Synopsis
Motivation:
Goals:
Approach:
Results:
630-01-006
ISMRM Abstract
A Novel Oxygen Extraction Fraction Mapping Technique by combining QSM and Monte-Carlo Simulation of Magnitude Signal: Qsim
Accepted
Full abstract & presentation
The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.
Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.
To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.
Log inReferences
1. Derdeyn CP, Videen TO, Yundt KD, et al. Variability of cerebral blood volume and oxygen extraction: stages of cerebral haemodynamic impairment revisited. Brain : a journal of neurology 2002; 125: 595–607. 2002/03/02.
2. Gupta A, Chazen JL, Hartman M, et al. Cerebrovascular reserve and stroke risk in patients with carotid stenosis or occlusion: a systematic review and meta-analysis. Stroke 2012; 43: 2884–2891. 2012/10/24. DOI: 10.1161/strokeaha.112.663716. [doi]
3. Gupta A, Baradaran H, Schweitzer AD, et al. Oxygen Extraction Fraction and Stroke Risk in Patients with Carotid Stenosis or Occlusion: A Systematic Review and Meta-Analysis. American Journal of Neuroradiology 2014; 35: 250–255. DOI: 10.3174/ajnr.A3668. [doi]
4. Cho J, Kee Y, Spincemaille P, et al. Cerebral metabolic rate of oxygen (CMRO2) mapping by combining quantitative susceptibility mapping (QSM) and quantitative blood oxygenation level-dependent imaging (qBOLD). Magnetic resonance in medicine 2018; 80: 1595–1604. DOI: doi:10.1002/mrm.27135. [doi]
5. Baazaoui H, Hubertus S, Maros ME, et al. Artificial neural network-derived cerebral metabolic rate of oxygen for differentiating glioblastoma and brain metastasis in MRI: a feasibility study. Applied Sciences 2021; 11: 9928.
6. Cho J, Zhang J, Spincemaille P, et al. Multi-Echo Complex Quantitative Susceptibility Mapping and Quantitative Blood Oxygen Level-Dependent Magnitude (mcQSM + qBOLD or mcQQ) for Oxygen Extraction Fraction (OEF) Mapping. Bioengineering 2024; 11: 131.
7. Wang Y, Liu Z, Zhang J, et al. System and method of perceptive quantitative mapping of physical properties. Patent US 12,072,403 B2, United States, 2024.
8. Wang Y, Wen Y, Jafari R, et al. System and method of accurate quantitative mapping of biophysical parameters from MRI data. Patent US 2023/0320611 A1, United States, 2023.
9. Wang Y, Liu Z, Zhang J, et al. System and method of perceptive quantitative mapping of physical properties. Patent US 11,782,112 B2, United States, 2023.
10. Zhou D, Cho J, Zhang J, et al. Susceptibility underestimation in a high‐susceptibility phantom: dependence on imaging resolution, magnitude contrast, and other parameters. Magnetic resonance in medicine 2017; 78: 1080–1086.
11. Kee Y, Liu Z, Zhou L, et al. Quantitative susceptibility mapping (QSM) algorithms: mathematical rationale and computational implementations. IEEE Transactions on Biomedical Engineering 2017; 64: 2531–2545.
12. Zhang J, Cho J, Zhou D, et al. Quantitative susceptibility mapping-based cerebral metabolic rate of oxygen mapping with minimum local variance. Magn Reson Med 2017 2017/03/16. DOI: 10.1002/mrm.26657. [doi]
13. Kee Y, Cho J, Deh K, et al. Coherence enhancement in quantitative susceptibility mapping by means of anisotropic weighting in morphology enabled dipole inversion. Magnetic Resonance in Medicine 2018; 79: 1172–1180.
14. Cho J, Zhou D, Kee Y, et al. Quantitative susceptibility mapping of magnetic quadrupole moments. Concepts in Magnetic Resonance Part A 2019; 2019: 7174937.
15. Wen Y, Nguyen T, Cho J, et al. Improved signal modeling in Quantitative Susceptibility Mapping using multi-echo complex Total Field Inversion (mcTFI). In.
16. Wen Y, Spincemaille P, Nguyen T, et al. Multiecho complex total field inversion method (mcTFI) for improved signal modeling in quantitative susceptibility mapping. Magnetic resonance in medicine 2021; 86: 2165–2178.
17. Li J, Huang W, Luo X, et al. The central vein sign in multiple sclerosis lesions: Susceptibility relaxation optimization from a routine MRI multiecho gradient echo sequence. Journal of Neuroimaging 2022; 32: 48–56. DOI: https://doi.org/10.1111/jon.12938. [doi]
18. Cho H, Lee H, Gong Y, et al. Quantitative susceptibility mapping and R1 measurement: Determination of the myelin volume fraction in the aging ex vivo rat corpus callosum. NMR in biomedicine 2022; 35: e4645.
19. Salman F, Ramesh A, Jochmann T, et al. Sensitivity of quantitative susceptibility mapping for clinical research in deep gray matter. Human brain mapping 2025; 46: 1–22.
20. Hubertus S, Thomas S, Cho JH, et al. Comparison of gradient echo and gradient echo sampling of spin echo sequence for the quantification of the oxygen extraction fraction from a combined quantitative susceptibility mapping and quantitative BOLD (QSM plus qBOLD) approach. Magnetic Resonance in Medicine 2019; 82: 1491–1503. DOI: 10.1002/mrm.27804. [doi]
21. Kim WT and Lee HY. Prediction of Oxygen Extraction Fraction based on LSTM Deep Learning Model using Brain MRI. The Journal of Korean Institute of Information Technology 2024; 22: 143–151. DOI: 10.14801/jkiit.2024.22.6.143. [doi]
22. Lee HY. OEF Calculation Method through Cluster-based Classification and Matching of QQ Model on Brain MRI Images. The Journal of Korean Institute of Information Technology 2020; 18: 15–23. DOI: 10.14801/jkiit.2020.18.10.15. [doi]
23. Lin F, Prince MR, Spincemaille P, et al. Patents on Quantitative Susceptibility Mapping (QSM) of Tissue Magnetism. Recent Patents on Biotechnology 2019; 13: 90–113. DOI: 10.2174/1872208313666181217112745. [doi]
24. Ma Y, Mazerolle EL, Cho J, et al. Quantification of brain oxygen extraction fraction using QSM and a hyperoxic challenge. Magnetic Resonance in Medicine 2020; 84: 3271–3285. DOI: https://doi.org/10.1002/mrm.28390. [doi]
25. Ma Y, Sun H, Cho J, et al. Cerebral OEF quantification: A comparison study between quantitative susceptibility mapping and dual-gas calibrated BOLD imaging. Magnetic Resonance in Medicine 2020; 83: 68–82. DOI: https://doi.org/10.1002/mrm.27907. [doi]
26. Wen Y, Spincemaille P, Nguyen T, et al. Multiecho complex total field inversion method (mcTFI) for improved signal modeling in quantitative susceptibility mapping. Magnetic Resonance in Medicine 2021; 86: 2165–2178. DOI: 10.1002/mrm.2881.4. [doi]
27. Misra A and Cho J. An Optimal, Routinely Applicable Multi-Echo Gradient Echo (mGRE) Data Acquisition Scheme for QQ-based Oxygen Extraction Fraction (OEF) Mapping.
28. Cho J, Zhang J, Spincemaille P, et al. 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 2022; 87: 1583–1594. 20211031. DOI: 10.1002/mrm.29057. [doi]
29. Cho J, Spincemaille P, Nguyen TD, et al. Temporal clustering, tissue composition, and total variation for mapping oxygen extraction fraction using QSM and quantitative BOLD. Magn Reson Med 2021 2021/06/11. DOI: 10.1002/mrm.28875. [doi]
30. Cho J, Zhang S, Kee Y, et al. 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 (CMRO2) mapping. 2020; 83: 844–857. DOI: 10.1002/mrm.27967. [doi]
31. Hubertus S, Thomas S, Cho J, et al. Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD. Magnetic Resonance in Medicine 2019; 82: 2199–2211. DOI: https://doi.org/10.1002/mrm.27882. [doi]
32. Kim HS and Lee HY. DNN-based Oxygen Extraction Fraction Prediction Method for QQ Model of Brain MRI. The Journal of Korean Institute of Information Technology 2023; 21: 35–41. DOI: 10.14801/jkiit.2023.21.6.35. [doi]
33. Lee HY. OEF Calculation Algorithm using Generalized QQ Model Clustering through Brain MRI Signal Decay Modeling. The Journal of Korean Institute of Information Technology 2022; 20: 1–8. DOI: 10.14801/jkiit.2022.20.5.1. [doi]
34. Seo YE, Son CH and Lee HY. Method for Improving QQ-based Oxygen Extraction Fraction Estimation Accuracy through GRU Model. The Journal of Korean Institute of Information Technology 2024; 22: 131–139. DOI: 10.14801/jkiit.2024.22.7.131. [doi]
35. Yun HS and Lee HY. QQ-based OEF Prediction Method on Brain MRI using Multi-Channel DenseNet. The Journal of Korean Institute of Information Technology 2024; 22: 105–113. DOI: 10.14801/jkiit.2024.22.10.105. [doi]
36. Cho J, Lee J, An H, et al. Cerebral oxygen extraction fraction (OEF): Comparison of challenge-free gradient echo QSM+qBOLD (QQ) with (15)O PET in healthy adults. J Cereb Blood Flow Metab 2021; 41: 1658–1668. 20201127. DOI: 10.1177/0271678x20973951. [doi]
37. Cho J, Ma Y, Spincemaille P, et al. Cerebral oxygen extraction fraction: Comparison of dual-gas challenge calibrated BOLD with CBF and challenge-free gradient echo QSM+qBOLD. Magnetic Resonance in Medicine 2021; 85: 953–961. DOI: https://doi.org/10.1002/mrm.28447. [doi]
38. Elanghovan P, Nguyen T, Spincemaille P, et al. Sensitivity assessment of QSM+qBOLD (or QQ) in detecting elevated oxygen extraction fraction (OEF) in physiological change. J Cereb Blood Flow Metab 2024: 271678x241298584. 20241105. DOI: 10.1177/0271678x241298584. [doi]
39. Jaroszynski KM, Lee H, Langham MC, et al. Comparison of Brain Oxygen Metabolic Parameters Between Constrained qBOLD and Whole-Brain Oximetric Methods at Baseline and in Response to a Physiologic Stimulus. NMR in biomedicine 2025; 38. DOI: 10.1002/nbm.70120. [doi]
40. Zhang S, Cho J, Nguyen TD, et al. Initial Experience of Challenge-Free MRI-Based Oxygen Extraction Fraction Mapping of Ischemic Stroke at Various Stages: Comparison With Perfusion and Diffusion Mapping. Frontiers in Neuroscience 2020; 14. Original Research. DOI: 10.3389/fnins.2020.535441. [doi]
41. Wu D, Zhou Y, Cho J, et al. The Spatiotemporal Evolution of MRI-Derived Oxygen Extraction Fraction and Perfusion in Ischemic Stroke. Frontiers in Neuroscience 2021; 15. Original Research. DOI: 10.3389/fnins.2021.716031. [doi]
42. Zhang S, Cho J, Nguyen TD, et al. Initial experience using combined quantitative susceptibility mapping and quantitative bold oxygen level dependent imaging (QSM+ qBOLD) oxygen extraction fraction for evaluation of acute ischemic stroke.
43. Cho J, Zhang S, Kee Y, et al. Data-driven regularized inversion (DRI) for improved QSM+ qBOLD based CMRO2 Mapping: a feasibility study in healthy subjects and ischemic stroke patients.
44. Yang L, Cho J, Chen T, et al. Oxygen extraction fraction (OEF) assesses cerebral oxygen metabolism of deep gray matter in patients with pre-eclampsia. European Radiology 2022; 32: 6058–6069. DOI: 10.1007/s00330-022-08713-7. [doi]
45. Zhang Q, Sui C, Cho J, et al. Assessing Cerebral Oxygen Metabolism Changes in Patients With Preeclampsia Using Voxel-Based Morphometry of Oxygen Extraction Fraction Maps in Magnetic Resonance Imaging. Korean J Radiol 2023; 24: 324–337. 20230307. DOI: 10.3348/kjr.2022.0652. [doi]
46. Zhuang H, Cho J, Chiang GC-Y, et al. Cerebral oxygen extraction fraction declines with ventricular enlargement in patients with normal pressure hydrocephalus. Clinical Imaging 2023; 97: 22–27. DOI: https://doi.org/10.1016/j.clinimag.2023.02.001. [doi]
47. Cho J, Nguyen TD, Huang W, et al. Brain oxygen extraction fraction mapping in patients with multiple sclerosis. J Cereb Blood Flow Metab 2021: 271678x211048031. 2021/09/25. DOI: 10.1177/0271678x211048031. [doi]
48. Xie Y, Zhang S, Wu D, et al. The changes of oxygen extraction fraction in different types of lesions in relapsing–remitting multiple sclerosis: A cross-sectional and longitudinal study. Neurological Sciences 2024; 45: 3939–3949. DOI: 10.1007/s10072-024-07463-2. [doi]
49. Cho J, Nguyen TD, Huang W, et al. Regional oxygen extract fraction mapping (rOEF) of multiple sclerosis brains.
50. Yan S, Lu J, Li Y, et al. Spatiotemporal patterns of brain iron-oxygen metabolism in patients with Parkinson's disease. Eur Radiol 2023 20231019. DOI: 10.1007/s00330-023-10283-1. [doi]
51. Shen N, Zhang S, Cho J, et al. 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. Frontiers in Neuroscience 2021; 15. Original Research. DOI: 10.3389/fnins.2021.736891. [doi]
52. Hubertus S, Thomas S, Cho J, et al. In MRI-based oxygen extraction fraction and cerebral metabolic rate of oxygen mapping in high-grade glioma using a combined quantitative susceptibility mapping and quantitative blood oxygenation level-dependent approach. Proceedings of the International Society for Magnetic Resonance in Medicine, Montréal, QC, Canada 2019: 11–16.
53. van Grinsven EE, de Leeuw J, Siero JCW, et al. Evaluating Physiological MRI Parameters in Patients with Brain Metastases Undergoing Stereotactic Radiosurgery—A Preliminary Analysis and Case Report. Cancers 2023; 15: 4298.
54. Wang J, Cho J, Zhang C, et al. Assessment of age-related changes of oxygen extraction fraction in of normal adults using QSM and quantitative BOLD.
55. Wu D, Li Y, Zhang S, et al. Trajectories and sex differences of brain structure, oxygenation and perfusion functions in normal aging. Neuroimage 2024; 302: 120903. DOI: https://doi.org/10.1016/j.neuroimage.2024.120903. [doi]
56. Chiang GC, Cho J, Dyke J, et al. Brain oxygen extraction and neural tissue susceptibility are associated with cognitive impairment in older individuals. Journal of Neuroimaging 2022; 32: 697–709. DOI: https://doi.org/10.1111/jon.12990. [doi]
57. Zhang S, Ma J, Wu S, et al. Evaluation of MRI-based brain oxygen extraction fraction mapping in patients with systemic lupus erythematosus. Lupus Science & Medicine 2025; 12: e001522. DOI: 10.1136/lupus-2025-001522. [doi]
58. Misra A, Wang Y, Chiang GC, et al. Oxygen extraction fraction is differently associated with pathological biomarkers in Alzheimer’s Disease and non-Alzheimer’s dementias.
59. Misra A, Oros-Peusquens A-M, Reetz K, et al. Assessing Abnormal Oxygen Extraction Fraction and Neural Tissue Susceptibility in Parkinson's Disease. Available at SSRN 5184105.
60. Zhang R, Lin M, Cho J, et al. Oxygen extraction fraction in small vessel disease: relationship to disease burden and progression. Brain : a journal of neurology 2025; 148: 1950–1962. DOI: 10.1093/brain/awae383. [doi]
61. Yan S, Lu J, Duan B, et al. Potential separation of multiple system atrophy and Parkinson’s disease by susceptibility-derived components. Neuroimage 2025; 318: 121241. DOI: https://doi.org/10.1016/j.neuroimage.2025.121241. [doi]
62. Vallejos G, Khalil MH, Keyes S, et al. Utilizing Oxygen Extraction Fraction to differentiate Multiple Sclerosis from Non-Multiple Sclerosis Fluid-Attenuated Inversion Recovery White Matter Lesions. In: MULTIPLE SCLEROSIS JOURNAL 2024, pp.933–934. SAGE PUBLICATIONS LTD 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND.
63. Yang A, Zhuang H, Du L, et al. Evaluation of whole-brain oxygen metabolism in Alzheimer's disease using QSM and quantitative BOLD. Neuroimage 2023; 282: 120381. DOI: https://doi.org/10.1016/j.neuroimage.2023.120381. [doi]
64. Cho J, Lv H, Guo L, et al. Neuroimaging of Brain Structure-Function Coupling Mechanism in Neuropsychiatric Disorders. Frontiers Media SA, 2023.
65. Hosseini SA, Servaes S, Therriault J, et al. Quantitative evaluation of oxygen extraction fraction (OEF) in Alzheimer's disease: A correlation with tau and amyloid pathology and cognitive status. Journal of the Neurological Sciences 2023; 455.
66. Biondetti E, Cho J and Lee H. Cerebral oxygen metabolism from MRI susceptibility. Neuroimage 2023; 276. DOI: 10.1016/j.neuroimage.2023.120189. [doi]
67. Engle J, Parastoo S, Bain PA, et al. The Clinical Applications of Oxygen Extraction Fraction (OEF) Metrics: A Systematic Review. SSRN Electronic Journal 2022. DOI: 10.2139/ssrn.4190247. [doi]
68. Fan AP, Khalil AA, Fiebach JB, et al. Elevated brain oxygen extraction fraction measured by MRI susceptibility relates to perfusion status in acute ischemic stroke. J Cerebr Blood F Met 2020; 40: 539–551. DOI: 10.1177/0271678x19827944. [doi]
69. Kataike VM, Desmond PM, Steward C, et al. Oxygen extraction fraction changes in ischemic tissue from 24-72 hours to 12 months after successful reperfusion. J Cerebr Blood F Met 2025; 45: 1748–1759. DOI: 10.1177/0271678x251333940. [doi]
70. Zhang J, Zhou D, Nguyen TD, et al. Cerebral metabolic rate of oxygen (CMRO2) mapping with hyperventilation challenge using quantitative susceptibility mapping (QSM). Magnetic resonance in medicine 2017; 77: 1762–1773. DOI: 10.1002/mrm.26253. [doi]
71. An H and Lin W. Cerebral venous and arterial blood volumes can be estimated separately in humans using magnetic resonance imaging. Magn Reson Med 2002; 48: 583–588. 2002/09/28. DOI: 10.1002/mrm.10257. [doi]
72. Sakai F, Nakazawa K, Tazaki Y, et al. Regional cerebral blood volume and hematocrit measured in normal human volunteers by single-photon emission computed tomography. J Cereb Blood Flow Metab 1985; 5: 207–213. 1985/06/01. DOI: 10.1038/jcbfm.1985.27. [doi]
73. Savicki JP, Lang G and Ikeda-Saito M. Magnetic susceptibility of oxy- and carbonmonoxyhemoglobins. Proceedings of the National Academy of Sciences 1984; 81: 5417–5419.
74. Hoffman R. Hematology: Basic Principles and Practice. Churchill Livingstone, 2005.
75. Spees WM, Yablonskiy DA, Oswood MC, et al. Water proton MR properties of human blood at 1.5 Tesla: magnetic susceptibility, T(1), T(2), T*(2), and non-Lorentzian signal behavior. Magn Reson Med 2001; 45: 533–542. 2001/04/03.
76. Zhang J, Liu T, Gupta A, et al. Quantitative mapping of cerebral metabolic rate of oxygen (CMRO2) using quantitative susceptibility mapping (QSM). Magnetic Resonance in Medicine 2015; 74: 945–952. DOI: 10.1002/mrm.25463. [doi]
77. Coudert T, Silva Martins Marçal M, Delphin A, et al. Fast MR signal simulations of microvascular and diffusion contributions using histogram-based approximation and recurrent neural networks. Magnetic Resonance in Medicine; n/a. DOI: https://doi.org/10.1002/mrm.30629. [doi]
78. Pathak AP, Ward BD and Schmainda KM. A novel technique for modeling susceptibility-based contrast mechanisms for arbitrary microvascular geometries: The finite perturber method. Neuroimage 2008; 40: 1130–1143. DOI: https://doi.org/10.1016/j.neuroimage.2008.01.022. [doi]
79. Paszke A, Gross S, Chintala S, et al. Automatic differentiation in PyTorch. Conference Proceedings 2017.
80. Kingma DP and Ba J. Adam: A Method for Stochastic Optimization. arXiv e-prints 2014: arXiv:1412.6980.
81. Fung SH, Roccatagliata L, Gonzalez RG, et al. MR diffusion imaging in ischemic stroke. Neuroimaging Clin N Am 2011; 21: 345–377, xi. 2011/06/07. DOI: 10.1016/j.nic.2011.03.001. [doi]
82. Aboul-Enein F, Rauschka H, Kornek B, et al. Preferential loss of myelin-associated glycoprotein reflects hypoxia-like white matter damage in stroke and inflammatory brain diseases. Journal of Neuropathology and Experimental Neurology 2003; 62: 25–33. DOI: 10.1093/jnen/62.1.25. [doi]
83. Sun X, He G, Qing H, et al. Hypoxia facilitates Alzheimer's disease pathogenesis by up-regulating BACE1 gene expression. Proceedings of the National Academy of Sciences of the United States of America 2006; 103: 18727–18732. 2006/11/24. DOI: 10.1073/pnas.0606298103. [doi]
84. Acosta-Cabronero J, Williams GB, Cardenas-Blanco A, et al. In vivo quantitative susceptibility mapping (QSM) in Alzheimer's disease. PloS one 2013; 8: e81093. 2013/11/28. DOI: 10.1371/journal.pone.0081093. [doi]
85. Trapp BD and Stys PK. Virtual hypoxia and chronic necrosis of demyelinated axons in multiple sclerosis. The Lancet Neurology 2009; 8: 280–291. 2009/02/24. DOI: 10.1016/s1474-4422(09)70043-2. [doi]
Cite this abstract
http://echo.ismrm.org/p/ISMRM2026/630-01-006