true susceptibility-weighted images, and, in the multi-echo case, R2* maps were generated from the gradient echo data. These maps were filtered with an inverted Hamming filter to suppress background contrast as well as artifacts from field inhomogeneities at the brain boundaries. A shearlet-based scale-wise representation was generated to calculate a vesselness function and to generate segmentations based on local thresholding. The accuracy of the proposed algorithm was evaluated for different echo times and image resolutions using a manually generated reference segmentation and two vein segmentation algorithms (Frangi vesselness-based, recursive vesselness filter) as a reference with the Dice and Cohen's coefficients as well as the modified Hausdorff distance. The Frangi-based and recursive vesselness filter methods were significantly outperformed with regard to all error metrics. Applying the algorithm, susceptibility differences likely related to differences in blood oxygenation between superficial and deep venous territories could be demonstrated.
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Affiliation(s)
- Sina Straub
- Divison of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Janis Stiegeler
- Divison of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Edris El-Sanosy
- Divison of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg, Im Neuenheimer Feld 400, Heidelberg 69120, Germany
| | - Mark E Ladd
- Divison 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
| | - Till M Schneider
- Department of Neuroradiology, University of Heidelberg, Im Neuenheimer Feld 400, Heidelberg 69120, Germany.
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Chen J, Zhang Z, Nie X, Xu Y, Liu C, Zhao X, Wang Y. Predictive value of thrombus susceptibility for cardioembolic stroke by quantitative susceptibility mapping. Quant Imaging Med Surg 2022; 12:550-557. [PMID: 34993100 DOI: 10.21037/qims-21-235] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 05/20/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND The hypointense blooming signal of thrombi on susceptibility-weighted imaging (SWI), known as the susceptibility vessel sign (SVS), is predictive of cardioembolic stroke. The SVS originates from the local magnetic susceptibility effect; thus, the susceptibility value of thrombi may provide useful information in discriminating stroke etiology. We aim to utilize quantitative susceptibility mapping (QSM) to assess thrombus's susceptibility value in acute ischemic stroke patients and explore the relationship of thrombus susceptibility with cardioembolic stroke. METHODS From 2018 to 2020, 132 consecutive acute ischemic stroke patients with middle cerebral artery occlusion were recruited within 48 hours of onset. All patients underwent a three-dimensional multi-echo SWI scan using a 3 Tesla magnetic resonance imaging scanner. The SVS presence and the diameter of the SVS-related hypointense signal were assessed on SWI. QSM was applied to compute the susceptibility value of the thrombus. The receiver operating characteristic (ROC) methodology was used to define the optimal cutoff value of the susceptibility in QSM and the diameter on SWI for predicting cardioembolic stroke. RESULTS The SVS was identified in 93 (70.5%) patients with symptomatic middle cerebral artery occlusion and was significantly associated with cardioembolism. The hyperintense signal on QSM in the corresponding middle cerebral artery occlusion was present in 116 (87.9%) patients. ROC analysis indicated that thrombus susceptibility had a greater area under the curve than that of the SVS diameter (0.88 vs. 0.70, P<0.001) and that the optimal cutoff value of thrombus susceptibility for cardioembolism was 0.35 ppm. Multivariate analysis demonstrated that thrombus susceptibility (≥0.35 ppm) was an independent predictor of cardioembolic stroke (odds ratio =20.75; 95% CI, 7.19-59.87; P<0.001), with sensitivity, specificity, a positive predictive value, and a negative predictive value of 85.2%, 80.8%, 75.4%, and 88.7%, respectively, while the SVS presence showed sensitivity, specificity, a positive predictive value, and a negative predictive value of 90.7%, 43.6%, 87.2%, and 52.7%, respectively. CONCLUSIONS Thrombus susceptibility provides superior diagnostic performance over the SVS for discriminating between cardioembolism and other stroke subtypes. Quantitative susceptibility measurements of thrombi may help predict cardioembolic stroke in patients with acute middle cerebral artery occlusion.
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Affiliation(s)
- Jie Chen
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhe Zhang
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Ximing Nie
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuyuan Xu
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Xingquan Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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30
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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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31
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Shen N, Zhang S, Cho J, Li S, Zhang J, Xie Y, Wang Y, Zhu W. Application of Cluster Analysis of Time Evolution for Magnetic Resonance Imaging -Derived Oxygen Extraction Fraction Mapping: A Promising Strategy for the Genetic Profile Prediction and Grading of Glioma. Front Neurosci 2021; 15:736891. [PMID: 34671241 PMCID: PMC8520989 DOI: 10.3389/fnins.2021.736891] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 09/06/2021] [Indexed: 11/13/2022] Open
Abstract
Background: The intratumoral heterogeneity of oxygen metabolism and angiogenesis are core hallmarks of glioma, unveiling that genetic aberrations associated with magnetic resonance imaging (MRI) phenotypes may aid in the diagnosis and treatment of glioma. Objective: To explore the predictability of MRI-based oxygen extraction fraction (OEF) mapping using cluster analysis of time evolution (CAT) for genetic profiling and glioma grading. Methods: Ninety-one patients with histopathologically confirmed glioma were examined with CAT for quantitative susceptibility mapping and quantitative blood oxygen level–dependent magnitude-based OEF mapping and dynamic contrast-enhanced (DCE) MRI. Imaging biomarkers, including oxygen metabolism (OEF) and angiogenesis [volume transfer constant, cerebral blood volume (CBV), and cerebral blood flow], were investigated to predict IDH mutation, O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status, receptor tyrosine kinase (RTK) subgroup, and differentiation of glioblastoma (GBM) vs. lower-grade glioma (LGG). The corresponding DNA sequencing was also obtained. Results were compared with DCE-MRI using receiver operating characteristic (ROC) analysis. Results: IDH1-mutated LGGs exhibited significantly lower OEF and hypoperfusion than IDH wild-type tumors (all p < 0.01). OEF and perfusion metrics showed a tendency toward higher values in MGMT unmethylated GBM, but only OEF retained significance (p = 0.01). Relative prevalence of RTK alterations was associated with increased OEF (p = 0.003) and perfusion values (p < 0.05). ROC analysis suggested OEF achieved best performance for IDH mutation detection [area under the curve (AUC) = 0.828]. None of the investigated parameters enabled prediction of MGMT status except OEF with a moderate AUC of 0.784. Predictive value for RTK subgroup was acceptable by using OEF (AUC = 0.764) and CBV (AUC = 0.754). OEF and perfusion metrics demonstrated excellent performance in glioma grading. Moreover, mutational landscape revealed hypoxia or angiogenesis-relevant gene signatures were associated with specific imaging phenotypes. Conclusion: CAT for MRI-based OEF mapping is a promising technology for oxygen measurement and along with perfusion MRI can predict genetic profiles and tumor grade in a non-invasive and clinically relevant manner. Clinical Impact: Physiological imaging provides an in vivo portrait of genetic alterations in glioma and offers a potential strategy for non-invasively selecting patients for individualized therapies.
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Affiliation(s)
- Nanxi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Shihui Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ju Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Xie
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States.,Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Reduced magnetic resonance angiography signal intensity in the middle cerebral artery ipsilateral to severe carotid stenosis may be a practical index of high oxygen extraction fraction. Eur Radiol 2021; 32:2023-2029. [PMID: 34642810 PMCID: PMC8831255 DOI: 10.1007/s00330-021-08272-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 07/27/2021] [Accepted: 08/12/2021] [Indexed: 12/04/2022]
Abstract
Objectives Angiographic “slow flow” in the middle cerebral artery (MCA), caused by carotid stenosis, may be associated with high oxygen extraction fraction (OEF). If the MCA slow flow is associated with a reduced relative signal intensity (rSI) of the MCA on MR angiography, the reduced rSI may be associated with a high OEF. We investigated whether the MCA slow flow ipsilateral to carotid stenosis was associated with a high OEF and aimed to create a practical index to estimate the high OEF. Methods We included patients who underwent digital subtraction angiography (DSA) and MRA between 2015 and 2019 to evaluate carotid stenosis. MCA slow flow by image count using DSA, MCA rSI, minimal luminal diameter (MLD) of the carotid artery, carotid artery stenosis rate (CASr), and whole-brain OEF (wb-OEF) was evaluated. When MCA slow flow was associated with a high wb-OEF, the determinants of MCA slow flow were identified, and their association with high wb-OEF was evaluated. Results One hundred and twenty-seven patients met our inclusion criteria. Angiographic MCA slow flow was associated with high wb-OEF. We identified MCA rSI and MLD as determinants of angiographic MCA slow flow. The upper limits of MCA rSI and MLD for angiographic MCA slow flow were 0.89 and 1.06 mm, respectively. The wb-OEF was higher in patients with an MCA rSI ≤ 0.89 and ipsilateral MLD ≤ 1.06 mm than patients without this combination. Conclusions The combination of reduced MCA rSI and ipsilateral narrow MLD is a straightforward index of high wb-OEF. Key Points • The whole-brain OEF in patients with angiographic slow flow in the MCA ipsilateral to high-grade carotid stenosis was higher than in patients without it. • Independent determinants of MCA slow flow were MCA relative signal intensity (rSI) on MRA or minimal luminal diameter (MLD) of the carotid stenosis. • The wb-OEF was higher in patients with an MCA rSI ≤ 0.89 and ipsilateral MLD ≤ 1.06 mm than patients without this combination. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-021-08272-3.
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Igarashi S, Ando T, Takahashi T, Yoshida J, Kobayashi M, Yoshida K, Terasaki K, Fujiwara S, Kubo Y, Ogasawara K. Development of cerebral microbleeds in patients with cerebral hyperperfusion following carotid endarterectomy and its relation to postoperative cognitive decline. J Neurosurg 2021; 135:1122-1128. [PMID: 33386017 DOI: 10.3171/2020.7.jns202353] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 07/27/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE A primary cause of cognitive decline after carotid endarterectomy (CEA) is cerebral injury due to cerebral hyperperfusion. However, the mechanisms of how cerebral hyperperfusion induces cerebral cortex and white matter injury are not known. The presence of cerebral microbleeds (CMBs) on susceptibility-weighted imaging (SWI) is independently associated with a decline in global cognitive function. The purpose of this prospective observational study was to determine whether cerebral hyperperfusion following CEA leads to the development of CMBs and if postoperative cognitive decline is related to these developed CMBs. METHODS During the 27-month study period, patients who underwent CEA for ipsilateral internal carotid artery stenosis (≥ 70%) also underwent SWI and neuropsychological testing before and 2 months after surgery, as well as quantitative brain perfusion SPECT prior to and immediately after surgery. RESULTS According to quantitative brain perfusion SPECT and SWI before and after surgery, 12 (16%) and 7 (9%) of 75 patients exhibited postoperative cerebral hyperperfusion and increased CMBs in the cerebral hemisphere ipsilateral to surgery, respectively. Cerebral hyperperfusion was associated with an increase in CMBs after surgery (logistic regression analysis, 95% CI 5.08-31.25, p < 0.0001). According to neuropsychological assessments before and after surgery, 10 patients (13%) showed postoperative cognitive decline. Increased CMBs were associated with cognitive decline after surgery (logistic regression analysis, 95% CI 6.80-66.67, p < 0.0001). Among the patients with cerebral hyperperfusion after surgery, the incidence of postoperative cognitive decline was higher in those with increased CMBs (100%) than in those without (20%; p = 0.0101). CONCLUSIONS Cerebral hyperperfusion following CEA leads to the development of CMBs, and postoperative cognitive decline is related to these developed CMBs.
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Affiliation(s)
| | | | | | | | - Masakazu Kobayashi
- 1Department of Neurosurgery and
- 2Cyclotron Research Center, Iwate Medical University School of Medicine, Morioka, Japan
| | | | - Kazunori Terasaki
- 2Cyclotron Research Center, Iwate Medical University School of Medicine, Morioka, Japan
| | | | | | - Kuniaki Ogasawara
- 1Department of Neurosurgery and
- 2Cyclotron Research Center, Iwate Medical University School of Medicine, Morioka, Japan
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Wu D, Zhou Y, Cho J, Shen N, Li S, Qin Y, Zhang G, Yan S, Xie Y, Zhang S, Zhu W, Wang Y. The Spatiotemporal Evolution of MRI-Derived Oxygen Extraction Fraction and Perfusion in Ischemic Stroke. Front Neurosci 2021; 15:716031. [PMID: 34483830 PMCID: PMC8415351 DOI: 10.3389/fnins.2021.716031] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 07/12/2021] [Indexed: 12/13/2022] Open
Abstract
Purpose This study aimed to assess the spatiotemporal evolution of oxygen extraction fraction (OEF) in ischemic stroke with a newly developed cluster analysis of time evolution (CAT) for a combined quantitative susceptibility mapping and quantitative blood oxygen level-dependent model (QSM + qBOLD, QQ). Method One hundred and fifteen patients in different ischemic stroke phases were retrospectively collected for measurement of OEF of the infarcted area defined on diffusion-weighted imaging (DWI). Clinical severity was assessed using the National Institutes of Health Stroke Scale (NIHSS). Of the 115 patients, 11 underwent two longitudinal MRI scans, namely, three-dimensional (3D) multi-echo gradient recalled echo (mGRE) and 3D pseudo-continuous arterial spin labeling (pCASL), to evaluate the reversal region (RR) of the initial diffusion lesion (IDL) that did not overlap with the final infarct (FI). The temporal evolution of OEF and the cerebral blood flow (CBF) in the IDL, the RR, and the FI were assessed. Results Compared to the contralateral mirror area, the OEF of the infarcted region was decreased regardless of stroke phases (p < 0.05) and showed a declining tendency from the acute to the chronic phase (p = 0.022). Five of the 11 patients with longitudinal scans showed reversal of the IDL. Relative oxygen extraction fraction (rOEF, compared to the contralateral mirror area) of the RR increased from the first to the second MRI (p = 0.044). CBF was about 1.5-fold higher in the IDL than in the contralateral mirror area in the first MRI. Two patients showed penumbra according to the enlarged FI volume. The rOEF of the penumbra fluctuated around 1.0 at earlier scan times and then decreased, while the CBF decreased continuously. Conclusion The spatiotemporal evolution of OEF and perfusion in ischemic lesions is heterogeneous, and the CAT-based QQ method is feasible to capture cerebral oxygen metabolic information.
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Affiliation(s)
- Di Wu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yiran Zhou
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States.,Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Nanxi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shihui Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guiling Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Su Yan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Xie
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States.,Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
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Berg RC, Preibisch C, Thomas DL, Shmueli K, Biondetti E. Investigating the effect of flow compensation and quantitative susceptibility mapping method on the accuracy of venous susceptibility measurement. Neuroimage 2021; 240:118399. [PMID: 34273528 DOI: 10.1016/j.neuroimage.2021.118399] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 06/15/2021] [Accepted: 07/13/2021] [Indexed: 11/25/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) is a promising non-invasive method for obtaining information relating to oxygen metabolism. However, the optimal acquisition sequence and QSM reconstruction method for reliable venous susceptibility measurements are unknown. Full flow compensation is generally recommended to correct for the influence of venous blood flow, although the effect of flow compensation on the accuracy of venous susceptibility values has not been systematically evaluated. In this study, we investigated the effect of different acquisition sequences, including different flow compensation schemes, and different QSM reconstruction methods on venous susceptibilities. Ten healthy subjects were scanned with five or six distinct QSM sequence designs using monopolar readout gradients and different flow compensation schemes. All data sets were processed using six different QSM pipelines and venous blood susceptibility was evaluated in whole-brain segmentations of the venous vasculature and single veins. The quality of vein segmentations and the accuracy of venous susceptibility values were analyzed and compared between all combinations of sequences and reconstruction methods. The influence of the QSM reconstruction method on average venous susceptibility values was found to be 2.7-11.6 times greater than the influence of the acquisition sequence, including flow compensation. The majority of the investigated QSM reconstruction methods tended to underestimate venous susceptibility values in the vein segmentations that were obtained. In summary, we found that multi-echo gradient-echo acquisition sequences without full flow compensation yielded venous susceptibility values comparable to sequences with full flow compensation. However, the QSM reconstruction method had a great influence on susceptibility values and thus needs to be selected carefully for accurate venous QSM.
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Affiliation(s)
- Ronja C Berg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany.
| | - 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, Ismaninger Str. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Neurology, Ismaninger Str. 22, 81675 Munich, Munich, Germany.
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom.
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, United Kingdom.
| | - Emma Biondetti
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, United Kingdom; Institut du Cerveau - ICM, Centre de NeuroImagerie de Recherche - CENIR, Team "Movement Investigations and Therapeutics" (MOV'IT), INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France.
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Cho J, Lee J, An H, Goyal MS, Su Y, Wang Y. Cerebral oxygen extraction fraction (OEF): Comparison of challenge-free gradient echo QSM+qBOLD (QQ) with 15O PET in healthy adults. J Cereb Blood Flow Metab 2021; 41:1658-1668. [PMID: 33243071 PMCID: PMC8221765 DOI: 10.1177/0271678x20973951] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We aimed to validate oxygen extraction fraction (OEF) estimations by quantitative susceptibility mapping plus quantitative blood oxygen-level dependence (QSM+qBOLD, or QQ) using 15O-PET. In ten healthy adult brains, PET and MRI were acquired simultaneously on a PET/MR scanner. PET was acquired using C[15O], O[15O], and H2[15O]. Image-derived arterial input functions and standard models of oxygen metabolism provided quantification of PET. MRI included T1-weighted imaging, time-of-flight angiography, and multi-echo gradient-echo imaging that was processed for QQ. Region of interest (ROI) analyses compared PET OEF and QQ OEF. In ROI analyses, the averaged OEF differences between PET and QQ were generally small and statistically insignificant. For whole brains, the average and standard deviation of OEF was 32.8 ± 6.7% for PET; OEF was 34.2 ± 2.6% for QQ. Bland-Altman plots quantified agreement between PET OEF and QQ OEF. The interval between the 95% limits of agreement was 16.9 ± 4.0% for whole brains. Our validation study suggests that respiratory challenge-free QQ-OEF mapping may be useful for non-invasive clinical assessment of regional OEF impairment.
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Affiliation(s)
- Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, USA
| | - John Lee
- Mallinkckrodt Institute of Radiology, Washington University School of Medicine, St Louis, USA
| | - Hongyu An
- Mallinkckrodt Institute of Radiology, Washington University School of Medicine, St Louis, USA
| | - Manu S Goyal
- Mallinkckrodt Institute of Radiology, Washington University School of Medicine, St Louis, USA
| | - Yi Su
- Computational Image Analysis, Banner Alzheimer's Institute, Phoenix, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, USA.,Department of Biomedical Engineering, Cornell University, Ithaca, USA
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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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Gozt A, Hellewell S, Ward PGD, Bynevelt M, Fitzgerald M. Emerging Applications for Quantitative Susceptibility Mapping in the Detection of Traumatic Brain Injury Pathology. Neuroscience 2021; 467:218-236. [PMID: 34087394 DOI: 10.1016/j.neuroscience.2021.05.030] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 05/24/2021] [Accepted: 05/25/2021] [Indexed: 12/16/2022]
Abstract
Traumatic brain injury (TBI) is a common but heterogeneous injury underpinned by numerous complex and interrelated pathophysiological mechanisms. An essential trace element, iron is abundant within the brain and involved in many fundamental neurobiological processes, including oxygen transportation, oxidative phosphorylation, myelin production and maintenance, as well as neurotransmitter synthesis and metabolism. Excessive levels of iron are neurotoxic and thus iron homeostasis is tightly regulated in the brain, however, many details about the mechanisms by which this is achieved are yet to be elucidated. A key mediator of oxidative stress, mitochondrial dysfunction and neuroinflammatory response, iron dysregulation is an important contributor to secondary injury in TBI. Advances in neuroimaging that leverage magnetic susceptibility properties have enabled increasingly comprehensive investigations into the distribution and behaviour of iron in the brain amongst healthy individuals as well as disease states such as TBI. Quantitative Susceptibility Mapping (QSM) is an advanced neuroimaging technique that promises quantitative estimation of local magnetic susceptibility at the voxel level. In this review, we provide an overview of brain iron and its homeostasis, describe recent advances enabling applications of QSM within the context of TBI and summarise the current state of the literature. Although limited, the emergent research suggests that QSM is a promising neuroimaging technique that can be used to investigate a host of pathophysiological changes that are associated with TBI.
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Affiliation(s)
- Aleksandra Gozt
- Curtin University, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Bentley, WA Australia; Perron Institute for Neurological and Translational Science, Nedlands, WA Australia
| | - Sarah Hellewell
- Curtin University, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Bentley, WA Australia
| | - Phillip G D Ward
- Australian Research Council Centre of Excellence for Integrative Brain Function, VIC Australia; Turner Institute for Brain and Mental Health, Monash University, VIC Australia
| | - Michael Bynevelt
- Neurological Intervention and Imaging Service of Western Australia, Sir Charles Gairdner Hospital, Nedlands, WA Australia
| | - Melinda Fitzgerald
- Curtin University, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Bentley, WA Australia; Perron Institute for Neurological and Translational Science, Nedlands, WA Australia.
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Ebrahimi T, Tafakhori A, Hashemi H, Ali Oghabian M. An interictal measurement of cerebral oxygen extraction fraction in MRI-negative refractory epilepsy using quantitative susceptibility mapping. Phys Med 2021; 85:87-97. [PMID: 33984822 DOI: 10.1016/j.ejmp.2021.03.039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 03/19/2021] [Accepted: 03/30/2021] [Indexed: 11/16/2022] Open
Abstract
PURPOSE Oxygen extraction fraction (OEF) can be a factor to identify brain tissue's disability in epileptic patients. This study aimed to assess the OEF's level measurement in refractory epileptic patients (REPs) using a quantitative susceptibility mapping (QSM) method and to determine whether the OEF parameters change. METHODS QSM-OEF maps of 26 REPs and 16 healthy subjects were acquired using 3T MRI with a 64-channel coil. Eighteen regions-of-interest (ROIs) were chosen around the cortex in one appropriate slice of the brain and the mean QSM-OEF for each ROI was obtained. The correlations of QSM-OEF among different clinical characteristics of the disease, as well as between the patients and normal subjects, were also investigated. RESULTS QSM-OEF was shown to be significantly higher in REPs (44.9 ± 5.8) than that in HS (41.9 ± 6.2) (p < 0.05). Mean QSM-OEF was statistically lower in the ipsilateral side (44.5 ± 6.6) compared to the contralateral side (46.4 ± 6.8) (P < 0.01). QSM-OEF was illustrated to have a strong positive correlation with the attack duration (r = 0.6), and a moderate negative correlation with the attack frequency (r = -0.3). Using an optimized support vector machine algorithm, we could predict the disease in subjects having abnormal OEF values in the brain-selected-ROIs with sensitivity, specificity, AUC, and the precision of 0.96, 1, 0.98, and 1, respectively. CONCLUSIONS The results of this study revealed that QSM-OEF of the REPs' brain is higher than that of HS, which indicates that QSM-OEF is associated with disease activity.
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Affiliation(s)
- Tayyebeh Ebrahimi
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Department of Neuroimaging and Analysis, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
| | - Abbas Tafakhori
- Iranian Center of Neurological Research (ICNR), Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Hassan Hashemi
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran.
| | - Mohammad Ali Oghabian
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Department of Neuroimaging and Analysis, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran; Research Center for Molecular and Cellular Imaging, Tehran University of Medical Science, Tehran, Iran.
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40
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McFadden JJ, Matthews JC, Scott LA, Parker GJM, Lohézic M, Parkes LM. Optimization of quantitative susceptibility mapping for regional estimation of oxygen extraction fraction in the brain. Magn Reson Med 2021; 86:1314-1329. [PMID: 33780045 DOI: 10.1002/mrm.28789] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 03/05/2021] [Accepted: 03/08/2021] [Indexed: 01/20/2023]
Abstract
PURPOSE We sought to determine the degree to which oxygen extraction fraction (OEF) estimated using quantitative susceptibility mapping (QSM) depends on two critical acquisition parameters that have a significant impact on acquisition time: voxel size and final echo time. METHODS Four healthy volunteers were imaged using a range of isotropic voxel sizes and final echo times. The 0.7 mm data were downsampled at different stages of QSM processing by a factor of 2 (to 1.4 mm), 3 (2.1 mm), or 4 (2.8 mm) to determine the impact of voxel size on each analysis step. OEF was estimated from 11 veins of varying diameter. Inter- and intra-session repeatability were estimated for the optimal protocol by repeat scanning in 10 participants. RESULTS Final echo time was found to have no significant effect on OEF. The effect of voxel size was significant, with larger voxel sizes underestimating OEF, depending on the proximity of the vein to the superficial surface of the brain and on vein diameter. The last analysis step of estimating vein OEF values from susceptibility images had the largest dependency on voxel size. Inter-session coefficients of variation on OEF estimates of between 5.2% and 8.7% are reported, depending on the vein. CONCLUSION QSM acquisition times can be minimized by reducing the final echo time but an isotropic voxel size no larger than 1 mm is needed to accurately estimate OEF in most medium/large veins in the brain. Such acquisitions can be achieved in under 4 min.
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Affiliation(s)
- John J McFadden
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Julian C Matthews
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Lauren A Scott
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Geoff J M Parker
- Bioxydyn Limited, Manchester, United Kingdom.,Centre for Medical Image Computing, Department of Computer Science and Department of Neuroinflammation, University College London, London, United Kingdom
| | - Maélène Lohézic
- Applications & Workflow, GE Healthcare, Manchester, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
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Jiang D, Deng S, Franklin CG, O’Boyle M, Zhang W, Heyl BL, Pan L, Jerabek PA, Fox PT, Lu H. Validation of T 2 -based oxygen extraction fraction measurement with 15 O positron emission tomography. Magn Reson Med 2021; 85:290-297. [PMID: 32643207 PMCID: PMC9973312 DOI: 10.1002/mrm.28410] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 05/19/2020] [Accepted: 06/11/2020] [Indexed: 12/20/2022]
Abstract
PURPOSE To evaluate the accuracy of T2 -based whole-brain oxygen extraction fraction (OEF) estimation by comparing it with gold standard 15 O-PET measurements. METHODS Sixteen healthy adult subjects underwent MRI and 15 O-PET OEF measurements on the same day. On MRI, whole-brain OEF was quantified by T2 -relaxation-under-spin-tagging (TRUST) MRI, based on subject-specific hematocrit. The TRUST OEF was compared to the whole-brain averaged OEF produced by 15 O-PET. Agreement between TRUST and 15 O-PET whole-brain OEF measurements was examined in terms of intraclass correlation coefficient (ICC) and in absolute OEF values. In a subset of 10 subjects, test-retest reproducibility of whole-brain OEF was also evaluated and compared between the two modalities. RESULTS Across the 16 subjects, the mean whole-brain OEF of TRUST and 15 O-PET were 36.44 ± 4.07% and 36.45 ± 3.65%, respectively, showing no difference between the two modalities (P = .99). TRUST whole-brain OEF strongly correlated with that of 15 O-PET (N = 16, ICC = 0.90, P = 4 × 10-7 ). The coefficient-of-variation of TRUST and 15 O-PET whole-brain OEF measurements were 1.79 ± 0.67% and 2.06 ± 1.55%, respectively, showing no difference between the two modalities (N = 10, P = .64). Further analyses on the effect of hematocrit revealed that correlation between PET OEF and TRUST OEF with assumed hematocrit remained significant (ICC = 0.8, P < 2 × 10-5 ). CONCLUSION Whole-brain OEF measured by TRUST was in excellent agreement with gold standard 15 O-PET, with highly comparable accuracy and reproducibility. These findings suggest that TRUST MRI can provide accurate quantification of whole-brain OEF noninvasively.
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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.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Shengwen Deng
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Crystal G. Franklin
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Michael O’Boyle
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Wei Zhang
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Betty L. Heyl
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Li Pan
- Siemens Healthineers, Baltimore, Maryland, USA
| | - Paul A. Jerabek
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Peter T. Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.,Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA,South Texas Veterans Health Care System, San Antonio, Texas, 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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Zhang S, Cho J, Nguyen TD, Spincemaille P, Gupta A, Zhu W, Wang Y. Initial Experience of Challenge-Free MRI-Based Oxygen Extraction Fraction Mapping of Ischemic Stroke at Various Stages: Comparison With Perfusion and Diffusion Mapping. Front Neurosci 2020; 14:535441. [PMID: 33041755 PMCID: PMC7525031 DOI: 10.3389/fnins.2020.535441] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Accepted: 08/18/2020] [Indexed: 01/01/2023] Open
Abstract
MRI-based oxygen extraction fraction imaging has a great potential benefit in the selection of clinical strategies for ischemic stroke patients. This study aimed to evaluate the performance of a challenge-free oxygen extraction fraction (OEF) mapping in a cohort of acute and subacute ischemic stroke patients. Consecutive ischemic stroke patients (a total of 30 with 5 in the acute stage, 19 in the early subacute stage, and 6 in the late subacute stage) were recruited. All subjects underwent MRI including multi-echo gradient echo (mGRE), diffusion weighted imaging (DWI), and 3D-arterial spin labeling (ASL). OEF maps were generated from mGRE phase + magnitude data, which were processed using quantitative susceptibility mapping (QSM) + quantitative blood oxygen level-dependent (qBOLD) imaging with cluster analysis of time evolution. Cerebral blood flow (CBF) and apparent diffusion coefficient (ADC) maps were reconstructed from 3D-ASL and DWI, respectively. Further, cerebral metabolic rate of oxygen (CMRO2) was calculated as the product of CBF and OEF. OEF, CMRO2, CBF, and ADC values in the ischemic cores (absolute values) and their contrasts to the contralateral regions (relative values) were evaluated. One-way analysis of variance (ANOVA) was used to compare OEF, CMRO2, CBF, and ADC values and their relative values among different stroke stages. The OEF value of infarct core showed a trend of decrease from acute, to early subacute, and to late subacute stages of ischemic stroke. Significant differences among the three stroke stages were only observed in the absolute OEF (F = 6.046, p = 0.005) and relative OEF (F = 5.699, p = 0.009) values of the ischemic core, but not in other measurements (absolute and relative CMRO2, CBF, ADC values, all values of p > 0.05). In conclusion, the challenge-free QSM + qBOLD-generated OEF mapping can be performed on stroke patients. It can provide more information on tissue viability that was not available with CBF and ADC and, thus, may help to better manage ischemic stroke patients.
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Affiliation(s)
- Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Thanh D. Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
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Guo R, Zhao Y, Li Y, Wang T, Li Y, Sutton B, Liang ZP. Simultaneous QSM and metabolic imaging of the brain using SPICE: Further improvements in data acquisition and processing. Magn Reson Med 2020; 85:970-977. [PMID: 32810319 DOI: 10.1002/mrm.28459] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 07/09/2020] [Accepted: 07/12/2020] [Indexed: 01/23/2023]
Abstract
PURPOSE To achieve high-resolution mapping of brain tissue susceptibility in simultaneous QSM and metabolic imaging. METHODS Simultaneous QSM and metabolic imaging was first achieved using SPICE (spectroscopic imaging by exploiting spatiospectral correlation), but the QSM maps thus obtained were at relatively low-resolution (2.0 × 3.0 × 3.0 mm3 ). We overcome this limitation using an improved SPICE data acquisition method with the following novel features: 1) sampling (k, t)-space in dual densities, 2) sampling central k-space fully to achieve nominal spatial resolution of 3.0 × 3.0 × 3.0 mm3 for metabolic imaging, and 3) sampling outer k-space sparsely to achieve spatial resolution of 1.0 × 1.0 × 1.9 mm3 for QSM. To keep the scan time short, we acquired spatiospectral encodings in echo-planar spectroscopic imaging trajectories in central k-space but in CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) trajectories in outer k-space using blipped phase encodings. For data processing and image reconstruction, a union-of-subspaces model was used, effectively incorporating sensitivity encoding, spatial priors, and spectral priors of individual molecules. RESULTS In vivo experiments were carried out to evaluate the feasibility and potential of the proposed method. In a 6-min scan, QSM maps at 1.0 × 1.0 × 1.9 mm3 resolution and metabolic maps at 3.0 × 3.0 × 3.0 mm3 nominal resolution were obtained simultaneously. Compared with the original method, the QSM maps obtained using the new method reveal fine-scale brain structures more clearly. CONCLUSION We demonstrated the feasibility of achieving high-resolution QSM simultaneously with metabolic imaging using a modified SPICE acquisition method. The improved capability of SPICE may further enhance its practical utility in brain mapping.
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Affiliation(s)
- Rong Guo
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Yibo Zhao
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Yudu Li
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Tianyao Wang
- Department of Radiology, The Fifth People's Hospital of Shanghai, Fudan University, Shanghai, People's Republic of China
| | - Yao Li
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Brad Sutton
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois.,Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Zhi-Pei Liang
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
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Cho J, Ma Y, Spincemaille P, Pike GB, Wang Y. Cerebral oxygen extraction fraction: Comparison of dual-gas challenge calibrated BOLD with CBF and challenge-free gradient echo QSM+qBOLD. Magn Reson Med 2020; 85:953-961. [PMID: 32783233 DOI: 10.1002/mrm.28447] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 06/23/2020] [Accepted: 07/06/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To compare cortical gray matter oxygen extraction fraction (OEF) estimated from 2 MRI methods: (1) the quantitative susceptibility mapping (QSM) plus quantitative blood oxygen level dependent imaging (qBOLD) (QSM+qBOLD or QQ), and (2) the dual-gas calibrated-BOLD (DGCB) in healthy subjects; and to investigate the validity of iso-cerebral metabolic rate of oxygen consumption assumption during hypercapnia using QQ. METHODS In 10 healthy subjects, 3 tesla MRI including a multi-echo gradient echo sequence at baseline and hypercapnia for QQ, as well as an EPI dual-echo pseudo-continuous arterial spin labeling for DGCB, were performed under a hypercapnic and a hyperoxic condition. OEFs from QQ and DGCB were compared using region of interest analysis and paired t test. For QQ, cerebral metabolic rate of oxygen consumption = cerebral blood flow*OEF*arterial oxygen content was generated for both baseline and hypercapnia, which were compared. RESULTS Average OEF in cortical gray matter across 10 subjects from QQ versus DGCB was 35.5 ± 6.7% versus 38.0 ± 9.1% (P = .49) at baseline and 20.7 ± 4.4% versus 28.4 ± 7.6% (P = .02) in hypercapnia: OEF in cortical gray matter was significantly reduced as measured in QQ (P < .01) and in DGCB (P < .01). Cerebral metabolic rate of oxygen consumption (in μmol O2 /min/100 g) was 168.2 ± 54.1 at baseline from DGCB and was 153.1 ± 33.8 at baseline and 126.4 ± 34.2 (P < .01) in hypercapnia from QQ. CONCLUSION The differences in OEF obtained from QQ and DGCB are small and nonsignificant at baseline but are statistically significant during hypercapnia. In addition, QQ shows a cerebral metabolic rate of oxygen consumption decrease (17.4%) during hypercapnia.
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Affiliation(s)
- Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Yuhan Ma
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Gilbert Bruce Pike
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.,Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA.,Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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Fan AP, An H, Moradi F, Rosenberg J, Ishii Y, Nariai T, Okazawa H, Zaharchuk G. Quantification of brain oxygen extraction and metabolism with [ 15O]-gas PET: A technical review in the era of PET/MRI. Neuroimage 2020; 220:117136. [PMID: 32634594 PMCID: PMC7592419 DOI: 10.1016/j.neuroimage.2020.117136] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/15/2020] [Accepted: 07/01/2020] [Indexed: 12/31/2022] Open
Abstract
Oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2) are key cerebral physiological parameters to identify at-risk cerebrovascular patients and understand brain health and function. PET imaging with [15O]-oxygen tracers, either through continuous or bolus inhalation, provides non-invasive assessment of OEF and CMRO2. Numerous tracer delivery, PET acquisition, and kinetic modeling approaches have been adopted to map brain oxygenation. The purpose of this technical review is to critically evaluate different methods for [15O]-gas PET and its impact on the accuracy and reproducibility of OEF and CMRO2 measurements. We perform a meta-analysis of brain oxygenation PET studies in healthy volunteers and compare between continuous and bolus inhalation techniques. We also describe OEF metrics that have been used to detect hemodynamic impairment in cerebrovascular disease. For these patients, advanced techniques to accelerate the PET scans and potential synthesis with MRI to avoid arterial blood sampling would facilitate broader use of [15O]-oxygen PET for brain physiological assessment.
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Affiliation(s)
- Audrey P Fan
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Biomedical Engineering and Department of Neurology, University of California Davis, Davis, CA, USA.
| | - Hongyu An
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Farshad Moradi
- Department of Radiology, Stanford University, Stanford, CA, USA
| | | | - Yosuke Ishii
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Tadashi Nariai
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hidehiko Okazawa
- Biomedical Imaging Research Center, University of Fukui, Fukui, Japan
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
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46
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Ma Y, Mazerolle EL, Cho J, Sun H, Wang Y, Pike GB. Quantification of brain oxygen extraction fraction using QSM and a hyperoxic challenge. Magn Reson Med 2020; 84:3271-3285. [DOI: 10.1002/mrm.28390] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 05/19/2020] [Accepted: 06/01/2020] [Indexed: 12/24/2022]
Affiliation(s)
- Yuhan Ma
- Department of Biomedical Engineering and McConnell Brain Imaging Centre McGill University Montréal Quebec Canada
| | - Erin L. Mazerolle
- Department of Radiology and Hotchkiss Brain Institute University of Calgary Calgary Alberta Canada
| | - Junghun Cho
- Department of Biomedical Engineering Cornell University Ithaca New York USA
| | - Hongfu Sun
- Department of Radiology and Hotchkiss Brain Institute University of Calgary Calgary Alberta Canada
- School of Information Technology and Electrical Engineering University of Queensland Brisbane Australia
| | - Yi Wang
- Department of Biomedical Engineering Cornell University Ithaca New York USA
- Department of Radiology Weill Cornell Medical College New York New York USA
| | - G. Bruce Pike
- Department of Biomedical Engineering and McConnell Brain Imaging Centre McGill University Montréal Quebec Canada
- Department of Radiology and Hotchkiss Brain Institute University of Calgary Calgary Alberta Canada
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Fujimoto K, Uwano I, Sasaki M, Oshida S, Tsutsui S, Yanagihara W, Fujiwara S, Kobayashi M, Kubo Y, Yoshida K, Terasaki K, Ogasawara K. Acetazolamide-Loaded Dynamic 7T MR Quantitative Susceptibility Mapping in Major Cerebral Artery Steno-Occlusive Disease: Comparison with PET. AJNR Am J Neuroradiol 2020; 41:785-791. [PMID: 32299799 DOI: 10.3174/ajnr.a6508] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 03/01/2020] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Dynamic changes in cerebrovascular reactivity after acetazolamide administration vary markedly among patients with major cerebral arterial steno-occlusive disease. MR quantitative susceptibility mapping can dynamically quantify the cerebral magnetic susceptibility. The purpose of this study was to determine whether dynamic changes in susceptibility after administration of acetazolamide on 7T quantitative susceptibility mapping are associated with pre-existing states of CBV and the cerebral metabolic rate of oxygen in the cerebral hemispheres with major cerebral arterial steno-occlusive disease. MATERIALS AND METHODS Sixty-five patients underwent 7T MR imaging at baseline and at 5, 10, 15, and 20 minutes after acetazolamide administration. Differences between the susceptibility of venous structures and surrounding brain tissue were calculated in the quantitative susceptibility mapping images. Susceptibility differences at 5, 10, 15, and 20 minutes after acetazolamide administration relative to baseline were calculated in 97 cerebral hemispheres with major cerebral arterial steno-occlusive disease. CBV and the cerebral metabolic rate of oxygen were also calculated using 15O-gas PET in the resting state. RESULTS Dynamic changes of susceptibility after acetazolamide administration were classified into 3 patterns: abnormally increasing 5 or 10 minutes after acetazolamide administration; abnormally decreasing within 20 minutes after acetazolamide administration; and remaining unchanged after acetazolamide administration. CBV was significantly greater in the first pattern than in the latter 2. The cerebral metabolic rate of oxygen differed significantly in descending order from the first to middle to last pattern. CONCLUSIONS Dynamic changes of susceptibility after acetazolamide administration on 7T MR quantitative susceptibility mapping are associated with pre-existing states of CBV and the cerebral metabolic rate of oxygen in major cerebral arterial steno-occlusive disease.
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Affiliation(s)
- K Fujimoto
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.)
| | - I Uwano
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences (I.U., M.S.)
| | - M Sasaki
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences (I.U., M.S.)
| | - S Oshida
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.)
| | - S Tsutsui
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.)
| | - W Yanagihara
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.)
| | - S Fujiwara
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.)
| | - M Kobayashi
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.)
| | - Y Kubo
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.)
| | - K Yoshida
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.)
| | - K Terasaki
- Cyclotron Research Center (K.T.), Iwate Medical University School of Medicine, Morioka, Japan
| | - K Ogasawara
- From the Department of Neurosurgery (K.F., S.O., S.T., W.Y., S.F., M.K., Y.K., K.Y., K.O.),
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48
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Fan AP, Khalil AA, Fiebach JB, Zaharchuk G, Villringer A, Villringer K, Gauthier CJ. Elevated brain oxygen extraction fraction measured by MRI susceptibility relates to perfusion status in acute ischemic stroke. J Cereb Blood Flow Metab 2020; 40:539-551. [PMID: 30732551 PMCID: PMC7026852 DOI: 10.1177/0271678x19827944] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Recent clinical trials of new revascularization therapies in acute ischemic stroke have highlighted the importance of physiological imaging to identify optimal treatments for patients. Oxygen extraction fraction (OEF) is a hallmark of at-risk tissue in stroke, and can be quantified from the susceptibility effect of deoxyhemoglobin molecules in venous blood on MRI phase scans. We measured OEF within cerebral veins using advanced quantitative susceptibility mapping (QSM) MRI reconstructions in 20 acute stroke patients. Absolute OEF was elevated in the affected (29.3 ± 3.4%) versus the contralateral hemisphere (25.5 ± 3.1%) of patients with large diffusion-perfusion lesion mismatch (P = 0.032). In these patients, OEF negatively correlated with relative CBF measured by dynamic susceptibility contrast MRI (P = 0.004), suggesting compensation for reduced flow. Patients with perfusion-diffusion match or no hypo-perfusion showed less OEF difference between hemispheres. Nine patients received longitudinal assessment and showed OEF ratio (affected to contralateral) of 1.2 ± 0.1 at baseline that normalized (decreased) to 1.0 ± 0.1 at follow-up three days later (P = 0.03). Our feasibility study demonstrates that QSM MRI can non-invasively quantify OEF in stroke patients, relates to perfusion status, and is sensitive to OEF changes over time. Clinical trial registration: Longitudinal MRI examinations of patients with brain ischemia and blood brain barrier permeability; clinicaltrials.org :NCT02077582.
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Affiliation(s)
- Audrey P Fan
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Ahmed A Khalil
- Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin, Berlin, Germany
| | - Jochen B Fiebach
- Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Arno Villringer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin, Berlin, Germany
| | - Kersten Villringer
- Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Claudine J Gauthier
- Department of Physics, Concordia University, Montreal, Canada.,Montreal Heart Institute, Montreal, Canada
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49
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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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50
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Sato R, Shirai T, Soutome Y, Bito Y, Ochi H. Quantitative susceptibility mapping of prostate with separate calculations for water and fat regions for reducing shading artifacts. Magn Reson Imaging 2020; 66:22-29. [DOI: 10.1016/j.mri.2019.11.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 11/03/2019] [Accepted: 11/03/2019] [Indexed: 12/12/2022]
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