Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
604-02-001 ISMRM Abstract

A flow-diffusion model of capillary oxygen transport for the estimation of venous cerebral blood volume from GE-SE signal

Primary: Contrast Mechanisms - Relaxometry
Secondary: Contrast Mechanisms - Perfusion
604-02-001 · Perfusion, Flow, and Hemodynamics Across Scales · Thursday, 14 May, 1:40 PM–3:30 PM · Ballroom East
Keywords: Quantitative BOLD MR Oxymetry Brain tumor GE-SE EPIK Cerebral blood volume
Accepted
Stefano Zappalà 1, Eleonora Patitucci2, James Powell3, Sahar Iqbal3, Fabian Küppers4, N. Jon Shah5,6,7, Richard G Wise8,9, Michael Germuska10
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
2Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
3Department of Oncology, Velindre University NHS Trust, Cardiff, United Kingdom
4Institute of Neuroscience and Medicine 4, Forschungszentrum Juelich, Juelich, Germany
5Department of Neurology, Department of Neurology, RWTH Aachen University, Aachen, Germany
6Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany
7Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Germany
8Department of Neurosciences, Imaging and Clinical Sciences, University 'G.d'Annunzio' of Chieti-Pescara, Chieti, Italy
9Institute for Advanced Biomedical Technologies, University 'G.d'Annunzio' of Chieti-Pescara, Chieti, Italy
10Department of Radiology, University of California Davis Medical Center, Sacramento, CA, United States of America, United States of America
Presenting Author: Stefano Zappalà

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References

1. Stone, A. J. and N. P. Blockley (2025). "Improving quantitative BOLD–based measures of oxygen extraction fraction using hyperoxia BOLD–derived measures of blood volume." Magnetic Resonance in Medicine 94(4): 1700-1713. https://doi.org/10.1002/mrm.30559 [doi]
2. Chiarelli, A. M., et al. (2022). "A flow-diffusion model of oxygen transport for quantitative mapping of cerebral metabolic rate of oxygen (CMRO(2)) with single gas calibrated fMRI." J Cereb Blood Flow Metab 42(7): 1192-1209. https://www.ncbi.nlm.nih.gov/pubmed/35107026 [pmid]
3. Zappala S. et al., Robust Estimation of Oxygen Extraction Fraction and Venous Cerebral Blood Volume Using Flow-Diffusion Modelling Combined with R2' and Perfusion Measurements ISMRM 2024 Power Pitch 1315.
4. Zappala S. et al., A comparison of gas-free MRI methods for CMRO2 quantification in primary brain tumour, ISMRM 2025 Digital Poster 2483.
5. Driver, I. D., et al. (2024). Velocity-selective arterial spin labelling bolus duration measurements: Implications for consensus recommendations, Cold Spring Harbor Laboratory. https://doi.org/10.1101/2024.05.04.592549 [doi]
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8. Kuppers, F., et al. (2022). "Development of a novel 10-echo multi-contrast sequence based on EPIK to deliver simultaneous quantification of T(2) and T(2)(*) with application to oxygen extraction fraction." Magn Reson Med 88(4): 1608-1623. https://doi.org/10.1002/mrm.29305 [doi]
9. Grubb, R. L., Jr., et al. (1974). "The effects of changes in PaCO2 on cerebral blood volume, blood flow, and vascular mean transit time." Stroke 5(5): 630-639. https://doi.org/10.1161/01.str.5.5.630 [doi]
10. Chen, J. J. and G. B. Pike (2010). "MRI measurement of the BOLD-specific flow-volume relationship during hypercapnia and hypocapnia in humans." Neuroimage 53(2): 383-391. https://doi.org/10.1016/j.neuroimage.2010.07.003 [doi]
11. Boxerman, J. L., et al. (2006). "Relative Cerebral Blood Volume Maps Corrected for Contrast Agent Extravasation Significantly Correlate with Glioma Tumor Grade, Whereas Uncorrected Maps Do Not." https://www.ajnr.org/content/27/4/859.full
12. Peruzzo, D., et al. (2011). "Automatic selection of arterial input function on dynamic contrast-enhanced MR images." Comput Methods Programs Biomed 104(3): e148-157. https://doi.org/10.1016/j.cmpb.2011.02.012 [doi]
13. Sørensen, P., Carlsen, J., Larsen, V., Andersen, F., Ladefoged, C., Nielsen, M., Poulsen, H., Hansen, A., 2023. Evaluation of the HD-GLIO Deep Learning Algorithm for Brain Tumour Segmentation on Postoperative MRI. Diagnostics 13, 363. https://doi.org/10.3390/diagnostics13030363 [doi]
14. Mazziotta, J., et al. (2001). "A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 356(1412): 1293-1322. https://doi.org/10.1098/rstb.2001.0915 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/604-02-001