1Institute for Systems and Robotics – Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
2Basque Center on Cognition, Brain and Language, San Sebastian - Donostia, Spain
3Ikerbasque, Basque Foundation for Science, Bilbao, Spain
Presenting Author: Catarina Domingos
Synopsis
Motivation:
Goals:
Approach:
Results:
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.
1. Pinto J, Bright MG, Bulte DP, Figueiredo P. Cerebrovascular Reactivity Mapping Without Gas Challenges: A Methodological Guide. Front Physiol. 2021;11:608475. doi:10.3389/fphys.2020.608475. [doi]
2. Schulman JB, Uludağ K. Problems and solutions in quantifying cerebrovascular reactivity using BOLD-MRI. Imaging Neurosci. 2025;3:imag_a_00556. doi: 10.1162/imag_a_00556. [doi]
3. Liu P, Karimigharighi E, Lu H, Badrzadeh F. Normalized cerebrovascular reactivity mapping using hypercapnia and hyperoxia challenges. in Proc. ISMRM UHF and Brain Function Workshop (Annapolis, 2025).
4. Hoffman G, Schmitzer L, Kufer J, et al., Dynamic Susceptibility Contrast MRI and Arterial Spin Labeling reveals blood volume dependence of BOLD-based Cerebrovascular Reactivity. in Proc. ISMRM (Hawaii, 2025).
5. Xu F, Xu C, Zhu D, et al. Evaluating cerebrovascular reactivity measured by velocity selective inversion arterial spin labeling with different post-labeling delays: The effect of fast flow. Magn Reson Med. 2024;92(5):2065-2073. doi: 10.1002/mrm.30166. [doi]
6. Taneja K, Liu P, Xu C, et al. Quantitative Cerebrovascular Reactivity in Normal Aging: Comparison Between Phase-Contrast and Arterial Spin Labeling MRI. Front Neurol. 2020;11:758. doi: 10.3389/fneur.2020.00758. [doi]
7. Leoni RF, Oliveira IA, Pontes-Neto OM, Santos AC, Leite JP. Cerebral blood flow and vasoreactivity in aging: an arterial spin labeling study. Braz J Med Biol Res. 2017;50(4):e5670. doi: 10.1590/1414-431X20175670. [doi]
8. Halani S, Kwinta JB, Golestani AM, Khatamian YB, Chen JJ. Comparing cerebrovascular reactivity measured using BOLD and cerebral blood flow MRI: The effect of basal vascular tension on vasodilatory and vasoconstrictive reactivity. Neuroimage. 2015;110:110-123. doi: 10.1016/j.neuroimage.2015.01.050. [doi]
9. Alsop DC, Detre JA, Golay X, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med. 2015;73(1):102-116. doi: 10.1002/mrm.25197. [doi]
10. Chu PPW, Golestani AM, Kwinta JB, Khatamian YB, Chen JJ. Characterizing the modulation of resting-state fMRI metrics by baseline physiology. Neuroimage. 2018;173:72-87. doi: 10.1016/j.neuroimage.2018.02.004. [doi]
11. Stickland RC, Zvolanek KM, Moia S, Caballero-Gaudes C, Bright MG. Lag-Optimized Blood Oxygenation Level Dependent Cerebrovascular Reactivity Estimates Derived From Breathing Task Data Have a Stronger Relationship With Baseline Cerebral Blood Flow. Front Neurosci. 2022;16:910025. doi: 10.3389/fnins.2022.910025. [doi]
12. Domingos C, Esteves I, Fouto AR, et al. Relationship between resting-state BOLD functional connectivity and baseline physiology. in Proc. ESMRMB (Barcelona, 2024).
13. Chavarría I, Vidorreta M, Fernández-Seara M, Caballero-Gaudes C. Calibrated fMRI with a background-suppressed PCASL and multi-echo BOLD dual-acquisition sequence. in Proc. ESMRMB (Barcelona, 2024).
14. Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM. FSL. Neuroimage. 2012;62(2):782-790. doi: 10.1016/j.neuroimage.2011.09.015. [doi]
15. Kundu P, Brenowitz ND, Voon V, et al. Integrated strategy for improving functional connectivity mapping using multiecho fMRI. Proc Natl Acad Sci U S A. 2013;110(40):16187-16192. doi: 10.1073/pnas.1301725110. [doi]
16. Chappell MA, Groves AR, Whitcher B, Woolrich MW. Variational Bayesian Inference for a Nonlinear Forward Model. IEEE Trans Signal Process. 2009;57(1):223-236.
doi: 10.1109/TSP.2008.2005752. [doi]
17. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. Neuroimage. 2014;92(100):381-397. doi: 10.1016/j.neuroimage.2014.01.060. [doi]
18. Makris N, Goldstein JM, Kennedy D, et al. Decreased volume of left and total anterior insular lobule in schizophrenia. Schizophr Res. 2006;83(2-3):155-171. doi: 10.1016/j.schres.2005.11.020. [doi]
19. Yeo BT, Krienen FM, Sepulcre J, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106(3):1125-1165. doi: 10.1152/jn.00338.2011. [doi]
20. R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. 2024.